Organizing Your Social Sciences Research Assignments

  • Annotated Bibliography
  • Analyzing a Scholarly Journal Article
  • Group Presentations
  • Dealing with Nervousness
  • Using Visual Aids
  • Grading Someone Else's Paper
  • Types of Structured Group Activities
  • Group Project Survival Skills
  • Leading a Class Discussion
  • Multiple Book Review Essay
  • Reviewing Collected Works
  • Writing a Case Analysis Paper
  • Writing a Case Study
  • About Informed Consent
  • Writing Field Notes
  • Writing a Policy Memo
  • Writing a Reflective Paper
  • Writing a Research Proposal
  • Generative AI and Writing
  • Acknowledgments

Definition and Introduction

Journal article analysis assignments require you to summarize and critically assess the quality of an empirical research study published in a scholarly [a.k.a., academic, peer-reviewed] journal. The article may be assigned by the professor, chosen from course readings listed in the syllabus, or you must locate an article on your own, usually with the requirement that you search using a reputable library database, such as, JSTOR or ProQuest . The article chosen is expected to relate to the overall discipline of the course, specific course content, or key concepts discussed in class. In some cases, the purpose of the assignment is to analyze an article that is part of the literature review for a future research project.

Analysis of an article can be assigned to students individually or as part of a small group project. The final product is usually in the form of a short paper [typically 1- 6 double-spaced pages] that addresses key questions the professor uses to guide your analysis or that assesses specific parts of a scholarly research study [e.g., the research problem, methodology, discussion, conclusions or findings]. The analysis paper may be shared on a digital course management platform and/or presented to the class for the purpose of promoting a wider discussion about the topic of the study. Although assigned in any level of undergraduate and graduate coursework in the social and behavioral sciences, professors frequently include this assignment in upper division courses to help students learn how to effectively identify, read, and analyze empirical research within their major.

Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students make the most of Scholarly Articles." Library Management 33 (2012): 525-535.

Benefits of Journal Article Analysis Assignments

Analyzing and synthesizing a scholarly journal article is intended to help students obtain the reading and critical thinking skills needed to develop and write their own research papers. This assignment also supports workplace skills where you could be asked to summarize a report or other type of document and report it, for example, during a staff meeting or for a presentation.

There are two broadly defined ways that analyzing a scholarly journal article supports student learning:

Improve Reading Skills

Conducting research requires an ability to review, evaluate, and synthesize prior research studies. Reading prior research requires an understanding of the academic writing style , the type of epistemological beliefs or practices underpinning the research design, and the specific vocabulary and technical terminology [i.e., jargon] used within a discipline. Reading scholarly articles is important because academic writing is unfamiliar to most students; they have had limited exposure to using peer-reviewed journal articles prior to entering college or students have yet to gain exposure to the specific academic writing style of their disciplinary major. Learning how to read scholarly articles also requires careful and deliberate concentration on how authors use specific language and phrasing to convey their research, the problem it addresses, its relationship to prior research, its significance, its limitations, and how authors connect methods of data gathering to the results so as to develop recommended solutions derived from the overall research process.

Improve Comprehension Skills

In addition to knowing how to read scholarly journals articles, students must learn how to effectively interpret what the scholar(s) are trying to convey. Academic writing can be dense, multi-layered, and non-linear in how information is presented. In addition, scholarly articles contain footnotes or endnotes, references to sources, multiple appendices, and, in some cases, non-textual elements [e.g., graphs, charts] that can break-up the reader’s experience with the narrative flow of the study. Analyzing articles helps students practice comprehending these elements of writing, critiquing the arguments being made, reflecting upon the significance of the research, and how it relates to building new knowledge and understanding or applying new approaches to practice. Comprehending scholarly writing also involves thinking critically about where you fit within the overall dialogue among scholars concerning the research problem, finding possible gaps in the research that require further analysis, or identifying where the author(s) has failed to examine fully any specific elements of the study.

In addition, journal article analysis assignments are used by professors to strengthen discipline-specific information literacy skills, either alone or in relation to other tasks, such as, giving a class presentation or participating in a group project. These benefits can include the ability to:

  • Effectively paraphrase text, which leads to a more thorough understanding of the overall study;
  • Identify and describe strengths and weaknesses of the study and their implications;
  • Relate the article to other course readings and in relation to particular research concepts or ideas discussed during class;
  • Think critically about the research and summarize complex ideas contained within;
  • Plan, organize, and write an effective inquiry-based paper that investigates a research study, evaluates evidence, expounds on the author’s main ideas, and presents an argument concerning the significance and impact of the research in a clear and concise manner;
  • Model the type of source summary and critique you should do for any college-level research paper; and,
  • Increase interest and engagement with the research problem of the study as well as with the discipline.

Kershaw, Trina C., Jennifer Fugate, and Aminda J. O'Hare. "Teaching Undergraduates to Understand Published Research through Structured Practice in Identifying Key Research Concepts." Scholarship of Teaching and Learning in Psychology . Advance online publication, 2020; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students make the most of Scholarly Articles." Library Management 33 (2012): 525-535; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946.

Structure and Organization

A journal article analysis paper should be written in paragraph format and include an instruction to the study, your analysis of the research, and a conclusion that provides an overall assessment of the author's work, along with an explanation of what you believe is the study's overall impact and significance. Unless the purpose of the assignment is to examine foundational studies published many years ago, you should select articles that have been published relatively recently [e.g., within the past few years].

Since the research has been completed, reference to the study in your paper should be written in the past tense, with your analysis stated in the present tense [e.g., “The author portrayed access to health care services in rural areas as primarily a problem of having reliable transportation. However, I believe the author is overgeneralizing this issue because...”].

Introduction Section

The first section of a journal analysis paper should describe the topic of the article and highlight the author’s main points. This includes describing the research problem and theoretical framework, the rationale for the research, the methods of data gathering and analysis, the key findings, and the author’s final conclusions and recommendations. The narrative should focus on the act of describing rather than analyzing. Think of the introduction as a more comprehensive and detailed descriptive abstract of the study.

Possible questions to help guide your writing of the introduction section may include:

  • Who are the authors and what credentials do they hold that contributes to the validity of the study?
  • What was the research problem being investigated?
  • What type of research design was used to investigate the research problem?
  • What theoretical idea(s) and/or research questions were used to address the problem?
  • What was the source of the data or information used as evidence for analysis?
  • What methods were applied to investigate this evidence?
  • What were the author's overall conclusions and key findings?

Critical Analysis Section

The second section of a journal analysis paper should describe the strengths and weaknesses of the study and analyze its significance and impact. This section is where you shift the narrative from describing to analyzing. Think critically about the research in relation to other course readings, what has been discussed in class, or based on your own life experiences. If you are struggling to identify any weaknesses, explain why you believe this to be true. However, no study is perfect, regardless of how laudable its design may be. Given this, think about the repercussions of the choices made by the author(s) and how you might have conducted the study differently. Examples can include contemplating the choice of what sources were included or excluded in support of examining the research problem, the choice of the method used to analyze the data, or the choice to highlight specific recommended courses of action and/or implications for practice over others. Another strategy is to place yourself within the research study itself by thinking reflectively about what may be missing if you had been a participant in the study or if the recommended courses of action specifically targeted you or your community.

Possible questions to help guide your writing of the analysis section may include:

Introduction

  • Did the author clearly state the problem being investigated?
  • What was your reaction to and perspective on the research problem?
  • Was the study’s objective clearly stated? Did the author clearly explain why the study was necessary?
  • How well did the introduction frame the scope of the study?
  • Did the introduction conclude with a clear purpose statement?

Literature Review

  • Did the literature review lay a foundation for understanding the significance of the research problem?
  • Did the literature review provide enough background information to understand the problem in relation to relevant contexts [e.g., historical, economic, social, cultural, etc.].
  • Did literature review effectively place the study within the domain of prior research? Is anything missing?
  • Was the literature review organized by conceptual categories or did the author simply list and describe sources?
  • Did the author accurately explain how the data or information were collected?
  • Was the data used sufficient in supporting the study of the research problem?
  • Was there another methodological approach that could have been more illuminating?
  • Give your overall evaluation of the methods used in this article. How much trust would you put in generating relevant findings?

Results and Discussion

  • Were the results clearly presented?
  • Did you feel that the results support the theoretical and interpretive claims of the author? Why?
  • What did the author(s) do especially well in describing or analyzing their results?
  • Was the author's evaluation of the findings clearly stated?
  • How well did the discussion of the results relate to what is already known about the research problem?
  • Was the discussion of the results free of repetition and redundancies?
  • What interpretations did the authors make that you think are in incomplete, unwarranted, or overstated?
  • Did the conclusion effectively capture the main points of study?
  • Did the conclusion address the research questions posed? Do they seem reasonable?
  • Were the author’s conclusions consistent with the evidence and arguments presented?
  • Has the author explained how the research added new knowledge or understanding?

Overall Writing Style

  • If the article included tables, figures, or other non-textual elements, did they contribute to understanding the study?
  • Were ideas developed and related in a logical sequence?
  • Were transitions between sections of the article smooth and easy to follow?

Overall Evaluation Section

The final section of a journal analysis paper should bring your thoughts together into a coherent assessment of the value of the research study . This section is where the narrative flow transitions from analyzing specific elements of the article to critically evaluating the overall study. Explain what you view as the significance of the research in relation to the overall course content and any relevant discussions that occurred during class. Think about how the article contributes to understanding the overall research problem, how it fits within existing literature on the topic, how it relates to the course, and what it means to you as a student researcher. In some cases, your professor will also ask you to describe your experiences writing the journal article analysis paper as part of a reflective learning exercise.

Possible questions to help guide your writing of the conclusion and evaluation section may include:

  • Was the structure of the article clear and well organized?
  • Was the topic of current or enduring interest to you?
  • What were the main weaknesses of the article? [this does not refer to limitations stated by the author, but what you believe are potential flaws]
  • Was any of the information in the article unclear or ambiguous?
  • What did you learn from the research? If nothing stood out to you, explain why.
  • Assess the originality of the research. Did you believe it contributed new understanding of the research problem?
  • Were you persuaded by the author’s arguments?
  • If the author made any final recommendations, will they be impactful if applied to practice?
  • In what ways could future research build off of this study?
  • What implications does the study have for daily life?
  • Was the use of non-textual elements, footnotes or endnotes, and/or appendices helpful in understanding the research?
  • What lingering questions do you have after analyzing the article?

NOTE: Avoid using quotes. One of the main purposes of writing an article analysis paper is to learn how to effectively paraphrase and use your own words to summarize a scholarly research study and to explain what the research means to you. Using and citing a direct quote from the article should only be done to help emphasize a key point or to underscore an important concept or idea.

Business: The Article Analysis . Fred Meijer Center for Writing, Grand Valley State University; Bachiochi, Peter et al. "Using Empirical Article Analysis to Assess Research Methods Courses." Teaching of Psychology 38 (2011): 5-9; Brosowsky, Nicholaus P. et al. “Teaching Undergraduate Students to Read Empirical Articles: An Evaluation and Revision of the QALMRI Method.” PsyArXi Preprints , 2020; Holster, Kristin. “Article Evaluation Assignment”. TRAILS: Teaching Resources and Innovations Library for Sociology . Washington DC: American Sociological Association, 2016; Kershaw, Trina C., Jennifer Fugate, and Aminda J. O'Hare. "Teaching Undergraduates to Understand Published Research through Structured Practice in Identifying Key Research Concepts." Scholarship of Teaching and Learning in Psychology . Advance online publication, 2020; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Reviewer's Guide . SAGE Reviewer Gateway, SAGE Journals; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946; Gyuris, Emma, and Laura Castell. "To Tell Them or Show Them? How to Improve Science Students’ Skills of Critical Reading." International Journal of Innovation in Science and Mathematics Education 21 (2013): 70-80; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students Make the Most of Scholarly Articles." Library Management 33 (2012): 525-535.

Writing Tip

Not All Scholarly Journal Articles Can Be Critically Analyzed

There are a variety of articles published in scholarly journals that do not fit within the guidelines of an article analysis assignment. This is because the work cannot be empirically examined or it does not generate new knowledge in a way which can be critically analyzed.

If you are required to locate a research study on your own, avoid selecting these types of journal articles:

  • Theoretical essays which discuss concepts, assumptions, and propositions, but report no empirical research;
  • Statistical or methodological papers that may analyze data, but the bulk of the work is devoted to refining a new measurement, statistical technique, or modeling procedure;
  • Articles that review, analyze, critique, and synthesize prior research, but do not report any original research;
  • Brief essays devoted to research methods and findings;
  • Articles written by scholars in popular magazines or industry trade journals;
  • Pre-print articles that have been posted online, but may undergo further editing and revision by the journal's editorial staff before final publication; and
  • Academic commentary that discusses research trends or emerging concepts and ideas, but does not contain citations to sources.

Journal Analysis Assignment - Myers . Writing@CSU, Colorado State University; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36.

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  • 40 Useful Words and Phrases for Top-Notch Essays

article analysis vocabulary

To be truly brilliant, an essay needs to utilise the right language. You could make a great point, but if it’s not intelligently articulated, you almost needn’t have bothered.

Developing the language skills to build an argument and to write persuasively is crucial if you’re to write outstanding essays every time. In this article, we’re going to equip you with the words and phrases you need to write a top-notch essay, along with examples of how to utilise them.

It’s by no means an exhaustive list, and there will often be other ways of using the words and phrases we describe that we won’t have room to include, but there should be more than enough below to help you make an instant improvement to your essay-writing skills.

This article is suitable for native English speakers and those who are  learning English at our Oxford Summer School or San Francisco Summer School and are just taking their first steps into essay writing.

General explaining

Let’s start by looking at language for general explanations of complex points.

1. In order to

Usage: “In order to” can be used to introduce an explanation for the purpose of an argument. Example: “In order to understand X, we need first to understand Y.”

2. In other words

Usage: Use “in other words” when you want to express something in a different way (more simply), to make it easier to understand, or to emphasise or expand on a point. Example: “Frogs are amphibians. In other words, they live on the land and in the water.”

3. To put it another way

Usage: This phrase is another way of saying “in other words”, and can be used in particularly complex points, when you feel that an alternative way of wording a problem may help the reader achieve a better understanding of its significance. Example: “Plants rely on photosynthesis. To put it another way, they will die without the sun.”

4. That is to say

Usage: “That is” and “that is to say” can be used to add further detail to your explanation, or to be more precise. Example: “Whales are mammals. That is to say, they must breathe air.”

5. To that end

Usage: Use “to that end” or “to this end” in a similar way to “in order to” or “so”. Example: “Zoologists have long sought to understand how animals communicate with each other. To that end, a new study has been launched that looks at elephant sounds and their possible meanings.”

Adding additional information to support a point

Students often make the mistake of using synonyms of “and” each time they want to add further information in support of a point they’re making, or to build an argument . Here are some cleverer ways of doing this.

6. Moreover

Usage: Employ “moreover” at the start of a sentence to add extra information in support of a point you’re making. Example: “Moreover, the results of a recent piece of research provide compelling evidence in support of…”

7. Furthermore

Usage:This is also generally used at the start of a sentence, to add extra information. Example: “Furthermore, there is evidence to suggest that…”

8. What’s more

Usage: This is used in the same way as “moreover” and “furthermore”. Example: “What’s more, this isn’t the only evidence that supports this hypothesis.”

9. Likewise

Usage: Use “likewise” when you want to talk about something that agrees with what you’ve just mentioned. Example: “Scholar A believes X. Likewise, Scholar B argues compellingly in favour of this point of view.”

10. Similarly

Usage: Use “similarly” in the same way as “likewise”. Example: “Audiences at the time reacted with shock to Beethoven’s new work, because it was very different to what they were used to. Similarly, we have a tendency to react with surprise to the unfamiliar.”

11. Another key thing to remember

Usage: Use the phrase “another key point to remember” or “another key fact to remember” to introduce additional facts without using the word “also”. Example: “As a Romantic, Blake was a proponent of a closer relationship between humans and nature. Another key point to remember is that Blake was writing during the Industrial Revolution, which had a major impact on the world around him.”

12. As well as

Usage: Use “as well as” instead of “also” or “and”. Example: “Scholar A argued that this was due to X, as well as Y.”

13. Not only… but also

Usage: This wording is used to add an extra piece of information, often something that’s in some way more surprising or unexpected than the first piece of information. Example: “Not only did Edmund Hillary have the honour of being the first to reach the summit of Everest, but he was also appointed Knight Commander of the Order of the British Empire.”

14. Coupled with

Usage: Used when considering two or more arguments at a time. Example: “Coupled with the literary evidence, the statistics paint a compelling view of…”

15. Firstly, secondly, thirdly…

Usage: This can be used to structure an argument, presenting facts clearly one after the other. Example: “There are many points in support of this view. Firstly, X. Secondly, Y. And thirdly, Z.

16. Not to mention/to say nothing of

Usage: “Not to mention” and “to say nothing of” can be used to add extra information with a bit of emphasis. Example: “The war caused unprecedented suffering to millions of people, not to mention its impact on the country’s economy.”

Words and phrases for demonstrating contrast

When you’re developing an argument, you will often need to present contrasting or opposing opinions or evidence – “it could show this, but it could also show this”, or “X says this, but Y disagrees”. This section covers words you can use instead of the “but” in these examples, to make your writing sound more intelligent and interesting.

17. However

Usage: Use “however” to introduce a point that disagrees with what you’ve just said. Example: “Scholar A thinks this. However, Scholar B reached a different conclusion.”

18. On the other hand

Usage: Usage of this phrase includes introducing a contrasting interpretation of the same piece of evidence, a different piece of evidence that suggests something else, or an opposing opinion. Example: “The historical evidence appears to suggest a clear-cut situation. On the other hand, the archaeological evidence presents a somewhat less straightforward picture of what happened that day.”

19. Having said that

Usage: Used in a similar manner to “on the other hand” or “but”. Example: “The historians are unanimous in telling us X, an agreement that suggests that this version of events must be an accurate account. Having said that, the archaeology tells a different story.”

20. By contrast/in comparison

Usage: Use “by contrast” or “in comparison” when you’re comparing and contrasting pieces of evidence. Example: “Scholar A’s opinion, then, is based on insufficient evidence. By contrast, Scholar B’s opinion seems more plausible.”

21. Then again

Usage: Use this to cast doubt on an assertion. Example: “Writer A asserts that this was the reason for what happened. Then again, it’s possible that he was being paid to say this.”

22. That said

Usage: This is used in the same way as “then again”. Example: “The evidence ostensibly appears to point to this conclusion. That said, much of the evidence is unreliable at best.”

Usage: Use this when you want to introduce a contrasting idea. Example: “Much of scholarship has focused on this evidence. Yet not everyone agrees that this is the most important aspect of the situation.”

Adding a proviso or acknowledging reservations

Sometimes, you may need to acknowledge a shortfalling in a piece of evidence, or add a proviso. Here are some ways of doing so.

24. Despite this

Usage: Use “despite this” or “in spite of this” when you want to outline a point that stands regardless of a shortfalling in the evidence. Example: “The sample size was small, but the results were important despite this.”

25. With this in mind

Usage: Use this when you want your reader to consider a point in the knowledge of something else. Example: “We’ve seen that the methods used in the 19th century study did not always live up to the rigorous standards expected in scientific research today, which makes it difficult to draw definite conclusions. With this in mind, let’s look at a more recent study to see how the results compare.”

26. Provided that

Usage: This means “on condition that”. You can also say “providing that” or just “providing” to mean the same thing. Example: “We may use this as evidence to support our argument, provided that we bear in mind the limitations of the methods used to obtain it.”

27. In view of/in light of

Usage: These phrases are used when something has shed light on something else. Example: “In light of the evidence from the 2013 study, we have a better understanding of…”

28. Nonetheless

Usage: This is similar to “despite this”. Example: “The study had its limitations, but it was nonetheless groundbreaking for its day.”

29. Nevertheless

Usage: This is the same as “nonetheless”. Example: “The study was flawed, but it was important nevertheless.”

30. Notwithstanding

Usage: This is another way of saying “nonetheless”. Example: “Notwithstanding the limitations of the methodology used, it was an important study in the development of how we view the workings of the human mind.”

Giving examples

Good essays always back up points with examples, but it’s going to get boring if you use the expression “for example” every time. Here are a couple of other ways of saying the same thing.

31. For instance

Example: “Some birds migrate to avoid harsher winter climates. Swallows, for instance, leave the UK in early winter and fly south…”

32. To give an illustration

Example: “To give an illustration of what I mean, let’s look at the case of…”

Signifying importance

When you want to demonstrate that a point is particularly important, there are several ways of highlighting it as such.

33. Significantly

Usage: Used to introduce a point that is loaded with meaning that might not be immediately apparent. Example: “Significantly, Tacitus omits to tell us the kind of gossip prevalent in Suetonius’ accounts of the same period.”

34. Notably

Usage: This can be used to mean “significantly” (as above), and it can also be used interchangeably with “in particular” (the example below demonstrates the first of these ways of using it). Example: “Actual figures are notably absent from Scholar A’s analysis.”

35. Importantly

Usage: Use “importantly” interchangeably with “significantly”. Example: “Importantly, Scholar A was being employed by X when he wrote this work, and was presumably therefore under pressure to portray the situation more favourably than he perhaps might otherwise have done.”

Summarising

You’ve almost made it to the end of the essay, but your work isn’t over yet. You need to end by wrapping up everything you’ve talked about, showing that you’ve considered the arguments on both sides and reached the most likely conclusion. Here are some words and phrases to help you.

36. In conclusion

Usage: Typically used to introduce the concluding paragraph or sentence of an essay, summarising what you’ve discussed in a broad overview. Example: “In conclusion, the evidence points almost exclusively to Argument A.”

37. Above all

Usage: Used to signify what you believe to be the most significant point, and the main takeaway from the essay. Example: “Above all, it seems pertinent to remember that…”

38. Persuasive

Usage: This is a useful word to use when summarising which argument you find most convincing. Example: “Scholar A’s point – that Constanze Mozart was motivated by financial gain – seems to me to be the most persuasive argument for her actions following Mozart’s death.”

39. Compelling

Usage: Use in the same way as “persuasive” above. Example: “The most compelling argument is presented by Scholar A.”

40. All things considered

Usage: This means “taking everything into account”. Example: “All things considered, it seems reasonable to assume that…”

How many of these words and phrases will you get into your next essay? And are any of your favourite essay terms missing from our list? Let us know in the comments below, or get in touch here to find out more about courses that can help you with your essays.

At Oxford Royale Academy, we offer a number of  summer school courses for young people who are keen to improve their essay writing skills. Click here to apply for one of our courses today, including law , business , medicine  and engineering .

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How Vocabulary is Learned

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Stefan Hofstetter, How Vocabulary is Learned, ELT Journal , Volume 73, Issue 4, October 2019, Pages 489–491, https://doi.org/10.1093/elt/ccz034

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How Vocabulary is Learned by Stuart Webb and Paul Nation focusses on key issues underlying the learning and teaching of vocabulary both from a theoretical perspective and with a strong emphasis on actually putting things into practice. Generally speaking, it is an absolute pleasure to read what these two extremely experienced writers have to say about this vital topic, which constitutes an essential component of language teaching and is thus part and parcel of any language instructor’s everyday teaching requirements.

Chapter 1 starts out by addressing the question of which words should be learnt, unsurprisingly stressing the importance of teaching high-frequency words along with technical and academic vocabulary occurring within various types of discourse, as well as introducing the reader to a number of frequency lists and suggesting a concrete testing format to check effectiveness afterwards. Chapter 2 then deals with the learning burden involved in studying words, putting the central focus on how to reduce this burden and also providing practical hands-on suggestions for teaching, in particular with respect to introducing opposites, synonyms and members of lexical sets.

Chapter 3 looks at vocabulary growth, contrasting natural acquisition in L1 with vocabulary learning in L2 and especially in the EFL situation. Having shown that absolute figures differ considerably depending on whether individual word forms, lemmas or whole word families are counted, Webb and Nation argue that the vocabulary size of EFL learners is often too small, due to insufficient language input, and they thus suggest combining deliberate learning with a great deal of incidental learning as a remedy. Surprisingly, the authors use a very loose und unrestricted definition of incidental learning, so that even explanations of new words by teachers or explicitly consulting dictionaries are considered as incidental instantiations of learning. In my opinion, the latter two rather feature deliberate forms of learning and strangely enough, later on, Webb and Nation state themselves that ‘dictionary use is a deliberate learning strategy’ (p. 119), which seems rather inconsistent. What I find very convincing, however, is the fact that they stress the great importance of spoken input for incidental vocabulary learning. This looks much more plausible to me than the so-called Incidental Learning Hypothesis in its original version (cf. Nagy, Herman and Anderson 1985 ) that displays a rather unnatural one-sided focus on reading and which, taken at face value, would, for example, wrongly predict that people who hardly read will never learn low-frequency words, which is clearly not tenable from a linguistic perspective.

Chapter 4 then proceeds to identify repetition and quality of attention as the two determining factors involved in vocabulary learning, further subdividing the latter into the aspects of noticing, retrieval, varied use/encounters and elaboration. The chapter also discusses teaching activities that promote these different components on a very general level and draws readers’ attention to the danger of detrimental interferences with exercises comprising incorrect forms.

These teaching activities are further elaborated on in chapter 5, which constitutes by far the longest chapter of the whole book and that practising teachers will certainly take to be its heart. Here, a total of 23 activities are critically examined in impressive detail. True, some of these activities are not particularly new, and some do not primarily focus on teaching words (but rather on training one or several of the four traditional skills of listening, speaking, reading and writing). However, Webb and Nation offer not only an in-depth description of these 23 classical teaching activities, but also a specific exploration of their individual validity for teaching vocabulary proper, and they make very concrete suggestions on how to maximize their efficiency when introducing new words.

Next, chapter 6 investigates teaching EFL, ESL and also teaching it to young children, providing the reader with precise ideas about how these different contexts affect vocabulary learning and teaching in practice, thereby also closely examining the special needs of learners at different levels of proficiency. It furthermore presents insights into how to adapt a vocabulary learning programme for teachers having to cope with very small or large groups of learners.

Chapter 7 stresses the importance of developing autonomous vocabulary learners, a topic gaining importance in an age where learner autonomy and life-long learning are widely propagated. To promote this autonomy, Webb and Nation identify four key strategies and elaborate on their practical implementation when teaching EFL or ESL alike. While all of the strategies presented seem perfectly reasonable to me, their suggestions for putting them into practice are not always so. The section on ‘affixes and stems’ contains, for example, excellent exercise material and that on ‘guessing from context’ likewise offers a nice practical application in the accompanying activity material, but the subsection on ‘finding ways to use the L2 outside the classroom’ mostly proposes activities that I could hardly imagine my own students implementing, such as learners ‘calling the customer service department of international companies’ (p. 176) in order to improve their language skills.

The following chapter sets up some core principles for designing vocabulary learning programmes in practice. In particular, it argues that such programmes should display an equal balance of activities promoting meaningful input and output, language-focused learning as well as fluency development (thus automatically also balancing receptive and productive forms of vocabulary learning). Similarly, Webb and Nation argue that the four basic skills of listening, reading, speaking and writing should also be taken into consideration in roughly equal proportions, once more offering precise ideas on how this intended balance can best be achieved in practical teaching.

Chapter 9 then identifies several word lists, various forms of vocabulary testing, flashcards, digitally accessible corpora, concordancers and lexical profilers alongside a range of reading material, television programmes, films and online videos as the most useful current resources supporting vocabulary teaching and learning, also discussing their actual availability on the internet in great detail. Here, I was somewhat surprised at the two authors putting such a clear focus on digital and/or online resources and barely taking classical print media into account anymore.

Chapter 10, concluding the body of this book, is dedicated to answering 12 practical questions on how teachers should go about introducing words. This nicely recapitulates some of the main insights arrived at in preceding sections and also results in an elegant overall circular structure in that precisely these 12 questions had already been formulated in the ‘Introduction’ at the very beginning.

In addition, the volume includes an appendix section featuring the ‘Essential Word List’ (established by Dang and Webb 2016 ), an overview of common word stems and two instantiations of vocabulary testing (which teachers will probably enjoy and have fun taking themselves) as well as a useful and comprehensive glossary of pretty much any technical term related to vocabulary teaching and learning.

In my opinion, How Vocabulary is Learned succeeds in linking substantial background knowledge on vocabulary learning on an academic level to actual hands-on advice on how to implement efficient work on vocabulary in practical teaching, thus perfectly bridging the gap between theory and practice. In particular, this book is characterized by an abundance of precise numbers and figures, leading to a degree of concreteness and precision hardly ever encountered in treatises on language teaching. In a similar fashion, Webb and Nation do not limit themselves to relating only common knowledge or received wisdom, but rely heavily on insights from empirical research, including some very recent studies. It is refreshing to see that on the rare occasions where claims cannot be empirically supported, they freely admit this (e.g. the frank acknowledgment ‘not researched’ on pp. 99ff) rather than trying to hide it or excluding such sections altogether. Once again, such an outstanding level of empirical substantiation is really exceptional and rarely found in handbooks for language teachers, where more often than not, practising teachers simply tend to present their own subjective experiences. Moreover, the fact that the book is written in a fairly simple style without unnecessary technicalities will surely also contribute to making it a valuable resource for all teachers of English. Nice also that at the end of each chapter, further references are not just listed as such, but that the authors include a short summary of these and give their readers an idea of what to expect from them. Furthermore, Webb and Nation include questions for further reflection after every chapter as well as activities inside the chapters, thus providing a more active role for their readers. Having said that, these differ considerably in quality, ranging from the truly excellent example of a text simplification (p. 146) down to a way too difficult list establishment task (p. 13) that ends in a fairly wild collection of all sorts of real lexical combinations (‘at all’), but also of grammatical forms like the going to -future or even single entity-denoting expressions that simply happen to be spelt as two words (‘no one’).

In spite of these undoubted and numerous merits, there are some minor issues I’d like to suggest revising if the book was to be republished: the word ‘bank’ is actually homophonous rather than polysemous (p. 282), given that the meanings involved are clearly unrelated, and a ‘pre-test’ crucially takes place ‘before’, not ‘after’ learning (cf. p. 283). Apart from such details, in a number of cases the points made by Webb and Nation run counter to my experience as a teacher. In spite of their claim that overall, ‘collocations tend to follow grammatical rules and are consistent with the meanings of the words involved’ (p. 32), I have found that collocations often prove particularly difficult to teach. Similarly, I doubt that in classes with 30 students and more, during reading assignments, teachers can really ‘move around and provide support for any students who are having difficulty understanding the input’ (p. 142), and I was also quite disappointed when reading the subsection on ‘teaching vocabulary when time is limited’, which happens to be very short and does not really get beyond the fairly vague suggestion that ‘the most pressing needs should be dealt with first’ (p. 147). Given that time restrictions are often the most crucial challenge in real-life teaching at school, I should definitely have expected more insights on this vital issue. Still in the same vein, I do not see how months of the year, numbers or colours could be taught ‘according to their frequency’ (p. 35) in order to avoid interferences, as these expressions hardly differ in frequency after all. Ultimately, it is also difficult for me to imagine how dictionaries could display the ‘core meanings’ of words (p. 30; cf. also pp. 105 and 120) rather than listing their various senses, as asked for quite radically by Webb and Nation, given that it is often not easy to capture this assumed common core.

At the end of the day, however, these are mostly minor issues indeed. On a more general level, what I miss in this book is a much more elaborated discussion of the different aspects of a word that need to be taught (some of them are simply listed in a short overview at the bottom of p. 26) with a particular focus on those aspects that are likely to cause difficulty when learning new words. On top of that, a separate section on teaching strategies used in direct vocabulary instruction would have been most useful in view of the fact that such direct teaching constitutes an essential part of language teachers’ everyday life requirements (at present, the use of synonyms, pictures, real objects or gestures is just hinted at on p. 240), just as an individual section on the psycholinguistic background of learning vocabulary is also missing (introducing, for example, key notions such as the mental lexicon, long- and short-term memory or the development and stability of neural connections), an area where many new discoveries have recently been made, but which is strangely enough not addressed at all in this (in other respects very comprehensive) book. From my perspective as a practising teacher, what is most striking, however, is Webb and Nation’s frequent overestimation of the actual workload that can be imposed on students. While they suggest reading ‘one graded reader every two weeks’ as a ‘minimum target’ (p. 92), the obligatory curriculum even for the highest type of secondary school in Germany, for example, merely asks teachers to read one graded reader every other year. Likewise, their idea of making students read for more than one hour every day (p. 91) seems just about as unrealistic to me as their proposal of a two-hour homework per week (p. 182): if teachers of all subjects proceeded like that, students would have to spend about 30 hours on homework every week. Funnily enough, these requirements also clearly contrast with a vital claim made by Webb and Nation themselves:

… clear vocabulary learning goals should be set which take into consideration the amount of time available for learning and are realistic in scope; there is no point in having unachievable goals, because this may discourage rather than encourage learning. (p. 147)

However, the above-mentioned strengths far outweigh these shortcomings, which is why I’d like to warmly recommend this book to any teacher of English who either wants to update their knowledge of the theoretical background underlying vocabulary learning or who looks for ideas on how to go about teaching words to students. Finally, to meet Michael Swan’s requirement that ‘every reviewer needs to draw attention to a misprint in order to prove that he or she has really read the book’ ( Swan 2018 , p. 108), in the second paragraph on page 206, the fifth word in the last line should actually read ‘test’ rather than ‘text’.

Stefan Hofstetter is a lecturer at the University of Tübingen. He did a doctorate in formal linguistics, but also followed a classical teacher training programme and taught English and French for several years at secondary schools in Baden-Württemberg, in the south of Germany, both in the public and the private sector. His current position is split between the Department of Linguistics (where he teaches generative syntax and formal semantics) and the TEFL Department, where he is mainly interested in how to effectively teach English vocabulary and grammar at secondary schools.

Email: [email protected]

Dang , T. N. Y. and S. Webb . 2016 . ‘Making an essential word list for beginners’ in I. S. P. Nation . Making and Using Word Lists for Language Learning and Testing . Amsterdam : John Benjamins .

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Nagy , W. E. , P. A. Herman and R. C. Anderson . 1985 . ‘Learning words from context’ . Reading Research Quarterly 20 / 2 : 233 – 53 .

Swan , M . 2018 . Review of ‘The Practice of English Language Teaching, 5th edition’ . ELT Journal 72 / 1 : 105 – 8 .

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Word Analysis to Expand Vocabulary Development

On this page:, teaching word analysis, word analysis in practice, in the classroom, online teacher resources, introduction.

When students engage in “word analysis” or “word study,” they break words down into their smallest units of meaning — morphemes. Each morpheme has a meaning that contributes to our understanding of the whole word. As such, students’ knowledge of morphemes helps them to identify the meaning of words and build their vocabulary . The Institute for Educational Science (IES) Practice Guide strongly recommends providing explicit vocabulary instruction, which includes providing students with strategies for acquiring new vocabulary. The ability to analyze words is a critical foundational reading skill and is essential for vocabulary development as students become college and career ready.

Teaching word analysis skills satisfies several of the Common Core State Standards for literacy , including:

  • CCSS.ELA-Literacy.CCRA.L.4 Determine or clarify the meaning of unknown and multiple-meaning words and phrases by using context clues , analyzing meaningful word parts , and consulting general and specialized reference materials, as appropriate.
  • CCSS.ELA-Literacy.CCRA.L.5 Demonstrate understanding of figurative language, word relationships, and nuances in word meanings.

As you create your plan for teaching word analysis strategies, think about the tools and methods that can support students’ understanding, and provide students with opportunities to practice using these tools and methods. Think, too, about how you could differentiate instruction and take advantage of technology tools to engage the diverse students in your classroom.

You can effectively differentiate word analysis techniques by providing clear and varied models, keeping in mind the principles of Universal Design for Learning (UDL). Model how to analyze a new word by breaking it down into its sub-parts, studying each part separately, and then putting the parts back together in order to understand the whole word (see UDL Checkpoint 3.3: Guide information processing, visualization, and manipulation ).

It also helps to demonstrate that when you are studying vocabulary in a specific content area (e.g., science), you can find patterns in the prefixes that will help you understand what the words mean in that context. For example:

  • Science: biology, biodegradable, biome, biosphere
  • Mathematics: quadruple, quadrant, quadrilateral, quadratic
  • Geography: disassemble, disarmament, disband, disadvantage

Students should also learn to track both the words and the word parts they learn through these strategies. Show students how to use offline and online visual diagrams, worksheets, and graphic organizers to visualize the relationship between words and store new vocabulary.

If you provide students with opportunities to repeatedly practice analyzing unfamiliar vocabulary, their word analysis skills will continue to develop. Engage students individually, in pairs, or in small groups in a variety of games and activities, based on their individual abilities and needs. Consider ways in which you could modify the following games and activities to benefit struggling students:

  • The mix-and-match game using roots, prefixes, and suffixes
  • A word search in social studies, science, and mathematics texts to find words with prefixes and suffixes
  • Using Scrabble or Boggle tiles to form and re-form words
  • Movement activities that involve students holding up cards with root words, prefixes, and suffixes and reordering themselves to make words
  • Inventing a word by creating and defining nonsense words with prefixes and suffixes

Build word study into your classroom reading routine by pre-teaching words, introducing new vocabulary words weekly, and reviewing new words. Motivate students to practice using their word analysis skills by having them create glossaries of words with prefixes and suffixes from self-selected, high-interest texts.

You can also make use of multimedia and embedded supports to further support your varied learners and foster vocabulary development. Take a look at the videos below on Captioning and Embedded Supports for more ideas on how to leverage multimedia for vocabulary learning.

Searching for meaning in new words can be a bit like gathering clues to solve a mystery. Mr. Chen took advantage of this analogy in his unit on Ancient India by thematically tying vocabulary acquisition to the archeological excavation of the sites his students were studying. In particular, Mr. Chen sought to assist his struggling readers by offering strategies for tackling the unfamiliar terms in the social studies text, which aligns with the CCSS for literacy (see above).

Mr. Chen focused his instruction on modeling a good technique for word analysis. He presented a word that students would encounter several times in their reading — terracotta — and led the class through an analysis of the roots and parts of the word. By listing other words that sound like the prefix terra- (such as terrarium and extraterrestrial), students were able to determine that terra- relates to dirt and the earth.

Mr. Chen has access to several technology tools that he knows will benefit his struggling students. On his interactive whiteboard, he will demonstrate how to use Harappa.com to explore audio, video, text, and photos. He will also encourage students to use online reference tools — such as Visual Thesaurus , the Merriam-Webster Online Dictionary , and PrefixSuffix.com — to help students understand word parts. He has found that the classroom wiki, which was created in order to record and share words, has become a “go-to” place for students.

Mr. Chen’s lesson plan is detailed in the chart below, which divides the lesson into three parts: before reading, during reading, and after reading.

Lesson Plan

This article draws from the PowerUp WHAT WORKS website, particularly the Word Analysis Instructional Strategy Guide . PowerUp is a free, teacher-friendly website that requires no log in or registration. The Instructional Strategy Guide on Word Analysis includes a brief overview that defines word analysis along with an accompanying slide show; a list of the relevant ELA Common Core State Standards; evidence-based teaching strategies to differentiate instruction using technology; another case story; short videos; and links to resources that will help you use technology to support instruction in word analysis. If you are responsible for professional development, check out the PD Support Materials for helpful ideas and materials for using the word analysis resources. Want more information? See PowerUp WHAT WORKS .

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The Influence of Reading on Vocabulary Growth: A Case for a Matthew Effect

a University of Iowa, Iowa City

J. Bruce Tomblin

b Florida State University, Tallahassee

Individual differences in vocabulary development may affect academic or social opportunities. It has been proposed that individual differences in word reading could affect the rate of vocabulary growth, mediated by the amount of reading experience, a process referred to as a Matthew effect ( Stanovich, 1986 ).

In the current study, assessments of written word–reading skills in the 4th grade and oral vocabulary knowledge collected in kindergarten and in the 4th, 8th, and 10th grades from a large epidemiologically based sample ( n = 485) allowed a test of the relationship of early word-reading skills and the subsequent rate of vocabulary growth.

Consistent with the hypothesis, multilevel modeling revealed the rate of vocabulary growth after the 4th grade to be significantly related to 4th-grade word reading after controlling for kindergarten vocabulary level, that is, above average readers experienced a higher rate of vocabulary growth than did average readers.

Conclusions

Vocabulary growth rate differences accumulated over time such that the effect on vocabulary size was large.

There are large differences between individual children in their vocabulary knowledge on school entry (e.g., Hart & Risley, 1995 ), and these differences in vocabulary extend into the school years. For example, Biemiller and Slomin (2001) reported that in the second grade, children at the lowest quartile for vocabulary had approximately half the number of known words compared to students in the top quartile. Furthermore, according to the Matthew effect model proposed by Stanovich (1986 , 2000) , those individual differences in vocabulary may even increase over time. The term Matthew effect refers to a biblical text and was originally proposed to describe the progress of scientific research careers ( Merton, 1968 ) in which advantages and disadvantages accumulate, so that the rich get richer and the poor get poorer. In terms of reading, the general premise of the Matthew effect model is that individual differences in reading skill (broadly conceived) could accumulate over time ( Stanovich, 1986 , 2000 ) so that a child's initial reading level would be positively related to his or her rate of growth in a reading skill. This pattern, in which growth rates differ across skill levels even while absolute skill levels increase for all, is considered a relative Matthew effect ( Rigney, 2010 ). Accumulating advantages and disadvantages, of course, are only one possible developmental pattern. A compensatory model would predict that initial reading level would be negatively related to rate of growth in reading skill so that differences in reading skill would decrease over time, effectively the opposite of a Matthew effect ( Pfost, Hattie, Dorfler, & Artelt, 2014 ). A third possibility would be a stable achievement pattern, with high and low skill readers having the same rates of growth over development ( Pfost et al., 2014 ).

This study concerns one specific prediction of the Matthew effect model, namely, that reading skill in general, and word reading skill in particular, could be related to the rate of vocabulary growth. Vocabulary skill is strongly related to a variety of academic, vocational, and social outcomes ( Dollinger, Matyja, & Huber, 2008 ; Gertner, Rice, & Hadley, 1994 ; Rohde & Thompson, 2007 ). The veracity of this prediction of the Matthew effect model is significant because it could help guide interventions for children at risk of poor vocabulary development. The current study includes children sampled from a large epidemiologic study, which includes children with language impairments and cognitive impairments.

The prediction that reading skill could be associated with rate of vocabulary growth is based on the premise that reading development could potentially have a significant effect on a child's exposure to novel words. In fact, there is empirical evidence that, for older children and adults, much learning of new words occurs through exposure to written texts ( Nagy, Herman, & Anderson, 1985 ; Sternberg, 1987 ). Because print material generally contains many more low frequency words than does spoken language ( Cunningham, 2005 ), reading text can provide key opportunities for advancement in vocabulary development. We predict that word learning through reading will affect vocabulary as measured on both oral and written tasks because words learned through reading text will be at least partially available to the individual for both written and oral language use ( Nelson, Michal, & Perfetti, 2005 ).

However, exposure to novel words in text does not occur uniformly throughout reading development. Prior to formal literacy instruction, children are clearly acquiring novel vocabulary through exposure to oral language. During early reading development, children rarely confront words in print that are not already present in their vocabulary, so much of the lexical knowledge of words, especially phonological and semantic representations, will be derived from oral language experience. As children become more proficient readers and advance to more complex print material, they are more likely to confront words during reading that they have not been exposed to via listening. This transition likely occurs around the third or fourth grade for many students ( Chall, 1987 ). Biemiller (2005) , for example, reported that, from the third grade onward, but not in earlier grades, 95% of children could read more words than they could explain.

The Existence of a Matthew Effect for Vocabulary

According to one of the predictions of the Matthew effect model, vocabulary development after the third or fourth grade would be affected by reading ability and the associated reading experiences enabled by these reading skills. This study investigates a rather straightforward prediction with respect to vocabulary development and reading during the middle grades and high school. We predict that better readers during this time will have a greater likelihood of confronting novel, low-frequency words than will weak readers and that this will affect the rate of vocabulary growth. This prediction is predicated on the notion that strong readers will engage in more reading activities than will weak readers. This assumption is consistent with Stanovich's (1986) proposal that the volume of reading experience is the key mediating variable between reading skill (broadly conceived) and vocabulary, with cumulative advantages occurring due to “the effect of reading volume on vocabulary growth, combined with large skill differences in reading volume” (p. 381). There is empirical evidence to support the assumption that reading skill and the amount of reading experience are strongly associated. For example, Allington (1983) reported that strong 1st-grade readers read three times as many words during reading instruction as do weak readers. Nagy and Anderson (1984) suggested that a motivated middle-school student might read 100 times more words a year in the classroom than a less skilled or motivated student. With respect to reading for pleasure, Juel (1988) reported that average and strong readers in the third and fourth grades read at home more times per week than did weak readers, and Martin-Chang and Gould (2008) reported correlations between reading speed (words per minute) and personal reading experience in undergraduate students.

A small number of studies have previously investigated a Matthew effect with vocabulary as an outcome variable. Aarnoutse and van Leeuwe (2000) reported that weak readers showed larger effect sizes in vocabulary growth than did strong readers in early elementary grades, thus leading the authors to question a Matthew effect of reading on vocabulary. Vocabulary was measured in a written format; thus, reading ability could have confounded the measure of vocabulary. In contrast, Cain and Oakhill (2011) reported that readers who had weak reading comprehension skills showed lower rates of vocabulary growth between the ages of 8 and 16, compared with good comprehenders, and concluded that there was a Matthew effect for reading skill on vocabulary. In this case, vocabulary was measured via both word reading and listening vocabulary. In a similar manner, Kempe, Eriksson-Gustavsson, and Samuelsson (2011) reported evidence of a Matthew effect on the growth of vocabulary in the 1st to third grades, as measured orally using the Wechsler Intelligence Scale for Children–Third Edition ( Wechsler, 1991 ). In addition, Stothard, Snowling, Bishop, Chipchase, and Kaplan (1998) reported a decrease in scores on the British Vocabulary Scale ( Dunn, Dunn, Whetton, & Pintilie, 1982 ) between ages 8 and 15 for children who had been classified as having persistent specific language impairment and general delay, but not for children whose language was within the expected range or for children whose early language concerns had resolved by age 5 years. None of these studies used developmental scaling to equate item difficulty across different age groups. Further, none of the afore-mentioned studies controlled for rate of vocabulary learning prior to literacy instruction. It is reasonable to expect that the various factors that contribute to these individual differences in word learning in early life might continue to exert effects on word learning when reading. There are, in fact, substantial differences in word-learning achievement in prereaders (e.g., Hart & Risley, 1995 ), which would affect the level of vocabulary knowledge when children start to learn new words through written language. Furthermore, these individual differences in word-learning skills would be expected to covary with reading skill, given the substantial overlap between disorders of word reading and of language skills ( Catts, Adlof, Hogan, & Ellis Weismer, 2005 ). In order to examine the specific effect of reading experience on vocabulary, it would seem wise to control for the child's general word-learning achievement. Thus, the evidence for a Matthew effect on vocabulary is mixed and is possibly confounded by word-learning abilities in general.

The above discussion concerns the effect of reading skill on vocabulary growth, which is only one prediction of the Matthew effect model. Other predictions of the model have also been tested, with similarly equivocal results ( Pfost et al., 2014 ). Some studies report data that support a Matthew effect for reading ability ( Juel, 1988 ), but others report a stable achievement pattern ( Aarnoutse & van Leeuwe, 2000 ; Catts, Adlof, & Fey, 2003 ; Scarborough & Parker, 2003 ; Shaywitz et al., 1995 ) or a compensatory effect ( Parrila, Auonola, Leskinen, Nurmi, & Kirby, 2005 ; Shaywitz et al., 1995 ). The diversity of findings in these studies is undoubtedly related to the wide variety of outcome variables and ages of readers as well as to the characteristics of the sample group and study methodologies. Indeed, some studies do report different conclusions on the basis of the outcome variable studied ( Bast & Reitsma, 1998 ; Shaywitz et al., 1995 ), the subgroup of children looked at ( Jacobson, 1999 ; Morgan, Farkas, & Hibel, 2008 ; Phillips, Norris, Osmond, & Maynard, 2002 ; Stothard et al., 1998 ), and even the language in which children were learning to read ( Parrila et al., 2005 ). In addition, a recent meta-analysis ( Pfost et al., 2014 ) concluded that the psychometric properties of the measures were also important: studies using measures without floor or ceiling effects and with good reliability were more likely to report the presence of a Matthew effect. As a final consideration, the populations studied may have differed in amount or kind of intervention received. Hence, although the Matthew effect model has been a very helpful framework for researchers, educators, and clinicians alike, evidence for it has remained elusive ( Pfost et al., 2014 ; Scarborough & Parker, 2003 ).

Where a Matthew effect is reported, there is more than one possible pattern because the effect of initial reading skill on subsequent growth rates may not necessarily be the same across the continuum of reading skill ( Protopapas, Sideridis, Mouzaki, & Simos, 2011 ; Rigney, 2010 ). On the one hand, strong readers might show increasing gains relative to average readers at the same time as weak readers show decreasing gains relative to average readers. We refer to this as a two-sided Matthew effect . On the other hand, strong readers could show increasing gains relative to average readers, whereas weak readers have gains similar in size to those of average readers. The reverse of this pattern is also possible in which weak readers show slower growth rates than average readers without strong readers showing faster growth rates (e.g., Morgan et al., 2008 ). These last two possibilities have been termed one-sided Matthew effects ( Morgan et al., 2008 ), and we describe them as such.

It is clear that the selection of outcome and predictor variables is of critical importance in tests of a Matthew effect. Stanovich's (1986) proposal about reading and vocabulary considered reading in a broad sense. In this study, word reading (of nonwords and single words) is used to operationalize reading skill. The rationale for using word-reading skill as a predictor variable is simply that is expected to be less confounded with vocabulary than reading comprehension scores would be because reading comprehension and vocabulary scores are highly correlated (e.g., Pearson, Hiebert, & Kamil, 2007 ). The use of word-reading scores therefore allows for a clearer interpretation of the data. Likewise, vocabulary can be defined in different ways, including across receptive and expressive dimensions. The data set used in this study has been previously analyzed for receptive/expressive dimensionality using revised modified parallel analysis and confirmatory factor analysis ( Tomblin & Zhang, 2006 ). This analysis concluded that the measures used in the study “are not likely to be able to reflect reliable differences within individuals with respect to receptive and expressive modalities” (p. 1206). Hence, despite the use of different tasks in receptive and expressive vocabulary measures in this study, the latent trait measured does not seem to be different. Therefore, in this study, vocabulary skill is operationalized as a composite score, including both receptive and expressive measures.

This study will test the specific prediction that rate of vocabulary growth is related to reading skill by examining the growth in oral vocabulary in an epidemiologically based sample between the fourth and 10th grades among children with a wide range of reading abilities, established at the fourth grade. The first specific question of this study is, is there evidence that fourth-grade word-reading skill is related to the rate of change of vocabulary growth between the fourth and 10th grades after accounting for individual differences in the level of vocabulary acquisition prior to reading instruction? In the current study, vocabulary skill in kindergarten is used as a measure of these individual differences in word learning prior to formal reading instruction. The hypothesis, based on Stanovich's (1986) model, is that that there will be a relationship between fourth-grade reading skill and the rate of vocabulary growth in the years between the fourth and 10th grades.

The second specific question of this study is, if there is a relationship between reading skill and vocabulary growth, is this relationship the same for both strong and weak readers? In other words, if a Matthew effect exists, is it a one-sided or a two-sided Matthew effect? There was no hypothesis for the second question in this study because no previous research has addressed this specific question and there might be some reason to expect either a two-sided or a one-sided Mathew effect. As Shefelbine (1990) pointed out, readers with lower initial vocabulary knowledge will necessarily have an impoverished semantic context for inferring new word meaning, which might lead to lower rates of vocabulary growth. On the other hand, those same readers are less likely to encounter ceiling effects because any given text is more likely to include words that are novel to them. This argument made by Shefelbine (1990) , however, concerns the effect of initial vocabulary skill on vocabulary growth. This is in contrast to the current study, which addresses the relationship of reading skill and vocabulary growth.

The data analyzed in the current study were drawn from a sample of 604 participants who originally took part in an epidemiologic study of language impairment ( Tomblin et al., 1997 ). The original epidemiologic sample participated in the 1993–1994 school year and consisted of 7,218 kindergarten students, representing all available kindergarten students who were monolingual English speakers in selected schools in rural, urban, and suburban areas in Iowa and Illinois. In this initial sample, a stratified cluster sample was used, with stratification by residential setting and cluster sampling according to school ( Tomblin, 2014 ). All students who failed the initial screening were given a diagnostic battery of language and cognitive measures, as were a representative sample of students who passed the screening, such that the group who passed the screening battery and the group who did not were of equal size. Each of these participants was recruited to be part of the longitudinal study, and all who consented became participants in the longitudinal study. All children who completed the longitudinal study and for whom vocabulary scores were available ( n = 485) were included in this sample. The children in fourth grade averaged 10.0 years ( SD = 0.40), and in the 10th grade, they averaged 15.8 years ( SD = 0.37).

The original sample of 485 children contained an oversample of children with poor language abilities. Because this oversampling was applied systematically to a population sample, it was possible to derive a weighting system that adjusted for this; that is, scores were weighted by multiplying each child's score by a constant that was equal to the expected prevalence of that diagnostic category and gender divided by the actual prevalence of those children in the sample. In this manner, children with poor language received proportionally less weight in the analyses than did children who showed typical language, a weighting procedure has been described in other published work involving the sample ( Catts et al., 1999 , 2005 ). The resulting sample of 485 children contained an equal proportion of boys and girls (50% of each). The distribution of the mothers' educational level was as follows: 4% had less than a 4-year high school education, 28% had a high school diploma, 41% had postsecondary education, 15% were college graduates, and 12% had postgraduate education.

As shown in Table 1 , standardized language measures in the fourth grade and performance IQ measured in the second grade before weighting were below the expected population means. However, after weighting the samples, they are very representative of a normal population. The current study uses data from all participants, with weighted measures for all analyses.

Descriptive statistics of sample with regard to oral language measures in the fourth grade and performance IQ obtained in the second grade.

All tasks were administered as part of a larger longitudinal study (for a complete description, see Tomblin & Nippold, 2014 ). Administration of tasks was standardized, and each examiner was given detailed training and monitoring by a data-collection manager, with a minimum of 5% of examination sessions scored blindly by both the examiner and the data collection manager to ensure consistency in scoring, as well as in administration ( Tomblin, 2014 ). Scoring of all tasks was done relative to the child's age at the time of testing.

For the present study, the following vocabulary measures were analyzed: in kindergarten, the Picture Identification and Oral Vocabulary subtests of the Test of Language Development–Primary: Second Edition ( Newcomer & Hammill, 1988 ), and in older grades, the Peabody Picture Vocabulary Test–Revised (PPVT-R; Dunn & Dunn, 1981 ) as well as the Expressive subtest of the Comprehensive Receptive and Expressive Vocabulary Test (CREVT; Wallace & Hammill, 1994 ). Receptive vocabulary measures were picture identification tasks, and expressive vocabulary measures were definition-generation tasks. Each of these is a well-established standardized measure, and information about their validity, specific to this data set, has been published ( Tomblin, Nippold, Fey, & Zhang, 2014 ).

For the present study, the following reading measures were analyzed: the Word Attack (WA) and Word Identification (WI) subtests of the Woodcock Reading Mastery Test–Revised ( Woodcock, 1987 ), which involve reading nonwords (WA) and sight words (WI). These measures are considered to be reliable assessments of word-reading skill ( Cooter, 1989 ).

Composite Developmental Ability Scores

Analysis of growth in a cognitive ability such as vocabulary requires that the children's performance be scaled on a continuum across the developmental period of interest. The principal challenge for the creation of a developmental scale is that the ability of the children must be measured by different items at different developmental time points; thus, the items need to be equated with each other in some meaningful way across development. In this study, developmental ability scores were computed using a Rasch model of item response theory (IRT). The resulting scores are often viewed as being well suited for growth curve modeling ( O'Malley, Francis, Foorman, Fletcher, & Swank, 2002 ). Within IRT, the probability of an item being passed in a test is a function of the participant's ability level, the item's difficulty, as well as its discrimination and the probability of guessing. When calibrating ( Mislevy & Bock, 1998 ), guessing can be set as a constant, and the probability for given items can be calculated from the administration of test items to participants. Thus, item difficulty could be calculated by holding examinee's ability constant. This is termed item calibration ( Mislevy & Bock, 1998 ). Items that were administered across more than one grade level, and which had overall pass rates of between 10% and 90%, were used as anchors ( Vale, 1986 ) for this item calibration. These anchor items were then used to calibrate item difficulty across age levels. For example, if Items 8 and 9 were given to fourth graders, and Items 9 and 10 were given to eighth graders, Items 8 and 10 can be calibrated via their overlap with Item 9 across grades. Table 2 provides a list of the specific items from the PPVT-R and the CREVT at each grade level used in the item calibration, resulting in Rasch-scaled vocabulary ability scores across the fourth to the 10th grades. The difficulty and the discriminating estimates for these items, along with estimates of expressive and receptive vocabulary ability for each examinee at each grade level, were computed using the computer program Bilog ( Mislevy & Bock, 1998 ). Item parameters were determined using marginal maximum likelihood estimation. The 0 value on the scale was set for the average 6-year-old. Resulting ability scores provided a means of measuring the examinees' ability across time.

Items from the Peabody Picture Vocabulary Test–Revised (PPVT-R) and the Comprehensive Receptive Expressive Vocabulary Test (CREVT) used in the item calibration.

Weighted Scores

As described above, weighted scores were used in the analyses of this study to correct for the high rate of language and/or cognitive impairment. This weighted scoring procedure is possible because of the availability of data from the carefully sampled pool of participants in the epidemiological sample. This ensures that the data analyzed in this study are representative of the epidemiological sample, including children with and without a history of language impairment.

Composite Scores

A composite score was derived for vocabulary for each participant, as discussed earlier. The composite was the mean of the developmental ability scores for receptive and expressive vocabulary. These composite scores were used to plot vocabulary growth curves.

In a similar vein, a composite score for word reading was calculated from the WA and WI scores at the fourth grade. A composite of these scores was used to incorporate the earlier developing skill of reading nonwords with the later developing skill of context-free word recognition ( Tunmer & Chapman, 2012 ). Within the context of this study, these skills were used to index basic reading skills in the fourth grade. We expect that these skills are also indirectly indicative of the volume and variety of reading experience that these children will obtain after the fourth grade. This assumption is supported by a meta-analysis by Mol and Bus (2011) that indicated moderate correlations between print exposure and measures of WI and WA during elementary school years. Because the word-reading scores were part of the analysis at a single time point only, developmental scores were not required.

Multilevel modeling . Multilevel modeling was used to test the questions in this study, a method that is expected to yield comparable results to latent growth curve analysis ( Chou, Bentler, & Pentz, 1998 ). Multilevel modeling of the weighted data in this study consisted of fitting each participant's vocabulary ability across the fourth, eighth, and 10th grades with parameters of intercept and linear slope. These parameters served as random effects in combination with a fixed effect of fourth-grade word reading as well as with the covariate of kindergarten vocabulary and their interactions with time (age) in a mixed model analysis using Proc Mixed software ( SAS Institute, 2011 ).

The particular question of interest was whether the slope in vocabulary differed in accord with variation in fourth grade word reading. However, it could be argued that any association between word reading and vocabulary growth in later school years was merely because strong word learners become strong readers. To the extent that this is the case, the basis for the relationship would not be attributable to a special influence of reading on vocabulary. To address this, we also included the kindergarten vocabulary abilities of these children in this analysis as a covariate in this model on both the slope and the intercept. This provides a test of whether word reading is related to vocabulary after controlling for the children's word-learning achievement during the years prior to formal reading instruction. This was considered to be a direct test of the long-term relationship between word-reading skill and vocabulary development.

Because word reading was related to the rate of vocabulary growth, we computed the effect size in the form of f 2 , which reflects the amount of variance in individual differences in vocabulary explained by fourth-grade reading after controlling for kindergarten vocabulary. This measure of the effect of reading on vocabulary growth concerns differences in slopes. A key feature of differential growth rates is that the individual differences accumulate over time; thus, the effect of the predictor variable—in this case, fourth-grade reading—on the outcome variable is likely to increase. Therefore, we measured the degree of association between fourth-grade word-reading ability and 10th-grade vocabulary after controlling for fourth-grade vocabulary ability.

Individual differences in vocabulary growth . Question 2 asked whether the effects of fourth-grade word reading on vocabulary growth were equally distributed across the range of word-reading ability. To do this, growth rates were contrasted between three groups of children categorized according to whether they had high, medium, or low fourth-grade word-reading ability. Vocabulary growth curves were plotted for participants with high word-reading skill (those who scored in the 80th percentile and above), middle word-reading skill (those who scored in the 40th–60th percentile range), and low word-reading skill (those who scored in the 20th percentile and below). We then used mixed modeling to contrast the middle group with the high and low groups with regard to growth rates.

Vocabulary Growth Curves

As expected, the mean of the composite developmental ability scores for vocabulary showed an increase in vocabulary knowledge at each time interval, beginning in kindergarten ( Figure 1 ). The average vocabulary score for the fourth-grade children was 2.26 ( SD = 0.56) and was 3.59 ( SD = 0.61) by the 10th grade. Figure 1 shows that the shape of the growth function was clearly nonlinear, with higher rates of vocabulary growth in early grades. However, between the fourth and 10th grades, the change was much more linear; thus, a linear model of vocabulary growth during this period of development was suitable. Figure 2 shows the mean vocabulary growth curves for readers with low, medium, and high reading skill in grade 4.

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Distribution of developmental ability scores for vocabulary at each observational interval from kindergarten through 10th grade for all children in the longitudinal study

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Vocabulary scores of participants grouped by word-reading skill (high-level readers, readers in the 80th percentile and above; midlevel readers, readers in the 40th–60th percentile range; low-level readers, readers in the 20th percentile or below).

As anticipated, vocabulary ability upon school entry at kindergarten was correlated with vocabulary ability at fourth ( r = .39, n = 485, p < .0001), eighth ( r = .52 n = 485, p < .0001), and 10th grades ( r = .55, n = 485, p < .0001). These correlations show that vocabulary ability at the onset of reading is associated with subsequent vocabulary ability, and therefore it is likely that there are factors influencing vocabulary growth in children that are not an outgrowth of their reading. In the subsequent analyses, the child's vocabulary ability in kindergarten will be used to represent these non–reading-related vocabulary learning skills and will be used as a covariate in order to better isolate later growth in vocabulary that is associated with reading ability.

Multilevel modeling using Proc Mixed software was used to test for differences in vocabulary growth across time where the child's age at testing was used to reference time. The results of this modeling are shown in Table 3 . These results show that the mean vocabulary intercept (average vocabulary at age 9) before entering covariates (unconditional model) was 2.16 units of developmental ability score, and the mean growth rate was 0.24 points per year. Plots of the modeled values from a random sample of children at different levels of fourth-grade reading levels are shown ( Figure 3 ). Because a linear model was used, these growth functions do not have the nonlinear quality of the data in Figures 1 and ​ and2 2 but, otherwise, these modeled data are similar to the obtained data.

Tests of random (Level 1) and fixed effects for vocabulary growth using kindergarten vocabulary as a covariate.

Note.  KV = kindergarten vocabulary; 4GR = fourth grade reading.

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Linear growth functions for random samples of readers for readers in high (80th percentile and above), medium (40th–60th percentile range), and low (20th percentile or below) skill groups for word reading in fourth grade.

Our first question concerned the degree to which fourth-grade reading is associated with vocabulary development (rate of change of vocabulary scores). This was tested within a conditional mixed model as also shown in Table 3 . Table 3 shows that after controlling for their kindergarten vocabulary level, the rate of growth in vocabulary between the fourth and 10th grades was significantly associated with the children's fourth-grade reading level, F (1, 485) = 15.88, p < .0001. The parameter value for this effect was .001, which indicates that higher word reading ability in the fourth grade is associated with greater rates of vocabulary growth, which can be seen in Figure 2 . It should be emphasized that this effect was estimated after the sources of variance concerned with kindergarten reading on overall vocabulary and change in vocabulary between the fourth and 10th grades had been entered into the model. Individual differences in kindergarten vocabulary also had a significant effect on the intercept of vocabulary score at the fourth grade, F (1, 485) = 19.60, p < .0001, and on the growth of vocabulary, F (1, 485) = 6.64, p = .01. Thus, children with higher vocabulary in kindergarten were likely to have higher vocabulary in the fourth grade and show greater rates of vocabulary growth after controlling for the effects of fourth-grade reading ability.

The slope parameter was found to be 0.001. This value represents the rate of change in vocabulary ability scores per year from the fourth through 10th grades that can be attributed to a 1-point change in fourth-grade word-reading skill. The average change in vocabulary ability across the 6 years was 1.38; however, some children changed by as much as 3.62 points and some actually declined by as much as −0.018. The relative size of the effect of fourth-grade reading ability on vocabulary growth compared with the overall growth in vocabulary can be represented using Cohen's f 2 , which reflects the proportion of variance of a single variable within the context of a multivariate regression model. Using a method developed by Selya, Rose, Dierker, Hedeker, and Mermelstein (2012) , we estimated that the individual differences in fourth-grade reading ability accounted for 8% ( f 2 = .08) of the variance in vocabulary growth rates from the fourth to 10th grades. Cohen's f 2 of this size are generally regarded as small to medium in magnitude.

The effect size above reflects the degree to which fourth-grade word reading accounts for variation in the slopes of vocabulary growth across children. Although this effect size is somewhat small, we need to consider that differences in growth are likely to accrue over time. Thus, even small differences in growth rates can lead to substantial long-term effects in absolute vocabulary skill. In order to examine this cumulative effect of differential growth, we computed the magnitude of the effect of fourth-grade word reading at 10th-grade vocabulary after controlling for fourth-grade vocabulary. Thus, this reflects the gain in the effect of reading on vocabulary between the fourth and 10th grades. This resulted in an η 2 partial = .26. Eta squared values of this magnitude are viewed as large, and thus we can see that small to moderate effect size of differential vocabulary growth can result in a large effect given sufficient time.

We can also interpret the magnitude of this effect by comparing this effect size to something that is more familiar. In this case, we can compare the effect of mother's education level on vocabulary development during this same period. It is known that socioeconomic status is related to early vocabulary levels (e.g., Hart & Risley, 1995 ), and we would expect that the effect of maternal education would also extend into the school years. Using the same approach to compute f 2 , we estimated the effect size for maternal education on vocabulary growth between the fourth and 10th grades and found that it was f 2 = .08. Thus, the effect obtained for fourth-grade reading ability on vocabulary is the same as that for maternal education.

The analysis above introduces the question of whether maternal education could be confounded with fourth-grade reading ability and whether this is the reason the effect sizes are similar. In this case, it could be argued that it is the child's home environment that explains the differential growth in vocabulary. However, in our test of reading effects on vocabulary between the fourth and 10th grades, we had controlled for kindergarten vocabulary, and one of the reasons for this was to control for socioeconomic factors that influence vocabulary growth. We tested this assumption by introducing both mother's education and kindergarten vocabulary in the same model and found that mother's education was not a significant predictor, F (4, 474) = 0.24, p = .91, of vocabulary growth after including kindergarten vocabulary. Thus, our inclusion of kindergarten vocabulary did effectively serve as a proxy variable for mothers' education.

The second question asked whether growth rates in vocabulary differed for the three groups of readers. This was addressed by performing a multilevel modeling analysis where the three groups of readers (high, medium, and low) were identified according to their fourth-grade word reading. Figure 2 is a plot of vocabulary growth functions for high-, medium-, and low-skill readers (as defined earlier). A pattern of divergence was shown. The significant effect of fourth-grade reading on growth confirms that differential growth in vocabulary exists in accord with fourth-grade reading; however, this differential could be concentrated in one region of reading ability. Contrasts in the group vocabulary growth between the low-level readers and the midlevel readers showed that the growth slope of the low readers was −0.02 ( SE = 0.0158) lower than that for the midlevel group, which was not significantly different, t (289) = 1.25, p = .21. In contrast, the growth slope of the high-level readers compared with the midlevel readers was 0.04 ( SE = 0.0160) higher, which was significantly different, t (289) = 2.18 , p = .03. These results suggest that the association of fourth-grade reading ability and subsequent vocabulary growth varied somewhat depending on the reading level; that is, the effect was a one-sided, not a two-sided, Matthew effect. In this case, the readers in the upper 20 percentile showed divergence in vocabulary growth relative to those in the middle or low levels of the reading ability distribution.

Relationship of Reading to Vocabulary Growth

The first specific question of this study was whether there was evidence that fourth-grade word-reading skill was related to the rate of change of vocabulary growth between the fourth and 10th grades after accounting for individual differences in vocabulary acquisition prior to reading instruction. Our results strongly support an association between word-reading ability and the rate of subsequent vocabulary growth as measured via an oral language task. It is quite unlikely, however, that word-reading ability in the fourth grade alone is sufficient to explain these results. Instead, we view our measure of fourth-grade reading ability as an indicator variable that is associated with reading-related activities of the children that unfolded between the fourth and 10th grades. These reading-related activities serve as the primary causes of vocabulary growth found in this study. We might add that the type of text the child is reading is also expected to be a variable because reading material that exposes the child to a wider range of vocabulary should also benefit vocabulary growth. Related to this point, Pfost, Dorfler, and Artelt (2013) reported that time reading narratives was much more predictive of vocabulary than was time reading newspapers, magazines, comics, or nonfiction. Thus, the results of this analysis are consistent with Stanovich's (1986) proposal as well as with that of Nagy et al.'s (1985) view that vocabulary growth during school years is largely due to incidental learning from written contexts. Given the importance of reading activity, we would ideally have measured these variables. Within this project, several measures of engagement in reading, such as author recognition, were collected but were found to be of questionable validity. However, other studies have shown an association between reading skill and the volume of reading experience ( Allington, 1983 ; Martin-Chang & Gould, 2008 ; Nagy & Anderson, 1984 ). Nonetheless, although we assume that reading experience is a mediator of the relationship between word reading and the outcome of vocabulary growth, this mediation was not tested as part of this study. Therefore, the results of the current study do not allow us to draw conclusions about whether reading experience is, indeed, the mediator of the effect we found.

Once kindergarten vocabulary levels were accounted for, word reading in the fourth grade accounted for 8% of total variance in rates of vocabulary growth between the fourth and 10th grades. This means that the effect of word reading on vocabulary growth is not trivial. In fact, the size of the effect of word reading on vocabulary growth rates is comparable to the effect of maternal education on vocabulary growth rates during the same developmental period. When the impact of that rate difference is considered in terms of absolute vocabulary levels in the 10th grade, the effect is large.

As Stanovich (2000) stated, his 1986 article contains “many micropredictions and microtheories” (p. 150). Previous studies of other Matthew effects have reported variable results. There might be several reasons for these equivocal results for Matthew effects in previous studies. First, one would not expect to find Matthew effects for all reading-related variables. Paris (2005) defined constrained skills as skills that are limited in scope, are learned quickly, and require the same material to be mastered by all learners, and argued that developmentally constrained skills “should not be conceptualized as enduring individual difference variables” (p. 184). Where outcome variables in other studies were constrained skills, such as word attack skills, one might not expect to find meaningful differences, especially for older or more skilled readers. Reading comprehension, on the other hand, is affected by different component skills through reading development. For very early readers, reading comprehension skill is largely a function of word reading or decoding skill. For more advanced readers, language comprehension skills make a more substantial contribution to reading comprehension. Because the components affecting reading comprehension scores differ in their contribution through development, longitudinal comparisons of reading comprehension skills may or may not show a Matthew effect. These challenges are compounded when combined measures of word reading and reading comprehension are used. Hence, it is possible that some previous studies have not found evidence to support the existence of a Matthew effect because the outcome measures were either developmentally constrained or were developmentally less constrained but were measured in age ranges before the effects would be expected to occur. This analysis would be supported by the meta-analysis of Pfost and colleagues ( Pfost et al., 2014 ), which suggested that there was less evidence for a Matthew effect for developmentally constrained variables such as decoding accuracy. In the case of the current study, reading would be expected to affect vocabulary growth after children are exposed to a large number of novel words through reading, beginning at about the third or fourth grade. This is the developmental point investigated in this study.

Second, as discussed earlier, previous studies of a Matthew effect for vocabulary did not control for word-learning skills prior to formal reading instruction. Indeed, the results of the current study indicate that this variable has a significant effect on the rate of vocabulary growth in the years between the fourth and 10th grades. This may be another reason for the variable findings in previous studies.

Third, the current study used developmental ability scores based on IRT to allow for meaningful comparisons between performance at different age groups, which was not true of previous studies of a Matthew effect for vocabulary. The rationale for the use of IRT-based scores was that they appear to have the best properties, such as an equal-appearing interval scale, for characterizing the growth of mental abilities. Concerns have been raised as to whether these scores are likely to show declining variance with increases in age, whereas grade-equivalence scores seem to produce increasing variance (e.g., Hoover, 1984 ; Yen, 1986 ). These patterns, however, have not been consistently reproduced ( Williams, Pommerich, & Thissen, 1998 ), and it remains unclear whether, or under what circumstances, IRT scores or other forms of developmental scores misrepresent the changes in ability over time. Nonetheless, the use of IRT (Rasch) scores has been critiqued in investigations of a Matthew effect fan spread ( Bast & Reitsma, 1998 ; Stanovich, 2000 ) on the grounds that forcing within-age scores into a normal distribution could cause a decrease in developmental score variance with age ( Hoover, 1984 ). For example, Stanovich (2000) proposed that the use of developmental ability scores could account for the compensatory effect found for reading scores in the study by Shaywitz et al. (1995) . In the current study, the use of developmental ability scores did not result in a decline in variance, and thus did not prohibit our ability to detect an effect of word-reading ability on vocabulary growth. It may be that the results of Shaywitz et al. (1995) with respect to reading are due to the use of a reading composite score that includes word identification, pseudoword identification, and reading comprehension. As Bast and Reitsma (1998) also argued, a composite score with these three skills would not have comparable meaning over time, which significantly obscures the interpretation of the results.

Also, the current study used an epidemiologically based sample. This study was conducted with a group of children who came from a population sample and are therefore more diverse than are often found in research studies, especially where participants need to come into a laboratory setting. Thus, the findings of the present study are more likely to be representative of the population at large.

Relationship Between Reading and Vocabulary Growth Across Reading Skill Levels

The second question of this study was whether the relationship between reading skill and vocabulary growth was the same for both strong and weak readers. Indeed, further examination of the data revealed that the effect of early word-reading ability on vocabulary was not uniform across different levels of initial word-reading ability. Instead, it would appear that the strong readers made greater vocabulary gains relative to the average and weak readers. In the language of the Matthew effect, the rich were getting richer due to their better reading, but the poor were not getting poorer due to their weak reading. Morgan et al. (2008) also reported a Matthew effect that did not apply to both strong and weak readers although they reported asymmetry in the opposite direction, with students most at risk of reading disorders being more likely to fall behind in reading, whereas those least at risk not gaining with respect to typical readers. A different prediction of the Matthew effect model was being tested in this study, and this is likely to account for the difference in results.

In the current study, several factors might account for this one-sided Matthew effect, with a nonuniform effect of word-reading skill on vocabulary growth across skill levels. The current study does not differentiate between these possibilities and, naturally, they are not mutually exclusive. The first possibility is that the gap in reading volume between strong and average readers is greater than the gap in reading volume between average and weak readers. The possibility that there are larger differences in reading volume between strong and average readers, compared to the differences between average and weak readers, is somewhat speculative. However, Cunningham (2005) discussed data indicating that, for independent reading in fifth-grade students, the absolute differences between avid and average readers (90th and 50th percentiles for reading volume) are greater than are the absolute differences between average and weak readers (50th and 10th percentile for reading volume). This would be consistent with the hypothesis that differences in reading experiences are not in a linear relationship with skill level. In addition to the amount of reading in which individual children engage, it may also be that the reading material selected by strong readers contains a greater degree of novel vocabulary than does the material assigned to, or selected by, average or weak readers.

The second possibility is that students differ in the amount that they benefit from reading new words and that those individual differences are greatest between average and strong readers. There is evidence that children differ in their ability to derive word meanings from written contexts ( Cain, Oakhill, & Elbro, 2003 ; Cain, Oakhill, & Lemmon, 2004 ; McKeown, 1985 ). Individual differences in word learning through text are related to differences in working memory and to the ability to learn new vocabulary in a direct instruction task ( Cain et al., 2004 ). The existence of these individual differences motivates interventions to improve children's skill in deriving word meanings from context ( Cain, 2007 ; Goerss, Beck, & McKeown, 1999 ; Nash & Snowling, 2006 ). Genetic evidence also provides support for the idea that environmental factors may have a nonuniform effect on vocabulary growth across skill levels. DeThorne, Petrill, Hayiou-Thomas, and Plomin (2005) reported that children with very low vocabulary scores had a higher heritability and a lower influence of shared environment, relative to children with less severe vocabulary deficits. Again, the possibility that these individual differences are greater between strong and average readers, compared to the differences between weak and average readers, is speculative.

It is also possible that weak readers were provided with educational interventions for reading skill or vocabulary knowledge, which reduced the cumulative disadvantage effect for them. The current study does not include information about intervention history, so this is speculative. However, this data suggests that the combination of behaviors chosen by students, differences in the ability to learn from exposure to new words in text, and educational policies are not further disadvantaging weak readers, at least in terms of their vocabulary growth. For those who are concerned about the poor getting poorer, this is an encouraging finding.

Limitations of the Current Study

As with any nonexperimental design, these conclusions are based on associations rather than on stronger experimental evidence involving random assignment to independent variable treatment conditions. The limitation of an observational design, such as this study, is that other confounding variables may play a role in observed effects. One such confounder could be the initial vocabulary level. Children with better word-reading skills in the fourth grade are also likely to have better listening vocabulary, as was true of the participants in this study. As a result, our analysis incorporated a measure of kindergarten-listening vocabulary ability as a covariate. This analysis is possible, in part, because the current study analyzes data from a large longitudinal sample of 485 participants, which provides adequate statistical power. We can assume that this measure of vocabulary in kindergarten was largely unaffected by the child's reading experience, but would reflect the child's general vocabulary–learning ability along with aspects of the child's environment that could be associated with individual differences in word learning. Thus, we can argue that the effects of fourth-grade reading ability on subsequent listening vocabulary are likely to be independent of the child's general vocabulary–learning ability.

Another limitation of the current study is the use of a linear model, which means that the vocabulary data between the fourth and 10th grades was fit using only a linear slope and intercept. However, the overall vocabulary scores between kindergarten and 10th grade suggest a curvilinear trend, and it is possible that the data might be better represented by a nonlinear model, but this would require data at more time points than is available with this data set. This means that the current analysis cannot address questions that are specific to acceleration or deceleration of vocabulary growth rate, but instead captures the primary feature of the growth trajectory, namely overall change through time.

The purpose of the original longitudinal study was to answer questions regarding outcomes of children with language impairment. The oversampling of children with language and/or cognitive impairments could potentially have biased the results of the current study. However, this was accounted for with the use of weighted scores. The findings, therefore, apply to both children and adolescents who were language impaired and typically developing.

The principal finding of this study is that fourth-grade reading-word skill was related to the rate of change in vocabulary growth between the fourth and 10th grades, controlling for preliterate vocabulary skill. We interpret measures of word reading in the fourth grade as being an indicator variable for a variety of reading-related activities occurring during and after the fourth grade, which would affect exposure to new words. The analysis controlled for vocabulary levels prior to formal reading instruction and used developmental scores based on IRT, addressing two potential limitations in studies of Matthew effects. Data in the current study was collected from a population-based sample, meaning that these findings apply to both readers who are typically developing and language impaired. Hence, the current study provides strong support for the existence of a Matthew effect between word-reading skill and vocabulary. It is significant that the magnitude of the effect on absolute vocabulary levels was found to be large. The effect seems to be driven by strong readers, rather than weak readers, an encouraging finding for those concerned about outcomes for weak readers. More broadly, these findings point to the importance of reading to the process of vocabulary acquisition in older children and adolescents.

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Theoretical trends of research on technology and L2 vocabulary learning: A systematic review

  • Published: 11 May 2021
  • Volume 8 , pages 465–483, ( 2021 )

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  • Xinyuan Yang   ORCID: orcid.org/0000-0002-4632-0822 1 ,
  • Li-Jen Kuo   ORCID: orcid.org/0000-0002-8317-4609 1 ,
  • Zohreh R. Eslami   ORCID: orcid.org/0000-0003-2969-5056 2 &
  • Stephanie M. Moody   ORCID: orcid.org/0000-0001-7796-130X 3  

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Vocabulary development is critical for second language (L2) learners in both English as a Second Language (ESL) and English as a Foreign Language (EFL) contexts. Recently, a large body of research has been dedicated to how computer-assisted language learning (CALL) and mobile-assisted language learning (MALL) can facilitate vocabulary knowledge in L2 learners in both EFL and ESL settings. A number of reviews on this topic have been conducted, however, little attention has been given to learners in PreK-12. Also missing from the existing research is an in-depth examination of the theories underlying vocabulary learning within technological programs. However, understanding theoretical foundations of vocabulary learning is critical for both researchers and educators who seek to improve vocabulary development in L2 learners. The current study aims to close these gaps by investigating research on the use of technology for L2 vocabulary learning for learners in PreK-12 between 2011 and 2020. Using systematic review procedures, a total of 80 articles were identified for analysis. Results showed information/cognitive theories were most frequently and explicitly referenced, followed by social theories of learning. Consistent with previous research syntheses on CALL and MALL, many studies did not articulate an explicit theoretical framework used in their research. These findings suggest that research on technology-mediated vocabulary learning for Prek-12 L2 learners should be conducted from more diverse and explicit theoretical perspectives.

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Yang, X., Kuo, LJ., Eslami, Z.R. et al. Theoretical trends of research on technology and L2 vocabulary learning: A systematic review. J. Comput. Educ. 8 , 465–483 (2021). https://doi.org/10.1007/s40692-021-00187-8

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The effectiveness of L2 vocabulary instruction: a meta-analysis

  • Mohammad Hossein Yousefi 1 &
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Asian-Pacific Journal of Second and Foreign Language Education volume  3 , Article number:  21 ( 2018 ) Cite this article

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The purpose of the present meta-analysis is to the investigate the overall effectiveness of L2 vocabulary instruction and to find the moderator variables affecting its effectiveness. By defining a rigorous inclusion and exclusion criteria, a total number of 16 primary studies ( N  = 1008), 7 published and 9 Ph.D. dissertations, were included. Under Random-Effects Model, the overall effect size of ( d  = 0.80) was observed. After conducting Q test of heterogeneity, a number of moderator variables were examined; context of instruction, publication type, age and L2 learners’ proficiency level. It was found that (a) studies conducted in foreign language contexts generated larger effect sizes than ones conducted in SL contexts.(b)intermediated learners show a larger effect size than advanced and elementary students. (c) child learners were better than adult learners in Learning L2 vocabulary. (d) Published studies generated larger effect size than doctoral dissertations. (e) employing “posters” for teaching L2 vocabulary items generated higher effect size than reading activities, CALL, and songs. (f) abstract words generated higher effect size than concrete ones. Possible explanations of the findings are discussed with regard to the similar meta-analyses in the field and directions for future research are proposed.

Introduction

Nowadays, nobody has reservations about the effectiveness of instructed (tutored) language learning. In instructed second language acquisition, the learner typically focuses on some aspect of language system (Klein, 1986 ). Many primary studies conducted in the field of SLA provided support in favor of instructed language learning. In the same vein, a number of meta-analyses demonstrated overall effectiveness of teaching dimensions of second languages. For example, L2 grammar acquisition (Shintani, 2015 ) corrective feedback (Li, 2010 ) and second language strategy instruction (Plonsky, 2011 ).

Undoubtedly, it is generally agreed that language vocabulary is an essential part of learning a second language (Fehr et al., 2012 ; Ko, 2012 ; Nation, 2001 ; Schmitt, 2008 ) and the lexicon may be the most important language component for learners (Hamada & Koda, 2008 ;Yamamoto, 2013 ). Lexical proficiency is also crucial because the understanding of lexical acquisition in relation to its deeper, cognitive functions can lead to increased awareness of how learners process and produce an L2 (Crossley et al., 2009 ). In what follows, we review a number of issues related to L2 vocabulary teaching.

Several meta-analyses have been conducted on some aspects of L2 vocabulary teaching. Huang ( 2010 ) conducted a systematic statistical synthesis of the effects of output stimulus tasks on L2 incidental vocabulary learning. A total of 12 studies were included in this meta-analysis. Results showed that language learners gained more benefit from using output stimulus tasks to learn vocabulary than those who only read a text. For these 16 studies, the mean effect size was 1.39 (SE = .07).

Given the fuzziness of the variables affecting L2 vocabulary learning and in order to gain a more reliable picture of what factors actually affect l2 vocabulary teaching, conducting a quantitative meta-analysis is justified. Because meta-analysis is a standard, well-grounded statistical procedure for combining the evidence from independent studies that address the same research hypothesis (Normand, 1999 ). A meta-analysis has three advantages. First, it provides research findings in a sophisticated fashion, which differs from findings represented in statistical significance. Second, it is able to detect effects that are obscure in narrative summaries of findings. Third, it provides a systematic approach to analyzing information from a large number of research findings (Lipsey & Wilson, 2001 ).

Literature review

In this section, we first review two distinct approaches to L2 vocabulary teaching and critically discuss the empirical studies related to these theoretical underpinnings. Then, we discuss the effects of a number of input and output-based tasks and activities on L2 vocabulary learning. Finally, the related meta-analyses will be subject to critical review.

Many vocabulary learning theories divide vocabulary study into two distinct approaches: explicit vocabulary learning and implicit vocabulary learning (Hulstijin, 2001 ; Nassaji, 2003 ). Incidental vocabulary learning is “learning without an intent to learn, or as the learning of one thing, for example vocabulary, when the student’s primary objective is to do something else (Laufer & Hulstijn, 2001 , p. 10).

Hulstijn ( 2001 ) suggested that it “is the quality and frequency of the information processing activities (i.e., elaborations on aspects of a word’s form and meaning, plus rehearsal) that determine retention of new information” (p. 275). However, the number of new words learned incidentally is relatively small compared to the number of words that can be learned intentionally (Hulstijn, 1992 ). Even with the use of a dictionary and the inferring strategy, incidental vocabulary learning tends to be incremental and slow (Hulstijn, 1992 ).

Nevertheless, incidental L2 vocabulary acquisition paradigm has not been free of criticisms: for instance, Paribakht and Wesche ( 1999 ) contend that it works for much advanced vocabulary acquisition. Moreover, they are of the belief that the process of incidental vocabulary acquisition is slow, often misguided, and seemingly haphazard, producing differential outcomes for different learners, word types, and contexts.

In intentional learning, on the other hand, learners try to commit new information to memory by using strategies, such as mnemonic devices (Paradis, 1994 ). In other words, intentional learning is a learning vocabulary out of context by using, for instance, word lists or word cards. One body of research employing the intentional learning model is the keyword method (see e.g. Ellis & Beaton, 1993 ). This technique involves the creation of a mediating word that is meant to facilitate retention of a target word by allowing the learner to develop a connection between the form and the meaning of the target word (Rukholm, 2011). The mediating word is the keyword and ideally its phonology should resemble the form of the target word while also allowing the learner to associate the target word with a visual representation of the keyword.

Furthermore, retention rates under intentional learning are on average, much higher than under incidental conditions (Hulstijn, 2003 ). The findings of Elgort ( 2010 ) provided evidence that deliberate learning triggered the acquisition of representational and functional aspects of vocabulary knowledge. The benefits of vocabulary-list learning are to gain not only receptive vocabulary knowledge, but also productive vocabulary knowledge as well as to increase learners’ breadth and depth of vocabulary knowledge (Yamamoto, 2013 ). Explicit teaching results in faster vocabulary gains and a higher level of vocabulary retention than learning vocabulary through reading (Schmitt, 2008 ). Nation recommends “the deliberate learning of vocabulary using word cards (as one way of speeding up learners’ progress towards an effective vocabulary size” (Nation 2001 : 533).

The role of input and output activities

It has been shown that reading is a powerful source of vocabulary acquisition for second and foreign English language learners. Research also indicates that vocabulary knowledge contributes significantly to learners’ reading comprehension (Hu & Nassaji, 2014 ). Moreover, several research findings (Hulstijn, 1992 ; Nagy, 1997 ; Zahar et al., 2001 ) supported the idea that language learners acquire second language vocabulary from reading.

Recently, Bolger and Zapata ( 2011 ) hypothesized that L2 learners’ processing of context and completion of reading comprehension tasks would trigger deeper processing than merely lists of words. In this study, the use of context guided by the need to reflect this importance and common pedagogical practices (e.g., the communicative approach) but not by the debate on its value as a pedagogical tool for L2 learning.

Additionally, glossing has been argued to help vocabulary learning and assist reading comprehension (Ko, 2012 ). A number of studies have provided evidence that glosses are effective in helping learners learn new lexical items in a second language (Bowles, 2004 ; Cheng & Good, 2009 ), for example , the results of (Ko, 2012 ) indicated that glossing had a positive effect on L2 vocabulary learning. Additionally, Zhang ( 2007 ) showed that in terms of vocabulary gains, the provision of marginal glosses was the more beneficial than the availability of dictionary and non-dictionary use. The results also demonstrated that there would be a significant difference between gloss and no-gloss groups with respect to gaining word meaning.

Research indicates that lexical inferencing, or guessing the meaning of an unfamiliar word, is the main strategy learners use in initial comprehension of unfamiliar words while reading (Paribakht, 2005 ; Paribakht & Wesche, 1999 ). A word with a derived meaning is more likely to be retained in an L2 lexical system than a word with a glossed meaning (Nation, 2001 ).

Much research has focused on how to enhance the effectiveness of incidental vocabulary learning in reading by using stimulus techniques such as output tasks, textual glosses, and think-aloud activities (Min, 2008 ; Rott, 2004 ; Watanabe, 1997 ). On the contrary, research suggests that learning words from context while focusing on reading is an inefficient method because of the limitations inherent in deriving meanings from contextual cues (Nagy, 1997 ; Nation, 2001 ).

Meta-analyses on L2 vocabulary teaching

Several meta-analyses have been conducted on some aspects of L2 vocabulary teaching. For example, Chiu ( 2013 ) investigated the general effectiveness of L2 computer-assisted vocabulary instruction, with analysis of the features of treatment duration, educational level, and the use of games and the role of teachers in the CALL studies. In general, computer-assisted language learning in L2 vocabulary was shown to have positive effects with a medium effect size ( d  = 0.745, p  = 0.000).The results of Abraham’s meta-analysis ( 2008 ) showed that computer-mediated glosses had an overall medium effect on second language reading comprehension and a large effect on incidental vocabulary learning. Huang ( 2010 ) conducted a systematic statistical synthesis of the effects of output stimulus tasks on L2 incidental vocabulary learning. A total of 12 studies were included in this meta-analysis. Results showed that language learners gained more benefit from using output stimulus tasks to learn vocabulary than those who only read a text. For these 16 studies, the mean effect size was 1.39 (SE = .07).

Although the meta-analyses on L2 vocabulary teaching have highly contributed to the field of instructed L2 vocabulary learning, the effectiveness of receptive L2 vocabulary learning remains a relatively under-researched line of inquiry in the literature. Additionally, a number of contextual factors and moderator variables have rarely been investigated..

Recently, meta-analysis has been described more broadly as a research synthesis method with the aim of estimating an average association across studies and to explore the degree and sources of heterogeneity (Sutton & Higgs, 2008 ). Additionally, one of the most frequently cited reasons for conducting a meta-analysis are the increase in statistical power that it bestows a reviewer (Cohen & Becker, 2003 ; Card, 2012 ).

Admittedly, one of the problems that associated with conducting meta-analyses is the publication bias (Borenstein, et al. 2009 ; Card, 2012 ; Sutton & Higgs, 2008 ). Meta-analysis it is not without its critics particularly because of the difficulties of knowing which studies should be included and to which population final results actually apply (Sutton et al. 2000 ; Sutton & Higgs, 2008 ). If the included studies are a biased sample of all related studies, then the mean effect computed by the meta-analysis will reflect this bias (Borenstein, et al., 2010 ). Publication status cannot be used as a criterion for quality; and should not be used as a basis for inclusion or exclusion of studies (Borenstein, et al. 2009 ).

One way to reduce the possible influence of publication bias is to include doctoral dissertations in a research synthesis. As, Light and Pillemer ( 1984 , p. 38) point out, dissertations have several advantages in that they are required to be approved by faculty, thereby enhancing quality, they often contain more detailed quantitative information than journals, and they also can provide more qualitative information about the research. This study utilized a meta-analysis methodology to combine the quantitative results of primary studies identified in the existing research literature.

Purpose of the study

The primary purpose of the present study is to investigate the overall effectiveness of L2 vocabulary instruction. Second, it aims to assess the potential heterogeneity across effect size measures. Third, the study attempts to evaluate the moderator variables such as context of instruction, publication type, the age of the participants, and the L2 learners’ proficiency level on the L2 vocabulary learning, type of technology, word type.

Research questions

The current meta-analysis is aimed to address the following research questions:

What is the overall effect of variables contributing to SLA vocabulary acquisition?

To what extent the effect sizes vary across studies?

What moderator variables affect the overall effectiveness of l2 vocabulary instruction?

Methodology

Literature search.

For the purpose of data collection, documents were accessed electronically through Web of Science , Academic Search Premier and Pro Quest Dissertations and theses databases. Then, Oxford Journals, Cambridge Journals, Sage Journals, and Taylor & Fransis Journals were subject to online search using the same search terms.

The second phase of study identification and retrieval stage of a meta-analytic review included: searching key applied linguistics and SLA journals, Applied Linguistics, Language Awareness, Language Learning, Language Teaching Research, Modern Language Journal, RELC Journal, Second Language Research, Studies in Second Language Acquisition, System, TESOL Quarterly .

Search terms

To retrieve the articles and dissertations, a set of search terms and combination of them were employed ; Foreign language vocabulary learning/ acquisition, L2 vocabulary acquisition, L2 vocabulary learning, second language vocabulary learning/ acquisition, L2 vocabulary knowledge, foreign language vocabulary knowledge, L2 lexical proficiency, second language vocabulary development, L2 vocabulary development , second language instruction , L2 vocabulary gain, L2 vocabulary retention .

Inclusion criteria

The criteria stipulated for the inclusion of the studies for the current meta-analysis were as follows;

Dependent variable, in this meta-analysis, is second or foreign language vocabulary acquisition.

Studies included for the current meta-analysis should be experimental or quasi-experimental. Studies included in the statistical analysis, must utilize an experimental design, quasi-experimental design, or pre-post design.

Eligible studies have interventions or treatments. So, the correlational studies were excluded.

Eligible studies must report sufficient statistical and descriptive data for inclusion in the analysis.

The current meta-analysis included both published and unpublished studies. Among unpublished studies, doctoral dissertations will be included in the current meta-analysis to the exclusions of the proceedings of the conferences.

To take account for the latest development in the field of L2 vocabulary instruction, the studies should be published between 2004 and May 2014. Thus, studies published before 2004 were excluded from the present meta-analysis.

this study concentrated on the acquisition of “receptive vocabularies”. So “productive words” was excluded from current meta-analysis.

Exclusion criteria

The criteria for exclusion of papers or dissertations are as follows:

The study did not examine L2 vocabulary learning, development or retention. For example, the study may have examined learners’ perception of L2 vocabulary learning strategies.

The study was a literature review, synthesis, or meta-analysis.

Studies on L2 vocabulary learning of people with language impairment were excluded.

Coding the studies

The primary investigator screened all articles for inclusion. To promote consistency in the screening process, a minimum of 50% of the studies were double-screened by a trained graduate research assistant. All articles selected for inclusion were coded and rated by the primary investigator and a graduate research assistant. The outcome of the coding was compared and any discrepancies resolved though discussion. The graduate assistant and the lead author coded 8 randomly selected studies and intercoder reliability was calculated through Cohen’s Kappa (k) coefficient. The agreement rate was 98.5% and the differences were resolved through discussion. Coding measurement procedures and research settings would enable the reviewer to assess whether effect size estimates had been affected by the choice of instrument or the location of the study (Ellis, 2010 ).

After identifying the body of research literature that meets the stipulated inclusion and exclusion criteria, a coding scheme was developed to classify common characteristics of the studies. Final comprehensive coding scheme was included two major categories for methodological features: 1) learner characteristics and 2) research design. Studies were coded for the number of participants, age of the participants, publication type, types of the target words, length of instruction, the technology used, context of L2 study, and the proficiency level of the participants. For the present meta-analysis, the coding scheme was constructed by reviewing previously published meta-analyses and based on the research questions that guided the present study.

Random –effects vs. fixed effects model

Borenstein et al. ( 2010 ) pointed out that the selection of the model is critically important. In addition to affecting the computations, the model helps us to define the goals of the analysis and the interpretation of the statistics. In the same way, Lau et al.( 1992 ) recommend using random-effects(RE) analyses rather than fixed-effects (FE) analyses because RE analyses yield wider confidence intervals around the weighted average effect size, thereby reducing the likelihood of committing a Type I error. Perhaps most importantly, RE analyses may permit generalizations that extend beyond the studies included in a review, whereas FE analyses are more restrictive and only permit inferences about estimated parameters (Cohen & Becker, 2003 ). Likewise, Borenstein, et al. ( 2009 ) pointed out that under the random-effects model the goal is not to estimate one true effect, but to estimate the mean of a distribution of effects. Since each study provides information about a different effect size, we want to be sure that all these effect sizes are represented in the summary estimate.

Calculation and interpretation of the effect sizes

All the analyses (including effect size measures) were run by using professional meta-analysis software called Comprehensive Meta-Analysis (CMA; Borenstein, Hedges, Higgins , &Rothstein, 2005 ). Hunter and Schmidt ( 2004 ) believe that this software is all-purpose meta-analysis program. There are different ways of interpreting the effect size measures. The most commonly used one is Cohen ( 1998 ) benchmark in that he suggested the following guidelines for designating effects as small, medium, and large: d  = .20 or r  = .10 is considered a small effect size, d  = .50 or r  = .30 is a medium effect size, and d  = .80 or r  = .50 is a large effect size. “The larger this value, the greater the extent to which the phenomenon under study is manifested” (Cohen, 1988 , p. 10). recently, however, Oswald and Plonsky, ( 2010 ) suggested a more field- sensitive criterion for SLA research. For mean differences between groups, d values in the neighborhood of .40 should be considered small, .70 medium, and 1.00 large. These estimates of (roughly) small, medium, and large effects were chosen based on their approximate correspondence to the 25th, 50th, and 75th percentiles, respectively, for between-group contrasts in primary and meta-analytic research (Plonsky & Oswald, 2014 ). The present study interprets the findings based on the latter one.

Approximately 2322 articles and PhD dissertations that have been published or not published between 2004 and 2014 were retrieved through first filtering. Eighty-two of these documents were selected through second filtering. Finally, 16 published articles and Ph.D. dissertations met the inclusion criteria and were included in this meta-analysis. All studies investigated the effects of different factors and variables on the acquisition of L2 receptive vocabulary. Nine of these documents were PhD dissertations and 7 were published papers. The principle of “one study, one effect size” was followed as much as possible to minimize the presence of sample size inflation and nonindependence of events. Only group contrasts, control vs. experimental groups, were gained and analyzed. Table 1 shows all the studies as well as the included studies.

Descriptive data

In order to address the overall effectiveness of L2 vocabulary instruction, the random-effects effect size, Cohen’s d, of the effects of the treatments on L2 vocabulary instruction was examined. Figure 1 . demonstrates forest plot of standardized mean effect for overall L2 vocabulary instruction.

figure 1

Forest plot of standardized mean effect sizes for overall L2 vocabulary instruction

Heterogeneity of effect sizes

The second research question asked, “To what extent the effect sizes varied across studies?” The Q test of homogeneity of effect size was conducted based on the random-effects model of meta-analysis. It indicated that the null hypothesis should be rejected, Q (16) = 59.94, p  < .01, finding that effect sizes varied significantly across studies. The tau-squared ( T 2 ) refers to the estimation of the variance of effect sizes, T 2  = 0.23. It indicated sizable variation in parameter effect sizes. The I 2 statistic (Higgins et al. 2003 ) was 74.97 which indicate that a high proportion of the between-effect size variance reflects real differences in effect sizes. Thus, the answer to the second research question is that there is sizable variation of effect sizes across studies. Table 2 demonstrates the Cohen ‘s d, upper limit and lower limit.

  • Publication bias

If publication bias were present, the bottom of the funnel plot would show a higher concentration of studies on one side of the mean than the other. This type of distribution would reflect the tendency for smaller studies with larger than average effect sizes, making them more likely to achieve statistical significance, to be published (Borenstein et al., 2009 ).

Funnel Plot (Light & Pillemer, 1984 ) is one of the approaches to display the relationship between effect size and study size and illustrate potential evidence of publication bias. When publication bias is not present, the studies should be distributed symmetrically around the average effect size because of random sampling error. Large studies cluster around the mean effect size on the top and smaller studies spread across wider range near the bottom.

Figure  2 demonstrates that the majority of effect sizes were equally distributed around the mean, indicating the absence of publication bias. Studies with larger sample sizes appear towards the upper portion of the funnel and are relatively evenly distributed about the mean, with the graph indicating that medium and larger scale studies with medium effect sizes were well represented. Additionally, to address the ‘file-drawer problem” that is characteristic of meta-analysis, Rosenthal’s ( 1979 ), Fail-Safe N test was conducted (using CMA software). The test showed N  = 1,600,000, z = 11.25464, p  < 0.00000). This statistic indicated that 1,600,000 studies would need to be added to the analysis to yield a statistically non-significant result that is a large Fail-safe.

figure 2

Publication bias: Funnel plot to assess publication bias

Moderator variable analysis

Table 3 delineates the characteristics of the moderator variables of the primary studies.

Table 4 shows the Moderator analysis: Means and Q-statistics for group contrasts of the study.

The context of L2 vocabulary instruction

Research setting can be divided into foreign language (FL) and second language (SL). A foreign language setting is one where the learner studies a language that is not the primary language of the linguistic community. A second language setting, on the other hand, is one in which the learner’s target language is the primary language of the linguistic community. A small to medium effect ( d  = 0.53) for Second language contexts and large effect for foreign language settings ( d  = 0.96) were obtained. 9 and 7 studies were conducted in foreign language and second language contexts, respectively. The difference between foreign language and second language contexts was not statistically significant ( Q  = 3.02, d f = 1, P  = 0.08).

The age of the participants

Following Jeon and Yamashita ( 2014 ), All participants who were at or below grade six (or age 12) were coded as Child and the participants who were at or older than grade seven (13 or older) were coded as Adult . we sought to account for variation in effect size measures by investigating the influence of the age of the participants in the primary studies. As shown in Table  2 , ( d  = 0.79) was observed for adult and ( d  = 0.85) was found for child participants. However, the differences are not statistically significant ( Q  = 0.47, df = 1, p  = 0.82).

L2 learners’ proficiency level

The third moderator variable of the current meta-analysis was the impact of the participants’ proficiency level on the overall effect size. To estimate it, three levels of L2 proficiency levels were coded in the included studies (elementary, intermediate, and advanced). Ten primary studies were conducted targeting intermediate l2 learners and 5 studies included participants in elementary level of L2 proficiency. Only one study was done with advanced L2 learners. With respect to L2 proficiency level, small effect size ( d  = 0.53) was obtained for both advanced and elementary levels ( d  = 0.54). However, large effect size ( d  = 0.95) was gained for intermediate L2 learners. However, the difference between three groups was not statistically significant ( Q  = 3.46, df = 2, P  = 0.17).

Publication type

To account for the variation in effect sizes , another moderator factor, publication type, was examined. 7 published and 9 Ph.D. dissertations were included in the present meta-analysis. Published articles generated effect size of ( d  = 1.12), whereas, Ph.D. dissertations produced the effect size of ( d  = 0.57). The difference is statistically significant ( Q  = 4.75, df = 1, p  = 0.02).

In order to examine the variation in effect size , another moderator variable, word type, was analyzed. This variable included; abstract words, and concrete words. Since some studies did not report type of the target words in the studies, another category labeled not mentioned . The effect size observed for abstract words was (d = 0.92) whereas, concrete words generated the effect size of (d = 0.65). Statistically speaking, the difference is not significant ( Q  = 0.24, df = 2, p  = 0.88).

Technology (technique) type

Four types of technology (technique) were classified in the included studies; Computer-assisted Language learning (CALL), poster, reading, and song. Appling “poster” generated the largest effect size (d = 1.37, k = 1). Employing reading activities to teach target words produced (d = 1.25, k = 5). CALL technology produced the effect size of ( d  = 0.68, k = 7). The smallest effect size was gained for studies that employed song to teach the target words (d = 0.47, k = 0.47). The differences, however, are not statistically significant (Q = 7.05, df = 3, p  = 0.07).

General discussion

This meta-analysis sought to determine the effectiveness of L2 vocabulary instruction and to identify the moderator variables for its effectiveness. The overall effect size for L2 vocabulary instruction was ( d  = 0.80). Based on Oswald and Plonsky ( 2010 ) criterion, this effect size is medium to large. The findings indicate that L2 vocabulary instruction is an effective instructional approach for improving L2 proficiency and should be incorporated as an integral part of L2 syllabus. The results of the present meta-analysis should be discussed considering other similar meta-analyses. As Plonsky and Oswald ( 2014 ) suggested that meta-analysts can look to the results of other meta-analyses when explaining their finding. Chiu ( 2013 ) investigated the general effectiveness of L2 computer-assisted vocabulary instruction, with analysis of the features of treatment duration, educational level, and the use of games and the role of teachers in the CALL studies. In general, computer-assisted language learning in L2 vocabulary was shown to have positive effects with a medium effect size ( d  = 0.745, p  = 0.000). The results of Abraham’s meta-analysis ( 2008 ) showed that computer-mediated glosses had an overall medium effect on second language reading comprehension and a large effect on incidental vocabulary learning. Huang ( 2010 ) conducted a systematic statistical synthesis of the effects of output stimulus tasks on L2 incidental vocabulary learning. A total of 12 studies were included in this meta-analysis. Results showed that language learners gained more benefit from using output stimulus tasks to learn vocabulary than those who only read a text. For these 16 studies, the mean effect size was 1.39 (SE = .07).

The mean effect size associated with the studies conducted in FL contexts was larger than those conducted in SL contexts, indicating that L2 vocabulary instruction was more effective in FL contexts than in SL ones ( d  = 0.96 vs. d  = 0.53). This finding is similar to other studies. For example, Cobb ( 2010 ) meta-analysis of task-based interaction found a strong advantage for studies carried out in foreign-language settings ( d  = 0.89 vs. 0.14 in L2 settings). Likewise, Li ( 2010 ) found larger effect for studies conducted in foreign language contexts than for studies conducted in second language contexts. Li ( 2010 ) attributes this difference to the instructional dynamics of FL contexts. We believe that one explanation is that teachers in FL contexts mainly tend to teach lexical items and grammatical structures whereas teachers in SL contexts might concentrate on the overall communication. We also hypothesize that language learners in foreign language contexts presumably have different objectives in language teaching. One of the reasons behind the difference of effect size across different contexts can be “language teaching system orientation” (Yousefi & Biria, 2011 , P.14). In addition , Liu ( 2007 ) surveyed 800 teachers of English throughout the world and found that EFL teachers tended to focus more on linguistic forms than ESL teachers. Likewise, Won ( 2008 ) suggested that ESL and EFL classroom teachers need to consider the differences of first and second language vocabulary acquisition as well as student learner characteristics.

With respect to the effect of publication type on the variation among primary studies, it was indicated that the published studies generated more effect size than PhD dissertations and the difference was statistically significant. This finding highlights one of the big threats and concerns about conducting meta-analyses. It also confirms the fact that studies with larger effect sizes give their ways to the publication more easily than those with smaller effect size and non-significant ones. We propose that in order to reduce publication bias, it is up to meta-analysts that include both published and unpublished studies including doctoral dissertations, conference proceedings, and working papers. We also believe that L2 researchers should report the effect size in their primary studies and larger effect size should not be interpreted as contributing to the field more than small effect size measures. In order to advance our understanding of SLA processes, the researchers should report the perceived phenomenon and justify the findings in the light of the current theories and hypotheses.

Similarly, Plonsky and Oswald ( 2014 ) believe that there is growing evidence of publication bias among L2 meta-analyses that have investigated this issue. Lee and Huang (2008) grouped and compared the effects of textual enhancement among (a) published results (not based on a dissertation; d  = .55, k = 8), (b) published results based on a dissertation ( d  = .24, k = 4), and (c) unpublished dissertation results ( d  = −.01,k = 4). In Li ( 2010 ) study, Published studies did not show a larger effect than PhD dissertations; in fact, the mean effect size for dissertations was larger than that yielded by published articles.

Proficiency level

The effect size that was obtained for intermediate learners was larger than elementary and advanced learners. This finding should be interpreted with caution. Since only one study has included the advanced learners. The larger effect size of intermediate participants can be attributed to the fact that they have already achieved a threshold level of L2 vocabulary. Intermediate learners also attained L reading strategies that enable them to benefit much from reading activities.

In Yun ( 2011 ) Learner proficiency was found a statistically significant moderator to affect the treatment effects with Q = 15.304, p  < 0.05; that is, studies with beginning learners had the largest mean effect size, 0.698 while those with intermediate learners had the least mean effect size, 0.233. That is, beginning learners who had access to multiple hypertext glosses most benefited from multiple glosses in reading. Abraham ( 2008 ) believes that Intermediate learners may possess deeper lexical knowledge allowing them to connect vocabulary encountered in the glosses more easily to a pre-existing semantic system and network of L2 vocabulary than beginners who are still developing their vocabulary base. The results of Huang’s ( 2010 ) meta-analysis showed that the vocabulary learning of language learners with low proficiency levels and vocabulary sizes may benefit more from L1 textual glosses than those who have higher proficiency levels and larger vocabulary sizes.

Li ( 2010 ) did not include proficiency measure as one the moderator analyses due to the high degree of heterogeneity in primary researchers’ use of proficiency measures. The researcher believes that the primary researchers’ decisions on the proficiency levels of participants were arbitrary and highly context-specific.Chiu ( 2013 ) showed that high school or college students ( d  = 1.032, p  = 0.001) can benefit more from computer-assisted language learning program than elementary school students (d = 0.321, p  = 0.004). Learners would have different learning styles and strategies. This may be due to the maturity level of high school or college students enabling more effective use of technology for English vocabulary learning. In the same vein, in Yun’s ( 2011 ) study, Learner proficiency was found to be a statistically significant moderator to affect the treatment effects with Q  = 15.304, p  < 0.05: studies with beginning learners had the largest mean effect size, 0.698 while those with intermediate learners had the least mean effect size 0.233.

Age of the participants

Following Jeon and Yamashita ( 2014 ), all participants who were at or below grade six (or age 12) were coded as Child and the participants who were at or older than grade seven (13 or older) were coded as Adult. The present meta-analysis revealed that the effect size observed for child learners was larger than adult participants in the primary studies ( d  = 0.85vs. 0.79). However, the difference statistically speaking, however, is not significant. With this in mind, this finding should be interpreted with caution.

The results of Nakanishi ( 2015 ) suggest that the effect of extensive reading might increase with older participants. The researcher attributes the reason to the beneficial for older learners who have learned the foreign language explicitly, as it might lead them to draw on and proceduralize their explicit knowledge. Nakanishi ( 2014 ) goes on to argue that another factor concerns the maturity of the participants in terms of their cognitive processing. As individuals age, they are able to understand and process more complex information, a development that could lead them to read more.

The influence of the age at which words are acquired on various measures of lexical processing was acknowledged (Balota et al., 2006 ). There have been a number of reports suggesting that age of acquisition produces a unique influence on word recognition performance above and beyond correlated variables such as word frequency Balota et al., ( 2006 ) believe that the intriguing argument here is that early acquired words could play a special role in laying down the initial orthographic, phonological, and/or semantic representations that the rest of the lexicon is built upon. Moreover, early acquired words will also have a much larger cumulative frequency of exposure across the lifetime.

Simply put, from the perspective of information processing theory, differences in problem-solving abilities have been identified as one of the main explanations for the difference between second language learning by younger and older learners (Munoz, 2006 ). With biological maturation, aspects such as rate of information processing increase regularly from childhood to adulthood.

Contrary to the research findings so far, the findings indicate that abstract words generated higher effect size than concrete words. We believe that one justification may be the fact that abstract words do not make extra cognitive processing demands on adult Language learners. However, it might be more demanding for young children to acquire abstract words than concrete ones. In first language (L1) acquisition, concrete words (e.g., table, paper) are typically learned prior to abstract words (e.g., liberty, myth) (Schwanenflugel, Akin, & Luh, 1992 ). Schwanenflugel et al. ( 1992 ) noted that the advantages demonstrated by concrete words may stem from the fact that concrete words have greater ‘context-availability’ than abstract words. It is typically easier to think of a context in which concrete words appear than it is to think of a context in which a given abstract word appears.

The last moderator variable of the present study was the effect of technology (technique) used for the purpose of teaching L2 vocabulary items. It was revealed that employing “posters” generated the highest effect size following by “reading activities and tasks”. CALL technology produced the third highest effect size. While using authentic songs for the purpose of L2 vocabulary teaching generated the smallest effect size.

This finding should be interpreted with caution since only one study has employed “posters” for the purpose of teaching L2 vocabulary items (Cetin & Flammand, 2012 ). Cetin and Flammand ( 2012 ) believe that using poster in the classroom provide support for the usefulness of the concept of self-directed inferential learning, raise students’ awareness, arouse their interest, and will allow them to take an interest in their own surroundings. The fact that “reading activities and tasks” generated higher effect size than CALL technology should be verified by more longitudinal studies. We believe that there is much room for manipulation of reading tasks on the part of language teachers and paving the way for input enhancement and making the target words more salient. As Fehr, et al. ( 2012 ) argued it is unrealistic to suggest that computer-delivered vocabulary instruction can be the sole vehicle for remediation of significant vocabulary deficits or L2 vocabulary learning. One possible explanation for this finding is that students welcome a higher degree of autonomy in their learning and they tend to be in control of their own learning when learning from vocabulary web sites with games (Yip & Kwan, 2006 ). Yip and Kwan ( 2006 ) suggested that sophisticated experiential games, such as simulated tasks, are needed, as they are more interactive and collaborative and can address cognitive issues and foster active learning. We propose that language teachers should incorporate CALL as well as reading activities and tasks into their syllabi to meet learners’ ongoing needs and expectations.

Suggestions for further studies

The findings of this study have practical implications for educators, Language teachers, and other scholars that advance our understanding of the mechanisms responsible for the most effective techniques of L2 vocabulary teaching. Research must try to establish what variations in participants, as well as in treatments, will provide the most benefit for most L2 learners. This meta-analysis highlighted important gaps in the following areas of research: first, the effects of the context of L2 vocabulary instruction on the acquisition and retention of the target words. Second, the modifying effects of background knowledge, L1 and L2 distance, type of different tests and tasks, different ways of operationalizing vocabulary learning and retention, duration of instruction. Future work aimed at understanding the interplay among language- learner related factors and language learning connected variables can illuminate our understanding of the mechanisms underlying L2 vocabulary learning and account for cost-effective l2 vocabulary learning model. We propose that different word types (concrete, abstract, emotion, and pseudo word) may be acquired differently. As Altarriba and Basnight-Brown ( 2011 ) suggest that the three word types – concrete, abstract, and emotion – were not acquired in the same way, even though the same basic mode of acquisition was used to teach these words in a new language.

Future research should examine other potential moderators, including setting (e.g., instructed vs. naturalistic setting), instructional variables (e.g., instructional tasks and activities), teacher orientation (e.g., beliefs and attitudes), and L2 learner variables (e.g., type of motivation, cognitive style, and learning strategies) that may influence the effectiveness of L2 vocabulary instruction.

We recommend that meta-analysts include PhD dissertations in their syntheses. By so doing, researchers will reduce publication bias and gain access to rich descriptions of the research procedures. In addition, by including doctoral dissertations, meta-analysts will gain access to rich data that would be able them to analyze more moderating variables that otherwise will go untouched.

Limitations

This review was intentionally limited to experimental-control studies. The strict inclusion criterion led to the relatively small number of included studies. Although the inclusion of studies with within-subject designs utilizing pre-post comparisons may contribute significantly to our understanding, the effect size statistics for these types of studies may add to the inflation of effect sizes when pooled with studies utilizing a separate control group. There are several issues that pose limitations and warrant consideration when evaluating the results of this study. Due to the relatively small number of studies, care should be exercised as to the generalization of its findings. Many of the included studies have employed relatively short duration of instruction. In order to grasp a total picture and construct an integrative model of L2 vocabulary learning more and more longitudinal studies should be conducted and analyzed through meta-analyses and Structural Equation Modeling (SEM).

The overall effectiveness of L2 vocabulary instruction gained through the present meta-analysis was ( d  = 0.80) which means that L2 vocabulary treatment programs have the effect size of medium to large. The research synthesis indicates that l2 vocabulary instruction was effective and given the significance of vocabulary, L2 vocabulary teaching should be incorporated as indispensable part of L2 syllabus. What remains unresolved, here, is the question of what factors and variables enhance L2 vocabulary development more effectively than the other variables. To gain such an insight, we call for constructing L2 vocabulary models and hypotheses that provide syllabus designers and language teachers with cost-effective techniques of teaching L2 vocabulary items. We are sure that this can be achieved through application of sophisticated statistical analyses and capitalizing on the development in the field of SLA.

One asterisk indicates that the study was included in the meta-analysis.

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Yousefi, M.H., Biria, R. The effectiveness of L2 vocabulary instruction: a meta-analysis. Asian. J. Second. Foreign. Lang. Educ. 3 , 21 (2018). https://doi.org/10.1186/s40862-018-0062-2

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Analysis: Amid a wide-open playoff race, a wide-open NBA MVP race might be brewing as well

Oklahoma City Thunder guard Shai Gilgeous-Alexander answers a question during media day at the NBA All-Star basketball game in Indianapolis, Saturday, Feb. 17, 2024. (AP Photo/Michael Conroy)

Oklahoma City Thunder guard Shai Gilgeous-Alexander answers a question during media day at the NBA All-Star basketball game in Indianapolis, Saturday, Feb. 17, 2024. (AP Photo/Michael Conroy)

Milwaukee Bucks forward Giannis Antetokounmpo (34) looks to shoots over Denver Nuggets center Nikola Jokic (15) during the second half of an NBA All-Star basketball game in Indianapolis, Sunday, Feb. 18, 2024. (AP Photo/Darron Cummings)

Dallas Mavericks guard Luka Doncic (77) drives on Milwaukee Bucks guard Damian Lillard (0) during the first half of an NBA All-Star basketball game in Indianapolis, Sunday, Feb. 18, 2024. (AP Photo/Darron Cummings)

Cleveland Cavaliers’ Donovan Mitchell prepares to shoot during the 3-point contest at the NBA basketball All-Star weekend, Saturday, Feb. 17, 2024, in Indianapolis. (AP Photo/Darron Cummings)

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The new rule that rendered Philadelphia’s Joel Embiid ineligible for a second consecutive NBA MVP award because he’s missing too many games has the potential to create something the league hasn’t seen in almost two decades.

That would be a wide-open MVP race.

Steve Nash won the MVP award for the 2005-06 season with only 46% of the first-place votes, marking the last time somebody won the NBA’s top individual honor without having his name atop more than half of the ballots.

The winner in every season since has gotten at least 50% of the first-place votes — and Stephen Curry even got 100% when he was MVP in 2016. This year sure seems like it could go differently, with several players in the realistic mix coming out of the All-Star break.

Denver Nuggets center Nikola Jokic (15) goes up for a shot during the first half of an NBA All-Star basketball game in Indianapolis, Sunday, Feb. 18, 2024. (AP Photo/Darron Cummings)

“There’s a lot of guys,” Boston forward Jaylen Brown said. “Who knows what the actual criteria is, to how it goes. I’ve had questions about a lot of different things that goes into stuff. But, you know, I guess we’ll see.”

Denver’s Nikola Jokic certainly could end up with the award for the third time in four years. Milwaukee’s Giannis Antetokounmpo may be in the mix for his third MVP as well. Oklahoma City’s Shai Gilgeous-Alexander was fifth last season and should be higher this year. Dallas’ Luka Doncic will likely be on plenty of ballots. If the Los Angeles Clippers keep playing the way they have been over the last couple months, don’t be surprised if a case gets made for Kawhi Leonard.

“Kawhi should definitely be in that conversation,” Clippers forward Paul George said. “But there’s a lot of guys. You talk about Shai, you talk about Luka, you talk about Jokic. There’s a lot of guys out West and even out East, there’s a lot of guys doing a hell of a job representing their team.”

Brown believes his Celtics teammate Jayson Tatum should be atop the MVP list. It’s a reasonable argument; Tatum is the best player on the team with the best record in the league and his averages of 27 points, nearly nine rebounds and nearly five assists per game certainly merit award consideration. A player has finished a season with those averages 26 times over the years; of those, nine have won that season’s MVP award.

Except this season, there are at least two other players — Doncic and Antetokoumpo — averaging that many points, rebounds and assists. Embiid was as well before he got hurt; it’s unclear when or if he’ll be back, but even if he does return he won’t be eligible for the MVP and probably won’t meet the threshold to rank among statistical leaders, either.

Part of the challenge of selecting an MVP is this: There’s no absolute definition. To some, it might mean “best player.” To others, it might mean “most valuable to his team.” And if that’s the case, it might be time to look at Cleveland’s Donovan Mitchell.

The Cavs are an NBA-best 23-5 since mid-December. They’re currently No. 2 in the Eastern Conference, when probably very few thought they’d be there. Mitchell is averaging 28.4 points, 6.3 assists, 5.4 rebounds and 1.9 steals – all career-highs.

He wants to be MVP. He knows he doesn’t get mentioned. He can’t figure out why.

“I feel like the work shows for itself. I’m not one to go out there and vocalize,” Mitchell said. “Just want to go out there and do it. Ultimately, it’s not up to me. At the end of the day, they don’t put my name in there. They don’t want to. I’m just going to continue to play the level I’m playing at.”

Gilgeous-Alexander is leading another surprise story in Oklahoma City. The Thunder haven’t won a playoff series since 2016; right now, they’re No. 2 in the West thanks in large part to the Canadian guard with averages of 31.1 points, 6.5 assists, 5.5 rebounds and 2.2 steals per game.

The only person to finish a season with all those averages: Michael Jordan, who did it 1988-89 – but didn’t win MVP that season. Go figure.

“He is more in the MVP race, I think, than people realize,” Orlando coach Jamahl Mosley said of Gilgeous-Alexander. “I mean, this is something special.”

Gilgeous-Alexander said he’s just going to keep blocking out any noise about awards or playoffs or anything besides who the Thunder play next.

“For me, it’s not any more difficult,” Gilgeous-Alexander said. “I think I’ve learned through experience -- and obviously as a young kid it’s easy to get caught up in it, just going back to high school and rankings and things like that. I’ve just found so much success from, not blocking it out, but not letting it faze me or control me.”

So, there’s a playoff race. There’s also an MVP race. Often by this time, it’s pretty easy to say that this guy or that guy will win. That’s not the case right now, and it only might get more muddled the rest of the way.

Which would be a great thing.

AP Sports Writer Tom Withers in Cleveland contributed to this story.

Tim Reynolds is a national basketball writer for The Associated Press. Write to him at treynolds(at)ap.org

AP NBA: https://apnews.com/hub/nba

TIM REYNOLDS

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