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Critical Discourse Analysis | Definition, Guide & Examples

Published on August 23, 2019 by Amy Luo . Revised on June 22, 2023.

Critical discourse analysis (or discourse analysis) is a research method for studying written or spoken language in relation to its social context. It aims to understand how language is used in real life situations.

When you conduct discourse analysis, you might focus on:

  • The purposes and effects of different types of language
  • Cultural rules and conventions in communication
  • How values, beliefs and assumptions are communicated
  • How language use relates to its social, political and historical context

Discourse analysis is a common qualitative research method in many humanities and social science disciplines, including linguistics, sociology, anthropology, psychology and cultural studies.  

Table of contents

What is discourse analysis used for, how is discourse analysis different from other methods, how to conduct discourse analysis, other interesting articles.

Conducting discourse analysis means examining how language functions and how meaning is created in different social contexts. It can be applied to any instance of written or oral language, as well as non-verbal aspects of communication such as tone and gestures.

Materials that are suitable for discourse analysis include:

  • Books, newspapers and periodicals
  • Marketing material, such as brochures and advertisements
  • Business and government documents
  • Websites, forums, social media posts and comments
  • Interviews and conversations

By analyzing these types of discourse, researchers aim to gain an understanding of social groups and how they communicate.

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Unlike linguistic approaches that focus only on the rules of language use, discourse analysis emphasizes the contextual meaning of language.

It focuses on the social aspects of communication and the ways people use language to achieve specific effects (e.g. to build trust, to create doubt, to evoke emotions, or to manage conflict).

Instead of focusing on smaller units of language, such as sounds, words or phrases, discourse analysis is used to study larger chunks of language, such as entire conversations, texts, or collections of texts. The selected sources can be analyzed on multiple levels.

Discourse analysis is a qualitative and interpretive method of analyzing texts (in contrast to more systematic methods like content analysis ). You make interpretations based on both the details of the material itself and on contextual knowledge.

There are many different approaches and techniques you can use to conduct discourse analysis, but the steps below outline the basic structure you need to follow. Following these steps can help you avoid pitfalls of confirmation bias that can cloud your analysis.

Step 1: Define the research question and select the content of analysis

To do discourse analysis, you begin with a clearly defined research question . Once you have developed your question, select a range of material that is appropriate to answer it.

Discourse analysis is a method that can be applied both to large volumes of material and to smaller samples, depending on the aims and timescale of your research.

Step 2: Gather information and theory on the context

Next, you must establish the social and historical context in which the material was produced and intended to be received. Gather factual details of when and where the content was created, who the author is, who published it, and whom it was disseminated to.

As well as understanding the real-life context of the discourse, you can also conduct a literature review on the topic and construct a theoretical framework to guide your analysis.

Step 3: Analyze the content for themes and patterns

This step involves closely examining various elements of the material – such as words, sentences, paragraphs, and overall structure – and relating them to attributes, themes, and patterns relevant to your research question.

Step 4: Review your results and draw conclusions

Once you have assigned particular attributes to elements of the material, reflect on your results to examine the function and meaning of the language used. Here, you will consider your analysis in relation to the broader context that you established earlier to draw conclusions that answer your research question.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Normal distribution
  • Measures of central tendency
  • Chi square tests
  • Confidence interval
  • Quartiles & Quantiles
  • Cluster sampling
  • Stratified sampling
  • Thematic analysis
  • Cohort study
  • Peer review
  • Ethnography

Research bias

  • Implicit bias
  • Cognitive bias
  • Conformity bias
  • Hawthorne effect
  • Availability heuristic
  • Attrition bias
  • Social desirability bias

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Literary Theory and Criticism

Home › Discourse › Discourse Analysis

Discourse Analysis

By NASRULLAH MAMBROL on November 20, 2020 • ( 0 )

For many years, discourse analysis was less an explicit “theory” than a practical and empirical approach for supporting field work on relatively little-recorded languages and cultures (see, e.g., Grimes, Longacre, Malinowski, Pike). One domain of early work that attracted notice in general and humanistic circles was the cross-cultural study of stories and narratives (e.g., Claude Lévi-Strauss, Structural Anthropology ). Major concerns later on included the discourse of schooling and education (Sinclair and Coulthard, Stubbs, Widdowson) and, with a sociological turn, the organization of conversation (Sacks, Schegloff, and Jefferson).

These practical and empirical emphases fostered some variance with the “theoretical linguistics” postulating a dichotomy between language and discourse (e.g., langue versus parole for Ferdinand de Saussure, “competence” versus “performance” for Noam Chomsky ). The project of abstracting “language” away from the cultural and social contexts in which it appears as a human phenomenon seemed attractive on theoretical grounds, especially for an emergent science like linguistics, but the consensus today is that this project is unrealistic. The rising pressure upon theory and method to resituate language in these contexts accounts for the explosive interest in discourse analysis, a field that from its very beginnings has implicitly or explicitly maintained the unity of language as both structure and event, both knowledge and action, both system and process, both potential and actual (Firth, Halliday, Hartmann, Pike).

In the 1970s, discourse analysis became a convergence point for a number of trends: “text linguistics” on the European continent; “functional” or “systemic linguistics” in Czechoslovakia, Britain, and Australia; “cognitive linguistics,” “critical linguistics,” “ethnography of communication,” ethnomethodology, and the structuralism, poststructuralism, deconstruction, and feminism emanating from France; along with semiotics and cognitive science, both convergence points in their own right. This drift has made it possible, indeed essential, to contemplate discourse from multiple viewpoints: linguistic, philosophical, cognitive, social, anthropological, literary, historical, political, and ideological. Admittedly, essaying to do so makes us keenly aware of how multifarious and complex discourse transactions can be. Our best guarantee that we can ultimately make sense of all this is that they generally succeed in social practice. The task of discourse analysis is to describe the systematic organization and intersubjectivity that enable the success.

Accordingly, theories and models are being developed on numerous fronts: for the syntactical contours and the large-scale (“global”) coherence of discourse; for the interactive performance of discourse actions, or “speech acts”; for the plans, goals, and strategies of discourse participants; for the interface of meaning or significance with culture, ideology, personality, gender, and emotion; for the roles and relations of power or solidarity among participants or institutions in discourse.

The notion of “discourse” itself has been commensurately expanded. Besides being the standard designation for a recorded sequence of utterances (Longacre, Pike) or of “texts” (Beaugrande and Dressier), “discourse” may designate elaborate complexes all the way up to a definite order of concepts (Hindess and Hirst) or the entire practice and communication within a social institution (e.g., Michel Foucault, The Archeology of Knowledge ; Language, Counter-Memory, Practice ). Such is the diversity that one can find two “introductions” to discourse analysis with no overlap at all (see Coulthard; Macdonnell).

literature review discourse analysis

Michel Foucault/AFP

Still, discourse analysis does manifest some general and consistent principles, which might be formulated as follows:

1. A “discourse” is not merely a linguistic unit, but a unit of human action, interaction, communication, and cognition. The habit of identifying the “discourse” with its recorded (usually written) language trace, though deeply entrenched, must be transcended.

2. The source of data should be naturally occurring discourses rather than isolated brief examples invented by investigators. Having established the importance of context, we must discard the convenient fiction of “context-free” words or sentences. Such items are merely transposed by our citation into a different context, and we should inquire how we may be changing their significance, for example, concealing constraints or mystifying institutional commitments.

3. Discourse analysis should balance analytic with synthetic viewpoints . The traditional methods of discovering “linguistic units” and “constituents” by segmenting discourse should be more evenly correlated with methods that focus on how discourses are assembled and how the various units or aspects contribute to a constellation of mutual relevance (Beaugrande).

4. A discourse is not a static, idealized, or totalized unity of words and significances, but a dynamic field of interests, engagements, tensions, conflicts, and contradictions. This field in turn reflects the organization of society and its institutions and the roles and power structures inherent therein (Fowler et al., Wodak et al.).

5. A discourse or discourse domain should not be isolated from others but be seen in its mutual relevance to them. To appreciate the nature and problems of a domain such as “technical language,” we should not reduce it to its incidental features, such as lists of special terms or tables of formulas. We must inquire how it functions within the general acquisition of knowledge through discourse and how it could function more effectively for wider participation.

6. Discourse analysis should continually reflect upon its own procedures. Given the unmanageably large and diverse range of data, each project must be selective and focused and so should declare and justify its motives in terms of epistemological interests. The discourse of science itself should be examined (Gilbert and Mulkay), as should that of specific fields such as anthropology (Geertz).

7. Discourse analysis obliges the investigator to engage and reengage with discourse. The idealized separation of subject from object, or investigator from data, is not feasible here. Since one’s involvement in the data and one’s commitments and priorities cannot be eliminated, they can be profitably made a further object of reflection: on how the discourse being analyzed correlates with the discourse of the analysis.

8. Discourse analysis is rich and expansive rather than formalized and reductive. Discourse cannot be adequately analyzed with a fixed algorithm for reifying it into a configuration of formal symbols. Instead, the analysis should pursue the relevance of a discourse in any direction and to any degree needed in order to grasp its status within social practices, such as in news reporting (Dijk) or psychotherapy (Labov and Fanshel, Wodak).

9. To master its issues and problems, discourse analysis must adopt an encompassing interdisciplinary perspective. In the past, interdisciplinarity has too often been restricted to programmatic statements of intent; we are now filling in the content of such programs with a creditable body of results. Hence, discourse analysis should be, not one more Kuhnian battleground for warring “paradigms,” but a domain for cooperation and integration among alternative paradigms (see Thomas S. Kuhn ).

10. Discourse analysis should interact with institutions and groups both inside and outside the academy to pursue urgent issues and problems. We cannot assume that our current methods address all the most pressing issues. Instead, we should periodically take stock of and adapt our methods to more issues, such as the discourse of politicians about the nuclear arms race (Chilton et al.) or the discourse of judges and defendants in courtrooms (Atkinson and Drew, Leodolter).

11. The highest goals of discourse analysis are to support the freedom of access to knowledge through discourse and to help in revealing and rebalancing communicative power structures. Following the lead of “critical linguistics” (Dijk, Fowler et al., Mey), this thesis has now been widely acknowledged. Special attention has been devoted to geopolitical problems such as public policy, colonialism, racism, and sexism, which, though restricted by laws and statutes, persist at deeper levels in discourse, not merely through lexical choices, but through background assumptions, hierarchical structuring, rights of turntaking, and so on.

12. The demanding tasks facing us today call for an explicit, coherent research plan. Past trends have been unduly dependent on personal or institutional commitments and decisions. Now that a global dispersion of discourse study is under way, larger projects seem feasible, provided that scholars can interact over long distances and shorter intervals.

The future of discourse analysis will depend to no small degree on whether principles such as these can be fully implemented and suitable frameworks and resources provided for research. The prospects seem especially favorable for interaction between discourse analysis and literary studies, a field in which the notion of discourse is being generally recognized as a foundational problem. The principles just enumerated readily invoke some ongoing trends as well as some future desiderata:

1. The traditional philological, formalistic, or New Critical focus on the literary text as language has been complemented by a concern for literary action, interaction, communication, and cognition, though so far (inspired by French scholars such as Foucault) more from a philosophical than a sociological or psychological orientation.

2. The literary texts taken as objects of study are almost never invented by the investigator. Yet their “natural occurrence” requires specific conditions and conventions that need to be more clearly formulated and understood (Schmidt). Further groundwork is now being supplied by literary journals with an empirical outlook, such as Poetics and Empirical Studies in the Arts.

3. Recent trends show a more even balance between the analytic tactics of “close reading” or “text exegesis” and synthetic models of literary “production” and “reception” (Jauss) (see Reception theory ).

4. The traditional harmonizing, or “totalizing,” tendencies of literary criticism have been offset by widening probes of literary discourse as a field of interests, engagements, and conflicts, including the estrangement from the putative “real world” of the reader (Iser) (see Reader-response theory and criticism ).

5. Scholars reveal a renewed willingness to resituate literature, long isolated as a privileged preserve set above other discourse or even in opposition to it, among the plurality of social and ideological discourses of its own time and ours (Fowler; Hayden White, Metahistory: The Historical Imagination in Nineteenth-Century Europe , Tropics of Discourse ; Fredric Jameson, The Political Unconscious ).

6. The enterprise of reflecting upon procedures is at the very heart of the prestigious “literary theory” movement (see Beaugrande, Critical Discourse ), though the theorizing is sometimes obscure about its goals.

7. The fastidious reaching for ultimate, tidy closure of the “meaning” of the literary work has been yielding to an open-ended readiness to engage and reengage the work, notably in J. Hillis Miller’s appropriation of “deconstruction” (“Deconstructing the Deconstructors” in Theory Then and Now ). The individual work itself is viewed as an “intertextual weaving” of other discourses (Geoffrey H. Hartman, Saving the Text ).

8. The expectation that analysis should be rich and expansive was only rarely suppressed in literary studies by the kind of strict “scientism” we have seen in some schools of linguistics. The brief “structuralist” turn to narrow linguistic method has long since swerved toward the wide-ranging “poststructuralist” revision (both trends documented by Harari).

9. The value of an encompassing interdisciplinary perspective on literature is no longer seriously contested today, and joint projects are commonplace, for example, between the Psychological Institute of the Hungarian Academy of Science and the American Council of Learned Societies (results edited by Martindale).

10. Shifts of focus outside the academy are still regrettably rare, but promising signs can be seen in some recent detailed investigations of the reading public and the literary publishing industry, as presented at the first symposium of the International Society for the Empirical Study of Literature in 1987 (Schmidt, ed.).

11. The freedom of access to the unique experiences literature affords is still not a firmly established goal, due to the elitist disdain for naive readers. But discourse analysis has shown the processing of quite ordinary discourse to be enormously sophisticated and the supposed naïveté of nonelite readers to be an illusion.

12. Literary theory has been replete with calls for an explicit, coherent research plan. So far, progress has been slowed by the idiosyncratic and self-indulgent communicative strategies of some conspicuous theorists, who seem less concerned with any such plan than with the enhancement of their personal prestige. Here, the paradigm of discourse analysis, which addresses issues of such complexity that unplanned research would remain ineffectual, could act as a model.

The problems facing both discourse analysis and literary studies in the coming years are obviously enormous, but a concerted interaction between the two would surely improve the prospects for significant advances on both sides.

Bibliography John Atkinson and Paul Drew, Order in Court: The Organization of Verbal Interaction in Judicial Settings (1979); Robert de Beaugrande, Critical Discourse: A Survey of Contemporary Literary Theorists (1988), Text, Discourse, and Process (1980), Text Production (1984); Robert de Beaugrande and Wolfgang Dressier, Introduction to Text Linguistics (1981), “A New Introduction to the Study of Text and Discourse” (forthcoming); Paul Chilton, ed., Language and the Nuclear Arms Debate: Nukespeak Today (1985); Malcolm Coulthard, An Introduction to Discourse Analysis (1985); Teun van Dijk, News as Discourse (1988); Teun van Dijk, ed., Discourse Analysis: Psychological Aspects (1986), Handbook of Discourse Analysis (1985); John Rupert Firth, Papers in Linguistics, 1934-1951 (1957); Roger Fowler, Literature as Social Discourse: The Practice of Linguistic Criticism (1981); Roger Fowler, Robert Hodge, Gunther Kress, and Tony Trew, Language and Control (1979); Clifford Geertz, Works and Lives: The Anthropologist as Author (1988); Nigel Gilbert and Michael Mulkay, Opening Pandora’s Box: A Sociological Analysis of Scientists’ Discourse (1984); Joseph Grimes, The Thread of Discourse (1975); Michael Halliday, Introduction to Functional Grammar (1985); Josué V. Harari, ed., Structuralists and Structuralism: A Selected Bibliography of French Contemporary Thought (1971), Textual Strategies: Perspectives in Post-Structuralist Criticism (1979); Peter Hartmann, Theorie der Sprachwissenschaft (1963); Barry Hindess and Paul Hirst, Modes of Production and Social Formation (1977); Wolfgang Iser, Der Akt des Lesens: Theorie ästhetischer Wirkung (1976, The Act of Reading: A Theory of Aesthetic Response, trans. Iser, 1978), Der implizite Leser: Kommunikationsformen des Romans von Bunyan bis Beckett (1972, The Implied Reader: Patterns of Communication in Prose Fiction from Bunyan to Beckett, trans. Iser, 1974); Hans Robert Jauss, Ästhetische Erfahrung und literarische Hermeneutik (1982, Aesthetic Experience and Literary Hermeneutics, trans. Michael Shaw, 1982), Toward an Aesthetic of Reception (1982); William Labov and David Fanshel, Therapeutic Discourse (1977); Ruth Leodolter, Das Sprachverhalten von Angeklagten bei Gericht (1975); Robert Longacre, An Anatomy of Speech Notions (1976), Grammar of Discourse (1983); Diane Macdonnell, Theories of Discourse: An Introduction (1986); Bronislaw Malinowski, “The Problem of Meaning in Primitive Languages,” The Meaning of Meaning (by C. K. Ogden and I. A. Richards, 1923); Colin Martindale, ed., Psychological Approaches to the Study of Literary Narratives (1988); Jacob L. Mey, Whose Language? A Study in Linguistic Pragmatics (1985); Kenneth Lee Pike, Language in Relation to a Unified Theory of the Structure of Human Behavior (1967); Harvey Sacks, Emmanuel Schegloff, and Gail Jefferson, “A Simplest Systematics for the Organization of Turntaking for Conversation,” Language 50 (1974); Siegfried J. Schmidt, Foundations for the Empirical Study of Literature: Components of a Basic Theory (1982); Siegfried J. Schmidt, ed., Aspects of the Empirical Study of Art and Media, special issue, Poetics 18 (1989); John McHardy Sinclair and Malcolm Coulthard, Toward an Analysis of Discourse (1975); Michael Stubbs, Discourse Analysis (1983); Henry Widdowson, Explorations in Applied Linguistics (1979); Ruth Wodak, Language Behavior in Therapy Groups (1986); Ruth Wodak et al., Language, Power, and Ideology (1989). Source: Groden, Michael, and Martin Kreiswirth. The Johns Hopkins Guide to Literary Theory and Criticism. Baltimore: Johns Hopkins University Press, 1994.

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Discourses of artificial intelligence in higher education: a critical literature review

  • Open access
  • Published: 24 October 2022
  • Volume 86 , pages 369–385, ( 2023 )

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  • Margaret Bearman   ORCID: orcid.org/0000-0002-6862-9871 1 ,
  • Juliana Ryan 2 &
  • Rola Ajjawi 1  

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Artificial intelligence (AI) holds significant implications for higher education; however, references to AI in the literature are often vague and open to debate. In order to understand how to progress AI-related research and analysis, this critical review systematically searched top higher education journals for references to the term ‘artificial intelligence’. We reviewed definitions and conducted a discourse analysis of included texts. Our findings identify few, confusing definitions and little overt reference to AI as a research object. We delineated two Discourses. The Discourse of imperative change outlines how AI is seen as an inevitable change to which all must respond. Additionally, the Discourse of altering authority describes how texts position AI as decentring the teacher and spreading authority across staff, machines, corporations and students. Our analysis prompts a call for new research foci that attend to the social implications of AI, including tracing accountability in AI-mediated practices and exploring how AI influences learning and teaching relationships.

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Introduction

The increasing reach of artificial intelligence (AI) has enormous implications for higher education. For instance, essays are graded by AI (Foltz et al., 2013 ), and AI-based facial recognition is being used to proctor online exams (Swauger, 2020 ). Moreover, it is not just the university workplace that is changing: graduates’ futures are increasingly dependent upon AI-mediated workplaces where job profiles and work practices may be radically shifting (Moscardini et al., 2020 ). A working paper of the Organisation for Economic Co-operation and Development (OECD) (Vincent-Lancrin & van der Vlies, 2020 , p. 16) captures these sentiments, concluding that there ‘is no doubt that AI will become pervasive in education …’ and that there is need to ‘…prepare students and learners for the transformation of work and society…’.

The pandemic has accelerated the introduction of online technologies in higher education (Bartolic et al., 2022 ) and the associated opportunity for ‘machine-to-student’ interactions brokered by AI (Rof et al., 2022 ). These may include commercial interests: learning management systems invoke AI as a selling point (Marachi & Quill, 2020 ) and ubiquitous commercial learning technologies such as language learning applications rely on some form of AI (Pikhart, 2020 ). Historically, computerisation has promoted a shift away from routine manual and cognitive tasks towards non-routine analytic and interactive tasks (Autor et al., 2003 ), suggesting that technologies such as AI could have real impact upon labour markets and thus higher education. Therefore, AI is not just a matter for technological innovation but also represents a fundamental change in the relationship between higher education and broader socioeconomic interests. At this time of accelerated change, where the social shifts are as significant as the technological ones, universities need to set strong policy and research agendas that attend to AI and take account of ethical implications.

How universities respond to AI depends not only on what AI is but also on what it is understood to be. The ways that AI is portrayed within the higher education literature helps shape research, policy and practice, and discourses about technology can be powerful. For example, such discourses can legitimate particular notions of labour and productivity, such as the promotion of flexible working and the conflation of work and home (Fisher, 2010 ). Indeed, Fisher ( 2010 , p. 231) writes ‘the discourse on technology is not simply a reflection of the centrality of technology in the operation of modern societies; instead, it plays a constitutive role in their operation, and enables precisely that centrality’. Thus, we suggest analysing the discourses of AI within the higher education literature provides insights into how we are constructing AI’s possibilities within our field.

This critical review rigorously examines a corpus of the higher education literature that makes reference to AI. We seek to illuminate how researchers define, debate, neglect or interpret AI. Thus, we aim to critically explore the discursive constructions underpinning higher education’s approach to an increasingly ubiquitous and influential technology. This is not just a matter of summarising gaps and strengths within the literature but a need to promote critical conversations and investigations about AI that grapple with the social and ethical in concert with the technological.

In the remainder of this article, we consider how AI is currently discussed with respect to higher education in the broader literature before outlining our guiding research question. Next, the “ Methods ” section reports on both critical review methodologies and the discourse analytic approach. We then summarise the 29 included articles and their limited definitions, before detailing two prominent Discourses that our analysis identified: the Discourse of imperative response and the Discourse of altering authority. These provide a platform to critique current conceptualisations of AI in the literature, outlining a research agenda that prioritises the social as much as the technical.

AI research in the context of higher education

A recent systematic review (Zawacki-Richter et al., 2019 ) details 146 papers that focus on AI in the context of higher education. This review primarily includes articles that have a strongly technical approach and describe applications such as profiling students for reasons such as admission and retention; intelligent tutoring and personalised learning systems; and assessment and feedback systems, including automated assessment and feedback information. There are only three articles from the main higher education journals (listed in Table 1 ); instead, most articles are from specialist AI, educational technology or computing journals. This is valuable work, but it means that the broader concerns of higher education are not reflected in these studies and vice versa. Concerningly, AI seems to be relegated to being a technological innovation without social implications. For example, Zawacki-Richter et al. ( 2019 , p. 10) note that a ‘stunningly low’ number of articles (2/146 papers) in their review consider ethical implications. However, as Hayward and Maas ( 2021 ) outline in their primer on crime and AI, this technology has been used to enhance criminal activity, promote racism and increase surveillance; moreover, AI can be considered part of a ‘digital colonialism’ that entrenches and extends current inequalities (Kwet, 2019 , p. 3).

We suggest that AI requires a debate that is specific to higher education, concerns the broader social impacts and is not only found in technologically focused journals. This need is articulated within Aoun’s ( 2017 ) seminal work Robot-proof education , which proposes that universities should be considering how to develop students’ uniquely human skills rather than replicating things that AI can already do better. So, how is AI discussed and investigated within the literature most relevant to our field?

Aim of this review

The overall aim of this critical literature review is to provide insight into the discursive constructions of AI within the field of higher education. We address this aim by answering the following question: how is the term ‘artificial intelligence’ invoked in the higher education research literature?

A critical literature review is a methodology that ‘seeks to identify most significant items in a field’ to produce a ‘conceptual contribution’ (Grant & Booth, 2009 , p. 94). A critical methodology aligns with our view that language has power beyond that which it is representing (Gee, 2014 ; Popkewitz, 2013 ). From this perspective, language, context and society are entwined to mutually constitute each other (Gee, 2004 ). Our approach is linguistically based: we target the most prominent higher education journals, employing a systematic search for the specific term ‘artificial intelligence’ as detailed below. The value of this approach is illustrated by other educational reviews where the terms such as ‘community of practice’ (McGrath et al., 2020 ) or ‘feedback’(Jensen et al., 2021 ) are analysed in a dataset constituted from recent publications in relevant high-profile journals. These analyses provide insight into underlying conceptualisations and assumptions within the research literature.

Gee ( 2004 , p. 45) notes that the ‘situated meanings of words and phrases within specific social language trigger specific cultural models in terms of which speakers (writers) and listeners (readers) make meaning from texts’. Accordingly, we seek the ways in which higher education researchers construct the term ‘artificial intelligence’. We do so by (a) analysing how the term is defined within the texts and (b) through a rigorous discourse analytic process (Gee, 2004 ). As we outline below, we employed this type of language analysis to illuminate social identities of academics, teachers and students that were connected to debates about the purpose of the university and varying perspectives on human–machine relations.

Search strategy

We established the top ten journals in the field by combining the ‘top ten’ higher education focussed journals from Scimago, JCR and Google Scholar (see Table 1 ). There was a high degree of concordance, and all journals appeared at least once. As we are interested in how the term ‘artificial intelligence’ is invoked higher education studies to reflect a specific research community, we did not include journals that commonly but not exclusively publish higher education literature nor journals that were primarily part of another field, such as medical or teacher education. While four journals could be regarded as specialist due to their focus on teaching or assessment (3) or technology (1), we argue that these are all commonly read in the field and constitute a broad corpus of literature that should reflect the predominant concerns in AI within the sector.

We individually searched each of these journals for use of the specific term ‘artificial intelligence’ within the text from any time up to November 2020. We included historical texts in order to chart shifts in discursive constructions, if present.

This yielded 92 peer-reviewed articles. We excluded articles based on the lack of meaningful engagement with the term ‘artificial intelligence’. Those that employed the term centrally or meaningfully were automatically included. Those that referenced the term outside of the body of the article (e.g. in the reference list) were automatically excluded. The rest were read for meaningful engagement with the term by two researchers (MB, JR) and discussed iteratively for development of meaning with the third (RA). Twenty-nine articles were included ( Supplemental materials  contain a full listing by journal).

We read each text for any explicit definitions of AI and any implicit associations with other forms of technology.

  • Discourse analysis

Discourse analysis is a complex and rigorous qualitative methodology; to make sense of our approach, we describe key analytical moves with associated illustrative examples from the texts included in our review. We followed Gee ( 2010 , 2014 ), as we elucidate below, to interpret textual references to AI with respect to their: situated meaning , social language , intertextuality , figured worlds and Conversations . These five aspects delineate Discourses : sets of language uses that encompass beliefs, values, interactions and actions (Gee, 2004 ). Thus, this analysis produces overarching Discourse categories, which provide insight into the social meanings ascribed to AI in the texts.

We commenced the discourse analysis by examining all textual references for specific meanings ascribed to AI within the context of the focus articles to highlight their situated meanings . For example, AI was variously associated with change at speed and scale through terminology such as ‘unprecedented’, ‘radical’, ‘transformation’ and ‘revolution’. Some of these change-associated meanings were dystopian in tone, for example, an ‘unleashed’ phenomenon. Other texts were utopian, constructing AI as ‘generative’ and a ‘solution’. We noticed how this examination of situated meanings intersected with recurrent dualisms , in this instance utopian and dystopian accounts, which persisted across all facets of the analysis. We began to trace these dualisms as we report in our findings.

Consideration was given to the distinctive language used to constitute particular social identities within the text through their social languages . For example, academic identities were variously framed in terms of autonomy, empowerment and leadership or as resistance to disempowerment due to processes of management and datafication. As we progressed, we systematically interpreted how the texts constructed different social identities for the institution, university teacher and student.

We noted intertextuality , that is, the extent to which articles relate to previous or other texts, for instance, in implicitly Orwellian evocations (e.g. Kwet & Prinsloo, 2019 ) and explicitly, as a reference to science fiction (e.g. Carson, 2019 ). Figured worlds were interpreted. That is, we considered any projected idealised social imaginaries (e.g. what a university should be) and how they were evoked within the texts. Finally, we looked for Conversations , namely, the debates about AI to which the articles refer explicitly or implicitly. For example, debates about the purpose of the university were directly related to marketisation and datafication in critical and dystopian accounts, while Conversations about quality, efficiency and performance took various forms. We also considered the historical placement of the papers and considered whether Conversations shifted over time periods in our analysis.

Description of articles

The 29 included articles were essays (11), empirical studies that collected data (11), case descriptions (5) or technical model development (2). Only ten had AI or an AI-enabled tool within the primary focus of the article. Papers ranged from the 1980s (4), 2000s (4) and 2010s (6), and 14 were from 2020. The authors’ countries were the USA (9), the UK (7), Australia (7) and Canada (2) and one each from Hong Kong, Ireland, Papua New Guinea and China. Predominant disciplines included education (11), technology (7), multiple disciplines (4) and business/law (3).

How AI is defined in the higher education literature

Few articles articulated definitions of AI. Only five texts discussed or provided definitions, and of these, four were from the 1980s. The definitions were vague or circular, and AI was generally defined by reference to human behaviours. The only current discussion of definitions was provided by Breines and Gallagher ( 2020 , p. 1), who stated ‘ Artificial intelligence is often referred to as a technology that can transform “traditional” education where students are passive recipients of information to more dynamic and better forms of education through “highly personalized, scalable, and affordable alternative AI [artificial intelligence] solutions ”’ (Popenici & Kerr, 2017, 10). Another take on artificial intelligence is provided by Cukurova, Kent and Luckin (2019, 3033) who see it as a means to support teachers and thereby augment ‘human intelligence’ to create ‘super educator minds’ . An example of a historical definition is from Barker ( 1986 , p. 202), who writes ‘ “Artificial Intelligence” is said to be exhibited when a computer is made to behave in ways that would be classed as “intelligent” if the behaviour were performed by humans.…’ . All definitions are in the supplemental materials .

AI is often found enmeshed with other concepts, notably data and analytics within more recent papers. For example, Loftus and Madden’s ( 2020 , p. 457) article title contains the prominent twinning: ‘ data and artificial intelligence ’ [bold ours]. Indeed, AI is most frequently described through association with other technological concepts or artefacts. (e.g. ‘ an AI/ machine learning approach ’ (Loftus & Madden, 2020 , p. 458) [bold ours]).

Two Discourses of AI within the higher education literature

The discourse analysis reveals remarkably congruent ideas associated with the term ‘artificial intelligence’ across disciplines, type of article and, more surprisingly, 40 years of publication. Through this, we interpret that AI is understood through two major Discourses. The first Discourse centres around the advent of unprecedented sociotechnical change and how higher education has an imperative to respond. The second Discourse focuses on how AI is altering the locus of authority and agency surrounding academic work. We describe each Discourse with respect to three social identities: (1) institutional, (2) staff and (3) student. Throughout both Discourses, we interpret two dominant dualisms: a present dystopia versus a near future utopia and the human versus the machine. Table 2 provides an overview.

Discourse of imperative response

This Discourse charts the imperatives to respond to a rapid and significant change towards a technology-driven and AI-mediated society.

How institutions are constructed within a Discourse of imperative response

The Discourse suggests that universities must respond to a rapidly changing technologically mediated landscape, of which AI forms a critical component . How universities should respond appears strongly shaped by a dualism of dystopia-is-now versus utopia-just-around-the-corner. For example, Carson ( 2019 , p. 1041) describes ‘ …the dystopian backdrop to a work of science fiction now sets the greatest challenges and opportunities that face universities … ’. Alternatively, inferring utopia-just-around-the-corner, Moscardini et al. ( 2020 , p. 1) write ‘ O ver the last ten years, there has been an unprecedented and exponential growth of technology and artificial intelligence capabilities which is challenging current working practices and will play a prominent role in the way that society develop s ’.

Accounts tending towards dystopia-is-now propose that universities must resist in order to survive. Here, AI has already changed what universities do: for example, ‘ the wider education context is increasingly being shaped by the forces of Artificial Intelligence ’ (Loftus & Madden, 2020 , p. 457). Taking a critical stance and linking the power of AI to the data upon which it is entangled, Williamson et al. ( 2020 , p.362) contend ‘ Academics and students are beginning to address the challenge of how to resist these [data power] trends … starting with a restatement of the inherent public good of higher education ’. This response is not only about technology but what it means to be a university.

Accounts tending towards utopia-just-around-the-corner also propose a response as a matter of survival but frame it as one of positive transformation. For example, Moscardini et al. ( 2020 , p. 11) state ‘ transformation of the university is not just a good idea, it is imperative for their survival ’ [bold ours]. They argue that universities need to shift their educational focus from employment to ethics and sustainability and become a ‘ learning organisation ’, thus raising the priority of the teaching role above the research role. Further, they foresee an emancipatory turn in which Industry 4.0 will create a ‘ Digital Athens ’ where citizens will have increased leisure and a living wage. This will lead people to seek education to forge social connections and learn how to live meaningfully, with both pursuits shaping the university purpose instead of the current vocational orientation. At a less lofty level, Jackson and Tomlinson ( 2020 ) note graduate labour market impacts of Industry 4.0, including AI, and argue that universities should focus on actively promoting students’ career planning.

How staff and staff practices are constructed within a Discourse of imperative response

This Discourse charts the requisite response as teaching and other academic practices shift to accommodate an AI future. There are competing views. At the dystopian extreme, AI replaces humans, and thus, key capabilities are lost. From the utopian perspective, humans employ AI to free themselves for other work. However, there are more nuanced accounts within the texts. For example, Bayne ( 2015 , p. 460) proposes exploring ‘ how human and non-human teachers might work together in a teaching “assemblage”… ’.

In general, those articles that explore teaching innovations with AI components suggest AI will enhance staff practices. This spans decades, from Marshall ( 1986 ) who proposes expert systems as a support for teacher assessment, through to contemporary innovations such as automated feedback on academic writing (Cheng, 2017 ; Shibani et al., 2020 ). Collectively, these texts construct identities of lecturers as hands-off expert guides, students as autonomous learners and technologies as neutral and cost-efficient. Therefore, in these accounts, enhancement of teacher practices underpins an imperative to respond to AI through uptake of practical innovations.

In contrast, Williamson et al. ( 2020 ) frame AI as part of a system promoting collective diminishment of teacher opportunities for thinking and judgement. They note (p.357) ‘ modern data systems with so-called AI capacity ’ require quantitative measures that once in use can alter pedagogy and ‘ teachers lose “pedagogic discretion and professional judgment”… ’ (p. 358). This creates an imperative for teachers to develop new skills, ranging from critical capabilities with respect to AI (Loftus & Madden, 2020 ; Williamson et al., 2020 ) to general understandings of AI (Selwyn & Gašević, 2020 ; Shibani et al., 2020 ). For some, administrative and tutor roles are positioned as replaceable by AI (Hickey et al., 2020 ; Sheehan, 1984 ). The implication is that the necessary response is to retain expert academics and diminish other staff roles.

How students and learning are constructed within a Discourse of imperative response

The texts construct the AI changes as having deep epistemic impact and thus a need for student response. Loftus and Madden ( 2020 , p. 456) argue that the data revolution is changing subjectivities, altering ‘ not only what we see, but how we see it ’ as well as ‘ l earning cultures, philosophies, learning experiences and classroom dynamics ’. Williamson et al. ( 2020 , p. 358) note: the students lose ‘ opportunities for pedagogic dialogue or critical independent thinking ’. Alternatively, Shibani et al., ( 2020 , p. 11) propose that the purpose of their AI-powered automated feedback tool was to ‘ develop students’ self-assessment ability, as a method to support their learning… ’.

Wherever they sit on the dystopian–utopian spectrum, these accounts suggest that students need to learn new understandings or practices in order to respond to changes brought about by AI-embedded technologies. Williamson et al., ( 2020 , p. 359) note ‘ students develop critical skills of using and evaluating data ’. As far back as 1985, Haigh (p 168) observes ‘ Our students need to acquire an understanding of what expert systems are and what is meant by artificial intelligence and how it resembles human intelligence. They must also develop an appreciation for the appropriate interplay of artificial intelligence and human intelligence in decisions ’. The collective implication of these texts is that unless they take necessary responses, students will be diminished or disempowered.

Discourse of altering authority

If the first Discourse traces the imperative of responding to seismic change associated with AI-embedded technologies as a matter of universities’ survival, this second Discourse charts authority and agency in a state of flux within higher education.

How institutions are constructed within a discourse of altering agency

We interpret two competing accounts regarding institutional authority aligned with the dualism of dystopia-is-here versus utopia-is-just-around-the-corner. From the utopian standpoint, Moscardini et al. ( 2020 ) contend that AI and big data can proactively and innovatively shape university offerings to meet student demand. At a similar but more practical level, Liu et al. ( 2020 , p. 2) propose that a ‘ mature artificial intelligent algorithm ’ can guide quality evaluation through running teaching quality questionnaire through a neural net to pick up patterns of teaching behaviours. This implicitly invests authority in quantification. In a similar vein, Grupe ( 2002 ) contends that an expert system can offer guidance to students unable to access a human academic advisor. In these accounts, AI is co-present with other technological players such as algorithms, computers and big data; they are afforded a prominent and positive authority position: ‘ mature ’ and ‘ expert ’.

The alternative dystopian account invokes a fear of powerful data and quantification processes. In these accounts, AI is part of what Kwet and Prinsloo ( 2020 , p. 512) call the ‘ tech hegemony ’. It is seen as entangled with a range of administrative technologies that are both controlling and invested with intentionality. Williamson et al. ( 2020 , p. 352) contend that ‘ … so-called AI products and platforms can now “learn from experience” in order to optimize their own functioning and adapt to their own use… ’ warning against trusting the ‘ magi c ’ of digital quantification, algorithmic calculation, and machine learning. Others share this concern, including Kwet and Prinsloo ( 2020 , p. 520) who caution against the datafication of universities, which they associate with technocratic control, data harvesting and exploitation in ‘ regimes of technocratic control whereby actors in the educational system are treated as objectified parts in a larger machine of bureaucracy ’.

AI is positioned as an intangible contributor to authority within both dystopian and utopian accounts of advancing datafication. AI’s contribution is rhetorical: a ‘ hot topic ’ (Selwyn & Gašević, 2020 , p. 532). It is also somewhat sinister in its invisibility, given its material effects, e.g. ‘ hidden ’ (Wilson et al., 2015 , p. 20) and ‘ deceiving ’ (Breines & Gallagher, 2020 , p. 11). AI is described as a necessary ‘ ingredient ’ that requires ‘ powering ’ with data (Selwyn & Gašević, 2020 , p. 536). But references to AI curiously fade away past this point. AI is mentioned but backgrounded in the critique of the deployment of data in university management (e.g. Kwet and Prinsloo ( 2020 ), Tsai et al. ( 2020 ), Williamson et al. ( 2020 )), which associate data-driven measurement as a tool for control.

How staff and teaching practices are constructed within a Discourse of altering authority

In many of the accounts, expert teaching is privileged and invested with authority. However, the texts chart different notions of where this authority is or will be located: with human teachers or the AI-embedded technologies or corporations or, as explored in the next section, with students.

There are explicit discussions around the power dynamics between teacher and AI. For example, ‘ …just as the emergence of AI in other contexts provokes debate about what makes us “truly human” and how we should relate to machines, the emergence of AI-powered feedback adds new dimensions to the concept of what “good feedback” looks like: it may no longer be only what humans can provide… “feedback literacy” may also need to expand to take into account the machine now in the feedback loop ’(Shibani et al., 2020 , p. 12). As these comments suggest, AI-mediated technologies foreground questions of what it means to be human and what authority teachers hold. In 1986, Knapper (p. 79) describes a utopia-just-round the corner, where computers can incorporate ‘ … pedagogical strategies derived from artificial intelligence or “expert systems” . The idea here is that the program would actually learn something about the student and adapt its teaching strategy accordingly (hence mimicking a good human instructor) ’. In early accounts, the machines are held to be lesser than humans. But over time this shifts: by 2020 Loftus and Madden (p.457) ask ‘ How can we … teach more effectively in this new learning landscape and be critical participants rather than passively tracked objects? ’.

This Discourse highlights the way AI challenges what it means to be a teacher. For some, the goal of AI is to invest the authority of the teacher into the technology, as with Knapper ( 1986 ). However, in Breines and Gallagher’s ( 2020 ) discussion of teacherbots, AI cannot interact with the broader community and hence lacks authority. Moreover, their language suggests AI is deceptive, implying that it intentionally undermines and competes with human agency. They note (p.11) ‘ We are not seeking to make bots resemble humans and risk deceiving the users about who they engaging with (Sharkey, 2016), but rather make bots that are recognized as such: automated agents that have been designed… to “leverage human intelligence”… ’ In this and other accounts (Breines & Gallagher, 2020 ; Loftus & Madden, 2020 ), staff identities are disempowered by AI and AI-embedded technologies, losing agency and authority to the technology and also to corporate interests behind that technology.

How students and learning are constructed within a Discourse of altering authority

The texts construct students’ altering agency and authority within a learning landscape mediated by technology with AI, as an implicit or explicit ingredient, particularly with respect to datafication. For example, Tsai et al. ( 2020 , p. 556) note ‘ Critical arguments within and beyond academia often take aim at data-based surveillance, algorithmic manipulation of behaviours and artificial intelligence to ask rather philosophical questions about what it means to be human, or to have “agency” ’.

Both utopian and dystopian accounts describe how the AI or the AI-embedded technology constrains what students can be or do. From a utopia-just-around-the-corner sense, this is a kind of benevolent efficiency. Moscardini et al. ( 2020 , p. 13) note ‘ There is encouraging progress in developing automated systems that will make online courses more efficient by helping students identify areas where they struggle and by repeating and reinforcing sections as needed ’. Many texts construct how AI-embedded technologies will grant agency and authority to students. This is from the earliest accounts: Marshall ( 1986 , p. 205) writes the main advantage of ‘ Intelligent Computer-Assisted Instruction’ [is] the student can be “involved actively in generating his [sic] own knowledge base” … ’.

From a dystopia-is-now perspective, AI-embedded technologies take away authority and agency from the student and may be ‘ harmful ’ (Marachi & Quill, 2020 , p. 431). For example, Williamson et al.’s ( 2020 , p. 361) account of datafication, with its implicit AI, shifts authority and indeed humanity in the form of sense-making away from students: ‘ … students are increasingly viewed as “transmitters” of data than can be sensed from autonomic signals emitted from the body, rather than as sense-making actors who might be engaged in dialogue ’. In the dystopian accounts, authority is variously held by institutions, technology companies and within the software itself. Bhatt and MacKenzie ( 2019 , p. 305) write, ‘ Without knowing just how such platforms work, how to make sense of complex algorithms, or that data discrimination is a real social problem, students may not be the autonomous and agential learners and pursuers of knowledge they believe themselves to be ’. Therefore, without the necessary skills, students will cede agency and authority over what and how they learn.

This critical review of the literature demonstrates how little in-depth discussion of AI there is within the leading higher education journals. Despite increasing references to AI from 2020, these are still not substantively concerned with AI itself. While there are some empirical articles exploring concrete technologies where AI is foregrounded, such as automated feedback (Shibani et al., 2020 ), in other similar articles, there is little explicit reference to AI, except as a ‘ hidden ingredient ’. This lack of clarity and focus becomes more obvious given that the texts invoke AI almost always in association with other aspects of technology. As the definitional analysis indicates, definitions of AI are rare and take for granted either the notion of AI itself or the notion of human intelligence.

The lack of explicit discussion of what AI means highlights the significance of the implicit conceptualisations within our discourse analysis, particularly when they are continuations of discourses first seen in the 1980s. The Discourse of imperative response describes how the texts construct institutions, staff and students as necessarily responding to a seismic shift, but it is not clear what this shift is or what the response should be with respect to AI. Similarly, while the Discourse of altering authority notes that AI profoundly changes the notions of agency and accountability either now or in the very near future, the implications of such changes tend to be highly speculative.

The clarity of the two dualisms that thread through both Discourses contrasts with, and tend to overwhelm, the ambiguous conceptions of AI. They do not only pertain to AI but to technology in higher education generally. The first dichotomy — utopia-just-around-the-corner versus dystopia-is-now — aligns with the doomster/booster dualism noted by Selwyn ( 2014 ). The second and, possibly an even older, duality is of human versus machine, invoking the mythic language historically associated with new technologies over time (Mosco 2005 ). The presence of these dualisms is not surprising, given the anthropomorphised machine made so popular in fiction or film. However, the insight that this review provides is that this intertextuality appears to be the predominant way in which AI is constructed in the field of higher education.

Dualisms in themselves are not necessarily problematic. The teacherly human may be better conceptualised through the consideration of the teacherly AI. Likewise, the dystopian accounts alert us to the real concerns of an AI-powered datafied world, reining in the more utopian accounts. However, we contend that dualisms have particular limitations when AI itself appears so intangible. Mythic language makes sense when a technology is on the cusp of social integration, like electricity or telegrams, but should dissipate as technologies become familiar (Mosco 2005 ). Such hyperbole can obscure definitional clarity and prevent more nuanced, generative conceptualisations or conversations, particularly as AI, like other technologies before it, is fundamentally changing higher education practices (see, for example, Foltz et al. ( 2013 ) and Swauger ( 2020 )).

Across all the discursive analyses, AI itself is truly the ‘ghost in the machine’, to appropriate Ryle’s classic phrase. By this we mean, despite material effects, AI is seen as intangible, close to invisible and evoked as a haunting, hidden presence, rather than any particular tangible feature. Distinguishing characteristics, aside from being either like a human or not like a human, are that AI is ‘ deceiving ’, which implies a kind of anthropomorphic ill-intent, or ‘ relentlessly consistent… at speed, scale or granularity ’, which implies a kind of mechanistic indefatigability, or it is a ‘ hot topic ’, a valuable rhetorical device.

Zawacki-Richter et al.’s ( 2019 ) systematic review of AI and higher education provides a useful point of comparison to our work, with articles drawn primarily from outside higher education journals and with very little overlap. Much of that literature is concerned with interventions and does not consider ethical implications (Zawacki-Richter et al., 2019 ). By contrast, our review contains considerable concern about the ethical, epistemic and hegemonic impacts of technology. In both reviews, however, there is limited discussion about how teachers might work with AI-powered technologies beyond immediate concrete applications or how teachers might inform future AI development. This is significant: as mentioned in the “ Introduction ”, AI is also the domain of commercial interests, and the sector would be wise to expand its horizons and investigate nuanced impacts of AI that encompass both the social and the technical.

We propose an alternative research agenda, based on the insights from this literature review, as well as the broader literature. We suggest there are three significant research foci for higher education that need attention: firstly, the language of AI; secondly, issues of accountability and labour; and finally, the implications for teaching and learning contexts beyond single innovations.

Debating a new language for AI

This literature review reinforces how discursively slippery the concept of AI is: it operates as a concrete technology, an abstract ideal, a rhetorical device, a metaphor and a social imaginary all at once. Zawacki-Richter et al.’s ( 2019 ) systematic review noted that only 5 out of 146 articles actually provided definitions and in this review, only one paper in the last three decades included a definition. This is a clear area for work. However, a singular definition may not suffice. AI may, simply, mean different things to different people (Bearman & Luckin, 2020 ; Krafft et al., 2020 ). Bringing these debates to the higher education literature is a good starting point.

We contend that AI ambiguity is not just a matter of definition. This review suggests the urgent need to rethink the language of AI in order to build a more substantial conversation about the role of AI within the higher education literature rather than its current intangible presence, underpinned by long-standing dualisms of human/machine and utopia/dystopia. For example, Johnson and Verdicchio ( 2017 ) make the distinction between computational artefacts that contain AI and AI systems that are sociotechnical arrangements including people, contexts and machines. They suggest that questions of autonomy can be discussed within the AI system but not ascribed to the computational artefacts. By bringing this or similar language to the field, nuanced understandings of AI can disseminate throughout academia and thereby may shed insight into challenges facing universities as they grapple with both AI as technology and social imaginary.

Tracing accountability in AI-mediated higher education

In the texts included in our review, AI did not come as a delineated technology. Indeed, it mostly appeared what Johnson and Verdicchio ( 2017 ) might call an AI system. We prefer the term ‘assemblage’ to refer to the entangled, self-generating constantly assembling collection of human and non-human actants that together make a whole (Fenwick & Edwards, 2012 ). As can be seen in the Discourses above, AI in higher education encompasses an assemblage of data, different kinds of software, bureaucracies and corporations that sometimes include and sometimes exclude teachers, students and administrators. Many critical perspectives in our review point out how much this assemblage impacts upon the authority of teachers and students, as we outline in the Discourse of altering authority. However, it remains unclear where accountability, a concrete and highly significant manifestation of authority, rests or should rest, now or into the future.

Tracing accountability — or other manifestations of authority — associated with AI offers significant value for higher education researchers. A new form of accountability, diffuse and held between actants, is seen in data-driven contexts such as healthcare (Hoeyer & Wadmann, 2020 ) but remains understudied in higher education. In an AI-mediated higher education landscape, who takes responsibility for decisions? What happens when mistakes are made? Studying the effects in a detailed empirical manner may prove valuable. We also note that lower status staff such as tutors and administrators was sometimes represented as expendable in the Discourse of imperative response. It may be worth interrogating the assumption that ‘lower level’ jobs or functions are seen as replaceable with AI. What actually happens when this labour is automated? What other assumptions are we making about labour and about humanity?

The learning and teaching perspective: exploring relationships rather than innovations

The literature in our review constructs a landscape of shifting authority and agency and hence relationships between teachers, students, technologies and institutions. Interestingly, while there may be an imperative to respond to the shifting landscape, the literature charted limited concrete scholarly consideration of what this change might be from a learning and teaching perspective. The few papers within our review which grappled with this directly raised interesting questions about AI-mediated technologies (Bayne, 2015 ; Breines & Gallagher, 2020 ; Shibani et al., 2020 ). While there are some publications outside of the journals listed in Table 1 , particularly in the field of feedback and assessment (e.g.Bearman & Luckin, 2020 ; González-Calatayud et al., 2021 ), there is scope for further inquiry, particularly empirical work (Bates et al., 2020 ). There would be great value in expanding empirical inquiry beyond investigating one AI education-specific tool such as a chatbot to consider multiple instances of increasingly common technologies. In coming to understand how AI works in situ, between and across other actants, we can gain more insight into how teachers, administrators, corporations, machines and students work with and around each other from a learning and teaching perspective. What pedagogies are needed? How can students learn to work in an AI-mediated world? Such studies might investigate how automated feedback tools on writing are shaping teaching and learning across the sector or by exploring how the algorithms in learning management systems influence teacher and student practice. In answering these questions, it is important to consider what is taught or learnt or transformed and also what is avoided, omitted and reconsidered.

Strengths and limitations

This critical literature review has closely examined how the term ‘artificial intelligence’ is invoked in the prominent higher education literature, using a rigorous discourse analytic approach to explore the included texts. We have drawn only on the most prominent higher education texts to capture the field; this is both a strength and a limitation. We have searched only on the term ‘artificial intelligence’ and therefore may have omitted texts which are focussing on AI but concern machine learning or data mining or a range of synonyms for technology that uses AI approaches to software development. While this may mean that parallel discussions have not be included within this literature review, it allows for an unambiguous focus. We searched for this term with no date limits, which has afforded an interesting perspective: while the technology has radically changed, some conceptualisations remain remarkably persistent over decades.

Conclusions

This critical literature review indicates a significant opportunity to investigate the role of AI in higher education. The two Discourses provide an insight into how higher education researchers fundamentally regard AI. It is an invisible ingredient but a force nonetheless. AI demands response, even as it alters the fundamental structures of agency and authority within the academy. These Discourses themselves lead to a research agenda for higher education studies by developing more nuanced language for AI; a sophisticated grasp of how AI-mediated technologies shift accountability; and a deep understanding of how AI is, or could, influence learning and teaching relationships.

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Thanks to Dr Emma Whatman for conducting the journal searches.

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Bearman, M., Ryan, J. & Ajjawi, R. Discourses of artificial intelligence in higher education: a critical literature review. High Educ 86 , 369–385 (2023). https://doi.org/10.1007/s10734-022-00937-2

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What does the literature mean by social prescribing? A critical review using discourse analysis

Sara calderón‐larrañaga.

1 Centre for Primary Care and Mental Health, Wolfson Institute of Population Health, Queen Mary University of London, London UK

2 Bromley‐by‐Bow Health Partnership, XX Place Health Centre, Mile End Hospital, London UK

Trish Greenhalgh

3 Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Primary Care Building, Radcliffe Observatory Quarter, Oxford UK

Sarah Finer

4 Barts Health NHS Trust, Newham University Hospital, London UK

Megan Clinch

Associated data.

The data that supports the findings of this study are available in the supplementary material of this article.

Social prescribing (SP) seeks to enhance the role of the voluntary and community sector in addressing patients' complex needs in primary care. Using discourse analysis, this review investigates how SP is framed in the scientific literature and explores its consequences for service delivery. Theory driven searches identified 89 academic articles and grey literature that included both qualitative and quantitative evidence. Across the literature three main discourses were identified. The first one emphasised increasing social inequalities behind escalating health problems and presented SP as a response to the social determinants of health. The second one problematised people's increasing use of health services and depicted SP as a means of enhancing self‐care. The third one stressed the dearth of human and relational dimensions in general practice and claimed that SP could restore personalised care. Discourses circulated unevenly in the scientific literature, conditioned by a wider political rationality which emphasised individual responsibility and framed SP as ‘solution’ to complex and contentious problems. Critically, this contributed to an oversimplification of the realities of the problems being addressed and the delivery of SP. We propose an alternative ‘care‐based’ framing of SP which prioritises (and evaluates) holistic, sustained and accessible practices within strengthened primary care systems.

INTRODUCTION

Over the past decades, there has been an increasing interest in enhancing the role of the voluntary and community sector (VCS) in addressing patients' needs in primary care (Milbourne,  2009 ; Teasdale et al.,  2012 ). Such efforts have mostly focussed on structuring intersectoral connections through the development of supported pathways for referring patients into the VCS. Social prescribing (SP) is one such example, whose most distinctive feature is the deployment of a new role, link workers or social prescribers, responsible for facilitating patients' journey from general practice to community‐based activities and organisations (Drinkwater et al.,  2019 ). Link workers' role may range from signposting to more intensive approaches involving patients' needs assessments, ongoing support, coaching and motivational interviewing, or the development of new VCS activities where gaps exist (Brown et al.,  2021 ). Community recommendations may be ‘lifestyle’ related (such as, cooking classes, exercise, or weight management schemes) or have a wider remit, including community engagement (volunteering, befriending) or welfare advice programmes (related to employment, housing or financial advice), depending on patients' needs and availability (Roland et al.,  2020 ).

Social prescribing is growing internationally, with initiatives in United States, New Zealand, Australia, Spain and elsewhere (Aggar et al.,  2020 ; Alderwick et al.,  2018 ; Calderón‐Larrañaga & Braddick,  2021 ; Tava’e & Nosa,  2012 ). However, United Kingdom seems to be leading the way in establishing formalised, national SP pathways, with explicit mentions in subsequent policy reports, such as the NHS Five Year Forward View (NHS England,  2014 ), the General Practice Forward View (NHS England,  2016 ) and, more recently, the NHS Long‐Term Plan (NHS,  2019 ). By considering SP into its “comprehensive model of personalised care” , the NHS Long‐Term Plan marked a step change in ambition and set a target of recruiting enough link workers to make the service available in every NHS England GP practice by 2023/2024 (Hancock,  2018 ).

However, despite growing policy interest and proliferation, the evidence‐base for the effectiveness of SP interventions is still sparse and inconclusive. Quantitative studies and systematic reviews have often failed to prove consistent health, service utilisation or cost benefits (Bickerdike et al.,  2017 ; Chatterjee et al.,  2018 ; Gottlieb et al.,  2017 ; Pavey et al.,  2011 ; Pescheny et al.,  2020 ; Public Health England,  2019 ), in part due to research methods and designs not best suited to evaluate such complex interventions. Qualitative studies and novel methodological approaches have enabled a better understanding of ‘why’, ‘for whom’, and ‘in what circumstances’ interventions might (or might not) work (Fixsen et al.,  2020 ; Husk et al.,  2020 ; Skivington et al.,  2018 ; Tierney et al.,  2020 ). Our previous realist review, for instance, critically explored what ‘good’ practice in SP looked like and how this could be best achieved, by identifying relevant individual, relational, organisational and policy resources (Calderón‐Larrañaga, Milner, et al.,  2021 ).

Beyond uncertainty of whether and how SP works, there is also a need to explore how SP is being framed, conceptualised and ‘used’ in contemporary society and the scientific literature. Social prescribing programmes are developed and implemented within a wider social and cultural context where different (and often competing) interests, expectations and priorities co‐exist. As highlighted by the systematic review of Rempel et al. ( 2017 ), the intended aims of SP programmes often vary and might be different for different stakeholders: from cost savings, to resource reallocation or improved patients' mental, physical or social wellbeing. Questions, therefore, need to be asked about how such a complex set of claims and concerns become seemingly rational and coherent, as well as their potential impact on the way services are designed, implemented and evaluated.

In this study, undertaken as a background to an empirical realist evaluation on SP in populations at high risk of type 2 diabetes (Calderón‐Larrañaga, Clinch, et al.,  2021 ), we sought to analyse how meaning and expectations around SP were constructed and reproduced in existing scientific literature. We adopted a critical and reflexive approach to the literature to identify recurring and conflicting discourses in evidence and theory. Our research questions were: ‘How is SP represented and understood in the scientific literature?’, ‘What are the implications of these different understandings for the development and implementation of SP?’ and ‘How do these understandings relate to larger overarching discourses within a broader socio‐historical and political context?’

Epistemological position: Constructing meaning from discourse patterns

As Dryzek ( 1997 ) puts it, discourses can be understood as “ shared ways of apprehending the world ”. Each discourse rests on certain assumptions, judgements and claims that can be analysed in relation to specific social and historical contexts. Different social understandings of the world lead to different social actions. Discourse analysis is, therefore, not only interested in how meaning is constructed, but also in its wider social consequences (Yazdannik et al.,  2017 ).

There is a wide range of approaches to discourse analysis, depending on the focus, sources of data or level of analysis (Glynos et al.,  2009 ; Hodges et al.,  2008 ). In this study, we drew on diverse discourse analytical approaches to explore the conceptual framings of SP in the scientific literature. Our study adopted a critical approach (in the sociological sense) to existing literature on SP that would go beyond a methods‐focussed critical appraisal. We sought to question the way in which the scientific literature frames its object of study (namely, SP) and the nature of the assumptions on which it draws. Following the classification of critique within the discourse‐historical approach proposed by Reisigl and Wodak ( 2009 ), we focussed on the contradictions, paradoxes and dilemmas in the text or discourse (immanent critique), while also revealing the underlying “ belief (and knowledge) systems ” in and by which these discourses operate (socio‐diagnostic critique).

All discourses are populated and constituted by elements of other texts, generating dynamic discourse systems linked across time and space (Conde,  2009 ). Within the SP literature, for instance, authors constantly quote and refer to previous texts in a dialogue that generates meaning (‘horizontal intertextuality’; Kristeva,  1991 ). Yet, as Fairclough ( 1992 ) emphasises, any given text is not only built out of texts from the past, but also transformed and emphasised in a manner which is socially and politically constrained. It is at this level that discourses come to be considered in light of broader ‘systems of knowledge’ or ‘ways of thinking’ (also referred to as ‘political rationalities’; Cornelissen,  2018 ). Our study sought to illuminate this dialectical relationship between discourses within particular scientific texts (‘micro‐’ or ‘little d’ discourse; Gee, 1999 ) and broader discursive patterns within a wider socio‐historical and political context (‘macro‐’ or ‘big D’ Discourse; Gee,  1999 ).

Discourse analysis is also concerned with the way in (and extent to) which certain behaviours or phenomena become a problem. The object of problematisation is, however, different across different discourse analysis approaches. In keeping with the discourse‐historic approach in critical discourse analysis, our review went beyond the identification of the contradictions and tensions within (and between) discourses, to also challenge the validity of these claims and their potential consequences (Glynos et al.,  2009 ).

Methodological approach

We applied critical discourse analysis to the studies included in a realist review on SP which we have published elsewhere (Calderón‐Larrañaga, Milner, et al.,  2021 ). The search strategy combined a protocol driven database search with additional manual searches as per best practice recommendations for systematic reviews of complex evidence (Greenhalgh & Peacock,  2005 ).

Two distinct literature searches were carried out between September 2019 and May 2020 under the guidance of a specialist librarian. The strategy and databases for the main search are specified in Appendix  1 . The main search and de‐duplication were reproduced by a second reviewer for consistency and discrepancies were solved by discussion. In addition to database searching, we manually retrieved citations contained in the reference list of relevant articles included in the review and searched for grey literature in websites of national charitable organisations related to SP. Based on the retrieved literature, policy‐level dimensions (including drivers and contractual agreements) were identified as in need of further exploration and refinement. In keeping with the iterative and theory driven nature of realist approaches to evidence synthesis (Pawson et al.,  2004 ), additional targeted searches focussing on these specific domains were performed by manually retrieving articles from the reference list of relevant studies. The review included all studies published in English, French or Spanish on interventions linking adults (>18) in primary care with VCS organisations, regardless of study design (quantitative, qualitative and mixed methods) and including all SP related outcome measures. The relevance, rigour, and richness of all studies included were assessed (Appendix  2 ). We advise readers to access the review protocol (PROSPERO CRD42020196259) and article for further details (Calderón‐Larrañaga, Milner, et al.,  2021 ).

Data analysis followed the guidelines provided by Willig ( 2008 ) and Potter and Wetherell ( 1987 ), supplemented by (macro‐level) features of Hajer's ( 2006 ) argumentative discourse analysis. It was conducted in five stages as specified in Table  1 : reading, coding, analysis, validation and writing. In practice, these stages did not adopt a clear sequential order, but rather merged together in a dynamic and iterative process. We first read and reread all the studies during an initial familiarisation stage to gain an overview of the data and explore the construction and function of texts. Using the research questions as the basis for selection, we considered each article in its ‘wholeness’ and identified recurring and dominant themes across sections, which were coded and grouped together developing what Potter and Wetherell ( 1987 ) refer to as ‘bodies of instances’. At this stage, we followed an ‘inclusive’ approach that avoided setting limits to the data. All studies coded as containing relevant instances and the preliminary coding frame were then uploaded to Nvivo, which provided a platform to manage the organisation of data (see Appendix  3 for further detail on the coding frame and data extracts).

Components of the discourse analysis in the critical literature review

Source : Adapted from other sources (Hajer,  2006 ; Potter & Wetherell,  1987 ; Willig,  2008 ).

Analysis involved careful reading and rereading of the coded data to identify relevant discursive patterns, both in terms of variation (differences and contradictions in the content of accounts) and consistency (similar features across accounts). We explored the potential function of texts, paying attention to the arguments being articulated and ‘pushed’ within (and across) discourses. We investigated the extent to which the identified discursive patterns embed, entail and presuppose other discourses, both in relation to previous texts and to broader systems of knowledge (‘discursive affinity’; Hajer,  2006 ). We validated our analysis iteratively by testing the coherence and fruitfulness of our findings, and through discussion within the research group. The process of writing helped clarify analytic issues and was therefore undertaken ongoingly. It involved writing down detailed explanations of the reasoning process and documenting our analytic claims and conclusions with specific examples and extracts from the data.

Overview of search results

Figure  1 illustrates the screening and selection process for our literature review. The above‐specified search strategy and inclusion criteria led to 140 studies. Following a familiarisation and coding stage, 89 references were included in the review for analysis. Of these, 28 were mixed‐methods studies, 26 used qualitative methods, 19 used quantitative methods, 15 were literature reviews and there was also an evaluability assessment study. 62 articles were published in peer‐reviewed journals, while the remaining 27 were publicly available reports produced by different academic companies and organisations (grey literature). Of our 89 texts, 83 were from UK, 4 from elsewhere in Europe, one from New Zealand and one from Australia. The characteristics of the studies included are further described in Appendix  4 .

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PRISMA flow diagram

We identified three main discourses within the SP scientific literature (summarised in Table  2 ). Discourse 1 ( SP as helping to overcome the social determinants of health ) emphasised the influence of underlying social and structural factors on patients’ health outcomes and proposed SP as a response to the social determinants of health. Discourse 2 ( “From dependence to independence”: SP as supporting patients' journey towards self‐activation ) depicted SP as a means (‘temporary’, ‘limited’) of supporting patients become ‘independent’ and reducing their reliance on overstretched health and social services. Discourse 3 ( SP as enhancing personalised care in general practice ) presented SP as shared, open‐ended and personalised care practices, capable of restoring person‐centredness in primary care. Discourses were distributed unevenly across different type of studies and article sections within the literature reviewed (see Appendix  3 for further detail). Although each discourse made distinct arguments and claims, they shared a tendency towards framing SP in terms of ‘solution’ delivered though individual patient care to address complex and contentious social and health system ‘problems’.

Summary of different discourses in the social prescribing scientific literature

Discourse 1. Social prescribing as helping to overcome the social determinants of health

Social prescribing interventions were often framed within a broader body of literature that emphasised the influence of wider “ social, economic and cultural factors ” on health outcomes (Bungay & Clift,  2010 ). ‘Unhealthy’ behaviours and subsequent higher risk of disease among study populations were often explained in terms of unequal distribution of opportunities and socio‐economic disadvantage. Health and community sectors were identified as key actors in addressing social inequalities, which meant that the response was often framed in terms of health and social service provision (e.g., SP, community‐centred approaches to health): “Evidence that people's education, income, housing and other social issues have a major impact on their health and wellbeing is well established. Given this important relationship, there is growing international interest in the role of healthcare systems in addressing patients' social (i.e. non‐medical) needs” (Pescheny et al.,  2020 ).

References to the social determinants of health were also present when characterising access and healthcare usage patterns in primary care. Growing pressures in general practice were explained in terms of the increasing number of patients contacting a healthcare professional for “non‐medical” reasons (Ferguson & Hogarth,  2018 ). This time, however, ‘social’ and ‘medical’ dimensions were not depicted as mutually determined (e.g., adverse social circumstances lead to poor health and greater healthcare need), but rather as separate (even dichotomised) reasons for consultation ( “20% of people attend GP surgeries for social problems” ; Coan,  2016 ): “GPs spend nearly a fifth of their consultation time dealing with non‐medical issues at a cost of £395 million per annum , equivalent to the salaries of 3750 full‐time GPs. Almost three‐quarters of GPs state that the proportion of time they spend dealing with non‐health issues as part of consultations has increased” (Ferguson & Hogarth,  2018 ).

Social prescribing users were depicted as individuals facing mainly “ social problems ”, such as “social isolation, loneliness, housing issues or bereavement” (Pescheny et al.,  2020 ). General practice was presented as unable to address adequately these ‘non‐medical’ concerns (for instance, as not having enough time to acknowledge patients' social circumstances, at risk of over‐medicalising patients' illnesses) and, consequently, in need of a structural change. Social prescribing was then framed as a means to addressing both existing failures of the health system and patients' wider social determinants of health:

… [name of the SP scheme] illustrates how social prescribing can offer the opportunity to address social needs through individual consultations. An added bonus may be the reduction of workload and more capacity to focus on medical problems. […] A claim can be made that social prescribing, through addressing the wider determinants of health, represents a reorientation of health services […] (South et al.,  2008 ).

References to the social determinants of health were mainly present in the introductory sections of the articles when defining the rationale and potential of SP interventions. Few studies acknowledged the value of link workers' advice (and support) for problems related to housing, employment or welfare benefits referencing patients' experience in the results section (Moffatt et al.,  2017 ; Pescheny et al.,  2020 ). In the remaining cases, the impact of SP interventions on socio‐economic dimensions was either not measured (mostly) or not demonstrated (Aggar et al.,  2020 ).

Discourse 2. “From dependence to independence”: Social prescribing as supporting patients' journey towards self‐activation

Within this discourse, SP was contextualised in a socio‐sanitary reality characterised by people's increasing use of and reliance on public services that were depicted, consequently, as being overstretched. Social prescribing was then presented as an alternative potentially capable of enhancing patients' capacity to self‐manage and reducing their reliance on health and social services: “In the UK, an ageing population combined with a growing number of people living with long term medical conditions is increasing demand and cost pressures on the acute, primary and social care services […] A key demand has been for services to become more integrated to better serve the complex needs of the older, frail population and to be more focussed on encouraging supported self‐management, as a means to reduce demand on primary and secondary care services, making them more sustainable” (Elston et al.,  2019 ).

As outlined by the title of the Rotherham SP evaluation report, “ From dependence to independence ” (Dayson et al.,  2013 ), patients were meant to overcome a status of ‘dependency’ (also referred to as ‘lack of control’, ‘vulnerability’) and move towards a state of ‘self‐efficacy’ (or ‘independence’, ‘activation’) with the help of appropriate techniques and community‐based interventions: “ The [SP programme] endeavours to signpost and provide the person with the information and support they require in order to help them to remain independent in their own homes for as long as possible and reduce their future reliance on health and social services.” (Beech et al.,  2017 )

Lack of ‘self‐perception’, ‘motivation’ or ‘confidence’ was considered a barrier for successful ‘engagement’ and ‘behavioural change’. Interventions, therefore, comprised and prioritised “ coaching ” and “ motivational ” strategies for achieving intended outcomes (Husk et al.,  2020 ). Training of link workers (also referred to as “ wellbeing coaches ” (Heijnders & Meijs,  2018 )) often involved motivational interviewing or goal‐setting techniques (Wildman, Moffatt, Penn, et al.,  2019 ).

Within this discourse, ‘independence’ was equated with self‐management and reduced utilisation of services, whereas ‘dependency’ was deemed problematic. Being (or becoming) ‘too’ reliant on others did not only need to be overcome (potentially with SP), but could also represent a threat to SP implementation and delivery: “There is a danger of patients becoming dependent on a link worker as the source of support; this should be tempered if individuals create new and meaningful connections within the community, which may include reconnecting with friends and family because of a more positive outlook on life. Such an improved outlook may encourage those with existing health conditions to actively engage in self‐care.” (Tierney et al.,  2020 )

Social prescribing schemes, consequently, developed different ‘boundary setting’ strategies to prevent or address ‘dependency’. Certain schemes offered a limited pre‐established number of appointments ( “up to three appointments of approximately up to 40 min each” ; South et al.,  2008 ) to discuss patients' needs and identify relevant community‐based resources. Further approaches identified by Wildman, Moffatt, Penn, et al. ( 2019 ) included “regularly reminding clients of the limits of the link worker role, creating distance by doubling‐up, swapping link workers or running group activities and reasserting the importance of empowerment rather than dependency” . Support (or care) was conceptualised either as a menu from which referred patients were encouraged to ‘choose’ or as a means (‘temporary’, ‘limited’) of helping patients become free from further needing it.

Both behavioural and social determinants of health were often framed as matters that could be addressed through individual action. The focus was placed on the individual (as opposed to on the structural constrains) and their capacity to ‘engage’ with (as opposed to ‘access’) the ‘prescribed’ advice, support and/or activities. This discourse reframed the ‘solution’ in terms of inner rearrangements (e.g., “change in attitude”, “raise of expectations”, “self‐confidence”, “re‐activation”; Beech et al.,  2017 ; Bertotti et al.,  2018 ), assuming that a rational decision‐making and behavioural change would follow: “ Improvements in confidence, self‐esteem, independence, and motivation enabled clients not only to set new goals, but also to actively pursue them” (Payne et al.,  2020 ).

Constrains were also often depicted as belonging to the private or personal sphere (of their “own” ; Bertotti et al.,  2018 ), rather than structural and hence shared by those in similar socio‐economic positions. ‘Empowerment’ was equated with patients' capacity to take “ownership of their problems” (Faulkner,  2004 ), successfully overcome them, and lessen any reliance on health services: “Socially orientated approaches delivered through [SP] may broaden community capacity and empower patients to better manage their own health and make more appropriate use of health services” (Southby & Gamsu,  2018 ). This discourse reinforced the idea of ‘positive change’ (‘advancement’, ‘improvement’, ‘progress’) as a single endeavour by placing the responsibility in the individual: “while a link worker could ‘encourage and support’, long‐term change was about ‘taking responsibility for yourself…nobody else is going to do it’” (Wildman, Moffatt, Steer, et al.,  2019 ).

The way authors measured and made sense of their study outcomes was heavily influenced by this discourse. Researchers often drew on theoretical references and frameworks that emphasised individual agency, resilience, and self‐efficacy. Morton et al. ( 2008 ), for instance, sought to investigate whether an exercise on prescription scheme could foster self‐determined motivation and subsequent behavioural change. Hanlon et al. ( 2019 ) explored whether Self Determination Theory could be used to understand the change (or lack thereof) in behaviour and wellbeing resulting from patients' involvement in a Links Worker Programme. Tierney et al. ( 2020 ) drew on Patient Activation Theory to conceptualise and analyse the role of link workers in SP interventions. Other studies drew on Salutogenesis Model (Beech et al.,  2017 ; Jensen,  2019 ) and its focus on “people's resources, capabilities and the mechanisms that create and sustain health ” (Swift,  2017 ). Bertotti et al. ( 2018 ) referenced self‐efficacy within Social Cognitive Theory to explain behavioural change when evaluating the conditions and mechanisms that facilitated (or hampered) the implementation of a SP intervention. The Social Cure perspective was also used to explain how social group membership developed within a SP programme enhanced participants' confidence building and wellbeing (Kellezi et al.,  2019 ).

Interventions were evaluated (and deemed successful) based on their potential to enhance participants' self‐concept, self‐management and/or behavioural change. Mental wellbeing questionnaires (such as, the Warwick‐Edinburgh Mental Wellbeing Scale), which involved the assessment of participants' self‐perception (e.g., confidence in themselves), were widely used amongst studies included in our sample. Physical health and behavioural questionnaires were also often employed. Many primary and secondary studies chose social and healthcare service utilisation indicators, including primary care attendance, secondary care referrals and/or contacts with community‐based NHS services and Accident and Emergency as outcome variables to monitor effectiveness (see Appendices  3 and 4 for further detail). Different SP interventions identified in our literature review targeted patients who frequently visited their GP or other primary care providers. Loftus et al. ( 2017 ), for instance, focussed on patients over 65 with long term conditions who attended their GP frequently or had multiple medications. Brandling and House ( 2007 ) evaluated a SP programme aimed at patients defined as “high resource users”. In all cases, researchers assessed the capacity of the intervention to reduce service utilisation or primary care workload, generally through the enhancement of self‐management or ‘activation’ strategies.

Discourse 3. Social prescribing as enhancing personalised care in general practice

This third discourse emphasised the dearth of human and relational dimensions within general practice. Clinical appointments were depicted as ‘rushed’, ‘hurried’, ‘impersonal’ and hence unable to accommodate patients' needs and expectations. Within this context, clinicians were often characterised as unable and/or unwilling to explore and listen to patients' wider psychosocial concerns, leading to ‘judgemental’, ‘prescriptive’ and ‘un‐empathetic’ encounters: “I am stuck in this wheelchair and have a lot of problems. I knew that my GP just wanted to get rid of me out of the door. I knew she didn't want to open up the can of worms that were in my head and forcing me to talk to the Samaritans” (Kimberlee,  2016 ).

Social prescribing was then framed as an alternative capable of counteracting these relational shortfalls, by removing ‘time bound’ appointments and providing a holistic, caring and personalised service. Time and space for “ feeling listened to and valued ” (Pescheny et al.,  2018 ) were considered key programme components and preconditions for ‘good’ practice: “I knew what was going on in my head, but I couldn't always, I didn't always want to tell anyone. It seemed, with the link‐worker, it seemed as though I could get over that more quickly. He wasn't demanding. He was very quiet and very gentle with it, and that is the way that I needed somebody to be, to maybe listen to me, really listen to me, and hear what I was saying […]” (Kellezi et al.,  2019 ).

Rather than a provisional transaction, SP was conceptualised as an ongoing ‘practice’ which required perseverance and attentiveness. Care was understood as a ‘need’, rather than a ‘choice’ (“I will always need somebody to help me”; Wildman, Moffatt, Steer, et al.,  2019 ), refined and reinvented dynamically over time depending on its results and patients' fluctuating needs: “[…] another [link worker] suggested that it takes time to develop relationships because of people's complex problems […]: ‘it took time, you know, to build up that relationship with the individual, but you can see just the difference it's made, you know, he knows I'm there and you know I guess it's like chiselling away, each time that I see him, you know, he'll tell me something else’” (Mercer,  2017 ).

Social prescribing was no longer articulated as a linear referral pathway towards a predefined destination, but as a care network comprising different actors. Patients moved back and forth across settings and sectors depending on their changing needs, which required ongoing and bidirectional coordination between care providers. A caring and supportive SP was deemed necessary to ensure successful outcomes. Patients, for instance, were more likely to participate when link workers contacted them directly after receiving the referral, made regular follow up phone calls, or even came along with them to the planned activities. Emotional and practical support seemed to allow patients to overcome (or cope with) the barriers that often prevented them from engaging: “ I just expected the Link Worker to introduce me to the gym, and that would have been it. And I think, if it had just been [that] I would have turned round, and I would have gone the opposite direction. But because of the way it was so gradually and really professionally linked into different things, I just felt as though I'd floated into it, rather than getting shoved from behind. I just felt as though I was gradually moved into it ” (Moffatt et al.,  2017 ).

Support and encouragement not only prevented dropouts, but also enabled people to push themselves harder than they would have by themselves. Similarly, patients were more likely to progress when feeling committed to a regular service provided (“ If you build up a relationship with somebody like Mary you're not going to let her down ” ; Stirrat,  2014 ). Yet, care was not only considered a means towards ‘engagement’, but also an outcome in itself. Knowing that support was available, as well as feeling listened to and cared for were sufficient and relevant endpoints (“ it is very comforting to know that you are not by yourself, that you can ring someone ”; Beech et al.,  2017 ). Social prescribing users were depicted as ‘patients’ (as opposed to ‘clients’) facing enduring and complex health issues and hence in need of continuous and open‐ended care for when things went wrong again: “ I mean with me, I'd still want to be in contact somewhere along the line, which I think they will do. If something happened to me, […] I think I would need them full time all the time then ” (Wildman, Moffatt, Steer, et al.,  2019 ).

As the verbatims above reveal, this discourse mostly drew on patients', link workers' and community stakeholders' lived experience and accounts gathered through qualitative interviewing. Questions related to the provision of enhanced, ongoing care were not, however, addressed explicitly in study aims nor informed by relevant theoretical references. Within the discussion sections, findings were either included as recommendations for improved SP delivery (Faulkner,  2004 ; Husk et al.,  2020 ), problematised in the context of an overstretched primary care system (Mercer,  2017 ) or treated as ‘unintended’ (and hence to be prevented) for potentially implying an increased patients' reliance on health services and running counter initial expectations (Wormald et al.,  2006 ).

This study, based on argumentative discourse analysis of 89 references, identified three main ways of understating the scope and potential of SP interventions. As summarised in Table  2 , discourses differed in their rationale, claims and the characterisation of SP and social reality. Discourses circulated unevenly across different type of studies and article sections within the literature reviewed. While discourse 1 was mainly present as a rationale for SP, discourse 2 was consistently used to design, measure, and interpret existing interventions. Discourse 3 was mostly stressed by participants in qualitative studies and often criticised by study authors. We also identified a shared tendency across discourses, whereby SP initiatives were consistently framed in terms of ‘solutions’ to complex and contentious problems. The extent to which this SP discursive landscape is shaped (and reinforced) by a wider political rationality and the consequences of these alignments are discussed below.

Tackling structural inequalities through health service innovation

Our first discourse exposed a tension whereby SP interventions tended to acknowledge structural injustice but then offered health service innovations and individualised strategies as ‘solutions’ for them. This critical distance between a starting upstream claim and an ultimate downstream denouement has already been acknowledged in the scientific literature (referred to as “lifestyle drift” [Popay et al.,  2010 ; Williams & Fullagar,  2019 ] or “ neoliberal justice narratives” [Littler,  2018 ]). Our study highlights that this ‘drift’ often happens through a process which enhances the role and responsibilities of individuals, health services and communities. We argue this may prove problematic on the following basis.

Growing health inequalities in the UK (and globally) are highly conditioned by underlying structural inequalities (Bambra & Garthwaite,  2015 ; Karanikolos et al.,  2013 ; Stuckler et al.,  2017 ). Maldistribution of power, wealth and resources operate through a wide range of social and economic pathways (including employment, income, housing and education) to generate unequal health outcomes (McCartney et al.,  2020 ). As pointed out by the WHO Commission on Social Determinants of Health, individual and community‐level interventions, such as SP, are well‐placed to ‘reduce the consequences’ of such inequalities through the provision of enhanced care and support. However, they fail to tackle the system which generates (and reproduces) maldistribution, for which system‐level interventions would prove more appropriate (Commission on Social Determinants of Health,  2008 ). Presenting SP as ‘the solution’ may hamper a broader understanding of and response to the social determinants of health, which also addresses its fundamental structural causes and asserts policy‐level responsibilities (Baum & Fisher,  2014 ; Gibson et al.,  2021 ).

Discourse 1 also depicted social determinants of health as definite (even computable) reasons for consultation in general practice, easily detachable from the more ‘medical’ ones. However, health and social dimensions tend to form a continuum, be mutually determined and appear intertwined in consultations (Heath,  1995 ). As pointed out by Stange and Ferrer ( 2009 ) the acknowledgement and understanding of these inter‐relations have proven to be a precondition for the provision of personalised, high quality clinical care in general practice. Presenting SP as a strategy capable of addressing the ‘non‐medical’ needs, may risk exacerbating this contrived dichotomy (‘social’ vs. ‘medical’) while eroding primary care clinicians' responsibility to explore, understand and integrate patients' wider social needs and circumstances in routine consultations (also referred to as ‘ holistic SP ’ and considered best practice (Calderón‐Larrañaga, Milner, et al.,  2021 ).

Easing pressure on the system through the enhancement of self‐care

Our review identified a dominant discourse around patients' ‘independence’, which depicted SP as a means of enhancing their capacity to self‐manage and easing pressure on the system. These expectations seem to have solidified in specific institutional arrangements. NHS England and Improvement, for instance, encourages the use of the Patient Activation Measure tool to assess the “ knowledge, skills and confidence of a person to manage their own health and care ”, as a proxy for reduced service utilisation when evaluating SP programmes (NHS England,  2018 ). The embeddedness of this discourse into specific institutional and organisational practices (also referred to as “ discourse institutionalisation” ; Hajer,  2006 ) highlights its consistency and dominance across the SP arena. We argue this may be problematic on the following basis.

This discourse assumedly linked self‐management with ‘independence’ and reduced reliance on further care. Yet, as highlighted by Hinder and Greenhalgh ( 2012 ), self‐management is rarely an individual, isolated endeavour. Rather, it is often enabled (or constrained) by economic, material and socio‐cultural conditions within the family, community and health services (Hinder & Greenhalgh,  2012 ). Shifting the work of (‘self’‐) care away from clinic risks placing additional demands and burdens on ‘informal’ care providers (family and community), raising ethical and sustainability issues (especially where sufficient or strengthened material and relational resources are not ensured; May et al.,  2014 ). Voluntary and community sector organisations and local authorities operating in deprived communities, for instance, have reported an increased demand for services as a result of patients' underlying socio‐economic circumstances, along with ongoing funding deficits, which affect the sustainability and capacity of their services (NAO,  2018 ; NCVO,  2015 ).

Critically, the notion of a capable, self‐sufficient and independent individual might prove unrealistic for some patients, and lead to significant frustration and guilt when unattained (Peacock et al.,  2014 ). For some patients and in certain circumstances, accepting personal boundaries (“relinquishing control” or “letting go”) and the need for help is beneficial and empowering (Aujoulat et al.,  2008 ). Besides, there are cases where trustful and personalised relationships with link workers and/or the VCS made patients feel safe to disclose problems which often required further clinical input (Tierney et al.,  2020 ). In such cases, patients were referred ‘back’ to general practice, enhancing access to (and utilisation of) health services. ‘Good’ practice in SP may not necessarily involve reduced service utilisation. A SP whose main aim is to ease pressure on the system risks overshadowing (and hence not strengthening) relations of interdependence, collaboration and mutual responsibility, which are relevant endpoints to patients and predict ‘good’ practice in SP (Calderón‐Larrañaga, Milner, et al.,  2021 ).

Lastly, pressures in general practice have resulted from an increasing workload over the last decades, without a matched growth in either funding or workforce (Baird et al.,  2016 ). While work has become more complex and intense in the UK general practice, funding for primary care as a share of the NHS overall budget has gradually fallen (Baird et al.,  2016 ). Framing SP (and the enhancement of self‐care) as the ‘solution’ to overstretched health services, may hinder the consideration and tackling of system factors and supply‐side deficiencies which highly contribute to explain increasing pressures in primary care.

Restoring person‐centredness in general practice through social prescribing

Discourse 3 depicted patient‐clinician interactions within general practice as overtly instrumental (oriented to preventing, diagnosing or treating disease – ‘cure’ talk) and devoid of any type of affective or socio‐emotional component (‘care’ talk) (Greenhalgh & Heath,  2010 ). Social prescribing was then presented as a strategy capable of restoring this imbalance, by creating a new role (link workers) in charge of providing a caring, person‐cantered, empathetic approach.

This discursive reality is reinforced by a general practice where the reason for consultation, rather than the relationship with the patient, shapes the organisation of service provision (Rudebeck,  2019 ). Triaging and task distribution have gradually replaced relationship continuity of care (understood as “the relationship between a single practitioner and a patient that extends beyond specific episodes of illness or disease ” ; Haggerty,  2003 ) despite being associated with better clinical outcomes and reduced all‐cause mortality (presumably in relation to improved clinical responsibility, physician knowledge, and patient trust; Baker et al.,  2020 ). Clinicians are increasingly meant to deal with diseases efficiently, while all the rest (including relationship competence; Rudebeck,  2019 ) is no longer recognised as a vital professional asset and may therefore be shifted to other members of staff (usually less specialised and resourced; Nancarrow & Borthwick,  2005 ). Objective and definable processes (‘cure’ talk) are more easily monitored, owned and regulated than the numerous intangibles in routine consultations (‘care’ talk), which are more prone to be overlooked and transferred (Nancarrow & Borthwick,  2005 ). However, both ‘talks’ are required in order for clinical care to reach its full potential. Framing SP as a ‘solution’ risks disregarding existing trends, their consequences, and the need to ensure therapeutic relationships across disciplinary boundaries (including in general practice).

Rethinking social prescribing beyond a ‘solutionist’ paradigm

As Peter Miller's and Nikolas Rose's ( 1990 ) work revealed, there tends to be a reciprocal interaction between language ( ‘linguistic features’ ) and wider systems of knowledge, where discourses act as means through which (and in which) specific political rationalities are reproduced, consolidate and influence human action (‘ govern’ ). A wider neoliberal rationality resonates with a (dominant) understanding of SP which focused on patients' knowledge and resilience (via informed discussions with link workers and motivational coaching) as a means of consolidating positive lifestyle choices and reducing their reliance on further care. Similarly, a shared “ solutionist ” (Morozov,  2013 ) approach to SP also contributed to enhance the role and responsibilities of individuals, communities and health services in tackling structural and contentious problems (such as, social inequalities, overstretched health services, or increasing fragmentation in general practice). While end users and providers were expected to invest themselves with new skills and ‘ways of doing’ (Brown & Baker,  2013 ), the context of possibilities and constrains in which these actions may (or may not) happen was frequently overshadowed (Mackenzie et al.,  2020 ; Scott‐Samuel & Smith,  2015 ).

The relationship between discourses, practices and wider political rationalities is, however, far from linear. As Brown ( 2015 ) points out, even when one political rationality becomes hegemonic, it carves itself against a range of other possibilities – “ tacitly arguing with them, keeping them at bay, or subordinating them ”. There are different ways of understanding and practicing SP which challenge (while co‐exist with) neoliberalism. Our realist review and ongoing realist evaluation, for instance, identified SP practices which contributed to enhance GPs' understanding of patients' wider needs and their capacity to provide ‘holistic’ and accessible care. Link workers and community organisations provided sustained, open‐ended care to better respond to patients' enduring and complex needs. Critically, this often involved going beyond what was expected, or even disregarding and questioning the way in which services had been designed and commissioned (Calderón‐Larrañaga, Milner, et al.,  2021 ).

These examples allow for the configuration of an alternative ‘care‐based’ framing of SP, which sees the provision of holistic, sustained and accessible primary care not so much as a means to an end, but as an end in itself (Heath,  2021 ; Mol,  2008 ). We speculate that these dissenting (and inspiring) practices contribute to enact an alternative ‘belief system’ whose main rationale is meeting patients' primary care needs through publicly accountable and collaborative services (of which SP would constitute an example). This conceptualisation of SP necessarily shifts the attention of research from measuring impact (via service utilisation indicators) to evaluating the extent to which SP may (or may not) succeed to support people in greatest need while contributing to stronger, fairer health care systems.

Strength and limitations

To our knowledge, this is the first study employing a discourse analysis approach to SP. Diverse and relevant theoretical references allowed us to explore the meanings and expectations around SP in the scientific literature, while highlighting the conditions of possibility and legitimacy for certain discourses to become dominant. Using a critical approach, our review unravelled existing tensions and taken‐for‐granted assumptions, and problematised what these assumptions meant and entailed for the implementation and delivery of SP.

The main limitation of this study is its reliance on a predefined literature search (as opposed to an iterative literature search strategy). As specified in the methods section, we applied a critical discourse analysis approach to the references included in our previous realist review on SP. However, the exhaustive realist review search strategy (which combined searches in 13 databases and additional manual searches, leading to the inclusion of 140 studies) proved sufficiently comprehensive to allow for the description and validation of the identified discursive axes.

CONCLUSIONS

The way in which SP is framed and conceptualised in the scientific literature influences its implementation and evaluation. Our review identified three main ways of understanding SP and unravelled overlaps between them. Discourse 1 emphasised increasing social inequalities behind escalating health problems, while presenting SP as a response to the social determinants of health. Discourse 2 problematised people's increasing use of health and social services and depicted SP as a means of enhancing self‐management and reducing patients' reliance on further care. Discourse 3 stressed the dearth of human and relational dimension in general practice, while presenting SP as an alternative capable of restoring person‐centeredness. Discourses circulated unevenly in the scientific literature, conditioned by a wider political rationality which emphasised individual responsibility and framed SP in terms of ‘solution’ to complex and contentious problems. We speculate that this contributed to oversimplify both the realities and problems being addressed and constrain the way interventions are delivered. Critically, once the “ solutionist ” narrative is exposed as a cover‐story, a range of different narratives and evaluative frameworks become possible. We conclude that these alternative framings broaden our political imagination to rethink (and enhance) the scope and possibilities of SP interventions within stronger and fairer primary health care systems.

CONFLICT OF INTEREST

The authors declare that no competing interests exist.

ETHICS STATEMENT

This project has been approved by the Office for Research Ethics Committees Northern Ireland (reference: 20/LO/0713).

AUTHOR CONTRIBUTIONS

Sara Calderón‐Larrañaga : Conceptualisation (lead); Data curation (lead); Formal analysis (lead); Funding acquisition (lead); Investigation (lead); Methodology (equal); Project administration (lead); Writing – original draft (lead). Trish Greenhalgh : Conceptualisation (supporting); Formal analysis (supporting); Funding acquisition (supporting); Investigation (supporting); Methodology (equal); Supervision (equal); Writing – review and editing (equal). Sarah Finer : Conceptualisation (supporting); Formal analysis (supporting); Funding acquisition (supporting); Investigation (supporting); Methodology (equal); Supervision (equal); Writing – review and editing (equal). Megan Clinch : Conceptualisation (supporting); Formal analysis (supporting); Funding acquisition (supporting); Investigation (supporting); Methodology (equal); Supervision (equal); Writing – review and editing (equal).

Supporting information

Supporting Information 1

Supporting Information 2

Supporting Information 3

Supporting Information 4

ACKNOWLEDGEMENTS

This research is funded by the Economic and Social Research Council (reference: ES/P000703/1) and Currier's Millennium Healthcare Bursary. The views expressed are those of the authors and not necessarily those of the funders.

Calderón‐Larrañaga, S. , Greenhalgh, T. , Finer, S. , & Clinch, M. (2022). What does the literature mean by social prescribing? A critical review using discourse analysis . Sociology of Health & Illness , 1–21. 10.1111/1467-9566.13468 [ PMC free article ] [ PubMed ] [ CrossRef ]

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  5. Discourse Analysis in English- A Short Review of the Literature

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  1. Discourse analysis model

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  3. Literary Criticism and theory Complete Discussion

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  1. Critical Discourse Analysis

    Critical discourse analysis (or discourse analysis) is a research method for studying written or spoken language in relation to its social context. It aims to understand how language is used in real life situations. When you conduct discourse analysis, you might focus on: The purposes and effects of different types of language

  2. PDF A Review on Critical Discourse Analysis

    Actually, the term Critical Discourse Analysis (CDA) is derived from Critical Language Study, whose characteristics are discussed by Fairclough in 1989 in his book, Language and Power. This book is regarded as a landmark in the developmental history of CDA.

  3. A General Critical Discourse Analysis Framework for Educational

    Critical discourse analysis (CDA) is a qualitative analytical approach for critically describing, interpreting, and explaining the ways in which discourses construct, maintain, and legitimize social inequalities.

  4. Critical Discourse Analysis in Education: A Review of the Literature

    During the past decade educational researchers increasingly have turned to Critical Discourse Analysis (CDA) as a set of approaches to answer questions about the relationships between language and society. In this article the authors review the findings of their literature review of CDA in educational research.

  5. Discourse analysis: a critical view

    Abstract. Discourse analysis is in vogue as a field of enquiry, particularly in the guise of critical discourse analysis, which employs procedures not essentially different from literary criticism to identify ideological bias in texts. This article argues that, perhaps as a consequence, there is a good deal of conceptual confusion in the field.

  6. A Framework for Using Discourse Analysis for the Review of the

    Thus, the purpose of this article is to provide a framework for counselor researchers and practitioners for using another qualitative data analysis technique to analyze and interpret literature review sources—a process that we call a Discourse Analysis-Based Research Synthesis (DARS).

  7. Critical Discourse Analysis: A Literature Review

    Critical Discourse Analysis: A Literature Review August 2016 Publisher: LAP Lambert Academic Publishing Authors: Jennifier Diamante Western Philippines University Download citation Abstract The...

  8. PDF Critical Discourse Analysis in Education: A Review of the Literature

    A Review of the Literature Rebecca Rogers, Elizabeth Malancharuvil-Berkes, Melissa Mosley, Diane Hui, and Glynis O'Garro Joseph Washington University in St. Louis ... Discourse Analysis was an attempt to bring social theory and discourse analysis together to describe, interpret, and explain the ways in which discourse constructs, ...

  9. Discourse Analysis in English- A Short Review of the Literature

    Discourse Analysis in English- A Short Review of the Literature Published online by Cambridge University Press: 23 December 2008 Malcolm Coulthard Article Metrics Get access Cite Rights & Permissions Abstract An abstract is not available for this content so a preview has been provided.

  10. Discourse Analysis

    1. A "discourse" is not merely a linguistic unit, but a unit of human action, interaction, communication, and cognition. The habit of identifying the "discourse" with its recorded (usually written) language trace, though deeply entrenched, must be transcended. 2.

  11. Critical Discourse Analysis in Literacy Education: A Review of the

    This article is a critical, integrative literature review of scholarship in literacy studies from 2004 to 2012 that draws on critical discourse analysis (CDA). We discuss key issues, trends, and criticisms in the field. Our methodology was carried out in three stages. First, we searched educational databases to locate literacy-focused CDA scholarship. Second, we completed an analytic review ...

  12. A Framework for Using Discourse Analysis for the Review of the

    Thus, the purpose of this article is to provide a framework for counselor researchers and practitioners for using another qualitative data analysis technique to analyze and interpret literature...

  13. (PDF) Critical Discourse Analysis as a Review ...

    Critical Discourse Analysis as a Review Methodology: An Empirical Example. Communications of the Association for Information Systems. DOI: 10.17705/1CAIS.03711. Authors: Jeffrey D Wall. Michigan ...

  14. Literature and discourse analysis

    Literary discourse analysis - viewed legitimately as a branch of discourse analysis - is a new approach to literature. In this article, we begin by studying its emergence, taking into account the evolution of the relationship between literature and linguistics throughout the twentieth century.

  15. Critical Discourse Analysis in Education: A Review of the Literature

    This article reviews critical discourse analysis scholarship in education research from 2004 to 2012. Our methodology was carried out in three stages. First, we searched educational databases. Second, we completed an analytic review template for each article and encoded these data into a digital spreadsheet to assess macro-trends in the field.

  16. Critical discourse analysis in education: A review of the literature

    During the past decade educational researchers increasingly have turned to Critical Discourse Analysis (CDA) as a set of approaches to answer questions about the relationships between language and society. In this article the authors review the findings of their literature review of CDA in educational research. The findings proceed in the following manner: the multiple ways in which CDA has ...

  17. Discourses of artificial intelligence in higher education: a critical

    We reviewed definitions and conducted a discourse analysis of included texts. Our findings identify few, confusing definitions and little overt reference to AI as a research object. We delineated two Discourses. The Discourse of imperative change outlines how AI is seen as an inevitable change to which all must respond.

  18. What does the literature mean by social prescribing? A critical review

    Discourse analysis is, therefore, not only interested in how meaning is constructed, but also in its wider social consequences (Yazdannik et al., 2017). There is a wide range of approaches to discourse analysis, depending on the focus, sources of data or level of analysis (Glynos et al., 2009; Hodges et al., 2008). In this study, we drew on ...

  19. Discourse Analysis of Deixis: A Literature Review

    Abstract. Discourse analysis is a prat of applied English linguistics that is used to analyze or examine the communication process of society. The study of language is related with the term of ...

  20. Discourse Analysis in Stylistics and Literature Instruction

    The terms discourse analysis and stylistic analysis mean different thing to different people. Most narrowly defined, discourse analysis has only to do with the structure of spoken discourse. Such a definition separates discourse analysis from literany stylistics and pragmatics—the study of how people understand language in context.

  21. Foucauldian Discourse Analysis: Moving Beyond a Social Constructionist

    Although social constructionism (SC) and Foucauldian discourse analysis ... Hui D., Joseph G. O. G. (2005). Critical discourse analysis in education: A review of the literature. Review of Educational Research, 75(3), 365-416. Crossref. ISI. Google Scholar. Rosiek J. L., Heffernan J. (2014). Can't code what the community can't see: A case ...

  22. A literature review on (Critical) Discourse Studies

    Discourse analysts provided explanations to phenomena such as the use of "masculine" pronouns in a group of Japanese lesbians (Abe, 2006) or the development of an accent that mixed "white-woman...

  23. Discourse Analysis of Deixis: A Literature Review

    Keyword: discourse analysis, deixis, literature review. Introduction. A Discourse will be seen as a text which is an object and data that is always open to. various readings and interpretations.