Encyclopedia of Educational Philosophy and Theory

2017 Edition
| Editors: Michael A. Peters

Digital Learning, Discourse, and Ideology

Reference work entry
DOI: https://doi.org/10.1007/978-981-287-588-4_122

Synonyms

Introduction

In recent decades, digital technologies have seen widespread use across global society and adoption at all levels of education. Digital learning might therefore simply be described as learning that is facilitated by digital technologies, but to discuss digital learning only in this way obscures important complexities linked to language, culture, politics, and the economy. To talk or write about learning as if it were directly facilitated by technology of any kind, places a strong focus on what technology has, or seems to be, achieving. At the same time, this marginalizes, or reduces the visibility of, human roles within the academia and beyond (Hayes and Jandrić 2014). Digital technologies are often introduced into educational institutions amid simple assumptions, or ideologies. Related policy discourse may suggest there will be economic improvements, such as educational performance and efficiency. This is linked to what sociologists and anthropologists have referred to as an “audit culture,” (Shore & Wright 1999) where, since the late 1980s in both education and wider society: “the techniques and values of accountancy have become a central organizing principle in the governance and management of human conduct – and the new kinds of relationships, habits and practices that this is creating” (Shore 2008, p. 279). These new principles of organization are said to be serving a “Knowledge Based Economy” (KBE), which is a widely used metaphor, without precise definition. It suggests that knowledge and related digital technologies have now overtaken human physical labor, to drive productivity and global economic growth. A KBE discourse, which assumes economic enhancement from technology, is very different to one that existed prior to the mid-nineteenth century, when technology was closely associated with the Greek concept of “techne,” referring to broader human interaction and knowledge, related to arts or craft.

A discourse of a KBE (Jessop et al. 2008) that treats technology only as a simple tool to drive and enhance economic productivity is described here as an example of: (1) an antihumanist, or a technologically deterministic viewpoint. It focuses on what technology is doing, to impact positively on digital learners, as if this were a simple, “outside intervention” (Knox, Education and Digital Cultures). A discourse that places more emphasis on human practices with technology in society is described as (2) a humanist perspective, which is socially deterministic, because it discusses humans as separate from the technology, objects, and other nonhuman things they use in practice (Knox, Education and Digital Cultures). Alternatively, a discourse where technology and humans are considered to be mutually shaping of each other is described as (3) a posthumanist position (Matthewman 2011). This entry treats these three categories as distinct, but overlapping, ideological stances that can be found in discourse about digital learning.

Discourse and Ideology

Critical linguistic studies suggest discourse carries particular values or ideologies that together with other elements in society may reinforce or disrupt a current state of affairs. A humanist perspective on education has links with poststructuralism, but this limits our understanding of the agency of technology, because poststructuralists treat the human subject as a bounded entity whose actions are completely separate from the outside world of objects, technologies, and other “nonhuman” things (Knox, Education and Digital Cultures). In an antihumanist perspective though, digital learners are treated as passive beings, and technology simply impacts upon them, so this conceals human agency to act. Norman Fairclough suggests that by approaching technology, ideology, and social practice through Cultural Political Economy (CPE), semiotic, or “meaning-making” relations between these elements might be understood as “dialectical,” (Fairclough 2007). In other words, not as entirely separate from each other, as in either a humanist or antihumanist perspective, but shaping of each other culturally, politically, and economically in a manner that moves closer towards a posthumanist position. This acknowledges that there are cultural dimensions to any economic crisis, economic dimensions within culture, and a political character to both in related discourse (Castells 2011).

Discourse then might be understood as written or spoken language, dialectically linked with human practices, in real contexts of use, where cultural, political, and economic elements affect each other. In this entry, discourse covers the meanings, effects, and strategies people use, as well as production and interpretation of actual texts that describe the role of technology and humans in digital learning. Ideology in this context refers to ways that people’s beliefs and values come to intersect with technology and human practices through discourse. Ideology may lead to forms of knowledge that appear to be freed of political interests to construct certain meanings that are presented as “common sense.” As with ideological claims generally, unquestioned assertions can have powerful and significant social and political implications (Friesen 2008). Choices made in discourse, to express ideologies about technology, or human practice, in digital learning contexts are often framed as if they were self-evident facts, or objectively “true.”

Varied terms are used to describe digital learning including: e-learning, networked learning, and Technology Enhanced Learning (TEL). While e-learning is short for electronic forms of learning, and networked learning suggests learning that takes place across digital networks, the term Technology Enhanced Learning (TEL) has recently become widely adopted in policy, and also critiqued. Criticisms of TEL question an inbuilt assumption of a direct economic connection between bringing technology into education and automatically “enhanced” learning, or productivity. Critically examining how digital learning is framed in discursive constructions that link technology with ideologies about learning is one way to confront such arguments (Fairclough 2007). Approached via critical social theory about technology and language, discourse and ideology are key concepts in linguistic study of how human understandings of digital learning are shaped.

Antihumanist, Humanist, and Posthumanist Reasoning About Technology

In the broadest sense, technology (including digital technology adopted in education) might be said to encompass everything, to affect human history and learning, and can be basically defined as: objects, activities, and knowledge (Matthewman 2011, p. 2). A body of literature that acknowledges technology in this way (Winner 1980, p. 122; MacKenzie and Wajcman 1999) is distinguished from more dominant antihumanist or humanist reasoning that suggests either technology, as a neutral entity, simply drives history to determine what humans know, or that human agency drives technological change.

Langdon Winner undermined both of these forms of logic by arguing that technologies themselves carry design choices that either open or close social options. Therefore taking a CPE approach, when adopting technology, people also make cultural, political, and economic, as well as technological, decisions (Winner 1980). These decisions can then manifest as ideologies too in discourse about digital learning, to alter how certain qualities are attributed to either technology, or to humans. As technology contributes to the economy, recognizing that related values are expressed culturally and politically in written policy discourse about education aids a linguistic exploration of digital learning, as a “scene of struggle,” rather than as a fait accompli (Friesen 2008).

Arguments about the role of technology can be examined then through the three broad categories already mentioned (antihumanist, humanist, and posthumanist) to notice what values are emphasized in discourse. Already applied by Matthewman to critically theorize technology more generally (Matthewman 2011, p. 15), firstly, antihumanist views would suggest digital devices themselves define how people use these to learn. This very common way of thinking is a form of technological determinism and contains a partial truth (MacKenzie and Wajcman 1999). Secondly, the humanist concept is a form of social determinism, which also presents a partial truth by treating technologies as “neutral” entities but placing emphasis on ways that society chooses to use them. Prior to the mid-nineteenth century, technology was associated with the Greek concept of “techne,” referring to broader human interaction and knowledge related to arts or craft. In this understanding there is room for varied and individual human interpretations of what people come to know through using technologies, and how in turn, human actions might shape changes to technologies and society. This approach to theorizing technology is closer to the third category (posthumanist), which does not choose to privilege either the role of technology or society. Instead, each might shape the other, in a manner that is “mutually constitutive” (MacKenzie and Wajcman 1999). In a posthumanist discourse about digital learning, technology is treated as an “ongoing encounter” (Matthewman 2011, p. 8). Humans coevolve with technology (Matthewman 2011, p. 176) in individual, material, and discursive encounters, where human and nonhuman actors shape and alter each other.

A Knowledge-Based Economy and Critical Theory About Knowledge

Having established three broad forms of discourse through which to examine ideologies about digital learning, these can be explored with reference to critical theory about knowledge. Buzz phrases such as Knowledge Based Economy (KBE) and Technology Enhanced Learning (TEL) might be interrogated linguistically.

Deterministic arguments tend to attribute technology with inherent and unquestionable “value” to improve human contexts (including learning). Examples can be noticed where discourse suggests technology enhances “student engagement” or “employability.” These phrases are things that might then be “audited,” evaluated, or scrutinized institutionally, or by government agencies. A phrase like “the student experience” when mentioned often in the media becomes treated as a social “problem,” discussed publically, with judgments made about the performance of teachers in relation to these “issues.” However, these forms of reasoning also frame students as passive consumers in a competitive market, rather than active participants experiencing technology in diverse contexts of learning.

In policy texts we may find “presuppositions,” where understandings about technology and what it does are discussed as “given.” This then enables further arguments to be constructed from this “given” position and treated as if it were a generally held “truth.” Particular relationships between technology and people may be represented through grammatical constructions that become hard to question but which obscure alternative understandings (Hayes 2015). Digital learning as a concept can be productively explored through a critical analysis of reasoning about technology in any surrounding discourse. This enables certain ideologies to be noticed and categorized. Without a close analysis, common sense arguments that become generally accepted to shape a particular view, for example, a logic that technology (rather than the human labor of teaching) enhances learning (Hayes 2015) may simply go unnoticed.

Findings from linguistic analysis can be articulated with reference to critical social theory. Firstly, in a macro overview, literature from critical theory applied to knowledge is examined. This builds on the body of work of the Frankfurt School, where all knowledge is considered to be political in nature and shaped by human interests (Habermas 1968). The widely referenced “knowledge-constitutive interests” of Habermas suggest human interests are “instrumental,” “practical,” and “emancipatory” in nature.

Instrumental knowledge relates to technical human interests that are associated with work, labor, production, or the natural sciences. Practical knowledge is more about interpretive ways of knowing, through which everyday and social human activities are coordinated and given meaning. Emancipatory knowledge is the kind of knowledge that critical theory itself seeks to generate, and it is articulated in terms of power, control, and emancipation (Friesen 2008). In critical theory these three forms of knowledge and interest are never entirely separate, and emancipatory or political knowledge is considered to be all pervasive and central to the critical theoretical concept of ideology. Therefore, ideology is any kind of knowledge (whether technical, practical, or emancipatory) that appears to be freed of political interests (Friesen 2008).

Secondly, in exploring assertions about a KBE, social change since the Industrial Revolution has seen rapid mechanical developments, alongside changes to political and organizational structures, and the emergence of digital technologies across global society. Where “capital” from physical labor had once been the dominant factor of production in industrial societies, in postindustrial societies, a focus has emerged on the role of “knowledge” (Bell 1999). Bell identifies four trends: (1) a shift from manufacturing to services, (2) an increase in the general importance of education, (3) the increased importance of technological infrastructure as a foundation for an electronically mediated global economy, and (4) the theory that knowledge now creates value-added and increasing returns. In this last point, Bell shifts the focus from Marx's, “labor theory of value,” where human physical labor in capitalist economies adds value to commodities and products that can then be sold at a profit, to a “knowledge theory of value,” where the exchange of knowledge in educational and research contexts now plays a value-adding, profit-making function (Friesen 2008).

This has implications that can be noticed in policy literature for educational technology. Schools, universities and teaching staff can find themselves being discussed as following outdated principles and methods, with reform and enhancement recommended, for greater efficiency in a KBE is recommended. In a knowledge theory of value, certain ideologies are spread through discourse (language-in-use) (Fairclough 2007) and these tend to privilege some characteristics of knowledge over others. Knowledge becomes characterized as a kind of service or utility to be bought and sold, used, enhanced, and reused as a “super commodity,” a thing that has market value like physical commodities but that also transcends even the products of physical labor (Friesen 2008). Consequently in government policy and in university strategy discourse, there is discussion of learning objects and learning outcomes, as knowledge that has been broken down into exchangeable packets within contemporary capitalism.

A further consequence is that the complex, contestable nature of knowledge emerging from varied human constitutive interests (Habermas 1968) becomes suppressed, as knowledge gets linked simply with “performance” within a culture that audits only the elements deemed to be useful, to support a KBE. New media enables the logic that we are now in a KBE and as humans must quickly adapt, to travel swiftly via technology, as well as discourse, spreading persistent values. Therefore, how digital learning is routinely discussed, in spoken and written discourse, can quickly reinforce powerful ideologies about learning through technology.

Ways to Critique How People Are Positioned in Discourse About Digital Learning

Economic, technical, cultural, and historical conditions surrounding digital learning are complex. A student or a teacher (online or in a classroom) is an individual who is cast into predefined relationships and structures, which are reproduced and reinforced through even the most trivial statements and actions (Friesen 2008). In order to examine these values as they play out in discourse, the following basic steps might be followed for an ideology critique:
  1. 1.

    Identify ideas or claims that are presented as obvious, common sense or inevitable, sources of knowledge.

     
  2. 2.

    Scrutinize these ideas or claims in the context in which they arise.

     
  3. 3.

    Reveal where behind dominant claims there are politically charged and often contradictory ways of understanding an issue or phenomenon.

     
  4. 4.

    Use this underlying conflict as the basis for developing alternative forms of understanding and point to concrete possibilities for action (Friesen 2008).

     

If claims of ideology in discourse about digital learning are to be supported, and not simply suspected, then under (2) a detailed linguistic analysis can help to demonstrate where particular patterns of discourse are often repeated. One approach is to build a large corpus, or bank of words, and to use software to reveal what quantitative patterns emerge. From here, one might undertake a more qualitative analysis to look more closely at patterns to suggest what might be happening, with reference to critical theory.

An example of this is to undertake Critical Discourse Analysis (CDA), which is best understood as an interdisciplinary approach, where researchers choose from a range of linguistic tools some ways to shed light on what is happening in the discourse. Through CDA techniques some researchers have found that there are strong repetitions of nominalization in policy texts about digital learning. Nominalization is noticeable where nouns stand in for verbal processes in texts. A common effect is a reduction in human agency. It becomes hard to detect who a proposition refers to, or who has declared it to be so. This then can lead to human labor being attributed to technologies and strategies, or to terms such as Technology Enhanced Learning (TEL), or e-learning, rather than to the actual people who are really enacting tasks, such as teachers and students (Hayes and Jandrić 2014; Hayes 2015). Therefore, if claims are to be made about ideology then empirical inquiry of this kind can help to pinpoint oversimplified presuppositions about digital learning in discourse (Fairclough 2007; Hayes 2015).

Conclusion

This entry has discussed how critical theory around discourse and ideology has emerged to challenge a dominant “marketized” view of how digital learning takes place in a KBE where “taken-for-granted” economic narratives (Jessop et al. 2008) can spread rapidly through digital media. Shifts in master economic narratives such as the KBE need to be understood at the macro level of capitalist markets, to notice where a culture of audit has arisen Shore (2008), leading to subordination of teaching and research to economic imperatives (Jessop et al. 2008). Policy discourse might then be examined at the micro level, in close linguistic analysis. CDA is just one approach that might be taken to confront contradictions and suggest alternative forms of discourse. This section classified three ways human practice in digital learning might be discussed and constituted through discourse. Some forms of close linguistic analysis were described as ways researchers might disrupt the more simplistic accounts, given the complexity around those learning through digital technologies.

Cross-References

References

  1. Bell, D. (1999). The coming of post-Industrial society: A venture in social forecasting (Special Anniversary Edition). New York: Basic Books.Google Scholar
  2. Castells, M. (2011). The rise of the network society: The information age: Economy, society, and culture (Vol. 1). John Wiley & Sons.Google Scholar
  3. Fairclough, N. (2007). Global capitalism and change in Higher Education: Dialectics of language and practice, technology, ideology. Edinburgh: In BAAL conference.Google Scholar
  4. Friesen, N. (2008). Critical theory: Ideology critique and the myths of e-learning. Ubiquity, 9(22). New York: ACMGoogle Scholar
  5. Habermas, J. (1968). Knowledge and human interests. Boston, MA: Beacon.Google Scholar
  6. Hayes, S. (2015). Counting on use of technology to enhance learning. In P. Jandrić & D. Boras (Eds.), Critical learning in digital networks (pp. 15–36). New York: Springer.Google Scholar
  7. Hayes, S., & Jandrić, P. (2014). Who is really in charge of contemporary education? People and technologies in, against and beyond the neoliberal university. Open Review of Educational Research, 1(1), 193–210.CrossRefGoogle Scholar
  8. Jessop, B., Fairclough, N., & Wodak, R. (Eds.). (2008). Education and the knowledge-based economy in Europe. London: Sense Publishers.Google Scholar
  9. MacKenzie, D., & Wajcman, J. (Eds.). (1999). The social shaping of technology (2nd ed.). Buckingham, UK: Open University Press.Google Scholar
  10. Matthewman, S. (2011). Technology and social theory. New York: Palgrave.CrossRefGoogle Scholar
  11. Shore, C., & Wright, S. (1999). Audit culture and anthropology: neo-liberalism in British higher education. Journal of the Royal Anthropological Institute, 557–575.CrossRefGoogle Scholar
  12. Shore, C. (2008). Audit culture and illiberal governance: Universities and the politics of accountability. Anthropological Theory, 8(3), 278–298.CrossRefGoogle Scholar
  13. Winner, L. (1980). Do artifacts have politics?. Daedalus, 121–136.Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  1. 1.Aston UniversityBirminghamUK