Henderson et al. (2015) ‘What works and why?…’

The researchers surveyed 1658 undergraduates in Australia on their usage of digital technologies. The survey suggests that digital technologies are not transforming learning and teaching.

The greatest use of technologies in the survey (46.9% of survey participants) was logistical rather than pedagogical; students were using technologies to get jobs done, which is also a starting point for technology use in Disruptive Innovation.  One popular practice noted by the researchers was ‘the viewing and listening of lecture recordings’ (p.4), a practice which underlines the idea of an HEI’s institutional technologies as having a repository function, rather than being Web2.0 technologies, despite their technical capacity for dialogue and exchange.

The survey participants’ responses draw attention to the extent to which convenience and size were relevant issues, with students preferring digital devices as opposed to ‘lugging heavy books around’ (p.6). One student cited a benefit of digital technologies as ‘mak[ing] my bag less heavier’ (p.6). It is worth recalling Christensen’s definition of disruptive technologies: cheaper, simpler, smaller and more convenient (1997, p.xv).

The researchers describe the use of Google for online research as ‘a relatively crude approach’ (p.7), but it is possible that the use of Google for research is simply part of the logistical rather than pedagogically weighted use of digital technologies by the survey participants. Students (often time-poor students) are interested in getting jobs done by arterial means. Hence the student who reported that they had not found a physical journal in a university library in their six years of study and had no intention of doing so because of the easy availability of journals online (p.7) is researching efficiently, not crudely.

A smaller number of particants (16.8% of respondents) were using digital technologies such as Google Docs and Facebook to learn collaboratively, and some (14.6%) were using technologies to augment their learning; one used You Tube videos to help understand new concepts, while another used Wikipedia because it ‘explain(s) concepts clearly’ (p.8). The money-saving aspects of digital technologies were mentioned by 4.4% of participants, with students not having to print paper copies of documents.

Based on their findings, the researchers argue that ‘digital technology is helping undergraduate students in a number of ways. Yet, often these tend not to be the creative, collaborative, participatory and hyper-connected practices that tend to be foregrounded in discussions of digital education and learning technology. Rather these are the activities, practices and processes that students feel compelled to undertake in order to “do” university’ (p.10, emphasis in original).

Christensen, C. M. (1997) The innovator’s dilemma: When new technologies cause great firms to fail (Boston, Mass: Harvard Business School Press).

Henderson, M., Selwyn, N. & Aston, R. (2015) ‘What works and why? Student perceptions of “useful” digital technology in university teaching and learning’, Studies in higher Education, DOI: 10.1080/03075079.2015.1007946

Heo & Lee (2013) ‘Blogs and Social Network Sites as Activity Systems’

One of the more complex nodes in the second generation activity system is community. Heo and Lee define it as consisting of ‘mutiple individuals who share the common general objectives’ (p.135).

Heo and Lee look at sub-triangles within the activity system. Building on Kuutti (1996) they define the subject-object-community sub-triangle as focusing on the relationship between the individual and their environment. Heo and Lee argue that the sub-triangle of subject-object-community influences the division of labour, because the division of labour ‘mediates the relationship between object and community’ (p.142; see also Kuutti, 1996).

Heo, G.M. & Lee, R. (2013), ‘Blogs and Social Network Sites as Activity Systems: Exploring Adult Informal Learning process through Activity Theory Framework,’ Educational Technology & Society, 16 (4), 133-145.

Kuutti, K. (1996), ‘Activity theory as a potential framework for human-computer interaction research,’ in B. Nardi (Ed.), Context and consciousness: Activity theory and human-computer interaction (pp.17-44), Cambridge, MA: MIT Press.

Crow & Debars (2015) Designing the New American University

Crow and Debars argue for the need for universities to create ‘an ecosystem of innovation’ (p.190). However, in practice, universities still exist in recognisable form from pre-1500 (Kerr, 1982).

Crow and Debars (2015) identify a problem in higher education, namely that tradition weighs heavily and therefore anything that deviates from tradition is disruptive (p.121). They further argue that universities emulate each other and thus begin to resemble each other (p.122), a tendency which is exacerbated by legislation. Crow and Debars further argue that universities strive for prestige and thus emulate the top-tier universities, not least as prestige correlates with wealth in the sector (p.123). Universities are also bureaucratic, another factor that militates against innovation (p.124). Consequently, universities are prone to structural inertia, which does not prohibit change but tends to favour incremental over disruptive change (p.125). Crow and Debars argue that these characteristics of universities are inappropriate ‘for institutions dedicated to the production of knowledge and diffusion of innovation’ (p.125).

Crow and Debars cite Powell and Snellman (2004) when they argue that economic growth in the West has been ‘driven by technologies based on knowledge and information production and dissemination’ (2004, p.199). Crow and Debars build on this position by arguing, ‘An appreciation of the role of technological innovation in our knowledge-based society requires less restrictive definitions of both technology and innovation’ (2015, p.155, emphasis in original). Crow and Debars are also interested in Etzkowitz’s term the ‘innovation of innovation’ to describe ‘any reconfiguration of elements into a more productive combination’ (Crow & Debars, 2015, pp.155-156; Etzkowitz, 2008, p.4).

Crow, M.M. & Dabars, W.B. (2015) Designing the New American University, Baltimore, John Hopkins University Press.

Etzkowitz, H. (2008) The Triple Helix: University-Industry-Government Innovation in Action, New York, Routledge.

Kerr, C. (1982) ‘The Uses of the University Two Decades Later: Postscript 1982,’ Change, 14, pp.122-123.

Powell, W.W. & Snellman, K. (2004) ‘the Knowledge Economy,’ Annual Review of Sociology, 30.

Knight & Pryke (2012) ‘Wikipedia and the University, a case study.’

The research on Wikipedia, undertaken at a UK HEI (Liverpool Hope University) and based on a sample of 133 academics and 1222 students found widespread usage (75%).

One of the attractions of Wikipedia as summarised in the article, it its ‘ease of access’ (p.649), a factor which also features in the definition of Disruptive Innovation (Christensen, 1997; Christensen and Raynor, 2003). Furthermore, the rate of Wikipedia usage did not vary between students and academics, i.e., both communities in the sample were making widespread use of it.

Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Boston, Mass: Harvard Business School Press.

Christensen, C. M., & Raynor, M. E. (2003). The innovator’s solution: Creating and sustaining successful growth. Boston, Mass. Harvard Business School Press.

Knight, C. & Pryke, S. (2012), ‘Wikipedia and the University, a case study,’ Teaching in Higher Education, 17 (6), 649-659.

Bayne, S. (2015) ‘What’s the matter with “technology-enhanced learning”?’

Bayne (2015) deconstructs the term ‘technology-enhanced learning’ (TEL) and states it is UK specific (p.6). She argues that the term ‘fails to do justice equally to the disruptive, disturbing and generative dimensions of the academy’s enmeshment with the digital’ (p.7).

One aspect of Bayne’s argument relates to the use of ‘enhancement’: ‘Part of the problem here is the inherent conservatism of any discourse of “enhancement”, assuming as it does a pre-existing set of practices which are not in any need of radical shift or displacement, but are rather simply open to being made even “better” by the judicious application of a little (in this case technological) assistance’ (p.10). It is, however, possible that ‘enhancement’ can imply a sufficiency rather than a deficit, and it is hard to imagine a system without scope forimprovement.

Bayne cites Fenwick, Edwards & Sawchuck (2011), who critique educational research for tending to ‘privilege the intentional human subject’ (2001, p. 1). However, the use of an Activity Theory lens can identify the human subject as one of a range of factors, but without asserting its pre-eminence or indeed centrality in practice.

Bayne raises an interesting point when she argues, ‘In most instances, when we speak of “TEL” we are in fact referring to technology enhanced teaching, and to institutional goals…’ (p.15). TEL strategies issued by UK HEIs might well bear out the argument. Bayne develops her point by arguing that the primary concern ‘is oriented to specific teaching and administrative goals (for example, improved assessment and feedback or more flexible course provision) rather than to learning per se’ (p.15, emphasis in original).

Drawing on Biesta (2012), Bayne argues that learning is teleological and contextual (2015, p.16). The point is, arguably, a truism, but it is sometimes in danger of being overlooked.

Bayne, S. (2015) ‘What’s the matter with “technology-enhanced learning”?’, Learning, Media and Technology, 40 (1), 5-20.

Biesta, G. 2012. ‘Giving Teaching Back to Education: Responding to the Disappearance of the Teacher,’ Phenomenology & Practice 6 (2), 35–49.

Fenwick, T., R. Edwards & P. Sawchuk (2011), Emerging Approaches to Educational Research: Tracing the Sociomaterial. London, Routledge.

Junco (2014) ‘iSpy: seeing what students really do online’

Junco (2014, p.76) cites research (Junco 2012a) stating that 92% of undergraduates use Facebook. Junco also cites evidence of demarcation, with students using email to communicate with academics, but not with friends.

In Junco’s own research, in which students’ computer usage was monitored, social networking emerges as ‘the most popular computer activity’ (p.81). The figures for the use of Facebook in the research ranged from 93-96%. It is, however, possible that the students altered their normal online behaviours in the foreknowledge that their usage was being monitored.

Some research (e.g., Junco 2012b) has argued that students can use social networking technologies to enhance their learning by increasing their social and academic integration, but demarcation is just as likely, and was one of the most consistent findings of my own doctoral research.

Junco, R. (2012a) ‘Too Much face and not Enough Books: The Relationship Between Multiple Indices of Facebook Use and Academic Performance,’ Computers in Human Behavior 28 (1), 187-198.

Junco, R. (2012b) ‘The Relationship between Frequency of Facebook Use, Participation in Facebook Activities, and Student Engagement,’ Computers & Education, 58 (1), 162-171.

Junco (2014) ‘iSpy: seeing what students really do online,’ Learning, Media and Technology, 39 (1), 75-89. doi: 10.1080/17439884.2013.771782