Future perfect: what will universities look like in 2030?

For those of us who deal with instructional technology and educational research, the argument where made in support of technology for the sake of it, is flawed. Enthusiastic technological determinists are usually those from the hard sciences that push this argument and technology enthusiasts and/or software vendors (Blackboard, Moodle and MOOCs variations) who have a stake to assume and prophesise an educational future determined exclusively by technologies. Since the widespread implementation of computers in the post 1970s, there is little indication that in essence teaching styles have changed radically. In fact, there is a growing critique on what exactly elearning has offered in terms of improvements beyond widening participation and empowering some of those who did not have traditional access to education. Teacher-centred (master-apprentice) approaches persist in most of the academic disciplines due mostly to the high-paradigmatic nature of most sciences. There are many according to a recent European report (ask me for the reference if you wish) disciplines such as Law and Art and Design that have never been on the bandwagon of technology embedded in a systemic and efficient manner in the respective curricula. These disciplines only wet their toes… Historically driven empires – and interests – hold back the sector(s)… firmly in the pre-1970s period. Professor Diana Laurillard in her seminal book (second edition) ‘Rethinking University Teaching: A Conversational Framework for the Effective Use of Learning Technologies’ (2002), mapped the potential affordances of various technologies emphasising – surprise, surprise – the importance of context and appropriate teaching and learning strategies. In brief, technologies are not a solution but rather a facilitator, an enabler when used appropriately – a very old aphorism for those who do educational research. There is empirical validity in Marshall McLuhan’s (2003) claim that “…What is indicated for our time, then, is not succession of media and educational procedures, like a series of boxing champions, but coexistence based on awareness of the inherent powers and messages of each of these unique configurations.” The radio did not wipe out newspapers. Television did not wipe out the radio. The Internet has not wiped out newspapers. We print more – despite the proliferation of computers – than we did during the pre-computer era. Co-existence of instructional media and a blended approach is the realistic way forward; has been for a while now. In brief, the sensational title from Times Higher Educational should have been better phrased as: “What do we want universities to look like in 2030”, or even better “What should universities look like in 2030”. Fortunately, some of the commentators in the article did hit the sport in this respect, for example, those who emphasised the need for cross-disciplinarity and a return to broad range skills and competencies. At best – according to studies from the USA and Canada – universities can provide about 30% of what graduates will need during their professional career, and the remaining 70% – in the form of informal learning – will be acquired out there through continues life-long learning/training. In short, this means that we need to provide beyond the specialised prescriptive skills of the respective disciplines, a heavy dosage of life-long learning skills. In this context, technology functions as enabler – assuming academics are prepared to let their little empires crumple, and stop supporting learning through osmosis. We established an entrepreneurship unit and bolted it at the edge of the campus, instead of thinking how we could best embed entrepreneurship in the actual curricula. Others perceive of learning as a master-apprentice monologue (plenty of that at many universities). The recipe for success, vis-a vis teaching and learning, is simple. As far as possible, embed learning in real-life scenarios. Contextualise knowledge and promote project-based learning. Use technology as a facilitator of transferable soft-skills. Equip each graduate with skills to carry out small-scale action-research and grounded theory. Acknowledge informal learning and connect it to a formal system of certification, and lastly place equal emphasis on rewarding good teaching as we would with good research. We live in hope… Happy New Year.

Another exceptional Op-Ed!

This is interesting, but all contributors missed student demand for social interaction. Students - leaving home for the first time - want to live in supportive communities that are remote from their parents. Many actively search for a prestigious academic community so as to brand their CV. They also like the structure - again a community element - that lectures bring to their lives. Finally, they get a lot out of interaction with academics. My guess - flipped classrooms won't last because students don't really like them, and - ironically - they don't save the academic any time. However, academic staff will be expected to develop very rich supplementary materials online. Universities that have done away with community infrastructure (e.g. close departments, teaching in central hubs, conversion of common rooms in teaching space) will suffer as a result of TEF, although they may - through advertising and branding - find ways to recruit despite a poor student experience on campus.

I feel the claims or prediction here is not that accurate or not sounding accurate due to the lack of proof of concept. "In 15 years, we will have no one to teach. The professional jobs for which we prepare students will be done by intelligent machines" There still needs some major leaps in cutting edge technology for intelligent machines to overtake professional human teachers. I feel we humans may develop better technology to enable some of us to perform better than intelligent machines to teach humans. Overall, this article contains too little studies to support it, furthermore, it seems like this is an article written in response to the media's hype about overly optimistic or exaggerated advances in artificial general technology.

Re-reading this after the 'AI' hype boom of late 2022-? is rather interesting, only 5 yrs to go to 2030!