For most people, learning something new is hard work – a necessary discomfort to endure on the way to mastering complex knowledge and skills. Some of us may get through this relatively unscathed, perhaps a little proud of our hard-earned battle scars and newly acquired wisdom. Many, however, face this educational ‘discomfort’ burdened by other complexities, from work and financial pressures to mental health issues, accessibility needs and a range of equity factors that are not always visible to others.
How we frame and support the ‘work’ of learning was the focus of a recent First and Further Year Experience (FFYE) Forum event on Building greater student engagement: Insights and strategies. Associate Professor Jason Lodge (University of Queensland) shared research findings contextualised by recent developments including Generative AI and the impact of increased flexibility in course delivery.
As the session evolved, a series of tensions and dilemmas for higher education emerged – a reminder not only of the systemic issues impacting student learning, but also some practical ways students can be better supported in the process of learning, no matter what their background.
The challenge of ‘satisfaction’ in learning
Learning is […] hard work, and sometimes it’s not satisfying, sometimes it’s difficult and uncomfortable, and that’s a normal part of the learning process.
Jason Lodge
Jason started by highlighting the complex background behind this issue, including increasing rates of attrition in higher education and the gap between structured high school learning and more flexible approaches at university. The guidance that helps students get into university doesn’t necessarily prepare them for the shift to independent learning once they get there.
Research also suggests that students may not be great evaluators of their own learning, judging more passive methods (e.g. lectures) as more effective than the ‘harder work’ of active engagement (problem-solving, group work). In this context, Jason noted that for all its potential benefits, the rapid, ‘transactional’ and output-focussed nature of Generative AI may not always be helpful as a learning support. The results may feel immediately satisfying, but could the processes (or lack of them) be taking students away from important ‘desirable difficulties‘ in learning?
Flexibility without guidance doesn’t work (for most)
We’ve created flexibility, but at the same time, we’ve also put more of the onus on the students to be able to make good decisions about what they do with that flexibility. Some students, as designed, are getting a lot out of that, and doing very well. The students who don’t necessarily have the same ability to […] self-direct their own learning don’t necessarily know the implications of the decisions that they’re making on the way through.
Jason Lodge
Drawing on a series of studies he has led on student learning, Jason discussed how students are engaging with their studies, expectations of university life, and the complexities of their diverse backgrounds and needs. Among the common themes were lack of time, resources and spaces for learning, negative emotions relating to learning, and difficulties in self-monitoring progress.
Against this backdrop, flexibility can be a double-edged sword. Jason highlighted unusual patterns, for example, in student outcomes across a range of large first year courses with flexible learning options. In many cases, student achievement often edged towards bimodal extremes (students doing particularly well or badly, with fewer sitting in the middle). The pattern suggests that without additional guidance, flexible learning options mean that those who can already organise and steer their own learning do better, whilst those who are struggling will continue to do so.
Importantly, qualitative analysis on student dropout and retention strategy (Greenland & Moore, 2022) suggests that institutional support could have encouraged some students to stick with their studies. Reasons for attrition are often simplified in institutional data, but deeper investigation through other methods (e.g. student interviews) surfaced more nuanced answers linked to study habits, time management, and motivation. A thoughtful and caring tutor, it would seem, could have made all the difference.
Focussing on the right kind of ‘difficulties’
It shouldn’t be hard to enrol. It shouldn’t be hard to figure out what your timetable should look like. It shouldn’t be hard to figure out what the assessment task is. But […] perhaps we have made those things a little more difficult that they needed to be.
Jason Lodge
Jason acknowledged that not all ‘difficulties’ are desirable, and there are other kinds of ‘work’ in higher education systems that should not be adding to students’ cognitive load, from enrolment to understanding assessment requirements. If we can get these obstacles out of the way, we can focus on the work that is crucial to the learning process, familiarising students with the right kinds of frustration as they grapple with complex learning, and ultimately the rewards of working through it.
Whilst we know that supporting students to engage with the work of learning is challenging, Jason noted that we also know (in theory) what to do about it. Research such as Pillars of online pedagogy: A framework for teaching in online learning environments (Archambault et al., 2022) may be situated in the online context, but there are plenty of transferable learnings too. The 5 pillars highlighted include the ability to:
- Build relationships and community
- Incorporate active learning
- Leverage learner agency
- Embrace mastery learning, and
- Personalise the learning process
Drawing the keynote to a close, Jason suggested many of our institutions are already putting such principles into practice, but that student feedback is telling us a more systemic approach is needed. We have good foundations and values to support student engagement and motivation; we should now look to build on these so we can all focus less on ‘undesirable’ difficulties – and get back to the work of learning.
References and further reading
Archambault, L., Leary, H., & Rice, K. (2022). Pillars of online pedagogy: A framework for teaching in online learning environments. Educational Psychologist, 57(3), 178–191. https://doi.org/10.1080/00461520.2022.2051513
Bjork, E. L., & Bjork, R. A. (2014). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In M. A. Gernsbacher and J. Pomerantz (Eds.), Psychology and the real world: Essays illustrating fundamental contributions to society (2nd edition). (pp. 59-68). New York: Worth.
Greenland, S. J., & Moore, C. (2022). Large qualitative sample and thematic analysis to redefine student dropout and retention strategy in open online education. British Journal of Educational Technology, 53, 647–667. https://doi.org/10.1111/bjet.13173