
In their chapter, Bjork & Bjork (2011) describe how “optimizing learning and instruction often requires going against one’s intuitions“, since “the trials and errors of everyday living and learning do not seem to result in the development of an accurate mental model of the self as learner or an appreciation of the activities that do and do not foster learning“.
They stress that short-term learning, long-term learning, and observable performance are very different things. If we want to support observable performance (and, presumably, long-term learning — but at least performance a long time after learning), desirable difficulties can contribute to better learning (even though not necessarily better performance in the moment). “Desirable” difficulties in contrast to undesirable difficulties unrelated to the learning outcomes, like having to deal with microaggressions, or the internet connection breaking down during online learning, or classes at hours where one would usually sleep. While students might still learn something from those difficulties, they don’t contribute to — and likely hinder — learning in the specific subject.
Examples for desirable difficulties are to learn several topics in parallel over a longer period of time (rather than have them blocked and learn one after the other, like we do at LTH), spacing out learning sessions (rather than cramming everything the weekend before an exam — at least if you are interested in long-term retention of what you are learning), learning in different context so that new knowledge and skills have to be constantly transferred and applied in different ways and don’t just become connected to a specific setting (and that includes studying in different spaces!), and frequent testing to practice retrieval (rather than just re-watching or re-reading).
Bjork & Bjork (2011) is an excellent first read on the subject, and if you are interested to read about this in more detail, I recommend Dunlosky et al. (2013) or Zakrajsek (2022)!
Bjork, E. L., & Bjork, R. A. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. Psychology and the real world: Essays illustrating fundamental contributions to society, 2(59-68), 56-64.
Currently reading Poulidis et al. (2025) on how “Self-Regulated AI Use Hinders Long-Term Learning” - Adventures in Oceanography and Teaching says:
[…] Usually we like to think that self-regulation in feedback seeking and learning is a good thing: When students get stuck, they can ask for support that helps them overcome the difficulty and continue learning. This can become problematic, though, when students ask for hints too early and often, get used to that behaviour, and then never struggle with difficulties in a productive way that actually contributes to learning. […]