The ability to manage one’s own learning effectively is an essential skill for a student in Higher Education. The ability to be an independent learner, to manage time effectively, and to be critical and analytical are commonly-cited graduate attributes in Higher Education. In the Biosciences, the complexity of factual information, and of the analytical and practical skills required for a graduate is very high. Our students are faced with increasingly intricate pathways, processes, and interactions within biological systems. These are reported in increasingly complex and challenging research outputs in a vast literature base. Navigating through this complexity, and structuring one’s own learning to manage it, requires that our students be effective at the process of ‘self-regulated learning’ (SRL).
Effective SRL is difficult, and requires considerable time and effort to master (Zimmerman, 2002). Proficiency in SRL is a skill which develops over time, and is impacted both by the student themselves, their personality, background, and (very significantly) the student’s learning environment (Bjork et al., 2013) The ability to self-regulate and manage/evaluate their own learning is one of the most important skills we can help our students develop. This blog, the first of a series of three linked blogs, focuses on defining SRL, and exploring how we can support it in our teaching practices in the Biosciences.
What is self-regulated learning?
Developing self-regulated learning is an ongoing process that develops progressively, and throughout the ‘lifelong learning’ journey of an individual, rather than a threshold competence to achieve (Panadero, 2017). There are many models of self-regulated learning (for example, Zimmerman, 1989; Boekaerts, 1999; Lehmann et al., 2014), but most centre around three ‘domains’ of factors (see Figure 1). Central to the process is the cognitive domain, which addresses how we learn and process information, develop skills and process an understanding. The cognitive domain manages how we retain information and retrieve it when required. The metacognitive domain focuses on the management of these cognitive strategies – how do we know that the approaches we take for learning and studying are effective and efficient? The metacognitive domain involves learners developing schema for evaluating their learning. Finally, the affective/motivational domain addresses the motivations and drives for a learner studying and attempting to learn. Why are they learning, and what do they hope to gain? Lehmann et al. (2014) also emphasise that each domain consists of two components: the behaviours/actions required to undertake the activity, and the capabilities and/or mental skills that are necessary.
Is SRL a solitary process?
While SRL is primarily a personal process, learning rarely occurs in isolation, and interactions with others are also important (Schoor et al., 2015; Hadwin et al., 2017). Co-regulated learning (interactions between a learner and a more-experienced mentor or teacher) is fundamental to most HE learning activities. Socially-shared regulation (learning between peers), is also fundamental to most HE learning environments, where peer-peer interactions have a major impact on the development of a learner’s SRL skills.
A key element to consider, therefore, is the learner-teacher and learner-peer interactions that are available to the learner as part of their course, and in the environment around it. Helping a learner develop their ‘personal learning network’ (Richardson & Mancabelli, 2011), the network of colleagues, groups, technologies and resources around them, to whom they can turn to for help, is fundamentally important in helping their development. Knowing whom to turn to for help, and (more importantly) what help to ask for, is an important understanding to develop.
How can we support the development of SRL in our students?
The key challenge to us as educators is how do we support the development of SRL so that our students are effective independent learners. Much of HE is designed for students to work independently. However, it is not sufficient to just send a learner out on their own, and assume that they will develop the skills needed for SRL. These abilities need to be taught, nurtured and developed. Work by Rutherford (2019) suggested that many undergraduate students are already capable and experienced self-regulated learners, but their strategies (developed through many years of trial and error at school) are focused on the more structured environment of secondary education. These SRL skills require a process of evolution into the more independent environment of HE. That process of refinement and evolution needs to be supported and scaffolded in order to be effective, through encouraging students to reflect on their learning approaches, and discuss their strategies with their tutors and peers.
We can support the development of SRL both through the way we teach and encourage students to learn, but also through the ways we assess and provide feedback to students. We can also adopt the new opportunities of Generative AI to help students develop self-regulation. Two subsequent blog posts will each address these two approaches. Here we will suggest ways in which we can support the development of SRL through the ways in which we frame our learning and teaching activities. How we teach, and how we structure (or don’t structure!) our students’ learning (both in and away from formal teaching sessions), has a major impact on how students’ SRL develops. An excellent review of how research in cognitive neuroscience can support bioscience education has been published by Friedlander et al. (2011) and has several useful tips.
Activities to support cognition
Any element of developing how our students think, and think in new ways, is of benefit here. The most straightforward approach is to engage the students in active or inquiry-based learning, rather than didactic teaching. Being challenged to research information for themselves develops cognitive strategies (Arifin et al., 2025). Flipped Learning approaches and/or problem-based learning (PBL) are powerful pedagogies here (Eggers et al., 2021; Zheng & Zhang, 2020). Experiential learning, such as working in a laboratory or field environment, is also a means of promoting active learning, as long as the activities involve students reflecting on what they have learned, and not just blindly following a protocol.
Approaches that identify areas of debate or uncertainty in biological research - especially an area where the research evidence is inconclusive, or contradictory – helps students challenge preconceptions. Approaches that identify areas of debate or uncertainty in biological research – especially an area where the research evidence is inconclusive, or contradictory – helps students challenge preconceptions. Trying to make sense of a dataset in the lab, or identifying reasons for anomalous results or experimental failures, supports this development of ways of lateral thinking. In similar ways, planning an experimental approach to answer a research question, or devising a strategy requires complex thought processes.
Overall, a move away from didactic teaching, and towards student-led inquiry is the key to developing the cognitive domain of SRL. This development is enhanced when students have the opportunity to reflect on what they are doing, and why, and to discuss their experiences with the educators and peers.
Activities to support metacognition
Metacognition is centred around the ability to evaluate the efficacy of one’s cognitive processes. The fundamental requirement for metacognition is the opportunity to benchmark one’s capabilities and use this benchmark to compare how these capabilities develop over time. Learning and teaching activities that require students to make frank reflections on their skill levels, and to chart their progress and achievements, are powerful tools for this. Repeated use of the same skills or activities helps a learner track their gradual mastery of those skills or activities. For example, repeated use of a micropipette in the lab will lead to the student being comfortable with how to manipulate that piece of equipment. They will be able to reflect on their progress in mastering its use as they make fewer mistakes, and gain confidence.
Simple activities that enable students to self-test themselves, or each other, can be very powerful. One of the most straightforward benchmarking tools is encouraging students to attempt to teach or explain a complex concept to a peer. That activity is extremely effective at highlighting gaps in knowledge or understanding. At the same time, managing that interaction by limiting the peer to only be allowed to ask questions in response is a very effective approach. Being presented with potentially naïve questions encourages the learner to really evaluate whether their cognitive learning processes are effective. Activities such as lightning talks, symposia, or ‘think-pair-share’ can help develop metacognition in a teaching setting.
Key to metacognition is reflection, encouraging the students to evaluate their strengths and limitations, and then put in an action-plan to capitalise on the strengths to address the limitations. It is important to encourage students to see limitations as areas for improvement, not failures. This framing is important in moving students from a fixed mindset about a skill/ability to a growth mindset (Dweck, 2006). A failure is not an inability to do something; it just means they cannot do that thing yet. Keeping portfolios, logs, or journals (either physical or virtual) can be powerful tools in this benchmarking and reflective learning process.
Activities to support motivation
Motivation for learning is needed before any effective learning can take place. Motivation is rooted in the concept of self-efficacy, the ability to do well in a particular skill, such as studying or performing academic tasks. There are several other theories that underpin motivation in learning. Action control theory (Kuhl & Kazen-Saad, 1989) focuses on goal-directed behaviour and how individuals control their actions when making choices or decisions. Self-Determination Theory (Deci & Ryan, 2008) focuses on three innate psychological needs that drive human motivation: Autonomy (the control over one’s actions and choices), Competence (the ability to perform) and Relatedness (building positive relationships with others). Finally, Control-Value Theory (Pekrun, 2006) focuses on how learners' emotions and motivations are influenced by that learner’s own perceived level of control over outcomes of their learning, and the value they place on the outcomes of learning activities.
Bringing these theories together, the key challenge for us as educators, therefore, is twofold: firstly, to provide learners with learning activities that are of interest and motivate them to learn more; secondly, to support learners in identifying what best motivates them to learn in general.
In any group of students, there will be some that are highly interested in the subject being taught, while others will be less interested. This will vary from subject to subject, such that there is no way of engaging all students at all times with the content of our teaching. They key, therefore, is to encourage students to draw connections between those aspects they find less-engaging to those they find more interesting. For example, encouraging a protein biochemist who cares little for cell biology by enabling them to break down the cellular processes into the network of protein interactions. Elements of student choice in their learning are powerful aids here, empowering students to approach each subject from a position they find engaging. For example, viewing enzyme kinetics from the standpoint of the action of a drug, or a physiological process, or a cellular interaction, or how an organism can adapt by evolving new metabolic pathways.
Encouraging students to identify what motivates them in learning, and applying that to their studying activities, is a powerful approach. Equally, identifying ways in which they have successfully motivated themselves to complete an activity they find tedious is a useful reflection to help them identify which strategies work to help motivate themselves, or to provide energy for studying when motivation is low.
Putting SRL into practice
For a subject such as the biosciences, where core factual information has a strong prominence, alongside the development of lab/field skills and analytical skills, it may seem that an area such as SRL is of limited importance. However, most scientific activities require a considerable amount of self-regulation and self-discipline. Particularly in practical research, where a student may face experimental setbacks and failures, the ability to be sufficiently self-aware to navigate a path through these challenges is important. In a discipline where factual content is not just high volume, but also increasingly complex, the skill of being able to manage (and improve) one’s own approach to learning is a core skill, and arguably one we should be actively supporting just as much as factual knowledge and research practices.
The two subsequent blogs in this series focus on ways we can use assessment and Generative AI opportunities to help students develop these skills.
References
Arifin, Z., Sukarmin, Saputro, S., & Kamari, A. (2025). The effect of inquiry-based learning on students’ critical thinking skills in science education: A systematic review and meta-analysis. Eurasia Journal of Mathematics, Science and Technology Education, 21(3), em2592. https://doi.org/10.29333/ejmste/15988
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