6 Promoting Student Self-Regulation and Adaptation
Clearly, an essential component of active learning is the active engagement of students. However, to actively engage students must also have the knowledge, capabilities and attributes to productively navigate the active learning ‘terrain’ and sustain their engagement, especially when previous learning experiences may not have sufficiently prepared them. This section explores approaches to building student confidence, capacity and skills to engage with active learning. As Sidorovitch highlights, developing self-monitoring and self-evaluation, fundamental attributes for active learning, requires deliberate scaffolding. Kostoulias and Hughes et al. offer two approaches to such scaffolding and supporting the associated confidence, capacity and skill development. Kostoulias offers Critical Team Coaching (CTcM) to develop the capabilities needed to engage effectively with active learning and sustain that engagement. These capabilities include critical reflection, collaboration, and self-directed problem-solving. They explore the benefits and impact of CTcM for both students and staff. Meanwhile, Hughes et al. offer academic coaches as their approach to support and nudge students to develop the capacity for active learning and derive the associated benefits of engagement. These benefits include self-confidence and self-reliance in how to study, as well as relevant skills and knowledge to thrive in higher education. Underpinned by a theoretical framework that draws on coaching and nudge theory, they highlight how others may adopt or adapt the approach for their students. Early indications suggest improved progression rates in students who engage with this support.
When exploring tools and technologies that can support active learning and self-reflection, Saman and Shoukry argue that when appropriately implemented with due attention to equitable implementation, expert oversight, and environmental sustainability, generative artificial intelligence (GenAI) has the potential to expand access to formative feedback, supporting active learning and self-reflection beyond class time or instructor availability. As Horrocks highlights, by fostering environments rich in active learning, we help students build their skills and capacities to be competent and confident active learners who can then resist the allure of using tools like GenAI in an inappropriate way. Smith‘s case study provides an interesting example of a GenAI-facilitated approach to active learning to foster critical thinking, legal reasoning, and digital skill development. Smith shows due consideration to several of the issues Saman and Shoukry and Horrocks raise, showing an example in practice for others to learn from.
Finally, Fisher offers another illustration of how thoughtfully designed learning experiences using digital tools and spaces, in this case the affordances offered by a Virtual Learning Environment (VLE), can foster reflection and active engagement. Fisher demonstrates this through the consistent use of low‑stakes microlearning prompts (‘Stop and Think’) embedded within the Virtual Learning Environment. These short reflective activities significantly improved student engagement and have since become standard practice across the university’s online provision. Fisher’s example highlights how practices designed with adaptability and transferability in mind are more easily sustained and embedded to support student engagement, critical thinking, and independent learning.
