Self-regulated learning reveals how students can direct and control their unique educational processes. Building upon the foundational work of Bandura’s Social Cognitive Theory, researchers and scholars are invited to examine four central topics regarding recent advancements, insights, and innovations in self-regulated learning. Bandura’s concept of self-efficacy emphasises self-observation, self-judgment, and self-reaction in the learning process. The book intends to cover the topic of motivational beliefs and examine how self-efficacy, goal orientation, and value attribution influence learning.

The book is also intended to cover the topic of metacognition, which explores the self-awareness required to process, plan, monitor, and evaluate one’s learning. Students should be aware of their personal strengths and weaknesses to develop strategies to understand the task at hand and regulate cognitive demands. Explicit modelling and teaching of metacognitive skills by educators can enhance learners’ reflective practices.

Emotional and behavioural self-regulation form the third topic to examine strategies to manage time, effort, anxiety, excitement, or frustration that affect learning. The impact of emotions on learning can influence cognitive processes such as attention, memory, problem-solving, and decision-making. Recognising and understanding one’s emotional states and behaviors are vital in maintaining a balance to persist in tasks to achieve goals despite challenges and distractions. Educators can nurture supportive relationships and positive learning environments to help students achieve this critical balance of emotions, behaviours, and self-regulation.

The book will also cover the synergy of personalised learning paths, artificial intelligence (AI), and human learning. AI changes the trajectory of self-regulation to emphasise the collaboration between emerging AI tools and human cognition in a new landscape of educational opportunities. Fueled by AI algorithms, new educational technology platforms provide personalised learning, real-time feedback, and optimised levels of challenge to assist students in understanding their mistakes and making improvements. AI-driven simulations and content gamification can address motivation and engagement central to self-regulated learning while providing educators with substantive data about students’ progress.

The collection of chapters in Self-Regulated Learning - Insights and Innovations examines how the education community can share insights to foster students’ success, achieve personal goals, and shape the future of self-regulated learning.