Why ‘Computational’ Learning Theories?

This chapter proposes that for artificial intelligence (AI) to enhance human learning effectively, learning theories must evolve into computational theories. The chapter underscores the need for interdisciplinary synthesis across neuroscience, psychology, and computer science to enrich learning science. It embraces the idea that computational models can be tools to simulate and test learning theories, provide empirical validation of theory, and support insights into the underlying processes by emulating human-like cognitive processes. The chapter concludes by emphasizing the necessity for learning theories to incorporate complexity and machine learning concepts and methods to guide AI applications to promote learning processes at every level, from individual to cultural, through a computational learning theory framework.