RT Book, Section
A1 Qian, Yufeng
T1 In Search of a Learning Theory for Synthetic Intelligence
T2 Synthetic Intelligence in Education: Transforming Pedagogy with AI
A2 Qian, Yufeng
YR 2026
DO 10.1108/978-1-80686-799-820261004
SP 0
SN 978-1-80686-800-1
PB Emerald Publishing Limited
AB Technology and learning have never evolved in isolation; each has continually reshaped the other. This chapter asks what that relationship looks like in an era of artificial intelligence (AI). It has two aims. First, it revisits major learning theories of the pre-AI era – behaviorism, cognitivism, constructivism, and connectivism – and traces how each engaged with the educational technologies of its time, from blackboards and textbooks to early computers and networked media. Second, it turns to emerging lenses for understanding hybrid human–AI learning ecologies in which human meaning-making is tightly coupled with machine computation. Drawing on contemporary work in distributed cognition, the extended mind, and posthumanist learning theory, the chapter asks what “learning theory” might mean when learning no longer resides only within individual humans but unfolds across learners, educators, and intelligent systems in an AI-saturated world.
RD 4/10/2026
UL https://doi.org/10.1108/978-1-80686-799-820261004