Six major self-regulated learning theories largely agree and fit together, but which one works best depends on students' age and education level.
Blended courses match or beat face-to-face and online options on student success and dropout rates, and students judge course quality by consistent rules regardless of format.
A review of 63 studies finds AI-driven adaptive e-learning personalizes learning paths and boosts engagement and test scores, though privacy and complexity remain obstacles.
A review of 147 studies finds AI adaptive learning systems are mostly small-scale prototypes that rarely tackle students' real, specific learning problems.
Personalized and adaptive learning tech can harm students if applied blindly; educators must balance data-driven tailoring with real human diversity and support needs.
AI education research is split across disconnected fields, so this review of 32 studies proposes a 'Hybrid Intelligence' framework uniting learners, teachers and machines.
Brain-sensing and eye-tracking tools can track students' mental effort live, and this review argues universities should use them to redesign STEM teaching around cognitive load.
Doctors should earn continuing-education credit for demonstrated clinical reasoning in AI chat sessions, not for hours sat in lectures, under a proposed scoring framework.
A new 33-item survey reliably measures six distinct dimensions of trainee teachers' digital teaching competence, validated across nearly 1,500 Turkish students.
A global study estimates deaths and disability from road injuries in every country from 1990 to 2023, giving comparable numbers to guide road safety policy.
AI tutors can boost grades while quietly eroding students' ability to judge and manage their own learning, so universities need a design framework that trains metacognition, minimises data collection and keeps students in control.