Active Learning in University Physics for Sustainable Higher Education: Effective Components, Mechanisms, and SDG-Aligned Competency Pathways—A Multidimensional Review

Active learning has increasingly been adopted as an evidence-aligned approach to improving learning quality in university physics—a domain characterized by high conceptual abstraction, persistent misconceptions, and substantial variability in student performance. Evidence from physics education research indicates that active-learning designs can outperform lecture-dominant instruction in conceptual learning and student engagement; however, reported effects vary substantially across instructional settings and implementation models. Here, empirical studies and review-level syntheses are integrated to delineate (i) the instructional components that most reliably underpin successful active learning, (ii) the mechanisms through which these components influence learning processes and outcomes, and (iii) the boundary conditions that moderate effectiveness across higher-education contexts. The synthesis is further situated within sustainability-oriented higher education by linking physics active-learning designs to competence development relevant to quality education, climate literacy, and collaborative problem solving. Evidence spanning flipped classroom implementations, peer instruction, collaborative problem solving, inquiry- and project-based approaches, and technology-enhanced formats is organized into a component–mechanism–outcome framework structured along cognitive, affective, and behavioral pathways. Two deliverables are advanced: an integrative mechanism model connecting instructional components to mediating processes, learning outcomes, and sustainability-aligned competencies, and an operational toolbox that translates the evidence into actionable design heuristics, measurement options, and scaling considerations. By redirecting attention from “which strategy works” to “which components work, how, and under what conditions,” the review aims to support instructors, departments, and institutions seeking scalable, evidence-aligned active learning in university physics.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2026-03-12
DOI
https://doi.org/10.3390/su18062791
Primary Topic
Science Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Active Learning in University Physics for Sustainable Higher Education: Effective Components, Mechanisms, and SDG-Aligned Competency Pathways—A Multidimensional Review

Chenglong Wang, Jun Jiang, Fan Xiao
Sustainability
Science Education and Pedagogy
article

Active Learning in University Physics for Sustainable Higher Education: Effective Components, Mechanisms, and SDG-Aligned Competency Pathways—A Multidimensional Review

Chenglong Wang, Jun Jiang, Fan Xiao
article en

Abstract

Active learning has increasingly been adopted as an evidence-aligned approach to improving learning quality in university physics—a domain characterized by high conceptual abstraction, persistent misconceptions, and substantial variability in student performance. Evidence from physics education research indicates that active-learning designs can outperform lecture-dominant instruction in conceptual learning and student engagement; however, reported effects vary substantially across instructional settings and implementation models. Here, empirical studies and review-level syntheses are integrated to delineate (i) the instructional components that most reliably underpin successful active learning, (ii) the mechanisms through which these components influence learning processes and outcomes, and (iii) the boundary conditions that moderate effectiveness across higher-education contexts. The synthesis is further situated within sustainability-oriented higher education by linking physics active-learning designs to competence development relevant to quality education, climate literacy, and collaborative problem solving. Evidence spanning flipped classroom implementations, peer instruction, collaborative problem solving, inquiry- and project-based approaches, and technology-enhanced formats is organized into a component–mechanism–outcome framework structured along cognitive, affective, and behavioral pathways. Two deliverables are advanced: an integrative mechanism model connecting instructional components to mediating processes, learning outcomes, and sustainability-aligned competencies, and an operational toolbox that translates the evidence into actionable design heuristics, measurement options, and scaling considerations. By redirecting attention from “which strategy works” to “which components work, how, and under what conditions,” the review aims to support instructors, departments, and institutions seeking scalable, evidence-aligned active learning in university physics.

SustainabilityVol. 18(6)
Harbin University (CN), Harbin Normal University (CN), Harbin Engineering University (CN)
Climate action
Openalex Percentile: Top 25%
Science Education and Pedagogy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.