Content area
The rapid integration of artificial intelligence technologies into higher education presents unprecedented opportunities for enhancing computational thinking development while simultaneously raising significant concerns about educational equity and algorithmic bias. This comprehensive review examines the intersection of AI integration, computational thinking pedagogy, and diversity, equity, and inclusion imperatives in higher education through a comprehensive narrative review of 167 sources of current literature and theoretical frameworks. From distilling principles from Human–AI Symbiotic Theory (HAIST) and established pedagogical integration models, this review synthesizes evidence-based strategies for ensuring that AI-enhanced computational thinking environments advance rather than undermine educational equity. The analysis reveals that effective AI integration in computational thinking education requires comprehensive frameworks that integrate ethical AI governance with pedagogical design principles, creating practical guidance for institutions seeking to harness AI’s potential while protecting historically marginalized students from algorithmic discrimination. This review contributes to the growing body of knowledge on responsible AI implementation in educational settings and provides actionable recommendations for educators, researchers, and policymakers working to create more effective, engaging, and equitable AI-enhanced learning environments.
Details
Competence;
Educational Research;
Science Education;
Intelligent Tutoring Systems;
Influence of Technology;
Cognitive Processes;
Equal Education;
Computer Science Education;
Educational Technology;
Evidence;
Ethics;
Access to Education;
Coding;
Information Seeking;
Artificial Intelligence;
Educational Assessment;
Elementary Secondary Education;
Educational Policy;
Educational Environment;
Database Management Systems;
Higher Education;
Educational Strategies;
Educational Equity (Finance);
Algorithms
Pedagogy;
Higher education;
Collaboration;
Citation management software;
Computer science;
Instructional design;
Interdisciplinary aspects;
Educational technology;
Ethics;
Generative artificial intelligence;
Bias;
Machine learning;
Tutoring;
Inclusion;
Science education;
Education policy;
Critical thinking;
Systematic review;
Adaptive learning