Construction professionals’ perspectives of adaptive learning adoption: an SEM-machine learning approach

Social Sciences

• Scanning Electron Microscopy 100%
• Electronic Learning 50%
• Technology Acceptance Model 50%
• Comparative Analysis 50%
• Professional Development 50%
• Self-Efficacy 50%
• Singapore 50%

Economics, Econometrics and Finance

• Machine Learning 100%
• Specific Industry 66%
• Consumer Attitude 66%
• Innovation Adoption 33%
• e-Learning 33%
• Professional Development 33%
• Unified Theory of Acceptance and Use of Technology 2 33%

Computer Science

• Adaptive Learning 100%
• Machine Learning Approach 100%
• Behavioral Intention 20%
• Influencing Factor 20%
• Unified Theory 10%
• Practical Implication 10%
• Influence Factor 10%
• Learning Technology 10%
• Comparative Analysis 10%
• Questionnaire Survey 10%
• Electronic Learning 10%
• Machine Learning 10%
• Learning System 10%