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Personalized Learning in Vocational and Continuing Education
Investigating Key Factors Influencing Learning Outcomes in Artificial Intelligence Within Adaptive Learning Environments
Introduction
Amid the growing significance of artificial intelligence (AI) in education and its increasing societal and economic impact on the contemporary workforce, this book examines the delivery of an AI additional qualification implemented through an adaptive learning system designed to support the acquisition of AI-related knowledge and skills among learners in vocational education and training (VET) and continuing vocational education and training (CVET).
Research Focus
At the core of the book lies the investigation of key learner characteristics and system features that contribute to enhancing AI learning outcomes. Drawing on a quasi-experimental research design, data from 222 participants were gathered over two school years.
Methodology
Self-reported questionnaires administered in standardized online surveys captured learners’ perceptions throughout the AI course. Statistical analyses in R provide empirical support for the effectiveness of learners’ prior AI knowledge and the system’s individualized and adaptive features in improving AI learning outcomes.
Findings
Nevertheless, the study reveals that learners’ experience with digital learning applications has no significant influence. In addition, the analysis of AI learning outcomes across learning style groups yields no conclusive support on the effect of learning preferences on cognitive achievements within adaptive learning environments.
Implications
The findings provide implications for researchers, stakeholders in VET and CVET, and developers of adaptive learning systems.
