Learner choice in a smart learning environment: insights into rationales and alignment with adaptive assignments

Research is underway exploring how learner choice influences engagement and outcomes within Smart Learning Environments (SLEs) that integrate adaptive technologies. This study investigates the balance between system-controlled adaptivity and learner-controlled adaptability, particularly focusing on task difficulty selection in a web-based SLE for quantitative physics problem-solving among secondary students. Understanding learner rationales for choices in hybrid adaptive-adaptable systems is crucial for future SLE design.

Why it matters

This research contributes to understanding how technology can best support personalized learning experiences. Effective integration of learner choice within adaptive systems can enhance engagement and learning outcomes, which is critical for the development of future educational and training platforms. Strategic investment in research in this domain can lead to more effective and user-centric learning solutions.

Key insights

• Smart Learning Environments (SLEs) are increasingly incorporating adaptive technologies to personalize instruction.
• A key design consideration for SLEs is balancing system-driven adaptivity with learner-controlled adaptability.
• Hybrid approaches, such as adaptive recommendations with learner override options, aim to combine instructional optimization with learner autonomy.
• The study specifically investigates learners' task difficulty selections in a web-based SLE focused on quantitative physics problem-solving.
• 530 secondary students were assigned to either a fully adaptive or an adaptable condition, indicating a comparative research design.
• Insights into learner choices within these hybrid systems can inform future SLE design.
• The source text describes the introduction and methodology of the study, but does not present its findings or conclusions.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1894519