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Education

Student Agency Crucial for Effective Learning, Yet Lacking in Personalized and Adaptive Learning Technologies

Strategic Insights

— 1 min read

Research by Oakland University has highlighted the growing recognition of student agency as a vital component of effective and equitable learning. However, its implementation in personalized and adaptive learning (PAL) technologies remains underemphasized. The study found that many PAL systems lack student-centered features, especially in low- and middle-income countries. To address this gap, the researchers introduced the Learner Adaptive Domain Agency (LADA) model, which integrates student agency into PAL system design by focusing on autonomy, competence, motivation, and connectedness. The LADA model was applied to 40 PAL systems deployed across 70 countries, revealing persistent limitations in how systems support student goal-setting, inclusive access, co-regulated learning, and reflective feedback.

Key Takeaways:

  • The LADA model emphasizes the importance of student agency in PAL systems, focusing on autonomy, competence, motivation, and connectedness.
  • The model was applied to 40 PAL systems deployed across 70 countries to evaluate how agency-supportive features are operationalized in practice.
  • Fewer than half of the platforms enabled shared control over learning pathways.
  • Most PAL systems relied on extrinsic motivation strategies rather than intrinsic supports.
  • The study highlights both the urgency and feasibility of reorienting PAL design toward agency-centered models.
  • The researchers concluded that designers, educators, and policymakers should advance equitable, empowering digital learning systems.
  • Ghaida S. Alrawashdeh, a researcher from Oakland University, is available for additional information.

Statistics:

  • 40 PAL systems were evaluated for their agency-supportive features.
  • 70 countries were represented in the deployment of these PAL systems.
  • 29-item rubric (AiPAL) was developed to translate theoretical principles into observable design criteria.
  • Fewer than half of the PAL systems enabled shared control over learning pathways (48%).
  • Intrinsically motivated features were lacking in most PAL systems (63% of the platforms).

Sources:

  • "Student Agency In Personalized and Adaptive Learning Technologies: From Conceptualization To Application." Education and Information Technologies, 2025.

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