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Education

Investigation Uncovers Key Factors Influencing Student Independent Learning

Strategic Insights

— 1 min read

Recent research from Universitas Pendidikan Ganesha, published in the Indonesian Journal of Instruction, has shed light on the complexities of student independent learning. The study found that low intrinsic motivation is a significant obstacle to self-directed learning, often exacerbated by educational platform designs that fail to provide adequate support. The researchers also discovered that cultural factors and learning support mechanisms have a profound impact on the quality of independent learning, highlighting the need for a more nuanced understanding of these dynamics.

Key Takeaways:

  • Low intrinsic motivation is a primary hindrance to student independent learning, often resulting from inadequate educational platform designs.
  • Cultural factors and learning support mechanisms significantly influence the quality of independent learning, emphasizing the importance of considering these elements in educational technology development.
  • Intrinsic motivation is the strongest predictor of self-directed learning quality, followed by identified regulation, while extrinsic motivation plays a weaker role.
  • The study employed a mixed method approach, combining quantitative and qualitative data from 400 students and 30 student interviews.
  • The researchers utilized Pearson's correlation test, regression, and qualitative thematic analysis to reinforce the findings.
  • The study's implications recommend that educational technology developers, educators, and policymakers prioritize creating platforms that are not only accessible but also supportive of student autonomy.
  • The study cited the Self-Determination Theory (SDT) framework as a crucial reference for understanding the relationship between motivation types and learning quality.
  • The study involved students who used various digital tools, including Learning Management Systems, mobile learning applications, and AI-based tutor systems.

Statistics:

  • 400 students participated in the quantitative stage of the study.
  • 30 students were involved in the qualitative stage through semi-structured interviews and platform log analysis.
  • The study used Pearson's correlation test, regression, and qualitative thematic analysis to analyze the data.
  • Intrinsic motivation was the strongest predictor of self-directed learning quality (92%)
  • Identified regulation was the second-strongest predictor, with an influence score of 85%
  • Extrinsic motivation played a weaker role, with an influence score of 70%

Sources:

  • Exploration of Students' Autonomous Learning Motivation in Educational Technology Environments. Indonesian Journal of Instruction, 2025, 6(2).
  • Universitas Pendidikan Ganesha. Indonesian Journal of Instruction.
  • Zhaoqiong W. U., I Nyoman Jampel, I Wayan Sukra Warpala. Exploration of Students' Autonomous Learning Motivation in Educational Technology Environments. Indonesian Journal of Instruction, 2025, 6(2). https://doi-org.sdpl.idm.oclc.org/10.23887/iji.v6i2.103718

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