Stimulating self-regulation for high and low achievers in a Self-Directed Learning environment

Andrew C.C. Lao, Mark C.L. Huang, Tak Wai Chan

Research output: Contribution to conferencePaperpeer-review


The forthcoming trend of personalized learning drives the further development of individualization. Studies that relate to individual learning show possibilities for personalized learning in current education. This is because the goal of both individual and personalized learning are focused on how to help students pursue their learning and provide assistance to help students become lifelong learners. From the basis of cognitive theories, we believe that elementary students are able to be responsible for their own learning. However, most studies that related to individual learning were mainly from adult and adolescent education. In addition, as stated in Self-Determination Theory (Deci & Ryan, 1985), Deci & Ryan believed that self-regulation showed possible relation to student's motivation in learning. Hence, students' motivation plays an essential role in both individual learning and personalized learning. There needs to explore the factor that affects students' motivation. In order to help elementary students learn autonomously, there needs to explore the factors that affect student's motivation in learning. As a result, this study applied Self-Directed Learning (SDL) into math classrooms for exploring differences between high and low achievers in the motivation for learning. In this study, high achievers were more beneficial than the low achievers, where high achievers showed a significant difference with the low achievers on self-efficacy for learning & performance, metacognitive self-regulation, intrinsic goal orientation and resource management strategies: time and study environment.

Original languageEnglish
Number of pages8
StatePublished - 2013
Event21st International Conference on Computers in Education, ICCE 2013 - Bali, Indonesia
Duration: 18 Nov 201322 Nov 2013


Conference21st International Conference on Computers in Education, ICCE 2013


  • Motivation
  • Self-directed learning
  • Self-regulation


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