Deep learning techniques are being unified for decision support in various applications. However, it remains challenging to train robust deep learning models, due to the inherent insufficient labeled data that is usually time-consuming and labor-intensive. Self-supervised learning is a feature representation learning paradigm to learn robust…

The number of online courses that have been developed by faculty continues to increase in higher education. The purpose of this mixed-methods research study is to investigate the effects of online courses developed using the Quality Matters (QM) framework on self-regulated learning behaviors for students enrolled in online courses. The research…

Training of self-regulated learning is most effective if it supports learning strategies in combination with metacognitive regulation, and learners can transfer their acquired metacognitive regulation skills to different tasks that require the use of the same learning strategy (near transfer). However, whether learners can transfer metacognitive…

It is well-established that being a self-regulated learner is beneficial academically, motivationally and is considered essential for productive life-long learning. Despite this, there is limited evidence examining how different measures of self-regulation for learning (SRL) relate to task performance for young students learning in digital…

Self-regulated learning is an essential skill that can help students plan, monitor, and reflect on their learning in order to achieve their learning goals. However, in situations where there is a lack of effective feedback and recommendations, it becomes challenging for students to self-regulate their learning. In this paper, we propose an…

This paper aimed to explore the impact of self-regulated learning strategies on English language abilities and knowledge of 421 final-year undergraduate students at a public university in Thailand. The instruments used in the present study were: (1) the 65-item Questionnaire of English Self-Regulated Learning Strategies (QESRLS), and (2) the…

Cover-copy-compare is a self-management intervention strategy developed to improve students' academic performance, particularly in spelling. In academic intervention research, it is often assumed that students are completing the intervention as intended, yet this is seldom examined during intervention implementation or subsequent data analysis.…

Self-regulation of learning (SRL) is an essential ability for academic success in multiple educational contexts, including programming education. However, understanding how students regulate themselves during programming learning is still limited. This exploratory research aimed to investigate the regulatory strategies externalized by 51 students…

Many instructional videos in mathematics education target knowledge of procedures and algorithms. To design instructional videos that support students in a non-algorithmic domain, such as mathematical modeling, we developed a framework based on research on heuristic worked examples and instructional videos. Because students' perceptions play an…

A quantitative predictive correlational study was conducted to find to what extent, if any, gender and adult student status, individually or in combination, moderates the predictive relationships between resilience and self-regulated strategies of Goal Setting (GS), Environment Structuring (ES), Task Strategies (TS), Time Management (TM), Help…

The online learning environment demands the ability to self-regulate, set up learning goals, monitor progress, and self-reflect on the learning process. Self-regulated learning (SRL) is an approach to learning where students actively have control over their behaviors. This student-centered, iterative process demands learners exhibit certain…

Search-as-learning research has emphasized the need to better support searchers when learning about complex topics online. Prior work in the learning sciences has shown that effective self-regulated learning (SRL), in which goals are a central function, is critical to improving learning outcomes. This dissertation investigates the influence of…

We replicated and extended Maurer and Shipp's (2021) intervention to teach students the successive relearning study strategy and encourage its use in preparation for course exams. This mixed-methods project was conducted in partnership between the faculty member teaching the course and an undergraduate student enrolled in the course. Results were…

Despite the proliferation of massive open online courses (MOOCs) and the impressive levels of enrolment they attract, many participants do not complete these courses. High drop-out has been identified as one of the major problems with existing MOOC formats. Our work addresses two factors relating to non-completion. Firstly, MOOCs require a high…

Lecturers often claim that time constraints cause tension regarding feedback on students' assessment opportunities. Assessment strategies for effective feedback procedures can lead to early identification of problem areas in student performance. Numerous students at higher education institutions (HEIs) do not complete their qualifications or take…