A Conceptual Model for Measuring and Supporting Self-Regulated Learning using Educational Data Mining on Learning Management Systems

Araka, Eric; Maina, Elizaphan; Gitonga, Rhoda; Oboko, Robert

doi:10.23919/istafrica.2019.8764852

Cited by 9 publications

(8 citation statements)

References 41 publications

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“…Adaptive learning systems need to develop learners with effective SLR skills (affect, emotion, self-regulation, higher-order thinking, etc.) to deal with complexities of the society, to be able to create social and collaborative work environments, and to know how to be lifelong learners in a non-patterned, complex, and ambiguous network of connections [38]. This research study extended existing literature via exploring the changes of SRL skills' score in an adaptive learning environment.…”

Section: Discussionmentioning

confidence: 95%

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Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students’ Perception and Self-Regulated Learning Skills

Harati

Sujo-Montes

et al. 2021

Education Sciences

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Adaptive learning is an educational method that uses computer algorithms and artificial intelligence (AI) to customize learning materials and activities based on each user’s model. Adaptive learning has been used for more than 20 years. However, it is still unique, and no other system could bring more or even similar capabilities than the ones adaptive technology offers, including the application of AI, psychology, psychometrics, machine learning, and providing a personalized learning environment. However, there are not many studies on its practicality, usefulness, improving students’ learning skills, students’ perception, etc., due to the limited number of institutes investing in this new technology. This paper presents the results of administering the newly developed Adaptive Self-regulated Learning Questionnaire (ASRQ) in an adaptive learning course equipped with the ALEKS (Assessment and Learning in Knowledge Spaces) system to study the amount of Self-regulated Learning Skills (SRL) score change, if any, of the students. The ASRQ was administered at the beginning and end of the semester as a pretest and posttest. Then, the quantitative Sample Paired t Test was run to measure the students’ SRL score change between the beginning and end of the semester. The results showed a significant decline in students’ SRL skills score while working with ALEKS. This paper also discusses the reasons for the considerable drop in SRL skills based on students’ perception and feedback collected through administering an open-ended survey at the end of the semester. The survey’s qualitative analysis showed various possible factors contributing to the decline of the SRL skills score, including lack of motivation, system complexity, hard penalty, lack of social presence, and lack of system practicality.

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Section: Discussionmentioning

confidence: 95%

“…Numerous studies showed the important role of SRL skills in students' success in online settings [38,39]. Web-based online learning requires developing SRL skills in learners which is not possible without understanding and paying attention to their characteristics and to develop strategic learning skills.…”

Section: Discussionmentioning

confidence: 99%

Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students’ Perception and Self-Regulated Learning Skills

Harati

Sujo-Montes

et al. 2021

Education Sciences

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“…Learner scaffolds can also be provided through learner dashboard. This implementation allows students to be supported and guided while studying online without the limitation of numbers of students enrolled (Araka et al, 2019). However, we found out that there is lack of a framework on how the EDM measurement and intervention models can be conceptualized and deployed on LMSs.…”

Section: Resultsmentioning

confidence: 99%

“…It would also be important to observe that there is a lack of a model that can be used to implement the "third wave" of SRL measurement and promotion in higher education especially in online learning environments. The existing studies did not describe an EDM model for implementation except for one study that proposed a conceptual model (Araka et al, 2019). To address the challenges encountered when using selfreport tools for measuring SRL in online learning environments, we propose the use of EDM techniques for measuring and promoting SRL as EDM relies on the use log or trace data collected from educational environments as indicators of SRL.…”

Section: Discussionmentioning

confidence: 99%

Research trends in measurement and intervention tools for self-regulated learning for e-learning environments—systematic review (2008–2018)

Araka

Maina

Gitonga

et al. 2020

RPTEL

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111

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For the last one decade, research in self-regulated learning (SRL) and educational psychology has proliferated. Researchers and educators have focused on how to support leaners grow their SRL skills on both face-to-face and e-learning environments. In addition, recent studies and meta-analysis have greatly contributed to the domain knowledge on the use of SRL strategies and how they contribute and boost academic performance for learners. However, there is little systematic review on the literature on the techniques and tools used to measure SRL on e-learning platforms. This review sought to outline recent advances and the trends in this area to make it more efficient for researchers to establish the empirical studies and research patterns among different studies in the field of SRL. The findings from this study are concurrent with existing empirical evidence that traditional methods designed for classroom supports are being used for measuring SRL on e-learning environments. Few studies have used learner analytics and educational data mining (EDM) techniques to measure and promote SRL strategies for learners. The paper finally points out the existing gaps with the tools presently used to measure and support SRL on learning management systems and recommends further studies on the areas of EDM which can support SRL.

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“…There are five different models of inductive learning such as like inquiry-based learning, problem-based learning, project-based learning, case-based learning, and just-in-time learning on students' self-regulated learning. The inductive learning processes do not force students to digest the facts or learning material, rather a learning environment is created which develops critical thinking, skills, habits, and behaviors among the students who can self-regulate learning and become able to overcome real-life problems, issues, and complex situations (Ainscough, Stewart, Colthorpe, & Zimbardi, 2018;Albert & Gómez-Fernández, 2020;Araka, Maina, Gitonga, & Oboko, 2019;Corrás-Arias, 2020).…”

Section: Introductionmentioning

confidence: 99%

The role of inductive learning models on the students self-regulated learning in math journaling

Amiruddin

Qorib

Naimi

et al. 2022

CJES

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Students’ self-regulated learning has become an essential element of student’s success in the education sector and therefore, needs the attention of policymakers and scholars alike. Thus, the current study investigates into the role of different learning styles such as just-in-time learning, case-based learning, inquiry learning, project-based learning and problem-based learning on students’ self-regulated learning in the context of public sector universities in Indonesia. Questionnaires are used by researchers to gather the data from respondents. The purposive sampling technique is used to select the student respondents who are using math journaling. Researchers also execute the PLS-SEM for the purpose of analysis and tests the validity, reliability and relationships among variables. The results indicate that all learning styles such as just-in-time learning, case-based learning, inquiry learning, project-based learning and problem-based learning have a positive nexus with students’ self-regulated learning in public sector universities in Indonesia. This study provides valuable insights to policymakers regarding formulating new policies about student self-regulated learning. Keywords: Just-in-time learning, inquiry learning, project-based learning, problem-based learning, students’ self-regulated learning

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A Conceptual Model for Measuring and Supporting Self-Regulated Learning using Educational Data Mining on Learning Management Systems

Cited by 9 publications

References 41 publications

Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students’ Perception and Self-Regulated Learning Skills

Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students’ Perception and Self-Regulated Learning Skills

Research trends in measurement and intervention tools for self-regulated learning for e-learning environments—systematic review (2008–2018)

The role of inductive learning models on the students self-regulated learning in math journaling

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