Microlearning and computer-supported collaborative learning: An agenda towards a comprehensive online learning system

Abstract

<p style='text-indent:20px;'>With the rise of the COVID-19 pandemic and its inevitable consequences in education, increased demand for robust online learning frameworks has occurred at all levels of the education system. Given the transformative power of Artificial Intelligence (AI) and machine learning algorithms, there have been determined attempts through the design and application of intelligent tools to overcome existing challenges in online learning platforms. Accordingly, educational providers and researchers are investigating and developing intelligent online learning environments which share greater commonalities with real-world classroom conditions in order to better meet learners' needs. However, short attention spans and the widespread use of smart devices and social media bring about new e-learning systems known as microlearning (ML). While there has been ample research investigating ML and developing micro-content, pedagogical challenges and a general lack of alternative frameworks, theories and practices still exist. The present models have little to say about the connections between social interaction, including learner–content, learner–instructor and learner–learner communication. This has prompted us to investigate the complementary aspects of Computer-supported Collaborative Learning (CSCL) as an interactive learning model, along with an embedded ML module in the design and development of a comprehensive learning platform. The purpose of this study is to explore the pedagogical frameworks and challenges with reference to interaction and retention in online learning environments, as well as the theoretical and pedagogical foundations of ML and its applications. In addition, we delve into the theories and principles behind CSCL, the main elements in CSCL, identifying the issues and challenges to be faced in improving the efficacy of collaboration processes and outcomes. In short, we aim to synthesize how microlearning and CSCL can be applied as effective modules within a comprehensive online learning platform, thereby offering STEM educators a relevant roadmap towards progress that has yet to be offered in previous studies.</p>

Analyzing learner profiles in a microlearning app for training language learning peer feedback skills

“…Microlearning is inherently flexible and can be connected with “multiple learning theories and approaches” (Garshasbi et al, 2021 , p. 241). For example, Khong and Kabilan ( 2022 ) developed a theoretical model of microlearning for second-language instruction.…”

Design and implementation of multi-purpose quizzes to improve mathematics learning for transitional engineering students

“…To provide more flexibility for the students who may be affected by their work and/or family commitments irregularly, the sequencing of MPQ was based on the concept of 'micro learning and assessment' [15,16], which allows a student to attempt one section of quizzes that only relate to the subset of topics just studied by the student, rather than waiting to the completion of all topics in foundation mathematics covered from Week 1 to Week 5 in TM. Accordingly, the twenty quiz questions were segmented into three parts associated with different topics covered in different weeks as follows.…”