The Electronic Journal of e-Learning provides perspectives on topics relevant to the study, implementation and management of e-Learning initiatives
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Journal Article

Highlighting E‑learning Adoption Challenges using data Analysis Techniques: University of Kufa as a Case Study  pp136-149

Ammar J. M. Karkar, Hayder K. Fatlawi, Ahmed A. Al-Jobouri

© Feb 2020 Volume 18 Issue 2, Editor: Heinrich Söbke and Marija Cubric, pp114 - 206

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Abstract

Electronic learning (e‑learning) plays a significant role in improving the efficiency of the education process. However, in many cases in developing countries, technology transfer without consideration of technology acceptance factors has limited the impact of e‑learning and the expected outcome of the education process. Therefore, this shift in learning method has been met with low enthusiasm from academic staff and students owing to its low perceived usefulness and perceived ease‑of‑use. The University of Kufa (UoK) in Iraq is considered a good case study because it has implemented the e‑learning platform since 2013. The UoK platform is based on open‑source Moodle owing to the latter’s advantages, such as low implementation cost, open community for support and continuous update and development. To identify and evaluate the challenges, this study uses a questionnaire survey that targets the level of adoption, implementation, familiarity and technology acceptance of staff and students. A total of 242 educators participate in the survey, and the data are subsequently analysed. Important information is extracted using data mining techniques, namely clustering and decision trees. One of the main crucial factors extracted from the analysis results is the perception that social media is easier to use compared with a dedicated e‑learning platform such as Moodle. This factor may also discourage educators/learners from adopting an offered e‑learning platform, regardless of actual usefulness, motivation and training programs. Therefore, this paper offers practical information regarding the main issues and a guideline to fully utilise e‑learning for policy makers and e‑learning developers, particularly in newly established institutions or developing countries.

 

Keywords: e-learning, technology acceptance model, Educational data mining, Moodle, social media, Facebook, clustering, decision trees

 

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Journal Article

Learning Analytics in Flipped Classrooms: A Scoping Review  pp397-409

Muriel Algayres, Evangelia Triantafyllou

© Oct 2020 Volume 18 Issue 5, Editor: Rikke Ørngreen, Mie Buhl and Bente Meyer, pp373 - 459

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Abstract

The Flipped Classroom (FC) is an instruction method, where the traditional lecture and homework sessions are inverted. Online material is given to students in order to gain necessary knowledge before class, while class time is devoted to application of this knowledge and reflection. The hypothesis is that there could be deep and creative discussions when teacher and students physically meet, which has known a significant surge of popularity in the past decade. A marked recent trend in the FC is the increased use of Learning Analytics (LA) to support the development of the FC and students’ reflexive learning. The aim of this paper is to investigate the literature on applications of LA in FCs, and to determine the best practices and needs for technological development supporting LA in the FC by means of a scoping review. This literature review revealed that there is potential in using LA in the FC, especially as a means to predict students’ learning outcome and to support adaptive learning and improvement on the curriculum. However, further long‑term studies and development is necessary to encourage self‑directed learning in students and to develop the whole of the FC for a more diverse population of students. We anticipate an increased and expanded use of LA to come, with focus on predictive and prescriptive analytics providing more adaptive learning experience. We also anticipate that LA will expand beyond data mining to correlate student performance and online engagement with the aim to include a wider range of possibilities of interventions and adaptation of the learning experience.

 

Keywords: active learning, flipped classroom, learning analytics, virtual learning environment, educational data mining

 

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Journal Issue

Volume 18 Issue 2 / Feb 2020  pp114‑206

Editor: Heinrich Söbke, Marija Cubric

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Keywords: Blended learning; constructivism, behaviourism, objectivism, learning theory, context, feedback, peer feedback, peer review, discussion boards, learner-learner interaction, formative assessment, MOOC, e-learning, technology acceptance model, Educational data mining, Moodle, social media, Facebook, clustering, decision trees

 

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