Evidence-Based Learning Design Through Learning Analytics

2020 ◽  
pp. 407-424
Author(s):  
Esin Caglayan ◽  
O. Osman Demirbas ◽  
Ali Burak Ozkaya ◽  
Mehmet Sahin
Keyword(s):  
Learning Analytics ◽  
Evidence Based ◽  
Learning Design

scholarly journals Learning Analytics to Reveal Links Between Learning Design and Self-Regulated Learning

2021 ◽  
Author(s):  
Yizhou Fan ◽  
Wannisa Matcha ◽  
Nora’ayu Ahmad Uzir ◽  
Qiong Wang ◽  
Dragan Gašević
Keyword(s):  
Learning Analytics ◽  
High Performance ◽  
Process Mining ◽  
Learning Experience ◽  
Learning Design ◽  
Metacognitive Control ◽  
Self Regulated Learning ◽  
Regulated Learning ◽  
High Level ◽  
Evaluation Of Learning

AbstractThe importance of learning design in education is widely acknowledged in the literature. Should learners make effective use of opportunities provided in a learning design, especially in online environments, previous studies have shown that they need to have strong skills for self-regulated learning (SRL). The literature, which reports the use of learning analytics (LA), shows that SRL skills are best exhibited in choices of learning tactics that are reflective of metacognitive control and monitoring. However, in spite of high significance for evaluation of learning experience, the link between learning design and learning tactics has been under-explored. In order to fill this gap, this paper proposes a novel learning analytic method that combines three data analytic techniques, including a cluster analysis, a process mining technique, and an epistemic network analysis. The proposed method was applied to a dataset collected in a massive open online course (MOOC) on teaching in flipped classrooms which was offered on a Chinese MOOC platform to pre- and in-service teachers. The results showed that the application of the approach detected four learning tactics (Search oriented, Content and assessment oriented, Content oriented and Assessment oriented) which were used by MOOC learners. The analysis of tactics’ usage across learning sessions revealed that learners from different performance groups had different priorities. The study also showed that learning tactics shaped by instructional cues were embedded in different units of study in MOOC. The learners from a high-performance group showed a high level of regulation through strong alignment of the choices of learning tactics with tasks provided in the learning design. The paper also provides a discussion about implications of research and practice.

scholarly journals The development and evaluation of an online educational tool for the evidence-based management of neck pain by chiropractic teaching faculty

2020 ◽  
Author(s):  
Leslie Verville ◽  
Pierre Côté DC ◽  
Diane Grondin ◽  
Silvano Mior DC ◽  
Robin Kay
Keyword(s):  
Clinical Practice ◽  
Neck Pain ◽  
Clinical Practice Guideline ◽  
Practice Guideline ◽  
Thinking Skills ◽  
Faculty Members ◽  
Evidence Based ◽  
Learning Design ◽  
Educational Tool ◽  
Learning Tool

Objective To develop an online, interactive educational tool to deliver an evidence-based clinical practice guideline to faculty members at a Canadian chiropractic college. Second, to evaluate the learning, design, and engagement constructs of the tool in a sample of chiropractic faculty members. Methods Using an integrated knowledge translation methodology and the Knowledge to Action Framework, we developed an evidence-based online learning tool. The context of the tool focused on a clinical practice guideline on the management of neck pain. We evaluated the learning, design, and engagement constructs in a sample of faculty members and residents using the Learning Object Evaluation Scale for Students. Participants were also asked to provide suggestions for improvement of the tool. Results Sixteen participants completed the evaluation. Most (68.8%) participants were chiropractors, 75% were male and 56% were between the ages of 25 and 44 years. At least 75% of participants agreed that the learning, design, and engagement constructs of the learning tool were adequate. The open-ended suggestions unveiled 3 pedagogical themes, relating to multimedia, thinking skills, and learner control, within the tool that could benefit from further development. These themes informed recommendations to improve the tool. Conclusion Our online, interactive, module-based learning tool has sound pedagogical properties. Further research is needed to determine if its use is associated with a change in knowledge.

scholarly journals Aligning learning design and learning analytics through instructor involvement: a MOOC case study

2019 ◽  
Vol 27 (5-6) ◽  
pp. 685-698 ◽  
Author(s):  
Erkan Er ◽  
Eduardo Gómez-Sánchez ◽  
Yannis Dimitriadis ◽  
Miguel L. Bote-Lorenzo ◽  
Juan I. Asensio-Pérez ◽  
...  
Keyword(s):  
Learning Analytics ◽  
Learning Design

scholarly journals Learning analytics for learning design in online distance learning

2019 ◽  
Vol 40 (3) ◽  
pp. 309-329 ◽  
Author(s):  
Wayne Holmes ◽  
Quan Nguyen ◽  
Jingjing Zhang ◽  
Manolis Mavrikis ◽  
Bart Rienties
Keyword(s):  
Distance Learning ◽  
Learning Analytics ◽  
Learning Design ◽  
Online Distance Learning ◽  
Online Distance

scholarly journals Learning design and learning analytics in mobile and ubiquitous learning: A systematic review

2020 ◽  
Vol 51 (4) ◽  
pp. 1078-1100 ◽  
Author(s):  
Gerti Pishtari ◽  
María J. Rodríguez‐Triana ◽  
Edna M. Sarmiento‐Márquez ◽  
Mar Pérez‐Sanagustín ◽  
Adolfo Ruiz‐Calleja ◽  
...  
Keyword(s):  
Systematic Review ◽  
Learning Analytics ◽  
Learning Design ◽  
Ubiquitous Learning

Modeling Students' Performances in Activity-Based E-Learning From a Learning Analytics Perspective

2020 ◽  
Vol 18 (4) ◽  
pp. 71-93 ◽  
Author(s):  
Yousra Banoor Rajabalee ◽  
Mohammad Issack Santally ◽  
Frank Rennie
Keyword(s):  
Learning Analytics ◽  
Predictive Analytics ◽  
Learning Activities ◽  
Learning Assessment ◽  
Learning Activity ◽  
Learning Design ◽  
Continuous Assessment ◽  
Online Module ◽  
E Learning ◽  
Teaching Interventions

This paper reports the findings of a research using marks of students in learning activities of an online module to build a predictive model of performance for the final assessment of the module. The objectives were (1) to compare the performances of students of two cohorts in terms of continuous learning assessment marks and final learning activity marks and (2) to model their final performances from their learning activities forming the continuous assessment using predictive analytics and regression analysis. The findings of this study combined with other findings as reported in the literature demonstrate that the learning design is an important factor to consider with respect to application of learning analytics to improve teaching interventions and students' experiences. Furthermore, to maximise the efficiency of learning analytics in eLearning environments, there is a need to review the way offline activities are to be pedagogically conceived so as to ensure that the engagement of the learner throughout the duration of the activity is effectively monitored.

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