Research on Visualized Design for Role-Based Online Learning Analytics

2016 ◽  
pp. 173-185
Author(s):  
Lamei Wang ◽  
Jun Xiao ◽  
Yuanyi Qi ◽  
Ye Yu
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Role Based

Learning Analytics Considered Harmful

2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Laurie P Dringus
Keyword(s):  
Big Data ◽  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Research Community ◽  
Current Status ◽  
Online Course ◽  
Full Potential

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.

Online Learning Analytics

2021 ◽  
Author(s):  
Jay Liebowitz
Keyword(s):  
Online Learning ◽  
Learning Analytics

scholarly journals Understanding Learner Behaviour in Online Courses through Learning Analytics

2021 ◽  
pp. 381-390
Author(s):  
D. Thammi Raju ◽  
G. R. K. Murthy ◽  
S. B. Khade ◽  
B. Padmaja ◽  
B. S. Yashavanth ◽  
...  
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Learning Experience ◽  
Training Needs ◽  
Online Course ◽  
Quality Of Education ◽  
Time Data

Building an effective online course requires an understanding of learning analytics. The study assumes significance in the COVID 19 pandemic situation as there is a sudden surge in online courses. Analysis of the online course using the data generated from the Moodle Learning Management System (LMS), Google Forms and Google Analytics was carried out to understand the tenants of an effective online course. About 515 learners participated in the initial pre-training needs & expectations’ survey and 472 learners gave feedback at the end, apart from the real-time data generated from LMS and Google Analytics during the course period. This case study analysed online learning behaviour and the supporting learning environment and suggest critical factors to be at the centre stage in the design and development of online courses; leads to the improved online learning experience and thus the quality of education. User needs, quality of resources and effectiveness of online courses are equally important in taking further online courses.

Using Learning Analytics to Enhance Student Learning in Online Courses Based on Quality Matters Standards

2016 ◽  
Vol 45 (2) ◽  
pp. 165-187 ◽  
Author(s):  
Florence Martin ◽  
Abdou Ndoye ◽  
Patricia Wilkins
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Online Courses ◽  
Online Course ◽  
Design Quality ◽  
Descriptive Data ◽  
Quality Matters ◽  
Frequency Of Use ◽  
And Performance ◽  
Enhance Student Learning

Quality Matters is recognized as a rigorous set of standards that guide the designer or instructor to design quality online courses. We explore how Quality Matters standards guide the identification and analysis of learning analytics data to monitor and improve online learning. Descriptive data were collected for frequency of use, time spent, and performance and analyzed to identify patterns and trends on how students interact with online course components based on the Quality Matters standards. Major findings of this article provide a framework and guidance for instructors on how data might be collected and analyzed to improve online learning effectiveness.

Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning

2014 ◽  
Vol 31 ◽  
pp. 542-550 ◽  
Author(s):  
Ángel F. Agudo-Peregrina ◽  
Santiago Iglesias-Pradas ◽  
Miguel Ángel Conde-González ◽  
Ángel Hernández-García
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Log Data

scholarly journals Using learning analytics to engage students: Improving teaching practices through informed interactions

2020 ◽  
Vol 9 (2) ◽  
pp. 231
Author(s):  
Justina Naujokaitienė ◽  
Giedrė Tamoliūnė ◽  
Airina Volungevičienė ◽  
Josep M. Duart
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Teaching Practices ◽  
Online Teaching ◽  
Teaching And Learning ◽  
New Technology ◽  
Research Problem ◽  
Qualitative Inquiry ◽  
Structured Interviews ◽  
Learner Engagement

Student engagement is one of the most relevant topics within the academic and research community nowadays. Higher education curriculum, teaching and learning integrate new technology- supported learning solutions. New methods and tools enhance teacher and learner interactions and influence learner engagement positively. This research addresses the need to explore new ways of improving teaching practices to better engage students with the help of learning analytics. The paper investigates how university teachers use the data from learning analytics to observe learners and to engage them in online learning. Qualitative inquiry was chosen to approach the research problem, and semi-structured interviews with the teachers using (blended) online learning were conveyed to explore teacher practices in students’ behaviour and engagement observations online, disclosing teachers’ abilities to understand the challenging learner engagement process based on the data from learning analytics. The new evidence provided by this research highlights the successful practices in the use of learning analytics data to observe students’ behaviour and engagement and to inform teachers on the presence needed in order to develop learner–centred activities and to make curriculum changes. The limitation of this study lies in the fact that the different online teaching experiences that research participants had might have restricted their understanding of the use of LA data for curriculum development and learners’ engagement.

scholarly journals A Teacher-facing Learning Analytics Dashboard for Process-oriented Feedback in Online Learning

2021 ◽  
Author(s):  
Raphael A. Dourado ◽  
Rodrigo Lins Rodrigues ◽  
Nivan Ferreira ◽  
Rafael Ferreira Mello ◽  
Alex Sandro Gomes ◽  
...  
Keyword(s):  
Online Learning ◽  
Learning Analytics ◽  
Process Oriented

scholarly journals Learning Analytics: Learning to Think and Make Decisions

2019 ◽  
Vol 16 ◽  
Author(s):  
Airina Volungevičienė ◽  
Josep Maria Duart ◽  
Justina Naujokaitienė ◽  
Giedrė Tamoliūnė ◽  
Rita Misiulienė
Keyword(s):  
Online Learning ◽  
Real Time ◽  
Learning Analytics ◽  
Online Teaching ◽  
Teacher Inquiry ◽  
Learning Design ◽  
Teaching Process ◽  
Research Results ◽  
Learning And Teaching ◽  
Specific Analysis

The research aims at a specific analysis of how learning analytics as a metacognitive tool can be used as a method by teachers as reflective professionals and how it can help teachers learn to think and come down to decisions about learning design and curriculum, learning and teaching process, and its success. Not only does it build on previous research results by interpreting the description of learning analytics as a metacognitive tool for teachers as reflective professionals, but also lays out new prospects for investigation into the process of learning analytics application in open and online learning and teaching. The research leads to the use of learning analytics data for the implementation of teacher inquiry cycle and reflections on open and online teaching, eventually aiming at an improvement of curriculum and learning design. The results of the research demonstrate how learning analytics method can support teachers as reflective professionals, to help understand different learning habits of their students, recognize learners’ behavior, assess their thinking capacities, willingness to engage in the course and, based on the information, make real time adjustments to their course curriculum.

scholarly journals Introduction to Section Two: MOOCs, Psychological Constructs, Communication Behaviors

2016 ◽  
Vol 20 (2) ◽  
Author(s):  
Peter Shea
Keyword(s):  
Online Learning ◽  
Qualitative Analysis ◽  
Learning Analytics ◽  
Online Students ◽  
Communication Behaviors ◽  
Psychological Constructs ◽  
Information Behaviors ◽  
Imposter Phenomenon ◽  
Anxiety Levels

This issue of Online Learning also contains four articles outside the theme of learning analytics. This section contains papers investigating MOOCs, a comparison of anxiety levels and the “imposter phenomenon” between online and classroom students, and a qualitative analysis of information behaviors among online students.

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