A learning analytics approach: Using online weekly student engagement data to make predictions on student performance

2018 ◽  
Author(s):  
Rahila Umer ◽  
Teo Susnjak ◽  
Anuradha Mathrani ◽  
Suriadi Suriadi
Keyword(s):  
Student Engagement ◽  
Student Performance ◽  
Learning Analytics

scholarly journals Assessing Student Engagement in Online Programmes: Using Learning Design and Learning Analytics

2019 ◽  
Vol 8 (6) ◽  
pp. 171 ◽  
Author(s):  
Maria Toro-Troconis ◽  
Jesse Alexander ◽  
Manuel Frutos-Perez
Keyword(s):  
Online Learning ◽  
Student Engagement ◽  
Student Performance ◽  
Cognitive Skills ◽  
Learning Analytics ◽  
Linear Regression Analysis ◽  
Learning Design ◽  
Online Forums ◽  
Postgraduate Students ◽  
Weak Evidence

This paper presents the learning design framework used in the design of the Online MA in Photography at Falmouth University. It discusses the importance of evaluating the success of online learning programmes by analysing learning analytics and student feedback within the overall pedagogic context and design of the programme. Linear regression analysis was used to analyse the engagement of three cohorts of students that completed four modules of the Online MA Photography (n=33) with over 80,000 entries in the dataset. The research explored student engagement with online content that promoted low-order cognitive skills (i.e. watching videos, reading materials and listening to podcasts) as well as high-order cognitive skills (i.e. participating in online forums and webinars). The results suggest there is weak evidence of an association between average overall mark in all modules and the level of engagement with self-directed content (P = 0.0187). There is also weak evidence of an association between average overall mark in all modules and the level of engagement in collaborative activities (P < 0.0528). Three major themes emerged from the focus group 1) weekly forums and webinars, 2) self-directed learning materials and 3) learning design and support. Online learning was acceptable and convenient to postgraduate students. These findings are discussed further in the paper as potential predictors of student performance in online programmes.

scholarly journals Theory-based learning analytics to explore student engagement patterns in a peer review activity

2021 ◽  
Author(s):  
Erkan Er ◽  
Cristina Villa-Torrano ◽  
Yannis Dimitriadis ◽  
Dragan Gasevic ◽  
Miguel L. Bote-Lorenzo ◽  
...  
Keyword(s):  
Student Engagement ◽  
Peer Review ◽  
Learning Analytics

Here Be Dragons

Big Data ◽  
2016 ◽  
pp. 1717-1735
Author(s):  
Paul Prinsloo ◽  
Sharon Slade
Keyword(s):  
Higher Education ◽  
Student Engagement ◽  
New Deal ◽  
Learning Analytics ◽  
Higher Education Institutions ◽  
Student Experience ◽  
Open University ◽  
Student Responsibility ◽  
Student Data ◽  
General Data

Learning analytics is an emerging but rapidly growing field seen as offering unquestionable benefit to higher education institutions and students alike. Indeed, given its huge potential to transform the student experience, it could be argued that higher education has a duty to use learning analytics. In the flurry of excitement and eagerness to develop ever slicker predictive systems, few pause to consider whether the increasing use of student data also leads to increasing concerns. This chapter argues that the issue is not whether higher education should use student data, but under which conditions, for what purpose, for whose benefit, and in ways in which students may be actively involved. The authors explore issues including the constructs of general data and student data, and the scope for student responsibility in the collection, analysis and use of their data. An example of student engagement in practice reviews the policy created by the Open University in 2014. The chapter concludes with an exploration of general principles for a new deal on student data in learning analytics.

scholarly journals A Learning Analytics Approach for Student Performance Assessment

2018 ◽  
Vol 10 (4) ◽  
pp. 79-94
Author(s):  
Mohamed H Haggag ◽  
Mahmood Abdel Latif ◽  
Deena Mostafa Helal
Keyword(s):  
Performance Assessment ◽  
Student Performance ◽  
Learning Analytics

Effects of Student Interests on Engagement and Performance in Biomechanics

2020 ◽  
Vol 36 (5) ◽  
pp. 360-367
Author(s):  
Erika M. Pliner ◽  
April A. Dukes ◽  
Kurt E. Beschorner ◽  
Arash Mahboobin
Keyword(s):  
Student Engagement ◽  
Student Performance ◽  
Student Teaching ◽  
Teaching Method ◽  
Underrepresented Students ◽  
Summer Program ◽  
Pedagogical Techniques ◽  
Student Interests ◽  
And Performance ◽  
And Mathematics

There is a need for pedagogical techniques that increase student engagement among underrepresented groups in engineering. Relating engineering content to student interests, particularly through biomechanics applications, shows promise toward engaging a diverse group of students. This study investigates the effects of student interests on engagement and performance in 10th grade students enrolled in a summer program for students underrepresented in the science, technology, engineering, and mathematics fields. The authors assessed the effects of interest-tailored lectures on student engagement and performance in a 5-week program with bioengineering workshops, focusing on the delivery of biomechanics content. A total of 31 students received interest-tailored lectures (intervention) and 23 students received only generic lectures (control) in biomechanics. In addition, the authors assessed the effects of teaching method (lecture, classroom activities, and laboratory tours) on student engagement. The authors found interest-tailored lectures to significantly increase student engagement in lecture compared with generic lectures. Students that received interest-tailored lectures had an insignificant, but meaningful 5% increase in student performance. Students rated laboratory tours higher in engagement than other teaching methods. This study provides detailed examples that can directly assist student teaching and outreach in biomechanics. Furthermore, the pedagogical techniques in this study can be used to increase engagement of underrepresented students in engineering.

scholarly journals Videos in Online Courses

2022 ◽  
Vol 4 (3) ◽  
pp. 94-110
Author(s):  
Eric Litton
Keyword(s):  
Quantitative Analysis ◽  
Student Engagement ◽  
Student Performance ◽  
Online Courses ◽  
Course Content ◽  
Analysis Techniques ◽  
Video Viewing ◽  
Online Videos ◽  
Traditional Setting ◽  
The Relationship

Many instructors use videos to support their teaching in online courses to convey course content that would normally be taught in a traditional setting. Prior studies have shown some connection between utilizing online videos and student performance but do not always support their finding statistically or consider the nuance of the online videos, such as if the videos are required and how long the videos are. This article uses various quantitative analysis techniques to investigate the relationship between video length, student video viewing patterns, and grades. The findings indicate that videos should stay within a certain length to encourage student engagement with the videos and course assignments. Also, watching online videos is only positively related to grades when students are not required to watch, a result that is consistent across course-level and student-level models. Student viewing patterns also differ for courses that require watching videos versus those that do not. The article concludes by discussing the relevance of these results and how instructors can best utilize online videos in their courses.

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