scholarly journals Predicting At-Risk Students Using Clickstream Data in the Virtual Learning Environment

2019 ◽  
Vol 11 (24) ◽  
pp. 7238 ◽  
Author(s):  
Naif Radi Aljohani ◽  
Ayman Fayoumi ◽  
Saeed-Ul Hassan
Keyword(s):  
Higher Education ◽  
At Risk ◽  
Learning Environment ◽  
Short Term Memory ◽  
At Risk Students ◽  
Virtual Learning ◽  
Classification Problem ◽  
Virtual Learning Environment ◽  
Clickstream Data ◽  
Education Decision

In higher education, predicting the academic performance of students is associated with formulating optimal educational policies that vehemently impact economic and financial development. In online educational platforms, the captured clickstream information of students can be exploited in ascertaining their performance. In the current study, the time-series sequential classification problem of students’ performance prediction is explored by deploying a deep long short-term memory (LSTM) model using the freely accessible Open University Learning Analytics dataset. In the pass/fail classification job, the deployed LSTM model outperformed the state-of-the-art approaches with 93.46% precision and 75.79% recall. Encouragingly, our model superseded the baseline logistic regression and artificial neural networks by 18.48% and 12.31%, respectively, with 95.23% learning accuracy. We demonstrated that the clickstream data generated due to the students’ interaction with the online learning platforms can be evaluated at a week-wise granularity to improve the early prediction of at-risk students. Interestingly, our model can predict pass/fail class with around 90% accuracy within the first 10 weeks of student interaction in a virtual learning environment (VLE). A contribution of our research is an informed approach to advanced higher education decision-making towards sustainable education. It is a bold effort for student-centric policies, promoting the trust and the loyalty of students in courses and programs.

scholarly journals Engaging Virtual Learning Environment System to Enhance Communication and Collaboration Skills among ASEAN Higher Education Learners

2016 ◽  
Vol 11 (04) ◽  
pp. 103 ◽  
Author(s):  
Jintavee Khlaisang ◽  
Kemmanat Mingsiritham
Keyword(s):  
Higher Education ◽  
Literature Review ◽  
Learning Environment ◽  
Undergraduate Students ◽  
21St Century ◽  
Virtual Learning ◽  
Virtual Learning Environment ◽  
Learning Activity ◽  
Cultural Community ◽  
Collaboration Skills

The study aims to design and develop a Virtual Learning Environment (VLE) system to enhance the communication and collaboration skills of higher education learners in the ASEAN cultural community. The system was developed based on a literature review of ASEAN to identity its educational goals for 2015, as well as the subjects of open learning, VLE, active learning, activity based learning, ASEAN cultural community, and collaboration and communication skills in 21st century. The results of the literature review were developed into a questionnaire for 400 higher education instructors. The survey results were then tabulated using G* Power and were analyzed using Exploratory Factor Analysis (EFA) to find the core elements to be developed to be an appropriate VLE system. The resulting system was tested using a sample group of 30 volunteer undergraduate students from 5 ASEAN member countries. Data analysis using t-test dependent indicated that there was statistical difference between pre and post self-assessment scores of the 21st century skills in communication and collaboration at a 0.05 level of significance. The result was consistent with the results of behavior and trace observations and the quality of project assignments produced using the system. The system developed consisted of four elements was approved by experts in the education field.

Analysis of engagement metrics vs student attainment using multiple sources across physical and virtual spaces: A case study.

2020 ◽  
Author(s):  
Caudia Wascher ◽  
Isobel Gowers ◽  
Matt East
Keyword(s):  
Higher Education ◽  
Learning Environment ◽  
Learning Analytics ◽  
Higher Education Institutions ◽  
Virtual Learning ◽  
Individual Learning ◽  
Virtual Learning Environment ◽  
Multiple Sources ◽  
Student Behaviour

Learning analytics, referring to the collection and analysis of data regarding the progress of learners, allows higher education institutions and individual academics to make data driven decisions regarding their teaching approaches and support they are providing. Further, they provide students with an opportunity to take control of their own learning, as they are gaining a better understanding of their own performance and can make informed decisions about their own learning progress. In early 2020 a global pandemic forced higher education institutions worldwide to quickly move teaching online. We argue that under these circumstances, detailed learning analytics provide a unique opportunity to understand student behaviour and support individual learning. We present a case study analysing engagement metrics and their relationship to student attainment in four courses in the area of behavioural biology, over a time period of two years pre-pandemic. Multiple sources of student engagement in the physical (attendance at lectures) and virtual space (access and engagement with online learning resources) were used. Our results show that grades of students were significantly affected by type of assignment, with grades being lower in exams compared to other types of assignment. Grades were not significantly affected by level of studies, gender and country of origin (UK versus non-UK). With regards to engagement metrics, grades significantly increased with percentage of attendance in class, percentage of resources accessed on Canvas and library access. Students accessed lecture notes longer compared to other resources. Physical attendance in class over all courses and levels of studies averaged at 55 %. Online, students accessed on average only 32 % of resources provided in the virtual learning environment. Students accessed the majority of the courses in the same week when materials were discussed in class compared to the weeks before and after. Our results show that both engagement with materials in the virtual learning environment and attendance in class are positively correlated with student achievement. We cannot make any inferences about the causality of this effect and it is likely that better students in general are more engaged. Our project provides detailed in-depth insight into student behaviour and reveals that students overall do not engage with all materials provided, resulting in an incomplete learning experience. We suggest that detailed data on engagement of students with individual resources can be used to better understand and shape individual learning experiences of students.

scholarly journals A peer-observation initiative to enhance student engagement in the synchronous virtual classroom: A case study of a COVID-19 mandated move to online learning

2021 ◽  
Vol 18 (4) ◽  
pp. 184-205
Author(s):  
Lesley Andrew ◽  
◽  
Ruth Wallace ◽  
Ros Sambell ◽  
◽  
...  
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Student Engagement ◽  
Learning Environment ◽  
Teaching And Learning ◽  
Virtual Learning ◽  
Virtual Learning Environment ◽  
Peer Observation ◽  
Learning And Teaching

The global COVID-19 pandemic has necessitated a rapid shift to online delivery in higher education. This learning and teaching environment is associated with reduced student engagement, a crucial prerequisite of student satisfaction, retention and success. This paper presents a case study that explored student engagement in the synchronous virtual learning environment, during the mandatory move to exclusive online learning in Australian higher education in April to June 2020. Three university instructors used the Teaching and Learning Circles Model to observe a series of their peers' synchronous virtual classrooms, from which they reflected on ways to enhance their own practice. The findings demonstrate how student engagement in these classrooms can be strengthened across the four constructs of Kahu and Nelson’s (2018) engagement conceptual framework: belonging; emotional response; wellbeing and self-efficacy. The case study also reveals limitations of the synchronous virtual environment as a means of supporting student engagement in the online learning and teaching environment, and proposes ways to address them. Against emerging reports of increased mental health issues among isolated university students during the current pandemic, the case study's recommendations to improve student wellbeing and belonging are particularly salient. This article also highlights the usefulness of the Teaching and Learning Circles Model of peer observation as a way to guide its participants' reflections on their own practice, support their collegiality with academic peers and build their confidence and competence in the synchronous virtual learning environment.

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