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Kelly Linden; Neil van der Ploeg; Noelia Roman – Journal of Higher Education Policy and Management, 2023
There is a small window of opportunity at the beginning of semester for a university to provide commencing students with timely and targeted support. However, there is limited information available on interventions that identify and support disengaged students from equity groups without using equity group status as the basis for the contact. The…
Descriptors: Learner Engagement, Identification, Intervention, Learning Analytics
Ahammed, Faisal; Smith, Elizabeth – Education Sciences, 2019
An association between students' learn-online engagement and academic performance was investigated for a third-year Water Resources Systems Design course at the University of South Australia in 2017. As the patterns of data were non-parametric, Mann-Whitney and Kruskal-Wallis tests were performed using SPSS. It was revealed from the test results…
Descriptors: Foreign Countries, Water, Engineering Education, Academic Achievement
Wells, Jason; Spence, Aaron; McKenzie, Sophie – Journal of Information Technology Education: Research, 2021
Aim/Purpose: This paper focuses on understanding undergraduate computing student-learning behaviour through reviewing their online activity in a university online learning management system (LMS), along with their grade outcome, across three subjects. A specific focus is on the activity of students who failed the computing subjects. Background:…
Descriptors: Student Participation, Undergraduate Students, At Risk Students, Academic Failure
Khosravi, Hassan; Shabaninejad, Shiva; Bakharia, Aneesha; Sadiq, Shazia; Indulska, Marta; Gasevic, Dragan – Journal of Learning Analytics, 2021
Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…
Descriptors: Learning Analytics, Visual Aids, Artificial Intelligence, Information Retrieval
Iraj, Hamideh; Fudge, Anthea; Khan, Huda; Faulkner, Margaret; Pardo, Abelardo; Kovanovic, Vitomir – Journal of Learning Analytics, 2021
One of the major factors affecting student learning is feedback. Although the importance of feedback has been recognized in educational institutions, dramatic changes--such as bigger class sizes and a more diverse student population--challenged the provision of effective feedback. In light of these changes, educators have increasingly been using…
Descriptors: Learner Engagement, Learning Analytics, Feedback (Response), Class Size
West, Deborah; Luzeckyj, Ann; Searle, Bill; Toohey, Danny; Vanderlelie, Jessica; Bell, Kevin R. – Australasian Journal of Educational Technology, 2020
This article reports on a study exploring student perspectives on the collection and use of student data for learning analytics. With data collected via a mixed methods approach from 2,051 students across six Australian universities, it provides critical insights from students as a key stakeholder group. Findings indicate that while students are…
Descriptors: Stakeholders, Undergraduate Students, Graduate Students, Student Attitudes
Baker, Sally; Field, Caitlin; Lee, Jung-Sook; Saintilan, Nicole – Journal of University Teaching and Learning Practice, 2021
While embedding Academic Language and Literacies (ALL) instruction in discipline-specific courses is known to be effective, it is difficult to enact across the siloed university. Moreover, the move to online/ remote delivery during COVID-19 has necessitated greater focus on the development of online supports. This article reports on an effort to…
Descriptors: COVID-19, Pandemics, Electronic Learning, Video Technology
Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Fudge, Anthea; Pardo, Abelardo; Gentili, Sheridan – Australasian Journal of Educational Technology, 2020
Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students' sense-making of…
Descriptors: Individualized Instruction, Learning Analytics, Data Collection, Student Attitudes
Prestigiacomo, Rita; Hunter, Jane; Knight, Simon; Martinez Maldonado, Roberto; Lockyer, Lori – Australasian Journal of Educational Technology, 2020
Data about learning can support teachers in their decision-making processes as they design tasks aimed at improving student educational outcomes. However, to achieve systemic impact, a deeper understanding of teachers' perspectives on, and expectations for, data as evidence is required. It is critical to understand how teachers' actions align with…
Descriptors: Preservice Teachers, Preservice Teacher Education, Elementary Secondary Education, Undergraduate Students
Dart, Sarah; Spratt, Belinda – Student Success, 2021
Widening participation initiatives in higher education have grown overall student numbers while also increasing the diversity of student cohorts. Consequently, enhancing student experiences and outcomes has become increasingly challenging. This study implemented personalised emails in two first-year mathematics courses as a scalable strategy for…
Descriptors: Mathematics Instruction, Electronic Mail, Comparative Analysis, Mathematics Achievement