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Mustafa Tepgec; Joana Heil; Dirk Ifenthaler – Assessment & Evaluation in Higher Education, 2025
Despite the widespread implementation of learning analytics (LA)-based feedback systems, there exists a gap in empirical investigations regarding their influence on learning outcomes. Moreover, existing research primarily focuses on individual differences, such as self-regulation and motivation, overlooking the potential of feedback literacy (FL).…
Descriptors: Feedback (Response), Learning Analytics, Outcomes of Education, Transfer of Training
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Tormey, Roland; Hardebolle, Cécile; Pinto, Francisco; Jermann, Patrick – Assessment & Evaluation in Higher Education, 2020
Although it is frequently claimed that learning analytics can improve self-evaluation and self-regulated learning by students, most learning analytics tools appear to have been developed as a response to existing data rather than with a clear pedagogical model. As a result there is little evidence of impact on learning. Even fewer learning…
Descriptors: Design, Learning Analytics, Self Evaluation (Individuals), Student Evaluation
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Er, Erkan; Dimitriadis, Yannis; Gaševic, Dragan – Assessment & Evaluation in Higher Education, 2021
Although dialogue can augment the impact of feedback on student learning, dialogic feedback is unaffordable by instructors teaching large classes. In this regard, peer feedback can offer a scalable and effective solution. However, the existing practices optimistically rely on students' discussion about feedback and lack a systematic design…
Descriptors: Cooperative Learning, Peer Evaluation, Feedback (Response), Learning Analytics
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Zheng, Lanqin; Zhong, Lu; Niu, Jiayu – Assessment & Evaluation in Higher Education, 2022
Learning analytics has been widely used in the field of education. Most studies have adopted a learning analytics dashboard to present data on learning processes or learning outcomes. However, only presenting learning analytics results was not sufficient and lacked personalised feedback. In response to these gaps, this study proposed a learning…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Feedback (Response)
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Barthakur, Abhinava; Joksimovic, Srecko; Kovanovic, Vitomir; Corbett, Frederique C.; Richey, Michael; Pardo, Abelardo – Assessment & Evaluation in Higher Education, 2022
The success and satisfaction of students with online courses is significantly impacted by the sequencing of learning objectives and activities. Equally critical is designing online degree programs and structuring multiple courses to reduce learners' cognitive load and attain maximum learning success. In its current form, the evaluation of program…
Descriptors: Sequential Approach, Course Objectives, Behavioral Objectives, Online Courses
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Summers, Robert J.; Higson, Helen E.; Moores, Elisabeth – Assessment & Evaluation in Higher Education, 2021
Effective use of learning analytics systems has been purported to confer various benefits to learners in terms of both attainment and retention. There is, however, little agreement on which data are meaningful or useful. Whilst measures of engagement might correlate with outcomes, thereby retrospectively 'predicting' them, there are fewer studies…
Descriptors: Learner Engagement, Learning Analytics, College Freshmen, Undergraduate Study
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Cormack, Sophie H.; Eagle, Laurence A.; Davies, Mark S. – Assessment & Evaluation in Higher Education, 2020
Many studies have found a relationship between students' self-reported procrastination and their grades. Few studies have used learning analytic data as a behavioural measure of procrastination in order to predict performance, and there is no systematic research on how this relationship may differ across assessments or disciplines. In this study…
Descriptors: Correlation, Time Management, Academic Achievement, Grades (Scholastic)
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Summers, Robert; Higson, Helen; Moores, Elisabeth – Assessment & Evaluation in Higher Education, 2023
The pandemic forced many education providers to pivot rapidly their models of education to increased online provision, raising concerns that this may accentuate effects of digital poverty on education. Digital footprints created by learning analytics systems contain a wealth of information about student engagement. Combining these data with…
Descriptors: Disadvantaged, Learner Engagement, COVID-19, Pandemics
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Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Pardo, Abelardo; Fudge, Anthea; Gentili, Sheridan – Assessment & Evaluation in Higher Education, 2021
Research and development in learning analytics has established viable solutions for scaling personalised feedback to all students. However, questions remain regarding how such feedback is perceived, interpreted and acted upon by stakeholders. The present study reports on the analysis of focus group data from four courses to understand students'…
Descriptors: Student Attitudes, College Students, Emotional Response, Individualized Instruction
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Tsai, Yi-Shan; Perrotta, Carlo; Gaševic, Dragan – Assessment & Evaluation in Higher Education, 2020
The emergence of personalised data technologies such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related…
Descriptors: Student Empowerment, Equal Education, Learning Analytics, Accountability
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Foster, Ed; Siddle, Rebecca – Assessment & Evaluation in Higher Education, 2020
In this article we investigate the effectiveness of learning analytics for identifying at-risk students in higher education institutions using data output from an in-situ learning analytics platform. Amongst other things, the platform generates 'no-engagement' alerts if students have not engaged with any of the data sources measured for 14…
Descriptors: Learning Analytics, At Risk Students, Identification, Higher Education
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Foster, Carly; Francis, Peter – Assessment & Evaluation in Higher Education, 2020
This is a systematic review conducted of primary research literature published between 2007 and 2018 on the deployment and effectiveness of data analytics in higher education to improve student outcomes. We took a methodological approach to searching databases; appraising and synthesising results against predefined criteria. We reviewed research…
Descriptors: Literature Reviews, Program Implementation, Program Effectiveness, Learning Analytics
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Tempelaar, Dirk – Assessment & Evaluation in Higher Education, 2020
How can we best facilitate students most in need of learning support, entering a challenging quantitative methods module at the start of their bachelor programme? In this empirical study into blended learning and the role of assessment for and as learning, we investigate learning processes of students with different learning profiles.…
Descriptors: Learning Analytics, Formative Evaluation, Blended Learning, Undergraduate Students
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Broughan, Christine; Prinsloo, Paul – Assessment & Evaluation in Higher Education, 2020
Student data, whether in the form of engagement data, assignments or examinations, form the foundation for assessment and evaluation in higher education. As higher education institutions progressively move to blended and online environments, we have access to, not only more data than before, but also a greater variety of demographic and…
Descriptors: Learning Analytics, Student Centered Learning, Student Empowerment, Data Collection
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Monbec, Laetitia; Tilakaratna, Namala; Brooke, Mark; Lau, Siew Tiang; Chan, Yah Shih; Wu, Vivien – Assessment & Evaluation in Higher Education, 2021
This paper reports on an interdisciplinary pedagogical research project involving academic literacy experts and lecturers at a School of Nursing. Specifically, the paper focusses on the development of a data-driven analytical rubric to teach and assess critical reflections in year-one nursing. The purpose of the project was to support the teaching…
Descriptors: Interdisciplinary Approach, Nursing Education, Literacy, Academic Language
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