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Nasheen Nur – ProQuest LLC, 2021
The main goal of learning analytics and early detection systems is to extract knowledge from student data to understand students' trends of activities towards success and risk and design intervention methods to improve learning performance and experience. However, many factors contribute to the challenge of designing and building effective…
Descriptors: Artificial Intelligence, Undergraduate Students, Learning Analytics, Time Factors (Learning)
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Lenhart, Cindy; Bouwma-Gearhart, Jana – Education Sciences, 2021
This paper explores the affordances and constraints of STEM faculty members' instructional data-use practices and how they engage students (or not) in reflection around their own learning data. We found faculty used a wide variety of instructional data-use practices. We also found several constraints that influenced their instructional data-use…
Descriptors: STEM Education, Data Use, Reflection, College Faculty
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Han, Jeongyun; Huh, Sun Young; Cho, Young Hoan; Park, SoHyun; Choi, Jinhan; Suh, Bongwon; Rhee, Wonjong – Educational Technology Research and Development, 2020
This study investigates the possibility of utilizing online learning data to design face-to-face activities in a flipped classroom. We focus on heterogeneous group formation for effective collaborative learning. Fifty-three undergraduate students (18 males, 35 females) participated in this study, and 8 students (3 males, 5 females) among them…
Descriptors: Electronic Learning, Learning Analytics, Data Use, Synchronous Communication
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Judy Shih, Hui-chia – Innovation in Language Learning and Teaching, 2021
This paper attempts to investigate and compare two forms of learning logs using Google Sheets -- individual and collaborative learning logs -- and their effect on EFL university students' development of learner autonomy over the course of a semester. Subjects were 62 EFL learners from an intact English elective course at a private university in…
Descriptors: Cooperative Learning, Learning Analytics, Data Use, Personal Autonomy
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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
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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
Hewitt, Rachel; Natzler, Michael – Higher Education Policy Institute, 2019
Higher education institutions collect and hold huge amounts of data on students, whether for regulatory purposes or to gather information about students' experiences. In this report we explore students views on data security, learning analytics and the information universities hold and share on students' health and wellbeing. [This report was…
Descriptors: Information Security, Student Attitudes, Young Adults, Learning Analytics