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Francis, Mary – ProQuest LLC, 2023
Learning analytics are starting to become standardized in higher education as institutions use the techniques of Big Data analytics to make decisions to help them reach their goals. The widespread use of student information brings forth ethical concerns primarily in relation to privacy. While the overarching ethical issues related to learning…
Descriptors: Learning Analytics, College Students, Privacy, Ethics
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Zamecnik, Andrew; Kovanovíc, Vitomir; Joksimovíc, Srécko; Grossmann, Georg; Ladjal, Djazia; Marshall, Ruth; Pardo, Abelardo – Journal of Computer Assisted Learning, 2023
Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…
Descriptors: Data Use, Group Dynamics, College Students, Cooperative Learning
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Earl H. McKinney Jr.; Simon Ginzinger – Journal of Information Systems Education, 2024
The growing use of analytics has increased the demand for more highly data literate graduates. Awareness of ambiguity in data has been suggested as a new data literacy skill. Here, we describe a student-centered semester-long project that can be used to teach this skill in an introductory analytics or database course. The project requires students…
Descriptors: Student Centered Learning, Student Projects, Consciousness Raising, Ambiguity (Context)
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Tal Soffer; Anat Cohen – Australasian Journal of Educational Technology, 2024
The rapid recent use of learning analytics (LA) in higher education, specifically during the COVID-19 pandemic, allows the monitoring of users' behavior while learning. Using LA may promote students' learning outcomes but also intrude into their privacy. This study aimed to explore students' behaviour and perceptions towards privacy and data…
Descriptors: Privacy, Educational Practices, College Students, Student Attitudes
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West, Paige; Paige, Frederick; Lee, Walter; Watts, Natasha; Scales, Glenda – Journal of Civil Engineering Education, 2022
The expansion of online learning in higher education has both contributed to researchers exploring innovative ways to develop learning environments and created challenges in identifying student interactions with course material. Learning analytics is an emerging field that can identify student interactions and help make data-informed course design…
Descriptors: Learning Analytics, Student Attitudes, Electronic Learning, Construction Management
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Ana Stojanov; Ben Kei Daniel – Education and Information Technologies, 2024
The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…
Descriptors: Higher Education, Learning Analytics, Well Being, Decision Making
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Tomás Bautista-Godínez; Gerardo Castañeda-Garza; Ricardo Pérez Mora; Hector G. Ceballos; Verónica Luna de la Luz; J. Gerardo Moreno-Salinas; Irma Rocío Zavala-Sierra; Roberto Santos-Solórzano; Carlos Iván Moreno Arellano; Melchor Sánchez-Mendiola – Journal of Learning Analytics, 2024
The adoption of learning analytics (LA) in higher education institutions (HEIs) in Mexico is still at an early stage despite increasing global interest and advances in the field. The use of educational data remains a challenging puzzle for many universities, which strive to provide students, teachers, and institutional administrators with…
Descriptors: Foreign Countries, Learning Analytics, Universities, Program Implementation
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Li, Warren; Sun, Kaiwen; Schaub, Florian; Brooks, Christopher – International Journal of Artificial Intelligence in Education, 2022
Use of university students' educational data for learning analytics has spurred a debate about whether and how to provide students with agency regarding data collection and use. A concern is that students opting out of learning analytics may skew predictive models, in particular if certain student populations disproportionately opt out and biases…
Descriptors: College Students, Learning Analytics, Student Attitudes, Informed Consent
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Mahmoud, Mai; Dafoulas, Georgios; Abd ElAziz, Rasha; Saleeb, Noha – International Journal of Information and Learning Technology, 2021
Purpose: The objective of this paper is to present a comprehensive review of the literature on learning analytics (LA) stakeholders' expectations to reveal the status of ongoing research in this area and to highlight gaps in research. Design/methodology/approach: Conducting a literature review is a well-known method to establish knowledge and…
Descriptors: Learning Analytics, Stakeholders, Expectation, Higher Education
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Zhao, Qun; Wang, Jin-Long; Pao, Tsang-Long; Wang, Li-Yu – Journal of Educational Technology Systems, 2020
This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…
Descriptors: Classification, Learning, Accuracy, Prediction
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Yürüm, Ozan Rasit; Taskaya-Temizel, Tugba; Yildirim, Soner – Education and Information Technologies, 2023
Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…
Descriptors: Video Technology, Educational Technology, Learning Management Systems, Data Collection
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Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
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Yury Rishko; Diana Boboshko; Evgeniya Eliseeva; Aleksandr Malkin; Dmitrii Treistar – SAGE Open, 2025
Discussion of the effectiveness of distance learning as a means of delivering higher education programs at classical universities has been ongoing for the past decade. The article presents the findings of a study of changes in academic performance of university students, covering the period from fall 2018 to fall 2023. This period included a rapid…
Descriptors: Outcomes of Education, Educational Change, Electronic Learning, Online Courses
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Ladino Nocua, Andrea Catalina; Cruz Gonzalez, Joan Paola; Castiblanco Jimenez, Ivonne Angelica; Gomez Acevedo, Juan Sebastian; Marcolin, Federica; Vezzetti, Enrico – Education Sciences, 2021
Student engagement allows educational institutions to make better decisions regarding teaching methodologies, methods for evaluating the quality of education, and ways to provide timely feedback. Due to the COVID-19 pandemic, identifying cognitive student engagement in distance learning has been a challenge in higher education institutions. In…
Descriptors: Learner Engagement, Cognitive Processes, Metabolism, Physiology
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Travis, Tiffini A.; Ramirez, Christian – portal: Libraries and the Academy, 2020
Libraries remain one of the last places on campus where the purging of usage data is encouraged and "tracking" is a dirty word. While some libraries have demonstrated the usefulness of analytics, opponents bring up issues of privacy and debate the feasibility of student-generated library data for planning and assessment. Using a study…
Descriptors: Academic Libraries, Data Collection, Learning Analytics, Ethics
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