NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Teachers1
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing all 8 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
Peer reviewed Peer reviewed
Direct linkDirect link
Viberg, Olga; Engström, Linda; Saqr, Mohammed; Hrastinski, Stefan – Education and Information Technologies, 2022
In order to successfully implement learning analytics (LA), we need a better understanding of student expectations of such services. Yet, there is still a limited body of research about students' expectations across countries. Student expectations of LA have been predominantly examined from a view that perceives students as a group of individuals…
Descriptors: Learning Analytics, Student Attitudes, Expectation, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
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)
Peer reviewed Peer reviewed
Direct linkDirect link
Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Peer reviewed Peer reviewed
Direct linkDirect link
Mutimukwe, Chantal; Viberg, Olga; Oberg, Lena-Maria; Cerratto-Pargman, Teresa – British Journal of Educational Technology, 2022
Understanding students' privacy concerns is an essential first step toward effective privacy-enhancing practices in learning analytics (LA). In this study, we develop and validate a model to explore the students' privacy concerns (SPICE) regarding LA practice in higher education. The SPICE model considers "privacy concerns" as a central…
Descriptors: Privacy, Learning Analytics, Student Attitudes, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
Forsyth, Carol M.; Graesser, Arthur; Millis, Keith – Technology, Knowledge and Learning, 2020
The current study investigated predictors of shallow versus deep learning within a serious game known as Operation ARA. This game uses a myriad of pedagogical features including multiple-choice tests, adaptive natural language tutorial conversations, case-based reasoning, and an E-text to engage students. The game teaches 11 topics in research…
Descriptors: Educational Games, Predictor Variables, Evidence Based Practice, Learning Analytics
Peer reviewed Peer reviewed
Direct linkDirect link
Jongile, Sonwabo – International Journal on E-Learning, 2022
The identification of predictor variables for students at-risk of dropping out of university has received increased attention in higher education settings internationally concerning the context of origin in which they are developed and the different academic context in which they are introduced, often lacking schema-theoretic perspectives to offer…
Descriptors: Predictor Variables, At Risk Students, Potential Dropouts, College Students
Morenike Adebodun – ProQuest LLC, 2020
The purpose of this study was to examine the predictive power of Academic and Learning Analytics models on the persistence, retention, and graduation rates for students enrolled in higher education institutions in the United States. Specifically, this study is concerned with the relationships between the present usage of Academic and Learning…
Descriptors: Predictor Variables, Learning Analytics, Academic Achievement, Higher Education