NotesFAQContact Us
Collection
Advanced
Search Tips
What Works Clearinghouse Rating
Showing 1,231 to 1,245 of 1,732 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Cohausz, Lea – Journal of Educational Data Mining, 2022
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…
Descriptors: Guidelines, Academic Achievement, Dropouts, Prediction
Peer reviewed Peer reviewed
Direct linkDirect link
Saqr, Mohammed; Jovanovic, Jelena; Viberg, Olga; Gaševic, Dragan – Studies in Higher Education, 2022
Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…
Descriptors: Meta Analysis, Learning Analytics, Predictor Variables, Correlation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Bozkurt, Aras – Journal of Interactive Media in Education, 2022
The blending learning model, a combination of onsite and online learning modalities formulated by relevant pedagogies, modalities, and technologies, offers learning experiences that involve the different factors shaping each modality, such as time, space, path, and pace, through sequential or parallel designs. In its relatively short history, this…
Descriptors: Blended Learning, Teaching Methods, Interdisciplinary Approach, Research Reports
Peer reviewed Peer reviewed
Direct linkDirect link
Sibgatullina, Alfiya; Ivanova, Rimma; Yushchik, Elena – International Journal of Web-Based Learning and Teaching Technologies, 2022
The current study examines Moodle learning management system as an effective tool for implementing the innovation policy of the university. For this, the following methods are employed: (1) monitoring of the Best Global Universities 2020 ranking results in the context of Moodle web-analytics; (2) evaluation of advantages attributed to innovative…
Descriptors: Integrated Learning Systems, Technology Uses in Education, Program Implementation, Educational Innovation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Chang, Li-ping; Chou, Chun-Ting – Research-publishing.net, 2022
In this study, we held a 12-hour workshop focused on training the Data-Driven Learning (DDL) approach for in-service Chinese teachers aiming to implement this pedagogy in Mandarin Chinese classrooms in the future. We analyzed data from a postworkshop questionnaire to understand how the individual-level traits of Chinese teachers (such as their…
Descriptors: Faculty Development, Language Teachers, Second Language Learning, Second Language Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Dooley, Laura; Makasis, Nikolas – Education Sciences, 2020
The flipped classroom has been increasingly employed as a pedagogical strategy in the higher education classroom. This approach commonly involves pre-class learning activities that are delivered online through learning management systems that collect learning analytics data on student access patterns. This study sought to utilize learning…
Descriptors: Student Behavior, Flipped Classroom, Learning Analytics, Data Interpretation
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Salas-Pilco, Sdenka Zobeida; Yang, Yuqin – British Journal of Educational Technology, 2020
This study presents several Latin American research initiatives in the field of learning analytics (LA). The study's purpose is to enhance awareness and understanding of LA among researchers, practitioners and decision makers, and to highlight the importance of supporting research on LA. We analyzed case studies of LA research conducted at four…
Descriptors: Learning Analytics, Latin Americans, Educational Research, Decision Making
Peer reviewed Peer reviewed
Direct linkDirect link
Brown, Michael – Teaching in Higher Education, 2020
Despite their increasingly widespread adoption in post-secondary education, scholars and practitioners know very little about the impact of digital data displays on instructors' sense-making and academic planning. In this manuscript, I report the results of comparative case studies of five different introductory physics instructors at three…
Descriptors: College Faculty, Learning Analytics, Introductory Courses, Physics
Peer reviewed Peer reviewed
Direct linkDirect link
Demmans Epp, Carrie; Phirangee, Krystle; Hewitt, Jim; Perfetti, Charles A. – Educational Technology Research and Development, 2020
From massive open online courses (MOOC) to the smaller scale use of learning management systems, many students interact with online platforms that are meant to support learning. Investigations into the use of these systems have considered how well students learn when certain approaches are employed. However, we do not fully understand how course…
Descriptors: Integrated Learning Systems, Student Experience, Learning Analytics, Online Courses
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Bailie, Jeffrey L. – Journal of Instructional Pedagogies, 2020
For close to three decades. the positive effects of online learner engagement in asynchronous discussions have been reported. Given the many positive effects of asynchronous discussion that have been conveyed in the literature, a preponderance of today's online courses include the activity as a part of the learning experience. It seems only…
Descriptors: Learning Analytics, Asynchronous Communication, Predictor Variables, Grades (Scholastic)
Peer reviewed Peer reviewed
Direct linkDirect link
Chen, Chen; Sonnert, Gerhard; Sadler, Philip M.; Sasselov, Dimitar D.; Fredericks, Colin; Malan, David J. – Distance Education, 2020
Participants' engagement in massive online open courses (MOOCs) is highly irregular and self-directed. It is well known in the field of television media that substantial parts of the audience tend to drop out at major episodic, or seasonal, closures, which makes creating cliff-hangers a crucial strategy to retain viewers (Bakker, 1993; Cazani,…
Descriptors: Online Courses, Dropouts, Learning Analytics, Dropout Rate
Peer reviewed Peer reviewed
Direct linkDirect link
Huang, Anna Y. Q.; Lu, Owen H. T.; Huang, Jeff C. H.; Yin, C. J.; Yang, Stephen J. H. – Interactive Learning Environments, 2020
In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…
Descriptors: Academic Achievement, Data Use, Learning Analytics, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
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
Pages: 1  |  ...  |  79  |  80  |  81  |  82  |  83  |  84  |  85  |  86  |  87  |  ...  |  116