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Gerardo Ibarra-Vazquez; Maria Soledad Ramirez-Montoya; Mariana Buenestado-Fernandez – IEEE Transactions on Learning Technologies, 2024
This article aims to study the performance of machine learning models in forecasting gender based on the students' open education competency perception. Data were collected from a convenience sample of 326 students from 26 countries using the eOpen instrument. The analysis comprises 1) a study of the students' perceptions of knowledge, skills, and…
Descriptors: Gender Differences, Open Education, Cross Cultural Studies, Student Attitudes
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Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
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Jonathan K. Foster; Peter Youngs; Rachel van Aswegen; Samarth Singh; Ginger S. Watson; Scott T. Acton – Journal of Learning Analytics, 2024
Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…
Descriptors: Learning Analytics, Automation, Classification, Artificial Intelligence
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David P. Reid; Timothy D. Drysdale – IEEE Transactions on Learning Technologies, 2024
The designs of many student-facing learning analytics (SFLA) dashboards are insufficiently informed by educational research and lack rigorous evaluation in authentic learning contexts, including during remote laboratory practical work. In this article, we present and evaluate an SFLA dashboard designed using the principles of formative assessment…
Descriptors: Learning Analytics, Laboratory Experiments, Electronic Learning, Feedback (Response)
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Weidlich, Joshua; Gaševic, Dragan; Drachsler, Hendrik – Journal of Learning Analytics, 2022
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…
Descriptors: Causal Models, Inferences, Learning Analytics, Comparative Analysis
Heeryung Choi – ProQuest LLC, 2022
Learning analytics researchers have been diligently integrating trace data to study Self-Regulated Learning (SRL). Compared to traditionally used survey data, trace data, such as log or clickstream data designed and interpreted to understand a certain SRL construct, are considered to be more effective in capturing dynamic SRL as fine-grained…
Descriptors: Learning Analytics, Metacognition, Validity, Comparative Analysis
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Shou, Tianze; Borchers, Conrad; Karumbaiah, Shamya; Aleven, Vincent – International Educational Data Mining Society, 2023
Spatial analytics receive increased attention in educational data mining. A critical issue in stop detection (i.e., the automatic extraction of timestamped and located stops in the movement of individuals) is a lack of validation of stop accuracy to represent phenomena of interest. Next to a radius that an actor does not exceed for a certain…
Descriptors: Classroom Design, Accuracy, Validity, Space Utilization
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Kim, Yoon Jeon; Knowles, Mariah A.; Scianna, Jennifer; Lin, Grace; Ruipérez-Valiente, José A. – British Journal of Educational Technology, 2023
Game-based assessment (GBA), a specific application of games for learning, has been recognized as an alternative form of assessment. While there is a substantive body of literature that supports the educational benefits of GBA, limited work investigates the validity and generalizability of such systems. In this paper, we describe applications of…
Descriptors: Learning Analytics, Validity, Generalizability Theory, Game Based Learning
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Flora Ji-Yoon Jin; Bhagya Maheshi; Roberto Martinez-Maldonado; Dragan Gasevic; Yi-Shan Tsai – Journal of Learning Analytics, 2024
Feedback is essential in learning. The emerging concept of feedback literacy underscores the skills students require for effective use of feedback. This highlights students' responsibilities in the feedback process. Yet, there is currently a lack of mechanisms to understand how students make sense of feedback and whether they act on it. This gap…
Descriptors: Scaffolding (Teaching Technique), Feedback (Response), Learning Analytics, Literacy
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Martinez-Maldonado, Roberto; Gaševic, Dragan; Echeverria, Vanessa; Fernandez Nieto, Gloria; Swiecki, Zachari; Buckingham Shum, Simon – Journal of Learning Analytics, 2021
Using data to generate a deeper understanding of collaborative learning is not new, but automatically analyzing log data has enabled new means of identifying key indicators of effective collaboration and teamwork that can be used to predict outcomes and personalize feedback. Collaboration analytics is emerging as a new term to refer to…
Descriptors: Learning Analytics, Cooperative Learning, Validity, Case Studies
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Aaron Bere; Patrick Chirilele; Rugare Chitiga – International Association for Development of the Information Society, 2022
The purpose of this paper is to present an empirical investigation of the critical determinants for the adoption of learning analytics in higher education. A conceptual model was proposed to understand better the adoption of learning analytics in higher education by teaching staff. Structural equation modelling is used for testing and validating…
Descriptors: Learning Analytics, Validity, Research Methodology, Higher Education
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Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
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Beasley, Zachariah J.; Piegl, Les A.; Rosen, Paul – IEEE Transactions on Learning Technologies, 2021
Accurately grading open-ended assignments in large or massive open online courses is nontrivial. Peer review is a promising solution but can be unreliable due to few reviewers and an unevaluated review form. To date, no work has leveraged sentiment analysis in the peer-review process to inform or validate grades or utilized aspect extraction to…
Descriptors: Case Studies, Online Courses, Assignments, Peer Evaluation
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Barragán, Sandra; González, Leandro; Calderón, Gloria – Interchange: A Quarterly Review of Education, 2022
A combination of mathematical and statistical modelling techniques may be used to analyse student dropout behaviour. The aim of this study is to combine Survival Analysis and Analytic Hierarchy Process methodologies when identifying students at-risk of dropping out. This combination favours the institutional understanding of dropout as a dynamic…
Descriptors: Undergraduate Students, Gender Differences, Age Differences, Decision Making
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Hakimi, Laura; Eynon, Rebecca; Murphy, Victoria A. – Review of Educational Research, 2021
This article presents the findings of a systematic qualitative analysis of research in the ethics of digital trace data use in learning and education. From the resulting analysis of 77 peer-reviewed studies, we (1) map the characteristics of research by study type, academic community, institutional setting, and national context; (2) identify the…
Descriptors: Ethics, Data Use, Data Collection, Learning Analytics
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