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Fan, Yizhou; Rakovic, Mladen; van der Graaf, Joep; Lim, Lyn; Singh, Shaveen; Moore, Johanna; Molenaar, Inge; Bannert, Maria; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Many learners struggle to productively self-regulate their learning. To support the learners' self-regulated learning (SRL) and boost their achievement, it is essential to understand the cognitive and metacognitive processes that underlie SRL. To measure these processes, contemporary SRL researchers have largely utilized think aloud or…
Descriptors: Learning Strategies, Self Management, Protocol Analysis, Data Analysis
Lodge, Jason M.; Alhadad, Sakinah S. J.; Lewis, Melinda J.; Gaševic, Dragan – Technology, Knowledge and Learning, 2017
The use of big data in higher education has evolved rapidly with a focus on the practical application of new tools and methods for supporting learning. In this paper, we depart from the core emphasis on application and delve into a mostly neglected aspect of the big data conversation in higher education. Drawing on developments in cognate…
Descriptors: Statistical Inference, Data Interpretation, Interdisciplinary Approach, Higher Education
Fan, Yizhou; Matcha, Wannisa; Uzir, Nora'ayu Ahmad; Wang, Qiong; Gaševic, Dragan – International Journal of Artificial Intelligence in Education, 2021
The importance of learning design in education is widely acknowledged in the literature. Should learners make effective use of opportunities provided in a learning design, especially in online environments, previous studies have shown that they need to have strong skills for self-regulated learning (SRL). The literature, which reports the use of…
Descriptors: Learning Analytics, Instructional Design, Independent Study, Multivariate Analysis
Gaševic, Dragan; Jovanovic, Jelena; Pardo, Abelardo; Dawson, Shane – Journal of Learning Analytics, 2017
The use of analytic methods for extracting learning strategies from trace data has attracted considerable attention in the literature. However, there is a paucity of research examining any association between learning strategies extracted from trace data and responses to well-established self-report instruments and performance scores. This paper…
Descriptors: Foreign Countries, Undergraduate Students, Engineering Education, Educational Research
Selwyn, Neil; Gaševic, Dragan – Teaching in Higher Education, 2020
A common recommendation in critiques of datafication in education is for greater conversation between the two sides of the (critical) divide -- what might be characterised as sceptical social scientists and (supposedly) more technically-minded and enthusiastic data scientists. This article takes the form of a dialogue between two academics…
Descriptors: Criticism, Data Analysis, Higher Education, Dialogs (Language)
Tsai, Yi-Shan; Perrotta, Carlo; Gaševic, Dragan – Assessment & Evaluation in Higher Education, 2020
The emergence of personalised data technologies such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related…
Descriptors: Student Empowerment, Equal Education, Learning Analytics, Accountability
Sha, Lele; Rakovic, Mladen; Li, Yuheng; Whitelock-Wainwright, Alexander; Carroll, David; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2021
Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…
Descriptors: Classification, Computer Mediated Communication, Learning Analytics, Data Analysis
Tsai, Yi-Shan; Moreno-Marcos, Pedro Manuel; Jivet, Ioana; Scheffel, Maren; Tammets, Kairit; Kollom, Kaire; Gaševic, Dragan – Journal of Learning Analytics, 2018
This paper introduces a learning analytics policy and strategy framework developed by a cross-European research project team -- SHEILA (Supporting Higher Education to Integrate Learning Analytics), based on interviews with 78 senior managers from 51 European higher education institutions across 16 countries. The framework was developed adapting…
Descriptors: Data Analysis, Learning, Educational Policy, Higher Education
Pardo, Abelardo; Jovanovic, Jelena; Dawson, Shane; Gaševic, Dragan; Mirriahi, Negin – British Journal of Educational Technology, 2019
There is little debate regarding the importance of student feedback for improving the learning process. However, there remain significant workload barriers for instructors that impede their capacity to provide timely and meaningful feedback. The increasing role technology is playing in the education space may provide novel solutions to this…
Descriptors: Learning, Data Analysis, Feedback (Response), Technology Uses in Education
Pardo, Abelardo; Bartimote-Aufflick, Kathryn; Shum, Simon Buckingham; Dawson, Shane; Gao, Jing; Gaševic, Dragan; Leichtweis, Steve; Liu, Danny; Martínez-Maldonado, Roberto; Mirriahi, Negin; Moskal, Adon Christian Michael; Schulte, Jurgen; Siemens, George; Vigentini, Lorenzo – Journal of Learning Analytics, 2018
The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms…
Descriptors: Individualized Instruction, Data Analysis, Learning, Feedback (Response)
Fincham, Ed; Gaševic, Dragan; Pardo, Abelardo – Journal of Learning Analytics, 2018
The widespread adoption of digital e-learning environments and other learning technology has provided researchers with ready access to large quantities of data. Much of this data comes from discussion forums and has been studied with analytical methods drawn from social network analysis. However, within this large body of research there exists…
Descriptors: Social Networks, Data Analysis, Academic Achievement, Correlation
Hilliger, Isabel; Ortiz-Rojas, Margarita; Pesántez-Cabrera, Paola; Scheihing, Eliana; Tsai, Yi-Shan; Muñoz-Merino, Pedro J.; Broos, Tom; Whitelock-Wainwright, Alexander; Gaševic, Dragan; Pérez-Sanagustín, Mar – British Journal of Educational Technology, 2020
In Latin American universities, Learning Analytics (LA) has been perceived as a promising opportunity to leverage data to meet the needs of a diverse student cohort. Although universities have been collecting educational data for years, the adoption of LA in this region is still limited due to the lack of expertise and policies for processing and…
Descriptors: Universities, Data Analysis, Student Diversity, College Students
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michalis – Journal of Learning Analytics, 2020
Programming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when…
Descriptors: Learning Analytics, Data Collection, Instructional Design, Learning Modalities
Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Fudge, Anthea; Pardo, Abelardo; Gentili, Sheridan – Australasian Journal of Educational Technology, 2020
Although technological advances have brought about new opportunities for scaling feedback to students, there remain challenges in how such feedback is presented and interpreted. There is a need to better understand how students make sense of such feedback to adapt self-regulated learning processes. This study examined students' sense-making of…
Descriptors: Individualized Instruction, Learning Analytics, Data Collection, Student Attitudes
Crosslin, Matt; Dellinger, Justin T.; Joksimovic, Srecko; Kovanovic, Vitomir; Gaševic, Dragan – Online Learning, 2018
Dual-layer MOOCs are an educational framework designed to create customizable modality pathways through a learning experience. The basic premise is to design two framework choices through a course: one that is instructor centered and the other that is student determined and open. Learners have the option to create their own customized pathway by…
Descriptors: Online Courses, Course Descriptions, Mixed Methods Research, Guidelines
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