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Showing 1 to 15 of 17 results Save | Export
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Pardos, Zachary A.; Horodyskyj, Lev – Journal of Learning Analytics, 2019
We introduce a novel approach to visualizing temporal clickstream behaviour in the context of a degree-satisfying online course, "Habitable Worlds," offered through Arizona State University. The current practice for visualizing behaviour within a digital learning environment is to generate plots based on hand-engineered or coded features…
Descriptors: Visualization, Online Courses, Course Descriptions, Data Analysis
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Herodotou, Christothea; Rienties, Bart; Verdin, Barry; Boroowa, Avinash – Journal of Learning Analytics, 2019
Predictive Learning Analytics (PLA) aim to improve learning by identifying students at risk of failing their studies. Yet, little is known about how best to integrate and scaffold PLA initiatives into higher education institutions. Towards this end, it becomes essential to capture and analyze the perceptions of relevant educational stakeholders…
Descriptors: Prediction, Data Analysis, Higher Education, Distance Education
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Rehrey, George; Shepard, Linda; Hostetter, Carol; Reynolds, Amberly; Groth, Dennis – Journal of Learning Analytics, 2019
To successfully implement Learning Analytics (LA) systems within higher education, we need to engage administrators, faculty, and staff alike. This paper is by and primarily for practitioners. We suggest implementation strategies that consider the human factor in adopting new technologies by analyzing the viability of our Learning Analytics…
Descriptors: Learning Analytics, Change Agents, School Culture, Technology Integration
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Atapattu, Thushari; Falkner, Katrina – Journal of Learning Analytics, 2018
Lecture videos are amongst the most widely used instructional methods within present Massive Open Online Courses (MOOCs) and other digital educational platforms. As the main form of instruction, student engagement behaviour, including interaction with videos, directly impacts the student success or failure and accordingly, in-video dropouts…
Descriptors: Lecture Method, Video Technology, Online Courses, Mass Instruction
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Gardner, Josh; Brooks, Christopher; Li, Warren – Journal of Learning Analytics, 2018
In this paper, we evaluate the complete undergraduate co-enrollment network over a decade of education at a large American public university. We provide descriptive and exploratory analyses of the network, demonstrating that the co-enrollment networks evaluated follow power-law degree distributions similar to many other large-scale networks; that…
Descriptors: Markov Processes, Classification, Undergraduate Students, Grade Point Average
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Khosravi, Hassan; Cooper, Kendra M. L. – Journal of Learning Analytics, 2018
Educational environments continue to evolve rapidly to address the needs of diverse, growing student populations while embracing advances in pedagogy and technology. In this changing landscape, ensuring consistency among the assessments for different offerings of a course (within or across terms), providing meaningful feedback about student…
Descriptors: Graphs, Academic Achievement, Student Evaluation, Models
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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
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Hart, Sara A.; Daucourt, Mia; Ganley, Colleen M. – Journal of Learning Analytics, 2017
In this study, we explore student achievement in a semester-long flipped Calculus II course, combining various predictor measures related to student attitudes (math anxiety, math confidence, math interest, math importance) and cognitive skills (spatial skills, approximate number system), as well as student engagement with the online system…
Descriptors: Academic Achievement, Calculus, Mathematics Instruction, Educational Technology
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Dvorak, Tomas; Jia, Miaoqing – Journal of Learning Analytics, 2016
This study analyzes the relationship between students' online work habits and academic performance. We utilize data from logs recorded by a course management system (CMS) in two courses at a small liberal arts college in the U.S. Both courses required the completion of a large number of online assignments. We measure three aspects of students'…
Descriptors: Online Courses, Educational Technology, Study Habits, Academic Achievement
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Colthorpe, Kay; Zimbardi, Kirsten; Ainscough, Louise; Anderson, Stephen – Journal of Learning Analytics, 2015
It is well established that a student's capacity to regulate his or her own learning is a key determinant of academic success, suggesting that interventions targeting improvements in self-regulation will have a positive impact on academic performance. However, to evaluate the success of such interventions, the self-regulatory characteristics of…
Descriptors: Data Analysis, Data Collection, Educational Research, Self Control
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Kovanovic, Vitomir; Gaševic, Dragan; Dawson, Shane; Joksimovic, Srecko; Baker, Ryan S.; Hatala, Marek – Journal of Learning Analytics, 2015
With widespread adoption of Learning Management Systems (LMS) and other learning technology, large amounts of data--commonly known as trace data--are readily accessible to researchers. Trace data has been extensively used to calculate time that students spend on different learning activities--typically referred to as time-on-task. These measures…
Descriptors: Time on Task, Computation, Validity, Data Analysis
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Aguiar, Everaldo; Ambrose, G. Alex; Chawla, Nitesh V.; Goodrich, Victoria; Brockman, Jay – Journal of Learning Analytics, 2014
As providers of higher education begin to harness the power of big data analytics, one very fitting application for these new techniques is that of predicting student attrition. The ability to pinpoint students who might soon decide to drop out, or who may be following a suboptimal path to success, allows those in charge not only to understand the…
Descriptors: Academic Persistence, Engineering Education, Portfolios (Background Materials), Dropouts
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Papamitsiou, Zacharoula; Economides, Anastasios A. – Journal of Learning Analytics, 2014
Accurate and early predictions of student performance could significantly affect interventions during teaching and assessment, which gradually could lead to improved learning outcomes. In our research, we seek to identify and formalize temporal parameters as predictors of performance ("temporal learning analytics" or TLA) and examine…
Descriptors: Time Factors (Learning), Predictor Variables, Student Behavior, Academic Achievement
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Buerck, John P.; Mudigonda, Srikanth P. – Journal of Learning Analytics, 2014
Academic analytics and learning analytics have been increasingly adopted by academic institutions of higher learning for improving student performance and retention. While several studies have reported the implementation details and the successes of specific analytics initiatives, relatively fewer studies exist in literature that describe the…
Descriptors: Higher Education, Educational Research, Data Analysis, Data Collection
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Gray, Geraldine; McGuinness, Colm; Owende, Philip; Carthy, Aiden – Journal of Learning Analytics, 2014
Increasing college participation rates, and diversity in student population, is posing a challenge to colleges in their attempts to facilitate learners achieve their full academic potential. Learning analytics is an evolving discipline with capability for educational data analysis that could enable better understanding of learning process, and…
Descriptors: Psychometrics, Data Analysis, Academic Achievement, Postsecondary Education
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