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Avila, Cecilia; Baldiris, Silvia; Fabregat, Ramon; Graf, Sabine – British Journal of Educational Technology, 2020
The learning analytics (LA) field seeks to analyze data about students' interactions, and it has been applied in the development of tools for supporting both learning and teaching processes. Recent research has paid attention on how LA may benefit teachers in the creation of educational resources. However, most of the research on LA solutions is…
Descriptors: Learning Analytics, Open Educational Resources, Teacher Developed Materials, Instructional Material Evaluation
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Zhao, Qun; Wang, Jin-Long; Pao, Tsang-Long; Wang, Li-Yu – Journal of Educational Technology Systems, 2020
This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…
Descriptors: Classification, Learning, Accuracy, Prediction
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Whitelock-Wainwright, Alexander; Gaševic, Dragan; Tsai, Yi-Shan; Drachsler, Hendrik; Scheffel, Maren; Muñoz-Merino, Pedro J.; Tammets, Kairit; Delgado Kloos, Carlos – Journal of Computer Assisted Learning, 2020
To assist higher education institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two-factor structure of "Ethical and…
Descriptors: Questionnaires, Test Construction, Test Validity, Learning Analytics
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Monllaó Olivé, David; Huynh, Du Q.; Reynolds, Mark; Dougiamas, Martin; Wiese, Damyon – Journal of Computing in Higher Education, 2020
Both educational data mining and learning analytics aim to understand learners and optimise learning processes of educational settings like Moodle, a learning management system (LMS). Analytics in an LMS covers many different aspects: finding students at risk of abandoning a course or identifying students with difficulties before the assessments.…
Descriptors: Identification, At Risk Students, Potential Dropouts, Online Courses
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Efremov, Aleksandr; Ghosh, Ahana; Singla, Adish – International Educational Data Mining Society, 2020
Intelligent tutoring systems for programming education can support students by providing personalized feedback when a student is stuck in a coding task. We study the problem of designing a hint policy to provide a next-step hint to students from their current partial solution, e.g., which line of code should be edited next. The state of the art…
Descriptors: Intelligent Tutoring Systems, Feedback (Response), Computer Science Education, Artificial Intelligence
Robert, Jenay; Reinitz, Betsy – EDUCAUSE, 2023
More data are collected, analyzed, and stored now than at any other time in history. Data processes play a foundational role in just about every professional discipline, and data stakeholders all over the world are grappling with modernizing and optimizing data governance policies and practices. In this rapidly evolving landscape, what challenges…
Descriptors: Data Collection, Learning Analytics, Higher Education, Governance
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Xu, Yinuo; Pardos, Zachary A. – International Educational Data Mining Society, 2023
In studies that generate course recommendations based on similarity, the typical enrollment data used for model training consists only of one record per student-course pair. In this study, we explore and quantify the additional signal present in course transaction data, which includes a more granular account of student administrative interactions…
Descriptors: Semantics, Enrollment Trends, Learning Analytics, STEM Education
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Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2023
In MOOCs for programming, Automated Testing and Feedback (ATF) systems are frequently integrated, providing learners with immediate feedback on code assignments. The analysis of the large amounts of trace data collected by these systems may provide insights into learners' patterns of utilizing the automated feedback, which is crucial for the…
Descriptors: MOOCs, Feedback (Response), Teaching Methods, Learning Strategies
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Yürüm, Ozan Rasit; Taskaya-Temizel, Tugba; Yildirim, Soner – Education and Information Technologies, 2023
Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…
Descriptors: Video Technology, Educational Technology, Learning Management Systems, Data Collection
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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Journal of Information Systems Education, 2023
Educators who teach programming subjects are often wondering "which programming language should I teach first?" The debate behind this question has a long history and coming up with a definite answer to this question would be farfetched. Nonetheless, several efforts can be identified in the literature wherein pros and cons of mainstream…
Descriptors: Comparative Analysis, Programming Languages, Probability, Error Patterns
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Aleksandra Maslennikova; Daniela Rotelli; Anna Monreale – Journal of Learning Analytics, 2023
Students organize and manage their own learning time, choosing when, what, and how to study due to the flexibility of online learning. Each person has unique learning habits that define their behaviours and distinguish them from others. To investigate the temporal behaviour of students in online learning environments, we seek to identify suitable…
Descriptors: Learning Analytics, Online Courses, Time Management, Self Management
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Patrick Ocheja; Brendan Flanagan; Hiroaki Ogata; Solomon Sunday Oyelere – Interactive Learning Environments, 2023
The use of blockchain in education has become one of the trending topics in education technology research. However, only a handful of education blockchain solutions have provided a measure of the impact on students' learning outcomes, teaching, or administrative processes. This work reviews how academic data stored on the blockchain is being…
Descriptors: Educational Technology, Learning Activities, Lifelong Learning, Information Security
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Torres Castro, Uriel Eduardo; Pineda-Báez, Clelia – Journal of Further and Higher Education, 2023
The objective of this article is to analyse the development and content of research in the global literature on student agency in higher education (SAHE) based on a bibliometric review of 224 articles published in the Scopus database during the period 2000-2022. VOSviewer, Excel, and Tableau software were used to analyse the texts. The review…
Descriptors: Personal Autonomy, Higher Education, Social Cognition, Student Motivation
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Youqin Pan; Jian Gu – International Journal of Technology in Teaching and Learning, 2023
This paper explores the potential of using Chat Generative PreTrained Transformer (ChatGPT), a powerful language model, as an innovative tool to enhance education in the classroom. Drawing from firsthand experience, this paper demonstrates how ChatGPT can be integrated into the teaching and learning process of statistics and data analytics…
Descriptors: Teaching Methods, Learning Processes, Artificial Intelligence, Computer Software
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Worsley, Marcelo; Martinez-Maldonado, Roberto; D'Angelo, Cynthia – Journal of Learning Analytics, 2021
Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…
Descriptors: Learning Analytics, Artificial Intelligence, Data Collection, Statistical Inference
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