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Showing 961 to 975 of 1,732 results Save | Export
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Mutahar Qassem; Buthainah M. Al Thowaini – Education and Information Technologies, 2024
Leveraging technological tools in educational research expands investigations into participants' behaviors and provides insights into learning patterns and teaching effectiveness through innovative data collection and analysis methods. Using keylogging data software, this study explored trainee translators' process and product behaviors under two…
Descriptors: Journalism, Translation, Keyboarding (Data Entry), Language Processing
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Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
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Alexandron, Giora; Yoo, Lisa Y.; Ruipérez-Valiente, José A.; Lee, Sunbok; Pritchard, David E. – International Journal of Artificial Intelligence in Education, 2019
The rich data that Massive Open Online Courses (MOOCs) platforms collect on the behavior of millions of users provide a unique opportunity to study human learning and to develop data-driven methods that can address the needs of individual learners. This type of research falls into the emerging field of "learning analytics." However,…
Descriptors: Online Courses, Data Collection, Learning Analytics, Reliability
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Rose, Carolyn Penstein – Journal of Learning Analytics, 2019
This contribution offers a commentary on Neil Selwyn's write up of his keynote talk from the Learning Analytics and Knowledge Conference in 2018 (Selwyn, this issue). The article has three main sections, namely an account of what Learning Analytics has done, an account of the values behind Learning Analytics, and some ideas for moving forward.…
Descriptors: Learning Analytics, Values, Futures (of Society), Educational Trends
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Armatas, Christine; Spratt, Christine F. – International Journal of Information and Learning Technology, 2019
Purpose: The purpose of this paper is to describe examples of the application of learning analytics (LA), including the assessment of subject grades, identifying subjects that need revision, student satisfaction and cohort comparisons, to program curriculum review. Design/methodology/approach: Examples of analyses that address specific questions…
Descriptors: Learning Analytics, Curriculum Evaluation, Grades (Scholastic), Evaluation Problems
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Savi, Alexander O.; Deonovic, Benjamin E.; Bolsinova, Maria; van der Maas, Han L. J.; Maris, Gunter K. J. – Journal of Educational Data Mining, 2021
In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed…
Descriptors: Learning Processes, Cognitive Processes, Error Patterns, Models
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Xu, Zhuojia; Yuan, Hua; Liu, Qishan – IEEE Transactions on Education, 2021
Contribution: This article explored blended learning by implementing a student-centered teaching method based on the flipped classroom and small private online course (SPOC). The impact of general online learning behavior on student performance was analyzed. This work is practical and provides enlightenment for learning analysis and individualized…
Descriptors: Academic Achievement, Blended Learning, Prediction, Performance Factors
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Wang, Dongqing; Han, Hou – Journal of Computer Assisted Learning, 2021
With the development of a technology-supported environment, it is plausible to provide rich process-oriented feedback in a timely manner. In this paper, we developed a learning analytics dashboard (LAD) based on process-oriented feedback in iTutor to offer learners their final scores, sub-scale reports, and corresponding suggestions on further…
Descriptors: Learning Analytics, Educational Technology, Feedback (Response), Intelligent Tutoring Systems
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Piotrkowicz, Alicja; Wang, Kaiwen; Hallam, Jennifer; Dimitrova, Vania – International Journal of Artificial Intelligence in Education, 2021
The paper presents a multi-faceted data-driven computational approach to analyse workplace-based assessment (WBA) of clinical skills in medical education. Unlike formal university-based part of the degree, the setting of WBA can be informal and only loosely regulated, as students are encouraged to take every opportunity to learn from the clinical…
Descriptors: Workplace Learning, Performance Based Assessment, Clinical Experience, Medical Education
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Hriez, Raghda Fawzey; Al-Naymat, Ghazi – Journal of Computing in Higher Education, 2021
Depicting the reason for the mismatch between instructor expectations of students' performance in advanced courses and their actual performance has been a challenging issue for a long time, which raises the question of why such a mismatch exists. An implicit reason for this mismatch is the student's weakness in prerequisite course skills. To solve…
Descriptors: Required Courses, Advanced Courses, Graphs, Outcomes of Education
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Wu, Hao; Molnár, Gyöngyvér – European Journal of Psychology of Education, 2021
The purpose of this study is to examine cross-national differences in students' exploration strategies in a computer-simulated CPS (complex problem-solving) environment and to identify similarities and qualitative differences in the way Hungarian and Chinese students explore a CPS environment. In a sample of 187 Chinese and 835 Hungarian students…
Descriptors: Cross Cultural Studies, Problem Solving, Computer Simulation, Teaching Methods
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Worsley, Marcelo; Anderson, Khalil; Melo, Natalie; Jang, JooYoung – Journal of Learning Analytics, 2021
Collaboration has garnered global attention as an important skill for the 21st century. While researchers have been doing work on collaboration for nearly a century, many of the questions that the field is investigating overlook the need for students to learn how to read and respond to different collaborative settings. Existing research focuses on…
Descriptors: Learning Analytics, Cooperative Learning, 21st Century Skills, College Students
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Deane, Paul; Wilson, Joshua; Zhang, Mo; Li, Chen; van Rijn, Peter; Guo, Hongwen; Roth, Amanda; Winchester, Eowyn; Richter, Theresa – International Journal of Artificial Intelligence in Education, 2021
Educators need actionable information about student progress during the school year. This paper explores an approach to this problem in the writing domain that combines three measurement approaches intended for use in interim-assessment fashion: scenario-based assessments (SBAs), to simulate authentic classroom tasks, automated writing evaluation…
Descriptors: Vignettes, Writing Evaluation, Writing Improvement, Progress Monitoring
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Rosenheck, Louisa; Cheng, Meng-Tzu; Lin, Chen-Yen; Klopfer, Eric – Educational Technology Research and Development, 2021
Games can be rich environments for learning and can elicit evidence of students' conceptual understanding and inquiry processes. Illuminating students' content-specific gameplay decisions, or methods of completing game tasks related to a certain domain, requires a context that is open-ended enough for students to make choices that demonstrate…
Descriptors: Game Based Learning, Decision Making, Learning Analytics, Genetics
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Alcaraz, Raul; Martinez-Rodrigo, Arturo; Zangroniz, Roberto; Rieta, Jose Joaquin – IEEE Transactions on Learning Technologies, 2021
Early warning systems (EWSs) have proven to be useful in identifying students at risk of failing both online and conventional courses. Although some general systems have reported acceptable ability to work in modules with different characteristics, those designed from a course-specific perspective have recently provided better outcomes. Hence, the…
Descriptors: Prediction, At Risk Students, Academic Failure, Electronic Equipment
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