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Showing all 12 results Save | Export
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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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Armatas, Christine; Kwong, Theresa; Chun, Cecilia; Spratt, Christine; Chan, Dick; Kwan, Joanna – Technology, Knowledge and Learning, 2022
The application of learning analytics (LA) to research and practice in higher education is expanding. Researchers and practitioners are using LA to provide an evidentiary basis across higher education to investigate student learning, to drive institutional quality improvement strategies, to determine at-risk behaviours and develop intervention…
Descriptors: Learning Analytics, Higher Education, Foreign Countries, Curriculum Evaluation
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Tanjea Ane; Tabatshum Nepa – Research on Education and Media, 2024
Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…
Descriptors: Artificial Intelligence, Prediction, Models, Teaching Methods
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Nesra Yannier; Scott E. Hudson; Henry Chang; Kenneth R. Koedinger – International Journal of Artificial Intelligence in Education, 2024
Adaptivity in advanced learning technologies offer the possibility to adapt to different student backgrounds, which is difficult to do in a traditional classroom setting. However, there are mixed results on the effectiveness of adaptivity based on different implementations and contexts. In this paper, we introduce AI adaptivity in the context of a…
Descriptors: Artificial Intelligence, Computer Software, Feedback (Response), Outcomes of Education
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Shaheen, Muhammad – Interactive Learning Environments, 2023
Outcome-based education (OBE) is uniquely adapted by most of the educators across the world for objective processing, evaluation and assessment of computing programs and its students. However, the extraction of knowledge from OBE in common is a challenging task because of the scattered nature of the data obtained through Program Educational…
Descriptors: Undergraduate Students, Programming, Computer Science Education, Educational Objectives
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Edwin Gonzalo Vargas; Andrés Chiappe; Julio Durand – Journal of Social Studies Education Research, 2024
This review explores how artificial intelligence (AI henceforth) can reshape education through insights from situated learning literature. The objective was to critically examine opportunities and challenges of situated learning, and how AI could augment strengths while overcoming obstacles. A systematic review using the PRISMA method analyzed 60…
Descriptors: Artificial Intelligence, Situated Learning, Computer Software, Technology Uses in Education
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Yanping Pei; Adam Sales; Johann Gagnon-Bartsch – Grantee Submission, 2024
Randomized A/B tests within online learning platforms enable us to draw unbiased causal estimators. However, precise estimates of treatment effects can be challenging due to minimal participation, resulting in underpowered A/B tests. Recent advancements indicate that leveraging auxiliary information from detailed logs and employing design-based…
Descriptors: Randomized Controlled Trials, Learning Management Systems, Causal Models, Learning Analytics
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Fancsali, Stephen E.; Murphy, April; Ritter, Steve – International Educational Data Mining Society, 2022
Ten years after the announcement of the "rise of the super experiment" at Educational Data Mining 2012, challenges to implementing "internet scale" educational experiments often persist for educational technology providers, especially when they seek to test substantive instructional interventions. Studies that deploy and test…
Descriptors: Learning Analytics, Educational Technology, Barriers, Data Analysis
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Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content
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Cohen, Anat; Ezra, Orit; Hershkovitz, Arnon; Tzayada, Odelia; Tabach, Michal; Levy, Ben; Segal, Avi; Gal, Kobi – Educational Technology Research and Development, 2021
Personalizing the use of educational mathematics applets to fit learners' characteristics poses a great challenge. The present study adopted a unique approach by comparing personalization processes implemented by a machine to those implemented by a human teacher. Given the different affordances--the machine's access to historical log file data,…
Descriptors: Mathematics Instruction, Comparative Analysis, Pedagogical Content Knowledge, Teaching Methods
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Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology
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Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology