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Showing all 13 results Save | Export
Zixuan Ke – ProQuest LLC, 2024
The essence of human intelligence lies in its ability to learn continuously, accumulating past knowledge to aid in future learning and problem-solving endeavors. In contrast, the current machine learning paradigm often operates in isolation, lacking the capacity for continual learning and adaptation. This deficiency becomes apparent in the face of…
Descriptors: Computational Linguistics, Computer Software, Barriers, Artificial Intelligence
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Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
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Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
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Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
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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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Sarah Blanchard Kyte; Celeste Atkins; Elizabeth Collins; Regina Deil-Amen – Journal of Postsecondary Student Success, 2023
Universities are increasingly turning toward data-driven technologies like data dashboards to support advisors' work in student success, yet little empirical work has explored whether these tools help or hinder best practices in advising, which is in many ways a relationship-based enterprise. This mixed-methods study analyzed whether and why the…
Descriptors: Learning Analytics, Computer Software, School Holding Power, Academic Persistence
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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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Ig Ibert Bittencourt; Geiser Chalco; Jário Santos; Sheyla Fernandes; Jesana Silva; Naricla Batista; Claudio Hutz; Seiji Isotani – International Journal of Artificial Intelligence in Education, 2024
The unprecedented global movement of school education to find technological and intelligent solutions to keep the learning ecosystem working was not enough to recover the impacts of COVID-19, not only due to learning-related challenges but also due to the rise of negative emotions, such as frustration, anxiety, boredom, risk of burnout and the…
Descriptors: Artificial Intelligence, COVID-19, Pandemics, Computer Software
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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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Absalom, Matt – Research-publishing.net, 2021
Using a corpora approach involves using a series of texts in the language under study as a type of corpus on which to base acquisition. Languages in all forms (written, spoken, performed, formal, informal, etc.) are captured all the time through online and digital platforms, apps, etc. making them highly accessible. Applying corpora in teaching…
Descriptors: Computational Linguistics, Second Language Learning, Second Language Instruction, Teaching Methods
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Sanguino, Juan; Manrique, Rubén; Mariño, Olga; Linares-Vásquez, Mario; Cardozo, Nicolas – International Educational Data Mining Society, 2022
Recommender systems in educational contexts have proven effective to identify learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In current recommendation techniques, and in particular, in…
Descriptors: Data Analysis, Learning Analytics, Student Interests, Student Needs
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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
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James M. Laffey; Sean Goggins – International Journal of Designs for Learning, 2014
The purpose of this design case is to tell the story of our work to design context-aware activity notification for learning management systems. The story of the design experience is not simple, in that it includes research and development, conceptual evolution, implementation and extinction, and multiple phases, including inspiration for future…
Descriptors: Learning Analytics, Integrated Learning Systems, Computer Software, Information Systems