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Murad, Dina Fitria; Murad, Silvia Ayunda; Irsan, Muhamad – Journal of Educators Online, 2023
This study discusses the use of an online learning recommendation system as a smart solution related to changing the face-to-face learning process to online. This study uses user-based collaborative filtering, item-based collaborative filtering, and hybrid collaborative filtering. This research was conducted in two stages using the KNN machine…
Descriptors: Online Courses, Grades (Scholastic), Prediction, Context Effect
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Soukaina Gouraguine; Mohammed Qbadou; Mohamed Rafik; Mustapha Riad; Khalifa Mansouri – Journal of Information Technology Education: Research, 2023
Aim/Purpose: Our study is focused on prototyping, development, testing, and deployment of a new knowledge primitive for the humanoid robot assistant NAO, in order to enhance student visual learning by establishing a human-robot interaction. Background: This new primitive, utilizing a convolutional neural network (CNN), enables real-time…
Descriptors: Robotics, Technology Uses in Education, Algorithms, Children
Dan Delmonaco – ProQuest LLC, 2023
In the United States, the internet is a vital resource for LGBTQ+ youth to meet their sexual and reproductive health information needs, especially those who cannot receive necessary information from family, healthcare providers, and classrooms. In this dissertation, I present three papers that connect content moderation policies and their impacts…
Descriptors: Sex Education, LGBTQ People, Information Seeking, Online Searching
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Kaiyi Long – International Journal of Web-Based Learning and Teaching Technologies, 2023
The test results show that the fast Fourier process with multiple time superposition and a dimension length of 40 is most beneficial to the accuracy of the model. The loss curve value of the convolutional recurrent network model (CRN) is much lower than the other three models. The music tone recognition model learns better. The accuracy rate value…
Descriptors: Music Education, Music Activities, Singing, Audio Equipment
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D. Steger; S. Weiss; O. Wilhelm – Creativity Research Journal, 2023
Creativity can be measured with a variety of methods including self-reports, others reports, and ability tests. While typical self-reports are best understood as weak proxies of creativity, biographical reports that assess previous creative activities seem more promising. Drawbacks of such measures -- including skewed item distributions, a lack of…
Descriptors: Creativity, Creativity Tests, Test Construction, Algorithms
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Andrew M. Olney – Grantee Submission, 2023
Multiple choice questions are traditionally expensive to produce. Recent advances in large language models (LLMs) have led to fine-tuned LLMs that generate questions competitive with human-authored questions. However, the relative capabilities of ChatGPT-family models have not yet been established for this task. We present a carefully-controlled…
Descriptors: Test Construction, Multiple Choice Tests, Test Items, Algorithms
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Hanif Akhtar – International Society for Technology, Education, and Science, 2023
For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…
Descriptors: Success, Probability, Computer Assisted Testing, Adaptive Testing
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Saida Ulfa; Ence Surahman; Agus Wedi; Izzul Fatawi; Rex Bringula – Knowledge Management & E-Learning, 2025
Online assessment is one of the important factors in online learning today. An online summary assessment is an example of an open-ended question, offering the advantage of probing students' understanding of the learning materials. However, grading students' summary writings is challenging due to the time-consuming process of evaluating students'…
Descriptors: Knowledge Management, Automation, Documentation, Feedback (Response)
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Dawei Zhang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This article aims to study and implement a deep learning algorithm-based information literacy assistance system for college students to solve the problems of insufficient personalization and untimely feedback in the existing information literacy education methods, so as to improve the information literacy level of college students. This article…
Descriptors: College Students, Artificial Intelligence, Information Literacy, Problem Solving
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David Van Nguyen; Shayan Doroudi; Daniel A. Epstein – Community College Journal of Research and Practice, 2025
Our preliminary experiment examined a potential pain point with ASSIST, California's database of articulation agreements. That pain point is cross-referencing multiple articulation agreements to manually develop an "optimal" academic plan. Optimal is defined as the minimal set of community college courses that satisfy all transfer…
Descriptors: Articulation (Education), Human Factors Engineering, Algorithms, Educational Planning
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Ruth Li – Thresholds in Education, 2025
In this article, I introduce a collaborative annotation activity that supports students in critically examining AI-generated writing in relation to criteria including specificity and complexity. I engage students in collaboratively annotating the AI-generated essays, guiding students to identify instances in which the essays could be more…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Assisted Instruction, Writing Instruction
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Huixiao Le; Yuan Shen; Zijian Li; Mengyu Xia; Luzhen Tang; Xinyu Li; Jiyou Jia; Qiong Wang; Dragan Gaševic; Yizhou Fan – British Journal of Educational Technology, 2025
Understanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' preferences between AI and human tutors to support their learning. While AI demonstrates growing…
Descriptors: Student Attitudes, Preferences, Electronic Learning, Artificial Intelligence
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Christoph G. Salzmann; Sophia M. Vecchi Marsh; Jinjie Li; Luca Slater – Journal of Chemical Education, 2025
Proportional-Integral-Derivative (PID) controllers are essential in ensuring the stability and efficiency of numerous scientific, industrial, and medical processes. However, teaching the principles of PID control can be challenging, especially when the introduction focuses on the underlying mathematical framework. To address this, we developed the…
Descriptors: Science Education, Science Instruction, Teaching Methods, Demonstrations (Educational)
Mohd Ali Samsudin; Hanil Raaj Singh Gill – Sage Research Methods Cases, 2025
This case study examines the changing trends in artificial intelligence (AI) education on YouTube using a blend of social network analysis and quantitative ethnography, explicitly employing the epistemic network analysis method. YouTube's function as a significant informal learning platform provides an opportunity to investigate the distribution…
Descriptors: Educational Trends, Artificial Intelligence, Technology Uses in Education, Video Technology
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Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
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