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Showing all 14 results Save | Export
Michael Wade Ashby – ProQuest LLC, 2024
Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…
Descriptors: Artificial Intelligence, Algorithms, Prediction, Learning Management Systems
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Akhrif, Ouidad; Benfaress, Chaymae; EL Jai, Mostapha; El Bouzekri El Idrissi, Youness; Hmina, Nabil – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this paper is to reveal the smart collaborative learning service. This concept aims to build teams of learners based on the complementarity of their skills, allowing flexible participation and offering interdisciplinary collaboration opportunities for all the learners. The success of this environment is related to predict…
Descriptors: Artificial Intelligence, Cooperative Learning, Interdisciplinary Approach, Universities
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Li, Jiansheng; Li, Linlin; Zhu, Zhixin; Shadiev, Rustam – Education and Information Technologies, 2023
A discussion forum is an indispensable part of a massive open online course (MOOC) environment as it enables knowledge construction through learner-to-learner interaction such as discussion of solutions to assigned problems among learners. In this paper, a machine prediction model is built based on the data from the MOOC forum and the depth of…
Descriptors: MOOCs, Discussion, Prediction, Models
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Xi Jin – International Journal of Web-Based Learning and Teaching Technologies, 2024
How to develop a teaching management system to improve the teaching efficiency of art courses has become an important challenge at present. This article takes university art teaching courses as the research object, uses dynamic L-M algorithm to optimize a large number of parameters, proposes an improved neural networks evaluation model,…
Descriptors: Instructional Effectiveness, Art Education, Barriers, Models
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Hui-Tzu Chang; Chia-Yu Lin – IEEE Transactions on Education, 2024
Contribution: This study incorporates competition-based learning (CBL) into machine learning courses. By engaging students in innovative problem-solving challenges within information competitions, revealing that students' participation in online problem-solving competitions can improve their information technology, and showcase competitions can…
Descriptors: Competition, Artificial Intelligence, Curriculum, Problem Solving
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Olga Ovtšarenko – Discover Education, 2024
Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…
Descriptors: Artificial Intelligence, Algorithms, Technology Uses in Education, Opportunities
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Wai Tong Chor; Kam Meng Goh; Li Li Lim; Kin Yun Lum; Tsung Heng Chiew – Education and Information Technologies, 2024
The programme outcomes are broad statements of knowledge, skills, and competencies that the students should be able to demonstrate upon graduation from a programme, while the Educational Taxonomy classifies learning objectives into different domains. The precise mapping of a course outcomes to the programme outcome and the educational taxonomy…
Descriptors: Artificial Intelligence, Engineering Education, Taxonomy, Educational Objectives
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José Luis Jiménez-Andrade; Ricardo Arencibia-Jorge; Miguel Robles-Pérez; Julia Tagüeña; Tzipe Govezensky; Humberto Carrillo-Calvet; Rafael A. Barrio; Kimmo Kaski – Research Evaluation, 2024
This paper analyzes the research performance evolution of a scientific institute, from its genesis through various stages of development. The main aim is to obtain, and visually represent, bibliometric evidence of the correlation of organizational changes on the development of its scientific performance; particularly, structural and leadership…
Descriptors: Organizational Change, Performance, Bibliometrics, Correlation
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Jui-Hung Chang; Chi-Jane Wang; Hua-Xu Zhong; Hsiu-Chen Weng; Yu-Kai Zhou; Hoe-Yuan Ong; Chin-Feng Lai – Educational Technology Research and Development, 2024
Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students' learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study…
Descriptors: Artificial Intelligence, Technological Advancement, Student Evaluation, Models
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Deliang Wang; Yaqian Zheng; Gaowei Chen – Educational Technology & Society, 2024
This study investigates the potential of ChatGPT, a cutting-edge large language model in generative artificial intelligence (AI), to support the teaching of dialogic pedagogy to preservice teachers. A workshop was conducted with 29 preservice teachers, wherein ChatGPT and another prominent AI model, Bert, were sequentially integrated to facilitate…
Descriptors: Artificial Intelligence, Preservice Teachers, Models, Teaching Methods
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Precup, Radu-Emil; Hedrea, Elena-Lorena; Roman, Raul-Cristian; Petriu, Emil M.; Szedlak-Stinean, Alexandra-Iulia; Bojan-Dragos, Claudia-Adina – IEEE Transactions on Education, 2021
This article proposes an approach based on experiments to teach optimization technique (OT) courses in the Systems Engineering curricula at undergraduate level. Artificial intelligence techniques in terms of nature-inspired optimization algorithms and neural networks are inserted in the lecture and laboratory parts of the syllabus. The experiments…
Descriptors: Engineering Education, Teaching Methods, Systems Approach, Undergraduate Students
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Zakaria, Fathiah; Che Kar, Siti Aishah; Abdullah, Rina; Ismail, Syila Izawana; Md Enzai, Nur Idawati – Asian Journal of University Education, 2021
This paper presents a study of correlation between subjects of Diploma in Electrical Engineering (Electronics/Power) at Universiti Teknologi MARA(UiTM) Cawangan Terengganu using Artificial Neural Network (ANN). The analysis was done to see the effect of mathematical subjects (Pre-calculus and Calculus 1) and core subject (Electric Circuit 1) on…
Descriptors: Correlation, Teaching Methods, Artificial Intelligence, Universities
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Sha, Lele; Rakovic, Mladen; Li, Yuheng; Whitelock-Wainwright, Alexander; Carroll, David; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2021
Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…
Descriptors: Classification, Computer Mediated Communication, Learning Analytics, Data Analysis
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Vishal Soodan; Avinash Rana; Anurag Jain; Deeksha Sharma – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This mixed-methods study aims to examine factors influencing academicians' intentions to continue using AI-based chatbots by integrating the Task-Technology Fit (TTF) model and social network characteristics. Background: AI-powered chatbots are gaining popularity across industries, including academia. However, empirical research on…
Descriptors: Artificial Intelligence, Social Networks, College Faculty, Computer Software