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Da Teng; Xiangyang Wang; Yanwei Xia; Yue Zhang; Lulu Tang; Qi Chen; Ruobing Zhang; Sujin Xie; Weiyong Yu – Education and Information Technologies, 2025
The swift advancement of artificial intelligence, especially large language models (LLMs), has generated novel prospects for improving educational methodologies. Nonetheless, the successful incorporation of these technologies into pedagogical methods, such as flipped classrooms, continues to pose a challenge. This study investigates the…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Flipped Classroom, Technology Uses in Education
Kuo, Yu-Chen; Chen, Yun-An – Education and Information Technologies, 2023
With the development of science and technology, the demand for programmers has increased. However, learning computer programs is not an easy task. It might cause a significant impact on programming if misconceptions exist at the beginning of the study. Hence, it is important to discover and correct them immediately. Chatbots are effective teaching…
Descriptors: Programming, Artificial Intelligence, Computer Science Education, Misconceptions
Alshammari, Mohammad T.; Qtaish, Amjad – Journal of Information Technology Education: Research, 2019
Aim/Purpose: Effective e-learning systems need to incorporate student characteristics such as learning style and knowledge level in order to provide a more personalized and adaptive learning experience. However, there is a need to investigate how and when to provide adaptivity based on student characteristics, and more importantly, to evaluate its…
Descriptors: Electronic Learning, Cognitive Style, Knowledge Level, Individualized Instruction
Mudrák, Marián; Turcáni, Milan; Reichel, Jaroslav – Journal on Efficiency and Responsibility in Education and Science, 2020
At current e-learning platforms, is often seen non-efficient usage of their possibilities when creating educational content. This article deals with the possibilities of using adaptive tools that are offered by learning management system (LMS) Moodle when creating a personalised e-course. The methodology created by the authors of the article for…
Descriptors: Individualized Instruction, Computer Science Education, Electronic Learning, Online Courses
Zheng, Lanqin; Zhong, Lu; Niu, Jiayu; Long, Miaolang; Zhao, Jiayi – Educational Technology & Society, 2021
In recent years, the rapid development of artificial intelligence has increased the power of personalized learning. This study aimed to provide personalized intervention for each group participating in computer-supported collaborative learning. The personalized intervention adopted a deep neural network model, Bidirectional Encoder Representations…
Descriptors: Instructional Effectiveness, Individualized Instruction, Computer Assisted Instruction, Cooperative Learning
Lin, Che-Chern; Liu, Zi-Cheng; Chang, Chih-Lin; Lin, Yu-Wen – IEEE Transactions on Education, 2019
Contribution: An online genetic algorithm-based remedial learning system is presented in order to strengthen students' understanding of object-oriented programming (OOP) concepts by tailoring personalized learning materials according to each student's strengths and weaknesses. Background: Prior studies on computer programming education have…
Descriptors: Individualized Instruction, Remedial Instruction, Computer Science Education, Programming Languages
González-Castro, Nuria; Muñoz-Merino, Pedro J.; Alario-Hoyos, Carlos; Delgado Kloos, Carlos – Australasian Journal of Educational Technology, 2021
Massive open online courses (MOOCs) pose a challenge for instructors when trying to provide personalised support to learners, due to large numbers of registered participants. Conversational agents can be of help to support learners when working with MOOCs. This article presents an adaptive learning module for JavaPAL, a conversational agent that…
Descriptors: Online Courses, Learning Modules, Computer Science Education, Programming
Hsieh, Tung-Cheng; Lee, Ming-Che; Su, Chien-Yuan – Educational Technology & Society, 2013
In recent years, the demand for computer programming professionals has increased rapidly. These computer engineers not only play a key role in the national development of the computing and software industries, they also have a significant influence on the broader national knowledge industry. Therefore, one of the objectives of information…
Descriptors: Foreign Countries, Computer Science Education, Individualized Instruction, Remedial Instruction
Hsiao, I.-H.; Sosnovsky, S.; Brusilovsky, P. – Journal of Computer Assisted Learning, 2010
Rapid growth of the volume of interactive questions available to the students of modern E-Learning courses placed the problem of personalized guidance on the agenda of E-Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a…
Descriptors: Electronic Learning, Guidance, Individualized Instruction, Computer Software
Liao, Ching-Jung; Chou, Chien-Chih; Yang, Jin-Tan David – International Journal of Distance Education Technologies, 2009
The purpose of this study is to incorporate adaptive ontology into ubiquitous learning grid to achieve seamless learning environment. Ubiquitous learning grid uses ubiquitous computing environment to infer and determine the most adaptive learning contents and procedures in anytime, any place and with any device. To achieve the goal, an…
Descriptors: Individualized Instruction, Simulation, Educational Environment, College Freshmen

Hambleton, Ian R.; Foster, William H.; Richardson, John T. E. – Higher Education, 1998
College mathematics and computer science students in two math courses (conventional lecture-based, and a multimedia variant of the Personalized System of Instruction) completed the Approaches to Studying Inventory. Students in the latter course obtained higher scores on meaning orientation. The effect was significant in computer-science students,…
Descriptors: Classroom Techniques, College Instruction, College Mathematics, College Students
Emurian, Henry H. – International Journal of Distance Education Technologies, 2006
Students in a graduate class and an undergraduate class in Information Systems completed a Web-based programmed instruction tutor that taught a simple Java applet as the first technical training exercise in a computer programming course. The tutor is a competency-based instructional system for individualized distance learning. When a student…
Descriptors: Web Based Instruction, Computer Science Education, Information Systems, Graduate Students