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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
Nongkhai, Lalita Na; Wang, Jingyun; Mendori, Takahiko – International Association for Development of the Information Society, 2022
This paper proposes the design of an ontology of multiple programming languages and give three examples to show the methodology. Our ontology aims to summarize the core of computational thinking logic by elaborating the concepts of three object-oriented programming languages in the industry: Python, Java, and C#. Therefore, the construction of the…
Descriptors: Programming Languages, Computer Science Education, Intelligent Tutoring Systems, Thinking Skills
Oliveira, Eduardo; de Barba, Paula; Corrin, Linda – Australasian Journal of Educational Technology, 2021
Smart learning environments (SLE) provide students with opportunities to interact with learning resources and activities in ways that are customised to their particular learning goals and approaches. A challenge in developing SLEs is providing resources and tasks within a single system that can seamlessly tailor learning experience in terms of…
Descriptors: Educational Technology, Technology Uses in Education, Artificial Intelligence, Undergraduate Students
Mao, Ye; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Modeling student learning processes is highly complex since it is influenced by many factors such as motivation and learning habits. The high volume of features and tools provided by computer-based learning environments confounds the task of tracking student knowledge even further. Deep Learning models such as Long-Short Term Memory (LSTMs) and…
Descriptors: Time, Models, Artificial Intelligence, Bayesian Statistics
Mousavinasab, Elham; Zarifsanaiey, Nahid; R. Niakan Kalhori, Sharareh; Rakhshan, Mahnaz; Keikha, Leila; Ghazi Saeedi, Marjan – Interactive Learning Environments, 2021
With the rapid growth of technology, computer learning has become increasingly integrated with artificial intelligence techniques in order to develop more personalized educational systems. These systems are known as Intelligent Tutoring systems (ITSs). This paper focused on the variant characteristics of ITSs developed across different educational…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Individualized Instruction, Web Based Instruction
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
Chen, Ling-Hsiu – Computers & Education, 2011
Although conventional student assessments are extremely convenient for calculating student scores, they do not conceptualize how students organize their knowledge. Therefore, teachers and students rarely understand how to improve their future learning progress. The limitations of conventional testing methods indicate the importance of accurately…
Descriptors: Foreign Countries, Educational Technology, Cognitive Style, Self Efficacy
Kert, Serhat Bahadir; Kurt, Adile Askim – Interactive Learning Environments, 2012
Electronic performance support systems (EPSSs) are the software programs commonly used in commercial environments since the early 1990s. These software programs are generally called performance-based systems and focus on the complete job rather than providing individual development. For that reason, the usage of these systems in learning…
Descriptors: Foreign Countries, Web Based Instruction, Program Effectiveness, Learning Strategies
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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
Tseng, Shian-Shyong; Su, Jun-Ming; Hwang, Gwo-Jen; Hwang, Gwo-Haur; Tsai, Chin-Chung; Tsai, Chang-Jiun – Educational Technology & Society, 2008
The popularity of web-based learning systems has encouraged researchers to pay attention to several new issues. One of the most important issues is the development of new techniques to provide personalized teaching materials. Although several frameworks or methods have been proposed, it remains a challenging issue to design an easy-to-realize…
Descriptors: Computer Assisted Instruction, Educational Technology, Individualized Instruction, Intelligent Tutoring Systems
Karampiperis, Pythagoras; Sampson, Demetrios – Educational Technology & Society, 2005
Adaptive learning resources selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems (AEHS). In order to adaptively select and sequence learning resources in AEHS, the definition of adaptation rules contained in the Adaptation Model, is required. Although, some efforts have…
Descriptors: Methods, Educational Resources, Models, Individualized Instruction