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Kamil Çelik; Ahmet Ayaz – Educational Technology Research and Development, 2025
Technological advancements in recent years have accelerated the development of information and communication technologies, introducing numerous innovations. One prominent innovation is the concept of the metaverse, which has gained significant popularity and is increasingly influencing various sectors, including the economy, art, entertainment,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intention, Computer Science Education
Md Al Amin; Yang Sok Kim; Mijin Noh – Education and Information Technologies, 2025
The introduction of artificial intelligence technologies like ChatGPT has brought a revolution in various sectors, including higher education. The study aims to examine the drivers that influence ChatGPT adoption among students in higher studies in Bangladesh. This study combined UTAUT model components with constructs such as perceived knowledge…
Descriptors: Trust (Psychology), Artificial Intelligence, Computer Software, Social Influences
Poe, Laura; Mew, Lionel – Industry and Higher Education, 2022
The objective of traditional software development courses focuses on competencies in the programming languages and technical tools. Project methodologies and software development are typically taught as theory-driven and separate courses in Information Systems undergraduate programs. Rather than teaching project methodologies as secondary to the…
Descriptors: Computer Software, Active Learning, Courses, Teaching Methods
McEneaney, John; Morsink, Paul – Journal of Learning Analytics, 2022
Learning analytics (LA) provides tools to analyze historical data with the goal of better understanding how curricular structures and features have impacted student learning. Forward-looking curriculum design, however, frequently involves a degree of uncertainty. Historical data may be unavailable, a contemplated modification to curriculum may be…
Descriptors: Curriculum Design, Learning Analytics, Educational Change, Computer Software
Ishartono, Naufal; Nurcahyo, Adi; bin Sufahani, Suliadi Firdaus; Afiyah, Asyifa Nur – Asian Journal of University Education, 2022
Many studies show the effectiveness of using the Flipped Learning model to increase students' understanding. However, there are scant research results that integrate PowerPoint in Flipped Learning to improve students' understanding. The present study aimed to describe the effectiveness of the PowerPoint-Based Flipped Learning model in increasing…
Descriptors: Computer Software, Flipped Classroom, Technology Integration, College Students
Jian-Hong Ye; Mengmeng Zhang; Weiguaju Nong; Li Wang; Xiantong Yang – Education and Information Technologies, 2025
ChatGPT, as an example of generative artificial intelligence, possesses high-level conversational and problem-solving capabilities supported by powerful computational models and big data. However, the powerful performance of ChatGPT might enhance learner dependency. Although it has not yet been confirmed, many teachers and scholars are also…
Descriptors: Artificial Intelligence, College Students, Problem Solving, Student Attitudes
Thomas, Paul J.; Patel, Devang; Magana, Alejandra J. – ACM Transactions on Computing Education, 2021
Software modeling is an integral practice for software engineers, especially as the complexity of software solutions increases. Unified Modeling Language (UML) is the industry standard for software modeling. however, it is often used incorrectly and misunderstood by novice software designers. This study is centered around understanding patterns of…
Descriptors: Computer Science Education, Models, Computer Software, Programming Languages
Thomas, Paul JoseKutty – ProQuest LLC, 2021
Software modeling is an integral practice for software engineers especially as the complexity of software solutions increase. There is precedent in industry to model information systems in terms of functions, structures, and behaviors. While constructing these models, abstraction and systems thinking are employed to determine elements essential to…
Descriptors: Computer Science Education, Programming Languages, Academic Achievement, College Students
Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
Felipe A. Feichas; Rodrigo D. Seabra – Informatics in Education, 2023
This research discusses the use of a gamified web platform for studying software modeling with Unified Modeling Language (UML). Although UML is constantly being improved and studied, many works show that there is difficulty in teaching and learning the subject, due to the complexity of its concepts and the students' cognitive difficulties with…
Descriptors: Gamification, Computer Software, Models, Teaching Methods
Yizhuo Zhou; Xuande Wu; Kunyang Qu – Language Teaching Research Quarterly, 2024
Recent advancements in artificial intelligence, particularly OpenAI's ChatGPT, have transformed English language learning through Computer-Assisted Language Learning (CALL) tools. This study examined the adoption of ChatGPT among university-level English learners employing the Hedonic Motivation System Adoption Model (HMSAM). An online survey was…
Descriptors: Artificial Intelligence, Computer Software, English (Second Language), Second Language Learning
Martínez, Salvador; Wimmer, Manuel; Cabot, Jordi – Computer Science Education, 2020
Background and Context: Reports suggest plagiarism is a common occurrence in universities. While plagiarism detection mechanisms exist for textual artifacts, this is less so for non-code related ones such as software design artifacts like models, metamodels or model transformations. Objective: To provide an efficient mechanism for the detection of…
Descriptors: Plagiarism, Identification, Computer Software, Computer Uses in Education
Silvia García-Méndez; Francisco de Arriba-Pérez; Francisco J. González-Castaño – International Association for Development of the Information Society, 2023
Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…
Descriptors: Higher Education, Artificial Intelligence, Computer Software, Usability
Khan, Md Akib Zabed; Polyzou, Agoritsa – International Educational Data Mining Society, 2023
Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…
Descriptors: Course Selection (Students), Learning Analytics, Academic Advising, Decision Making
Jimenez, Fernando; Paoletti, Alessia; Sanchez, Gracia; Sciavicco, Guido – IEEE Transactions on Learning Technologies, 2019
In the European academic systems, the public funding to single universities depends on many factors, which are periodically evaluated. One of such factors is the rate of success, that is, the rate of students that do complete their course of study. At many levels, therefore, there is an increasing interest in being able to predict the risk that a…
Descriptors: Prediction, Risk, Dropouts, College Students