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Jin Wang; Wenxiang Fan – Journal of Computer Assisted Learning, 2025
Background: For students, digital literacy is an essential competency, and technology-supported learning has become one of the most crucial methods for developing students' digital literacy. However, no academic consensus exists regarding whether technology-supported learning is effective in improving students' digital literacy. Objectives: This…
Descriptors: Technological Literacy, Technology Uses in Education, Program Effectiveness, Influences
Jelle Wemmenhove; Dorina Bór; Rianne Conijn; Jim Portegies – Journal of Computer Assisted Learning, 2025
Background: Recently human-centred design plays an increasing role in learning analytics, however this approach is mostly lacking in the design and evaluation of Intelligent Tutoring Systems (ITSs). A potential way to incorporate human-centred design principles in ITS development is by adopting a service design approach. Objectives: This article…
Descriptors: Intelligent Tutoring Systems, Program Evaluation, Design, Stakeholders
Maria Priego-Ojeda; Gemma Filella-Guiu; Núria Pérez-Escoda – Journal of Computer Assisted Learning, 2025
Background: Video games can be innovative, educational and therapeutic tools that have demonstrated positive outcomes in enhancing emotional skills. Many of these programmes have shown benefits in improving children and adolescents' emotional competencies, but there is a lack of research evidence on programmes that aim to intervene within the…
Descriptors: Educational Games, Parent Education, Parent Attitudes, Emotional Experience
Kairit Tammets; Kaire Kollom; Tobias Ley; Paula Joanna Sillat; Manisha Khulbe – Journal of Computer Assisted Learning, 2025
Background Study: Learning Analytics (LA) has emerged as a powerful tool for personalising learning, gaining insights into students' learning processes, and enhancing teachers' reflective practices and awareness. Over the past decades, extensive research has been conducted to understand the factors that play a crucial role in the adoption of…
Descriptors: Training, Instructional Design, Individual Characteristics, Intention
Eleftheria Siklafidou; Maya Satratzemi; Stelios Xinogalos – Journal of Computer Assisted Learning, 2025
Background: Serious games (SGs) have been increasingly utilised in various domains of education and training. These SGs are a compelling and impactful pedagogical tool that have demonstrated the potential to transform users' perspectives in a multitude of fields, including music. Objectives: This paper presents a systematic literature review (SLR)…
Descriptors: Music Education, Game Based Learning, Teaching Methods, Musical Instruments
Tsung-Yen Chuang; Szu-Kai Tsai; Yu-Hsuan Lu – Journal of Computer Assisted Learning, 2025
Background: Current education increasingly emphasises the development and significance of Critical Thinking (CT), aiming to enhance individuals' adaptability in a rapidly evolving society. However, few effective teaching methods have been identified for integrating CT into existing on-site courses. While previous studies have focused on the…
Descriptors: Game Based Learning, Critical Thinking, Thinking Skills, Technology Uses in Education
Petri Nokelainen; Terhi Kaarakka; Jani Hirvonen; Ilmari Puhakka; Riikka Kangaslampi; Simo Ali-Löytty; Vikke Vuorenpää; Elina Viro – Journal of Computer Assisted Learning, 2025
Background: First-year engineering mathematics courses present a critical academic challenge, often leading to a significant decline in student self-efficacy, a key predictor of retention and success. While flipped learning is a proposed solution, a lack of longitudinal research using robust comparison groups has limited our understanding of its…
Descriptors: Flipped Classroom, Self Efficacy, Emotional Response, Engineering Education
Mohamed Ali Nagy Elmaadaway; Mohamed Elsayed El-Naggar; Mohamed Radwan Ibrahim Abouhashesh – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) made substantial progress with language recognition. Proficiency in spoken English reading is a prerequisite for fluency in written English. However, research on its use, especially for non-native speakers, is lacking despite increased usage. Objectives: This study aimed to enhance the oral reading fluency…
Descriptors: Artificial Intelligence, Reading Fluency, Elementary School Students, Oral Reading
Chen-Chen Liu; Hai-Jie Wang; Gwo-Jen Hwang; Yun-Fang Tu; Youmei Wang; Kai Chen – Journal of Computer Assisted Learning, 2025
Background: Vocal music education is a skill-oriented course. Students not only need to improve their skills through repeated practice, but also need to learn self-reflection on their singing skills to achieve improvement in their vocal music performance. To promote students' reflection, previous studies have introduced peer assessment (PA) in…
Descriptors: Music Education, Singing, Skill Development, Reflection
Osman Özdemir – Journal of Computer Assisted Learning, 2025
Background: In recent years, the widespread use of technology in classrooms has encouraged the transition from traditional lecture methods to digital-based learning environments. Technological game-based learning platforms, such as Kahoot!, which are used to encourage students' active participation and interaction in learning environments, are…
Descriptors: Game Based Learning, Video Games, Academic Achievement, Student Motivation
Seyma Çaglar-Özhan; Perihan Tekeli; Selay Arkün-Kocadere – Journal of Computer Assisted Learning, 2025
Background: Feedback is an essential part of the educational process as it enriches students' learning experiences, provides information about their current performance, shows them what is lacking in achieving goals, and provides guidance on the strategies needed to achieve those goals. Teachers, especially in crowded classrooms, often have…
Descriptors: Feedback (Response), Artificial Intelligence, Teacher Role, Technology Uses in Education
Pei-Ching Ngu; Chih-Chung Chien; Huei-Tse Hou – Journal of Computer Assisted Learning, 2025
Background: Situated simulation is a pedagogical method used for on-the-job training in many occupations. Establishing a framework that uses mobile devices to provide both simulation elements and incorporates instant feedback as reasoning scaffolding is a promising and relatively unexplored research topic. Objective: In this study, we designed a…
Descriptors: Decision Making, Educational Games, Handheld Devices, Simulation
Chorng-Shiuh Koong; Chih-Hung Chen; Yu-Tzu Chen; Gwo-Haur Hwang – Journal of Computer Assisted Learning, 2025
Background: Rhythm is the fundamental element of music and one of the indispensable aspects of training in music education, making it highly valued. However, due to the limitations of teaching hours and the large number of students in each class, it is difficult to foster the rhythm ability of elementary school students. Objectives: Hence, this…
Descriptors: Music Education, Telecommunications, Handheld Devices, Teaching Methods
Jyun-Chen Chen; Chia-Yu Liu – Journal of Computer Assisted Learning, 2025
Background: Based on the embodied cognition perspective, interdisciplinary hands-on learning combines several disciplines, such as science, technology, engineering and mathematics (STEM), to improve students' capacity to solve real-world problems. Despite the popularity of interdisciplinary hands-on learning, particularly the six-phase 6E model,…
Descriptors: Interdisciplinary Approach, Experiential Learning, STEM Education, Problem Solving
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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