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Hai-Jie Wang; Kai Chen; Youmei Wang; Chen-Chen Liu – Journal of Computer Assisted Learning, 2025
Background: Vocal music is a multifaceted subject, as students not only need to master skills but also to appreciate and critically interpret the singing process. Conventional vocal music learning methods emphasise practice and feedback, but deeper learning often stems from reflective assessment, especially when students adopt the perspective of…
Descriptors: Music Education, Teaching Methods, Singing, Music Appreciation
Fangzheng Zhao; Richard E. Mayer – Journal of Computer Assisted Learning, 2025
Introduction: While prior research has delved into the emotional aspects of instructional design, it has not extensively examined whether integrating affective features specifically relevant to the theme of the learning materials is essential for enhancing learning effectiveness compared to incorporating general affective features. This study aims…
Descriptors: Multimedia Instruction, Teaching Methods, Cartoons, Psychological Patterns
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
Ahmed Tlili; Soheil Salha; Juan Garzón; Mouna Denden; Kinshuk; Saida Affouneh; Daniel Burgos – Journal of Computer Assisted Learning, 2024
Background Study: Several meta-analysis studies have investigated the effects of mobile learning on learning performance. However, limited attention has been paid to pedagogy in mobile learning, making quantitative evidence of the effects of pedagogical approaches on learning performance in mobile learning scarce. Filling this gap can therefore…
Descriptors: Teaching Methods, Instructional Effectiveness, Electronic Learning, Student Experience
Suping Yi; Wayan Sintawati; Yibing Zhang – Journal of Computer Assisted Learning, 2025
Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…
Descriptors: Reflection, Feedback (Response), Cooperative Learning, Natural Language Processing
Qian Tian; Xudong Zheng – Journal of Computer Assisted Learning, 2024
Background: During the COVID-19 pandemic, online collaborative problem solving (online CPS) has become one of the most crucial learning methods to develop students' learning performance. However, it remains unclear of the effectiveness of the online CPS method on students' learning performance. Objectives: To explore the overall effect of online…
Descriptors: Electronic Learning, COVID-19, Pandemics, Teaching Methods
Adi Perry-Kates; Anat Cohen – Journal of Computer Assisted Learning, 2025
Background: In light of the growing need to understand interactive learning effectivity and especially post-COVID 19 pandemic constraints, the key question is how to develop interactive videos in order to get the most effective results. Objectives: This research aims to explore the pedagogical benefits of interactive video with branching…
Descriptors: Video Technology, Interaction, Instructional Effectiveness, Teaching Methods
Qin Wang; Yanping Li – Journal of Computer Assisted Learning, 2024
Background: Virtual reality (VR), augmented reality (AR) and mixed reality (MR) have sparked recently in improving the effectiveness of teacher education. However, there is a lack of review regarding the utilisation of these technologies in this field. These three technologies, namely VR, AR and MR, can be collectively referred to as extended…
Descriptors: Computer Simulation, Technology Uses in Education, Teaching Methods, Educational Improvement
Radovan Šikl; Karla Brücknerová; Hana Švedová; Filip Dechterenko; Pavel Ugwitz; Jirí Chmelík; Hana Pokorná; Vojtech Jurík – Journal of Computer Assisted Learning, 2024
Introduction: Media comparison studies examining the effectiveness of immersive virtual reality in education have yielded inconclusive findings, leaving the question of its impact on learning compared to conventional media unanswered. To address this issue, our study employs a novel approach that combines media comparison with an investigation on…
Descriptors: Computer Simulation, Educational Technology, Secondary School Students, Topography
Topali, Paraskevi; Chounta, Irene-Angelica; Martínez-Monés, Alejandra; Dimitriadis, Yannis – Journal of Computer Assisted Learning, 2023
Background: Providing feedback in massive open online courses (MOOCs) is challenging due to the massiveness and heterogeneity of learners' population. Learning analytics (LA) solutions aim at scaling up feedback interventions and supporting instructors in this endeavour. Paper Objectives: This paper focuses on instructor-led feedback mediated by…
Descriptors: Teaching Methods, Learning Analytics, Feedback (Response), MOOCs
Xu, Xinhao; Kang, Jina; Yan, Lili – Journal of Computer Assisted Learning, 2022
Objective: The aim of this current paper is to investigate the salient embodiment features in the empirical studies on technology-enabled embodied learning environments (TEELEs), and to contribute a comprehensive conceptual framework to direct the understanding and the designing of TEELEs -- to embody and how to embody. Method: In this thematic…
Descriptors: Technology Uses in Education, Educational Environment, Literature Reviews, Teaching Methods
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
Yiwen Jin; Lies Sercu – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence has been reshaping many industries, and education is no exception. When ChatGPT burst onto the scene in late 2022, it ignited conversations among educators and researchers alike. Despite growing interest and experimentation with this technology in university classrooms, the field has been missing a comprehensive…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Higher Education
J. Weidlich; D. Gaševic; H. Drachsler; P. Kirschner – Journal of Computer Assisted Learning, 2025
Background: As researchers rush to investigate the potential of AI tools like ChatGPT to enhance learning, well-documented pitfalls threaten the validity of this emerging research. Issues of media comparison research, where the confounding of instructional methods and technological affordances is unrecognised, may render effects uninterpretable.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits, Barriers
Anne Husted Henriksen; Marta Topor; Gustav Bøg Petersen; Rasmus Ahmt Rohde; Linn Damsgaard; Anne-Mette Veber Nielsen; Andreas Wulff-Abramsson; Guido Makransky; Jacob Wienecke – Journal of Computer Assisted Learning, 2025
Background: The study was motivated by the need to enhance children's literacy skills through innovative teaching methods. This research aims to address limitations in regular classroom teaching by exploring embodied learning and virtual reality (VR) as potential solutions. Objectives: The primary aim of the study was to investigate the effects of…
Descriptors: Young Children, Literacy, Intervention, Teaching Methods

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