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Showing 1 to 15 of 178 results Save | Export
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Ferhan Sahin; Gizem Yildiz – Journal of Computer Assisted Learning, 2024
Background: Despite the significant emphasis on self-determination in special education and the crucial role of mobile learning, there is a notable absence of path modelling studies that explore the effect of self-determination on the usage of mobile learning by students with special needs. Objectives: This study sought to investigate the…
Descriptors: College Students, Special Needs Students, Assistive Technology, Electronic Learning
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Joaquín Jiménez-Puerto; Gianni Gallello – Journal of Computer Assisted Learning, 2025
Background: In the dynamic landscape of higher education, innovation through gamification has emerged as a successful approach to enhance student learning and motivation. Archaeological studies have particularly benefited from innovative pedagogy, as traditional teaching methods often struggle to engage younger generations. Aims: To evaluate the…
Descriptors: Archaeology, Instructional Innovation, History Instruction, College Students
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Yun Zhang; Fangzheng Zhao; Richard E. Mayer – Journal of Computer Assisted Learning, 2025
Background and Objective: The positivity principle states that students learn better from instructors who display positive rather than negative or neutral emotions in multimedia lessons (Lawson et al. 2021a). This study extends this work by exploring the role of affective and social cues displayed by feedback providers, such as their emotional…
Descriptors: Multimedia Instruction, Psychological Patterns, Feedback (Response), Gender Differences
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Chengliang Wang; Xiaojiao Chen; Zhebing Hu; Sheng Jin; Xiaoqing Gu – Journal of Computer Assisted Learning, 2025
Background: ChatGPT, as a cutting-edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and educational equity. Existing studies have not fully explored learners' intentions to adopt artificial intelligence generated content (AIGC) technology, highlighting the need…
Descriptors: College Students, Student Attitudes, Computer Attitudes, Computer Uses in Education
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Fuxing Wang; Xiaoxue Leng; Ziyi Kuang; Tingting Zhao – Journal of Computer Assisted Learning, 2025
Background: Both eye movement modelling examples (EMMEs) and cues guide attention and improve learning in multimedia learning environments. EMME can act as a special form of cue. However, no studies have directly examined whether EMME would be superior to visual cues. Objective: The study was to investigate whether there were advantages of EMME…
Descriptors: Eye Movements, Cues, Attention, Multimedia Instruction
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Heping Xie; Zongkui Zhou – Journal of Computer Assisted Learning, 2024
Background: Drawing is generally regarded as a promising learning strategy and has been explored in the touchscreen setting with different drawing modes. Although both a finger and a digital pencil can help individuals complete drawing activities effortlessly on touchscreen devices, there is no guarantee that they show the same effect on learning,…
Descriptors: Computer System Design, Visual Aids, Eye Movements, Freehand Drawing
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Olga Viberg; Martine Baars; Rafael Ferreira Mello; Niels Weerheim; Daniel Spikol; Cristian Bogdan; Dragan Gasevic; Fred Paas – Journal of Computer Assisted Learning, 2024
Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported…
Descriptors: Feedback (Response), Peer Evaluation, Computer Assisted Instruction, Cooperative Learning
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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
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Wollny, Sebastian; Di Mitri, Daniele; Jivet, Ioana; Muñoz-Merino, Pedro; Scheffel, Maren; Schneider, Jan; Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gaševic, Dragan; Drachsler, Hendrik – Journal of Computer Assisted Learning, 2023
Background: Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners and their contexts to gain insights into learning processes. As the technology of Learning Analytics is evolving, many systems are being implemented. In this context, it is essential to understand stakeholders'…
Descriptors: Foreign Countries, College Students, Learning Analytics, Expectation
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Fan, Yizhou; Rakovic, Mladen; van der Graaf, Joep; Lim, Lyn; Singh, Shaveen; Moore, Johanna; Molenaar, Inge; Bannert, Maria; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Many learners struggle to productively self-regulate their learning. To support the learners' self-regulated learning (SRL) and boost their achievement, it is essential to understand the cognitive and metacognitive processes that underlie SRL. To measure these processes, contemporary SRL researchers have largely utilized think aloud or…
Descriptors: Learning Strategies, Self Management, Protocol Analysis, Data Analysis
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Dominic Lohr; Hieke Keuning; Natalie Kiesler – Journal of Computer Assisted Learning, 2025
Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…
Descriptors: College Students, Programming, Artificial Intelligence, Feedback (Response)
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Saleh Alhazbi; Afnan Al-ali; Aliya Tabassum; Abdulla Al-Ali; Ahmed Al-Emadi; Tamer Khattab; Mahmood A. Hasan – Journal of Computer Assisted Learning, 2024
Background: Measuring students' self-regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self-report questionnaires and think aloud protocols have been used to measure self-regulated learning skills (SRL). However, these methods are…
Descriptors: Learning Analytics, Independent Study, Higher Education, College Students
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Jian Li; Zhaojie Wang; Shubin Zhao – Journal of Computer Assisted Learning, 2025
Background: In today's high-tech society, the relationship between social networks and the formation of political orientation and socio-political activity within the student environment has become a key subject of research. Objectives: The aim of this article is to investigate the correlations between the influence of various social media…
Descriptors: College Students, Social Networks, Social Media, Political Influences
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Zhicheng Dai; Ling Wang; Xian Peng; Liang Zhao; Junxia Xiong – Journal of Computer Assisted Learning, 2024
Background: Smart classroom environment has drawn worldwide attention, however, there is still a lack of studies that can explore and analyse potential factors, which affect students' satisfaction with smart classrooms in higher education. Objectives: To assess students' satisfaction with smart classrooms in higher education, this study proposed…
Descriptors: Student Satisfaction, Classroom Environment, College Students, Educational Technology
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Sayginer, Senol; Tüzün, Hakan – Journal of Computer Assisted Learning, 2023
Background: Studies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or to the level of learners. Moreover, studies that present evidence of the effectiveness of block-based environments by comparing…
Descriptors: Programming, Academic Achievement, Logical Thinking, Thinking Skills
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