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Ankora, Carlos; Bolatimi, Stephen Oladagba; Bensah, Lily; Mahama, Francois; Kuadey, Noble Arden; Adu, Adolph Sedem Yaw; Adjei, Laurene – Journal of Computer Assisted Learning, 2023
Background: The degree to which Computer Science (CS) and Information Communication Technology (ICT) students are motivated to learn greatly impacts their study habits, academic achievement in school and ultimately their job prospects. In recent times, skills in programming languages have become vital in searching for employment. Objective: This…
Descriptors: College Students, Student Motivation, Course Selection (Students), Programming Languages
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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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Zhihui Cai; Caiyan Liu; Jieni Zhan; Zhikeng Wang; Xin Hao; Si Zhang; Xinjie Chen – Journal of Computer Assisted Learning, 2025
Background: Attention has been paid to collaboration in digital game-based learning, as it fosters interaction and student engagement, thereby enhancing learning outcomes. Previous findings about the effect of collaboration in digital game-based learning were inconsistent, and few studies have explored the underlying mechanisms, particularly…
Descriptors: Cooperative Learning, Computer Games, Game Based Learning, Learning Experience
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Wenji Wang; Wenjuan Wang – Journal of Computer Assisted Learning, 2025
Background Study: The combination of artificial intelligence (AI) and foreign language learning is emerging as a significant trend in language education. Objectives: This study aimed to investigate the impact of technology acceptance, attitude and motivation on behavioural intentions regarding the use of AI in language learning. Methods:…
Descriptors: College Students, Student Behavior, Intention, Educational Technology
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Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
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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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Hatice Yildiz Durak – Journal of Computer Assisted Learning, 2024
Background: Collaboration is a crucial concept in learning and has the potential to foster learning. However, the fact that collaborative groups act with a common understanding in a common task brings many difficulties. Therefore, there is a need for group regulation and guidance to support effective group regulation in collaborative learning. On…
Descriptors: Feedback (Response), Groups, Group Guidance, Cooperation
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Lu, Kaili; Pang, Feng; Shadiev, Rustam – Journal of Computer Assisted Learning, 2023
Background: Inquiry-based learning is a salient instructional approach to cultivate students' higher order thinking skills (HOTS). With the presence and advancement of new technologies, their usage for inquiry learning in university context is increasingly ubiquitous. However, in most circumstances, college students cannot integrate technologies…
Descriptors: College Students, Technology Uses in Education, Teaching Methods, Thinking Skills
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van Harsel, Milou; Hoogerheide, Vincent; Verkoeijen, Peter; van Gog, Tamara – Journal of Computer Assisted Learning, 2022
Nowadays, students often practice problem-solving skills in online learning environments with the help of examples and problems. This requires them to self-regulate their learning. It is questionable how novices self-regulate their learning from examples and problems and whether they need support. The present study investigated the open questions:…
Descriptors: Sequential Learning, Independent Study, Problem Solving, Electronic Learning
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Alamer, Abdullah; Al Khateeb, Ahmed; Jeno, Lucas M. – Journal of Computer Assisted Learning, 2023
Background: Mobile-assisted language learning (MALL) has long been advocated to promote students' language study outcomes. However, little is known about how using instant messaging applications (an example of MALL) affect student motivation, language anxiety, and actual achievement. Objectives: To help close this gap, we have conducted a…
Descriptors: Foreign Countries, College Students, Synchronous Communication, Handheld Devices
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Liping Jiang; Menglei Lv; Mengmeng Cheng; Xia Chen; Changhong Peng – Journal of Computer Assisted Learning, 2024
Background: The introduction of Small Private Online Courses (SPOCs) in English as a Foreign Language (EFL) instruction at Higher Vocational Colleges (HVCs) signifies a shift in education. Understanding the factors that affect deep learning in this SPOC context is crucial for improving educational outcomes. Objectives: By employing grounded…
Descriptors: Higher Education, Vocational Education, College Students, Private Education
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Truzoli, Roberto; Viganò, Caterina; Galmozzi, Paolo Gabriele; Reed, Phil – Journal of Computer Assisted Learning, 2020
The current study explored the relationship between problematic internet use (PIU) and motivation to learn, and examined psychological and social factors mediating this relationship. Two hundred and eighty-five students in an Italian University were recruited for the current study. There was a negative relationship between PIU and motivation to…
Descriptors: Internet, Learning Motivation, College Students, Psychological Patterns
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Wang, Cong; Zhu, Sida; Zhang, Haijing – Journal of Computer Assisted Learning, 2023
Background: Since the outbreak of COVID-19, universities in Hong Kong have implemented online and hybrid teaching modes, making computer-assisted language learning (CALL) a primary way for English learning. Research on English learning motivation and self-regulation has seldom considered learners' emotions (satisfaction and preparedness) and the…
Descriptors: Foreign Countries, Student Motivation, Online Courses, English (Second Language)
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Luciana Maria Cavichioli Gomes Almeida; Stefan Münzer; Tim Kühl – Journal of Computer Assisted Learning, 2024
Background: According to the personalization effect in multimedia learning, the use of personal and possessive pronouns in instructional materials (e.g., 'you' and 'your') is beneficial. However, current research suggests that the personalization effect is inverted for emotionally aversive content (e.g., illnesses). Objective: This study…
Descriptors: Foreign Countries, Health Education, Health Promotion, Information Sources
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Fu, En; Gao, Qiufeng; Wei, Chuqian; Chen, Qianyi; Liu, Yijun – Journal of Computer Assisted Learning, 2021
Smartphone use in learning settings is a common behaviour amongst college students. Building on the theory of consumerism, self-efficacy and addictive behaviours, the current study developed a three-component conceptual framework to understand college students' smartphone use in organizational as well as self-directed learning settings. One…
Descriptors: Foreign Countries, College Students, Handheld Devices, Telecommunications
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