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Tamisha Thompson; Jennifer St. John; Siddhartha Pradhan; Erin Ottmar – Journal of Computer Assisted Learning, 2025
Background: Educational technologies typically provide teachers with analytics regarding student proficiency, but few digital tools provide teachers with process-based information about students' variable problem-solving strategies as they solve problems. Utilising design thinking and co-designing with teachers can provide insight to researchers…
Descriptors: Mathematics Instruction, Educational Technology, Problem Solving, Instructional Design
Hahnel, Carolin; Ramalingam, Dara; Kroehne, Ulf; Goldhammer, Frank – Journal of Computer Assisted Learning, 2023
Background: Computer-based assessment allows for the monitoring of reader behaviour. The identification of patterns in this behaviour can provide insights that may be useful in informing educational interventions. Objectives: Our study aims to explore what different patterns of reading activity exist, and investigates their interpretation and…
Descriptors: Reading Habits, Student Behavior, Hypermedia, Educational Assessment
Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
Peijian Paul Sun; Zeqi Ren; Xian Zhao – Journal of Computer Assisted Learning, 2025
Background: Student engagement has been conceptualised and operationalised in various learning environments. However, there is currently a lack of established scales to measure student engagement in synchronous online learning. One possible reason is the existence of the conceptual and structural ambiguity regarding student engagement. Objective:…
Descriptors: Student Participation, Second Language Learning, Synchronous Communication, Electronic Learning
Thao Pham; Wu-Yuin Hwang; Xuan-Lam Pham – Journal of Computer Assisted Learning, 2024
Background: Examining student attention in physical classrooms is crucial, but it faces challenges due to the lack of accurate monitoring. Constraints posed by device limitations and the design of educational materials impede the integration of eye-tracking technology in these settings. Objectives: This study aims to (1) develop a wearable…
Descriptors: Attention, Eye Movements, Physical Environment, Classroom Environment
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
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
Lämsä, Joni; Mannonen, Joonas; Tuhkala, Ari; Heilala, Ville; Helovuo, Arto; Tynkkynen, Ilkka; Lampi, Emilia; Sipiläinen, Katriina; Kärkkäinen, Tommi; Hämäläinen, Raija – Journal of Computer Assisted Learning, 2023
Background: Cognitive load (CL) management is essential in safety-critical fields so that professionals can monitor and control their cognitive resources efficiently to perform and solve scenarios in a timely and safe manner, even in complex and unexpected circumstances. Thus, cognitive load theory (CLT) can be used to design virtual reality (VR)…
Descriptors: Cognitive Processes, Difficulty Level, Computer Simulation, Flight Training
Zhongling Pi; Xuran Li; Mengjie Tong; Xin Zhao; Jiayu Wang; Xiying Li; Xiangchao Guo – Journal of Computer Assisted Learning, 2025
Background: Instructors' facial expressions in instructional videos can greatly influence how learners perceive their emotions, thereby affecting students' attention to the learning content and their overall performance. While the short-term effects of instructors' specific facial expressions in instructional videos have been well documented, less…
Descriptors: Video Technology, Technology Uses in Education, Teacher Behavior, Nonverbal Communication
Jansen, Renée S.; Leeuwen, Anouschka; Janssen, Jeroen; Kester, Liesbeth – Journal of Computer Assisted Learning, 2022
Background: Learners in Massive Open Online Courses (MOOCs) are presented with great autonomy over their learning process. Learners must engage in self-regulated learning (SRL) to handle this autonomy. It is assumed that learners' SRL, through monitoring and control, influences learners' behaviour within the MOOC environment (e.g., watching…
Descriptors: Student Behavior, Learning Processes, Online Courses, Personal Autonomy
Yin-Rong Zhang; Zhong-Mei Han; Tao He; Chang-Qin Huang; Fan Jiang; Gang Yang; Xue-Mei Wu – Journal of Computer Assisted Learning, 2025
Background: Collaborative programming is important and challenging for K12 students. Scaffolding is a vital method to support students' collaborative programming learning. However, conventional scaffolding that does not fade may lead students to become overly dependent, resulting in unsatisfactory programming performance. Objectives: This study…
Descriptors: Middle School Students, Grade 8, Scaffolding (Teaching Technique), Programming
Slaviša Radovic; Niels Seidel; Joerg M. Haake; Regina Kasakowskij – Journal of Computer Assisted Learning, 2024
Background: Self-assessment serves to improve learning through timely feedback on one's solution and iterative refinement as a way to improve one's competence. However, the complexity of the self-assessment process is widely recognized, as well as that students can benefit from it only if their assessment is accurate enough. Objectives: In order…
Descriptors: Self Evaluation (Individuals), Distance Education, Student Behavior, Accuracy
Lanqin Zheng; Yunchao Fan; Zichen Huang; Lei Gao – Journal of Computer Assisted Learning, 2024
Background: Online collaborative learning has been widely adopted in the field of education. However, learners often find it difficult to engage in collaboratively building knowledge and jointly regulating online collaborative learning. Objectives: The study compared the impacts of the three learning approaches on collaborative knowledge building,…
Descriptors: Cooperative Learning, Electronic Learning, College Students, Learning Strategies
Chia-Chen Chen; Man-Hong Chai; Pei-Hsuan Lin – Journal of Computer Assisted Learning, 2025
Background: Environmental education is crucial for promoting pro-environmental attitudes and behavior change. However, traditional teaching methods may not effectively engage learners in environmental protection. This study aims to address the limitations of traditional teaching methods and contribute to the development of effective environmental…
Descriptors: Multimedia Materials, Electronic Publishing, Books, Environmental Education
Josef Šedlbauer; Jan Cincera; Martin Slavík; Adéla Hartlová – Journal of Computer Assisted Learning, 2024
Background: The emergence of Generative Artificial Intelligence has brought a number of ethical and practical issues to higher education. Solid experimental evidence is yet inadequate to set the functional rules for the new technology. Objectives: The objective of this study is to analyse the experience of undergraduate students' interaction with…
Descriptors: Artificial Intelligence, Higher Education, Undergraduate Students, Interaction

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