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Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention
Liru Hu; Gaowei Chen; Jiajun Wu – Journal of Computer Assisted Learning, 2024
Background: The existing research on dialogue-based learning and teaching predominantly highlights its capacity to yield productive educational outcomes, yet it often overlooks the pivotal factor of participation equity, which is fundamental to ensuring the efficacy of dialogic teaching and learning. Objectives: In this study, participation equity…
Descriptors: Problem Solving, Participation, Equal Education, Student Participation
Pramila-Savukoski, Sari; Kärnä, Raila; Kuivila, Heli-Maria; Oikarainen, Ashlee; Törmänen, Tiina; Juntunen, Jonna; Järvelä, Sanna; Mikkonen, Kristina – Journal of Computer Assisted Learning, 2023
Background: Health sciences education prepares students for social- and healthcare by developing evidence-based nursing, leadership and working life skills, including collaboration. Due to the changes caused by the global pandemic, health sciences education has shifted more to online and hybrid contexts, which can challenge students' competence…
Descriptors: Competence, Health Sciences, Student Development, Blended Learning
Angxuan Chen; Yuyue Zhang; Jiyou Jia; Min Liang; Yingying Cha; Cher Ping Lim – Journal of Computer Assisted Learning, 2025
Background: Language assessment plays a pivotal role in language education, serving as a bridge between students' understanding and educators' instructional approaches. Recently, advancements in Artificial Intelligence (AI) technologies have introduced transformative possibilities for automating and personalising language assessments. Objectives:…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Assisted Testing, Language Tests
Kittel, Anne Frieda Doris; Seufert, Tina – Journal of Computer Assisted Learning, 2023
Background: Most workplace learning is informal. However, some employees struggle to execute informal learning strategies effectively because they lack the necessary knowledge or skills or use their knowledge and skills ineffectively or not at all. Objectives: We examined the effects of computer-based micro-learning interventions that provide…
Descriptors: Informal Education, Learning Strategies, Workplace Learning, Job Skills
Tomoko Yabukoshi; Atsushi Mizumoto – Journal of Computer Assisted Learning, 2024
Background: While self-regulated learning (SRL) strategy-based writing instruction has been proposed in English as a foreign language (EFL) classrooms, there is insufficient evidence with Japanese EFL learners and little discussion on incorporating online resources into SRL strategy-based writing instruction, despite the availability of various…
Descriptors: Writing (Composition), Educational Technology, Self Management, Learning Strategies
Shao, Kaiqi; Kutuk, Gulsah; Fryer, Luke K.; Nicholson, Laura J.; Guo, Jidong – Journal of Computer Assisted Learning, 2023
Background: Considerable evidence suggests that students' achievement emotions are important contributors to their learning and success online. It is, therefore, essential to understand and support students' emotional experiences to enhance online education, especially under the COVID-19 context. However, to date, very few studies have…
Descriptors: Student Attitudes, Undergraduate Students, English (Second Language), Second Language Learning
Fatimah H. Aldeeb; Omar M. Sallabi; Monther M. Elaish; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: This paper examines the use of augmented reality (AR) as a concept-association tool in schools, with the aim of enhancing primary school students' learning outcomes and engagement. Conflicting findings exist in previous studies regarding the cognitive load of AR-enriched learning, with some reporting reduced load and others indicating…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Jaramillo-Morillo, Daniel; Ruipérez-Valiente, José A.; Burbano Astaiza, Claudia Patricia; Solarte, Mario; Ramirez-Gonzalez, Gustavo; Alexandron, Giora – Journal of Computer Assisted Learning, 2022
Background: Small private online courses (SPOCs) are one of the strategies to introduce the massive open online courses (MOOCs) within the university environment and to have these courses validates for academic credit. However, numerous researchers have highlighted that academic dishonesty is greatly facilitated by the online context in which…
Descriptors: Learning Analytics, Cheating, Integrated Learning Systems, Intervention
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
Hanzhu Yang; Linlin Hu; Hao Wang; Yunfei Xin – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) is a cognitive approach intricately linked with core competencies in Science, Technology, Engineering, and Mathematics (STEM). Numerous studies have explored strategies to effectively integrate CT into STEM education and systematically evaluated the multidimensional impact on student learning outcomes.…
Descriptors: Integrated Activities, Computation, Thinking Skills, STEM Education
Hans G. K. Hummel; Rob Nadolski; Hugo Huurdeman; Giel van Lankveld; Konstantinos Georgiadis; Aad Slootmaker; Hub Kurvers; Mick Hummel; Petra Neessen; Johan van den Boomen; Ron Pat-El; Julia Fischmann – Journal of Computer Assisted Learning, 2024
Background: Complex skills, like analytical thinking, are essential in preparing students for future professions. Serious games hold potential to stimulate the online acquisition of such professional skills in an active and experiential way. Objective: Rubrics are proven assessment and evaluation instruments, but were never directly integrated…
Descriptors: Game Based Learning, Scoring Rubrics, Educational Games, Computer Simulation
Zeng-Wei Hong; Che-Lun Liang; Ming-Chi Liu – Journal of Computer Assisted Learning, 2025
Background: Online video-based learning often leads to fatigue, which detracts from engagement and learning outcomes. Previous studies have examined monitoring mental states like attention through electroencephalography (EEG) headsets, but limitations such as high costs, discomfort, and limited scalability persist. Objectives: This study evaluates…
Descriptors: Technology Uses in Education, Electronic Learning, Video Technology, Fatigue (Biology)
Zhiwei Liu; Haode Zuo; Yongjing Lu – Journal of Computer Assisted Learning, 2025
Background: ChatGPT, a generative artificial intelligence (GenAI) chatbot, has gained significant traction as a tool for supporting students learning. Despite its growing popularity, there is still no academic consensus on its effectiveness in enhancing students' academic achievement. Objectives: This study aims to explore the effect of ChatGPT on…
Descriptors: Artificial Intelligence, Technology Uses in Education, Academic Achievement, Meta Analysis
Jiahong Su; Weipeng Yang; Iris Heung Yue Yim; Hui Li; Xiao Hu – Journal of Computer Assisted Learning, 2024
Background: While the integration of robot-based learning in early childhood education has gained increasing attention in recent years, there is still a lack of evidence regarding the impact of AI robots on young children's learning. Objectives: The study explored the effectiveness of two AI education approaches in advancing kindergarteners'…
Descriptors: Early Childhood Education, Artificial Intelligence, Kindergarten, Program Effectiveness

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