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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
Weipeng Yang; Xinyun Hu; Ibrahim H. Yeter; Jiahong Su; Yuqin Yang; John Chi-Kin Lee – Journal of Computer Assisted Learning, 2024
Background: Artificial Intelligence (AI) literacy is a crucial part of digital literacy that all individuals should possess in today's technologically advanced world. Despite the potential benefits that AI education offers, little research has been done on how to teach AI literacy to children. Objectives: This study aimed to fill that gap by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Digital Literacy
Novak, Elena; Mulvey, Bridget K. – Journal of Computer Assisted Learning, 2021
There is growing demand in our society to cultivate creativity and foster innovation. Design thinking has been successfully practiced as an educational framework for supporting innovation in educational and work contexts. However, research on design thinking education that facilitates the acquisition of knowledge related to design process and…
Descriptors: Design, Innovation, Educational Technology, Instructional Design
Bacca-Acosta, Jorge; Avila-Garzon, Cecilia – Journal of Computer Assisted Learning, 2021
Research on mobile-based assessment systems is still an emerging topic in the mobile learning field. Current research has demonstrated that the use of mobile-based assessment systems seems to have a positive impact on students' learning outcomes and motivation. The paper identifies some factors that influence student engagement with mobile-based…
Descriptors: Learner Engagement, Handheld Devices, Computer Assisted Testing, Electronic Learning
Asare, Andy Ohemeng; Yap, Robin; Truong, Ngoc; Sarpong, Eric Ohemeng – Journal of Computer Assisted Learning, 2021
The current educational disruption caused by the COVID-19 pandemic has fuelled a plethora of investments and the use of educational technologies for Emergency Remote Learning (ERL). Despite the significance of online learning for ERL across most educational institutions, there are wide mixed perceptions about online learning during this pandemic.…
Descriptors: COVID-19, Pandemics, School Closing, Online Courses
Heidari, Elham; Mehrvarz, Mahboobe; Marzooghi, Rahmatallah; Stoyanov, Slavi – Journal of Computer Assisted Learning, 2021
During the COVID-19 crisis, digital informal learning is important for students' academic engagement. Although scholars have highlighted the importance of students' digital competence in improving digital informal learning (DIL), the mediating role of DIL between digital competence and academic engagement has remained ambiguous. The purpose of…
Descriptors: Electronic Learning, Informal Education, Correlation, Technological Literacy
Yang, Weipeng; Huang, Runke; Li, Yongyan; Li, Hui – Journal of Computer Assisted Learning, 2021
Collective academic supervision (CAS) is a collective model for students' academic supervision to reduce their isolation and as a measure to establish a congenial culture and to develop networks with their peers. Most studies focus on the benefits of online CAS, leaving the pedagogical process and students' learning experiences understudied. This…
Descriptors: Teacher Researchers, Graduate Students, Masters Programs, Supervision
Lahza, Hatim; Khosravi, Hassan; Demartini, Gianluca – Journal of Computer Assisted Learning, 2023
Background: The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.…
Descriptors: Learning Analytics, Learning Strategies, Electronic Learning, Independent Study
Yeung, Matthew W. L.; Yau, Alice H. Y.; Lee, Crystal Y. P. – Journal of Computer Assisted Learning, 2023
Background: The existing literature has predominantly focused on instructor social presence in videos in an asynchronous learning environment and little is known about student social presence on webcam in online learning in the context of COVID-19. Objectives: This paper therefore contrasts students' and teachers' perspectives on student social…
Descriptors: Video Technology, Electronic Learning, COVID-19, Pandemics
Zhidkikh, Denis; Saarela, Mirka; Kärkkäinen, Tommi – Journal of Computer Assisted Learning, 2023
Background: Measurement of students' self-regulation skills is an active topic in education research, as effective assessment helps devising support interventions to foster academic achievement. Measures based on event tracing usually require large amounts of data (e.g., MOOCs and large courses), while aptitude measures are often qualitative and…
Descriptors: Independent Study, Junior High School Students, Secondary School Mathematics, Mathematics Education
Yorganci, Serpil – Journal of Computer Assisted Learning, 2022
Background: Continuous advances in mobile and multimedia technologies have increased interest in the use of e-books in educational settings. Objectives: The current study investigated how the e-book technology and different types of feedback influenced the learning, motivation, and cognitive load of students within the differentiation unit of…
Descriptors: Books, Electronic Publishing, Video Technology, Feedback (Response)
Theelen, Hanneke; van Breukelen, Dave H. J. – Journal of Computer Assisted Learning, 2022
Background: Since about 2010 e-learning has been embedded in educational practice and has become, surely due to the COVID-19 pandemic, increasingly important. Objectives: Although much has been written about e-learning, little is known about crucial didactic and pedagogical design principles for e-learning. This review tried to fill that gap.…
Descriptors: Instructional Design, Electronic Learning, Higher Education, COVID-19
Gökçearslan, Sahin; Yildiz Durak, Hatice; Esiyok, Elif – Journal of Computer Assisted Learning, 2023
Background: The COVID-19 pandemic has spread quickly, e-learning became compulsory and disseminated throughout the world. During the pandemic, smartphones are frequently used to access e-learning content, but connecting to technological tools increased the risk of cyberloafing during e-courses. Currently, there are a limited number of studies on…
Descriptors: Students, Emotional Response, Psychological Patterns, Self Management
Liu, Caihua; Zowghi, Didar; Kearney, Matthew; Bano, Muneera – Journal of Computer Assisted Learning, 2021
Recent years have seen a growing call for inquiry-based learning in science education, and mobile technologies are perceived as increasingly valuable tools to support this approach. However, there is a lack of understanding of mobile technology-supported inquiry-based learning (mIBL) in secondary science education. More evidence-based, nuanced…
Descriptors: Active Learning, Inquiry, Electronic Learning, Technology Integration
Exploring Learner Motivation and Mobile-Assisted Peer Feedback in a Business English Speaking Course
Xu, Qi; Peng, Hongying – Journal of Computer Assisted Learning, 2022
Background: Peer-to-peer feedback exchanges have been recognized as crucial to language learning. While studies on peer feedback proliferate, little is known about whether and how peer feedback is affected by learners' motivational levels. Objectives: Situated in a mobile collaborative learning context, the current study examined how English as a…
Descriptors: Student Motivation, Electronic Learning, Handheld Devices, Peer Evaluation

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