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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)
Wen Xin Zhang; John J. H. Lin; Ying-Shao Hsu – Journal of Computer Assisted Learning, 2025
Background Study: Assessing learners' inquiry-based skills is challenging as social, political, and technological dimensions must be considered. The advanced development of artificial intelligence (AI) makes it possible to address these challenges and shape the next generation of science education. Objectives: The present study evaluated the SSI…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Inquiry, Active Learning
Yue Huang; Joshua Wilson – Journal of Computer Assisted Learning, 2025
Background: Automated writing evaluation (AWE) systems, used as formative assessment tools in writing classrooms, are promising for enhancing instruction and improving student performance. Although meta-analytic evidence supports AWE's effectiveness in various contexts, research on its effectiveness in the U.S. K-12 setting has lagged behind its…
Descriptors: Writing Evaluation, Writing Skills, Writing Tests, Writing Instruction
Mohammad Nayef Ayasrah; Mohamad Ahmad Saleem Khasawneh; Mazen Omar Almulla; Amoura Hassan Aboutaleb – Journal of Computer Assisted Learning, 2025
Background: One area that has been dramatically changed by artificial intelligence (AI) is educational environments. Chatbots, Recommender Systems, Adaptive Learning Systems and Large Language Models have been emerging as practical tools for facilitating learning. However, using such tools appropriately is challenging. In this regard, the…
Descriptors: Test Construction, Test Validity, Test Reliability, Rating Scales
Ali Alqarni – Journal of Computer Assisted Learning, 2025
Background: Critical thinking is essential in modern education, and artificial intelligence (AI) offers new possibilities for enhancing it. However, the lack of validated tools to assess teachers' AI-integrated pedagogical skills remains a challenge. Objectives: The current study aimed to develop and validate the Artificial Intelligence-Critical…
Descriptors: Artificial Intelligence, Technology Uses in Education, Test Construction, Test Validity
Juliana do Amaral; Ladislao Salmerón; Davi Alves Oliveira – Journal of Computer Assisted Learning, 2025
Background: Misconceptions are unjustified beliefs about a topic. Nonetheless, they are pervasive among educational practitioners. Although the internet can be a powerful tool to learn and debunk misconceptions, their use requires competencies like navigating through search engine results pages (SERPs), evaluating the reliability of content, and…
Descriptors: Eye Movements, Second Language Learning, Second Language Instruction, Computer Assisted Instruction
Wafa Mohammed Aldighrir; Fatima's Mohamed Asiri – Journal of Computer Assisted Learning, 2025
Background: As educational institutions increasingly operate as multicultural hubs, leaders must navigate the complexities of cultural differences, language barriers and diverse learning styles in digital environments. These challenges are amplified by the lack of non-verbal cues and the asynchronous nature of online communication, which can lead…
Descriptors: Foreign Countries, Test Construction, Measures (Individuals), Test Validity

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