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Zirou Lin; Hanbing Yan; Li Zhao – Journal of Computer Assisted Learning, 2024
Background: Peer assessment has played an important role in large-scale online learning, as it helps promote the effectiveness of learners' online learning. However, with the emergence of numerical grades and textual feedback generated by peers, it is necessary to detect the reliability of the large amount of peer assessment data, and then develop…
Descriptors: Peer Evaluation, Automation, Grading, Models
Michelle Cheong – Journal of Computer Assisted Learning, 2025
Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…
Descriptors: Artificial Intelligence, Performance Based Assessment, Spreadsheets, Models
Alejandra Ruiz-Segura; Andrew Law; Sion Jennings; Alain Bourgon; Ethan Churchill; Susanne Lajoie – Journal of Computer Assisted Learning, 2024
Background: Flying accuracy is influenced by pilots' affective reactions to task demands. A better understanding of task-related emotions and flying performance is needed to enhance pilot training. Objective: Understand pilot trainees' performance and emotional dynamics (intensity, frequency and variability) based on training phase and difficulty…
Descriptors: Foreign Countries, Flight Training, Aviation Technology, Computer Simulation
Chao-Jung Wu; Chia-Yu Liu – Journal of Computer Assisted Learning, 2025
Background: Although comprehending illustrated texts is essential, adult readers in this era may not have acquired reading comprehension strategies. Eye-movement modelling example (EMME) is promising for helping less-skilled learners master these strategies; however, its benefits for adults remain unknown. Another understudied factor in the EMME…
Descriptors: Eye Movements, Models, Reading Strategies, Reading Comprehension
Andersen, Nico; Zehner, Fabian; Goldhammer, Frank – Journal of Computer Assisted Learning, 2023
Background: In the context of large-scale educational assessments, the effort required to code open-ended text responses is considerably more expensive and time-consuming than the evaluation of multiple-choice responses because it requires trained personnel and long manual coding sessions. Aim: Our semi-supervised coding method eco (exploring…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
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
Xiaowei Lei – Journal of Computer Assisted Learning, 2024
Background: This research aimed at investigating the effectiveness of online digital audio software Logic Pro X and offline audio studios in creating an original folk-style track. The goal was to define the more effective method for the perspective and quality of musical compositions that students create during learning. Objectives: This research…
Descriptors: Music Education, Accuracy, Audio Equipment, Musical Composition
Jiang, Michael Yi-Chao; Jong, Morris Siu-Yung; Lau, Wilfred Wing-Fat; Chai, Ching-Sing; Wu, Na – Journal of Computer Assisted Learning, 2023
Background: While automatic speech recognition (ASR) is increasingly used for commercial purposes, its influence on the learners' linguistic performance in terms of oral complexity, accuracy and fluency was under-explored. To date, few studies have been conducted to investigate how the dictation ASR technology could be incorporated into language…
Descriptors: Speech Communication, Automation, Accuracy, Language Fluency
Verwimp, Cara; Snellings, Patrick; Wiers, Reinout W.; Tijms, Jurgen – Journal of Computer Assisted Learning, 2023
Background: Learning which letters correspond to which speech sounds is fundamental for learning to read. Based on previous experimental studies, we developed a serious game aiming to boost letter-speech sound (L-SS) correspondences in a motivational game environment. Objectives: The goal of this study was to determine the efficacy of this game in…
Descriptors: Phoneme Grapheme Correspondence, Reading Instruction, Game Based Learning, Program Effectiveness
Ahnaf Chowdhury Niloy; Salma Akter; Nayeema Sultana; Jakia Sultana; Sayed Imran Ur Rahman – Journal of Computer Assisted Learning, 2024
Background: The increasing prevalence of Artificial Intelligence (AI) language models, exemplified by ChatGPT, has sparked inquiries into their influence on creative writing skills in educational contexts. This study aims to quantitatively investigate whether ChatGPT's use negatively affects university students' creative writing abilities,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Creative Writing, Writing Ability
Martin Merkt; Daniel Bodemer – Journal of Computer Assisted Learning, 2024
Background: When watching educational online videos, learners need to determine whether the videos' contents are suitable for learning. Whereas this may induce metacognitive monitoring processes, it may also distract learners from the learning materials. Objectives: In the current set of experiments, we investigated whether asking participants to…
Descriptors: Video Technology, Teaching Methods, Metacognition, Instructional Materials
Nikola Ebenbeck; Morten Bastian; Andreas Mühling; Markus Gebhardt – Journal of Computer Assisted Learning, 2024
Background: Computerised adaptive tests (CATs) are tests that provide personalised, efficient and accurate measurement while reducing testing time, depending on the desired level of precision. Schools have different types of assessments that can benefit from a significant reduction in testing time to varying degrees, depending on the area of…
Descriptors: Computer Assisted Testing, Elementary Secondary Education, Public Schools, Special Schools
Flor, Michael; Andrews-Todd, Jessica – Journal of Computer Assisted Learning, 2022
Background: Collaborative problem solving (CPS) is important for success in the 21st century, especially for teamwork and communication in technology-enhanced environments. Measurement of CPS skills has emerged as an essential aspect in educational assessment. Modern research in CPS relies on theory-driven measurements that are usually carried out…
Descriptors: Automation, Documentation, Cooperative Learning, Teamwork
Abed, Fayez; Barzilai, Sarit – Journal of Computer Assisted Learning, 2023
Background: YouTube is widely used for learning about scientific issues in and out of school. However, much of the scientific information on YouTube is inaccurate. Prior studies have mostly focused on how students evaluate textual online information sources and have not yet systematically examined how they evaluate authentic scientific YouTube…
Descriptors: Video Technology, Web Sites, Evaluative Thinking, Scientific and Technical Information
Kok, Ellen; Hormann, Olle; Rou, Jeroen; Saase, Evi; der Schaaf, Marieke; Kester, Liesbeth; Gog, Tamara – Journal of Computer Assisted Learning, 2022
Background: Performance monitoring plays a key role in self-regulated learning, but is difficult, especially for complex visual tasks such as navigational map reading. Gaze displays (i.e. visualizations of participants' eye movements during a task) might serve as feedback to improve students' performance monitoring. Objectives: We hypothesized…
Descriptors: Metacognition, Eye Movements, Task Analysis, Visualization

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