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Peng Chen; Dong Yang; Jia Zhao; Shu Yang; Jari Lavonen – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT…
Descriptors: Computation, Thinking Skills, Programming, Learning Processes
Inka Sara Hähnlein; Pablo Pirnay-Dummer – Educational Technology Research and Development, 2024
Multiple document comprehension and knowledge integration across domains are particularly important for pre-service teachers, as integrated professional knowledge forms the basis for teaching expertise and competence. This study examines the effects of instructional prompts and relevance prompts embedded in pre-service teachers' learning processes…
Descriptors: Preservice Teachers, Prompting, Cues, Learning Processes
Maria Tulis; Markus Dresel – British Journal of Educational Psychology, 2025
Background: Interest in the potential of learning from errors to benefit innovation and organizational and personal growth is currently increasing. In practice, individuals frequently do not appear to learn spontaneously from errors and setbacks without support. Based on prior work, this paper considers antecedents and consequences of adaptive…
Descriptors: Undergraduate Students, Student Attitudes, Beliefs, Student Motivation
Sonja Dieterich; Stefan Rumann; Marc Rodemer – Educational Psychology Review, 2025
Example-based learning is a well-known instructional method for effective cognitive skill acquisition in complex domains. "(Contrasting) erroneous examples" are a promising extension that embed errors in instructional material, potentially fostering not only positive but negative knowledge. However, the mechanisms and conditions for…
Descriptors: Learning Processes, Teaching Methods, Instructional Effectiveness, Models
Daryn A. Dever; Megan D. Wiedbusch; Sarah M. Romero; Roger Azevedo – British Journal of Educational Technology, 2024
Intelligent tutoring systems (ITSs) incorporate pedagogical agents (PAs) to scaffold learners' self-regulated learning (SRL) via prompts and feedback to promote learners' monitoring and regulation of their cognitive, affective, metacognitive and motivational processes to achieve their (sub)goals. This study examines PAs' effectiveness in…
Descriptors: Intelligent Tutoring Systems, Scaffolding (Teaching Technique), Independent Study, Prompting
Yanqing Wang; Shaoying Gong; Ning Jia; Ying Liu – Journal of Computer Assisted Learning, 2025
Background: Online learning is becoming increasingly popular among learners. To enhance the effectiveness of online learning, researchers have embedded an affective pedagogical agent (PA) on the computer screen to help regulate learners' emotions and support their learning. However, previous research has paid little attention to the effects of…
Descriptors: Metacognition, Prompting, Electronic Learning, Computer Uses in Education
Olivia Hadjadj; Margaret Kehoe; Samuel Maistre; Hélène Delage – Journal of Speech, Language, and Hearing Research, 2025
Purpose: This study aims to investigate the learning potential of French-speaking children, either with typical development (TD) or with developmental language disorder (DLD), when learning an invented inflectional morphological rule. We tested the children's performance in learning pseudomorphemes of gender and number with dynamic assessment…
Descriptors: Morphology (Languages), Developmental Disabilities, Language Impairments, Morphemes
Wang, Yanqing; Wang, Fuxing; Mayer, Richard E.; Hu, Xiangen; Gong, Shaoying – Journal of Computer Assisted Learning, 2023
Background: How to improve learning with online multimedia lessons has attracted widespread concern. Prior studies have attempted to help students learn by breaking a video lesson into several segments. However, there has been a debate about whether learners can use pause time effectively and whether prompting them to engage in different types of…
Descriptors: Multimedia Instruction, Multimedia Materials, Prompting, Documentation
Derek McClellan; Raymond J. Chastain; Marci S. DeCaro – Journal of Computing in Higher Education, 2024
Use of online video lectures is increasingly common. However, students may struggle to self-regulate their attention and passively process the content. This study examined whether, and for whom, different types of embedded learning prompts improve student learning from video lectures. Undergraduate physics students (N = 253) watched an online,…
Descriptors: Video Technology, Electronic Learning, Lecture Method, Prompting
O'Neill, Sean J.; McDowell, Claire; Leslie, Julian C. – Journal of Behavioral Education, 2022
Variations in prompt delay procedures are used in discrete-trial training to reduce the occurrence of errors before task mastery. However, the variations are seldom compared systematically. Using an adapted alternating treatments design, the present study compared progressive prompt delay with 2-s or 5-s constant prompt delay, on the acquisition…
Descriptors: Learning Processes, Prompting, Intervals, Autism
Amanda M. Clevinger; John H. Mace – Applied Cognitive Psychology, 2024
Our aim in the current study was to examine how different diary methods might impact the results of involuntary memory studies. We compared three different commonly used diary methods, record all memories experienced per day, record up to two memories per day, or record only the first two per day. Results showed that the record-all group had the…
Descriptors: Journal Writing, Diaries, Personal Narratives, Autobiographies
Lambert, Joseph M.; Torelli, Jessica N.; Houchins-Juarez, Nealetta J.; Tate, Savannah A.; Paranczak, Jessica L. – Journal of Behavioral Education, 2021
Previously applied research has shown independent manding is not likely to emerge when functional communication training (FCT) is implemented in conjunction with dense schedules of noncontingent reinforcement (NCR) but does emerge when it is implemented after NCR schedules have been leaned. One interpretation of these data may be that participants…
Descriptors: Reinforcement, Therapy, Prompting, Behavior Modification
Jiyou Jia; Tianrui Wang; Yuyue Zhang; Guangdi Wang – Asia Pacific Journal of Education, 2024
In designing an intelligent tutoring system, a core area of the application of AI in education, tips from the system or virtual tutors are crucial in helping students solve difficult questions in disciplines like mathematics. Traditionally, the manual design of general tips by teachers is time-consuming and error-prone. Generative AI, like…
Descriptors: Problem Solving, Artificial Intelligence, Learning Processes, Prompting
C. Gregg; A. Bowling – NACTA Journal, 2023
The purpose of this project was to explore the experiences of students when facilitating class discussions through Cooperative Discussion Groups. In addition, students particularly compared their experiences within this class with their experiences in Whole Class Discussion in previous classes. Students participated in structured cooperative…
Descriptors: Undergraduate Students, Student Attitudes, Cooperative Learning, Discussion Groups
Vogt, Andrea; Babel, Franziska; Hock, Philipp; Baumann, Martin; Seufert, Tina – British Journal of Educational Technology, 2021
Presenting a pictorial representation followed by a textual representation supports learners to build a coherent mental model. Providing an elaboration prompt stimulates learners to process the learning content semantically. Hence, combining both approaches might result in synergetic effects as both foster mental model development, which could be…
Descriptors: Computer Simulation, Schemata (Cognition), Pictorial Stimuli, Auditory Stimuli

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