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Angie Van Arsdale; Nicole Perrino; Ronald J. Clark; Vivian F. Ibañez; Timothy R. Vollmer – Journal of Applied Behavior Analysis, 2025
Behavior-analytic interventions are empirically supported treatments for pediatric feeding disorder; however, there are a limited number of intensive feeding programs in the country, making access to services and specialized training difficult. Given the prevalence of this disorder and scarcity of in vivo training resources, clinicians would…
Descriptors: Computer Assisted Instruction, Nutrition Instruction, Functional Behavioral Assessment, Eating Disorders
Cecilie Carlsen Bach; Ewa Bergqvist; Uffe Thomas Jankvist – ZDM: Mathematics Education, 2024
In mathematics, students' abilities to make transformations between mathematical representations are fundamental. The recent implementation of digital technologies, such as Dynamic Geometry Environments (DGEs), have changed students' access to mathematical representations by providing a variety of different representations, available just by…
Descriptors: Geometry, Mathematics Instruction, Computer Assisted Instruction, Secondary School Students
Cohen, Etan; Ben-Zvi, Dani; Hod, Yotam – International Journal of Computer-Supported Collaborative Learning, 2023
In this article we discuss some of the ethical dimensions of design-based research, which we believe should feature more prominently in CSCL scholarship. We begin by sketching out why it is important for CSCL researchers to articulate their visions of the good and how this can be accomplished in a systematic way. We then outline how ethical…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Ethics, Design
Waight, Noemi; Liu, Xiufeng; Whitford, Melinda – Research in Science Education, 2023
This study examined high school chemistry students' understandings of big ideas--matter and energy, how these understandings are related to macro and submicro representations and fine-grained distinguishing characteristics of students' explanations. The study was conducted in the context of computer-based models and model-based assessments.…
Descriptors: Chemistry, Scientific Concepts, Computer Assisted Instruction, Models
Nicolas Pope; Juho Kahila; Henriikka Vartiainen; Matti Tedre – IEEE Transactions on Learning Technologies, 2025
The rapid advancement of artificial intelligence and its increasing societal impacts have turned many computing educators' focus toward early education in machine learning (ML). Limited options for educational tools for teaching novice learners about the mechanisms of ML and data-driven systems presents a recognized challenge in K-12 computing…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Computer Science Education, Grade 4
Rasha R. Baruni; Raymond G. Miltenberger; Jennifer L. Cook; Anthony Concepcion; Trevor C. Maxfield – Journal of Applied Behavior Analysis, 2025
Researchers have shown that behavioral skills training (BST) and in situ training are effective for teaching firearm safety skills to children. Within the safety skills literature, there is evidence that manualized interventions are effective for teaching parents and teachers to conduct BST. An approach that has not been evaluated for teaching…
Descriptors: Weapons, Safety Education, Computer Assisted Instruction, Instructional Effectiveness
Roseline Osayi Uwaifo; Mark Igho Osah; Sunday Obro – Journal of Education and Learning (EduLearn), 2025
The study explored innovative instructional strategy: effect of computer-aided instruction on social studies students' achievement and retention outcome. The study was an experimental study. The sample of the study was 180 students. The instrument used for the study was the scholarly achievement test (SAT). Descriptive statistics were utilized to…
Descriptors: Computer Assisted Instruction, Social Studies, Academic Achievement, Academic Persistence
Zhu Zhu; Yingying Ren; An ran Shen – Education and Information Technologies, 2025
Current educational trends leverage artificial intelligence (AI) to provide high-quality teaching and enhance students' learning competitiveness. This study aimed to evaluate the acceptance of artificial intelligence generated content (AIGC) for assisted learning and design creation among art and design students. Based on an extended technology…
Descriptors: Artificial Intelligence, Computer Assisted Design, Computer Assisted Instruction, Art Education
Yingbin Zhang; Luc Paquette; Nigel Bosch – International Journal of Artificial Intelligence in Education, 2025
Understanding the transitions among affective states during computer-based learning may guide the design of affect-responsive learning environments. Current studies have focused on the marginal strength of an affect transition, which is the average transition tendency over possible affective states preceding the transition. However, marginal…
Descriptors: Affective Behavior, Emotional Response, Electronic Learning, Learning Experience
Dana Opre; Camelia ?erban; Andreea Ve?can; Romi?a Iucu – Active Learning in Higher Education, 2024
In recent years, the use of information technology to promote active learning in higher education has raised great interest. Teachers are continuously challenged to identify new research-informed approaches and educational practices for supporting students to actively learn and apply their knowledge. The present study tests the effects on…
Descriptors: Active Learning, Computer Assisted Instruction, Educational Technology, Outcomes of Education
Kerstin Huber; Maria Bannert – Journal of Computing in Higher Education, 2024
The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining…
Descriptors: Learning Processes, Data Analysis, Navigation (Information Systems), Student Behavior
Olga Viberg; Martine Baars; Rafael Ferreira Mello; Niels Weerheim; Daniel Spikol; Cristian Bogdan; Dragan Gasevic; Fred Paas – Journal of Computer Assisted Learning, 2024
Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported…
Descriptors: Feedback (Response), Peer Evaluation, Computer Assisted Instruction, Cooperative Learning
Hussein Meihami – Computer Assisted Language Learning, 2024
Research in computer-assisted language learning (CALL) has turned into a critical way of addressing the interrelationships between L2 pedagogy and technology. This autobiographical narrative inquiry aimed to investigate CALL researchers' strategies to conduct genuine CALL research (Colpaert, 2020). To that end, the autobiographical narratives of…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Educational Research, Communities of Practice
Neelam Bansal; Mala Tandon; Himangshu Das – Journal of Applied Research in Higher Education, 2024
Purpose: The main purpose of the study to identify the importance of computer devices in vocational studies for person with disabilities (PwDs) are as follows: This study aims to observe the role of computer training in vocational training of a PwD. This study plays an important role in the vocational training of a PwD. With the help of ICT…
Descriptors: Students with Disabilities, Vocational Education, Computer Assisted Instruction, Educational Technology
Greta R. Underhill; Cat Turk – Online Learning, 2024
Although instructors in higher education are oftentimes content matter experts, they may not have received training on instructional design or inclusive practices, such as Universal Design for Learning. However, instructors may serendipitously implement aspects of UDL without full knowledge of the framework. This qualitative study used sensemaking…
Descriptors: Usability, Electronic Learning, Teacher Attitudes, Curriculum Design

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