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Mümüne Merve Parlak; Aysen Köse; Murat Güç; Özlem Bizpinar Munis – International Journal of Language & Communication Disorders, 2024
Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease. Cognitive functions and communication skills worsen as the disease progresses, thereby reducing patients' independence levels. Therefore, recommending software that can be used at home may be a useful means of slowing down the cognitive and communicative decline in…
Descriptors: Handheld Devices, Alzheimers Disease, Cognitive Ability, Communication (Thought Transfer)
Nuo Cheng; Wei Zhao; Xiaoqing Xu; Hongxia Liu; Jinhong Tao – Education and Information Technologies, 2024
Learning analytics dashboards are becoming increasingly common tools for providing feedback to learners. However, there is limited empirical evidence regarding the effects of learning analytics dashboard design features on learners' cognitive load, particularly in digital learning environments. To address this gap, we developed goal-based,…
Descriptors: Learning Analytics, Learning Management Systems, Cognitive Ability, Online Courses
McLoughlin, Shane; Tyndall, Ian; Pereira, Antonina – Journal of Behavioral Education, 2022
In recent years, small-scale studies have suggested that we may be able to substantially strengthen children's general cognitive abilities and intelligence quotient (IQ) scores using a relational operant skills training program (SMART). Only one of these studies to date has included an active Control Condition, and that study reported the smallest…
Descriptors: Cognitive Ability, Intelligence Quotient, Early Adolescents, Programming
Chih-Hung Wu; Ting-Sheng Weng; Chih-Hsing Liu – Educational Technology & Society, 2025
With the growing attention directed towards ChatGPT and its applications in education, this study explored its impact on various variables pertaining to student learning. Specifically, an integrated theoretical framework was used to investigate the factors that influence student problem-solving and critical thinking abilities when using ChatGPT…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Learning Motivation
Aronshtam, Lior; Shrot, Tammar; Shmallo, Ronit – Education and Information Technologies, 2021
Improving code while preserving its functionality is a common task in the hi-tech industry. Yet students have difficulties improving an algorithm's run-time complexity by an order of magnitude. The paper focuses on assessing students' abilities in this area. We designed a Structure of the Observed Learning Outcome (SOLO) taxonomy, using software…
Descriptors: Difficulty Level, Computer Software, Taxonomy, Coding
Kamelia Sepanloo; Daniel Shevelev; Md Tariqul Islam; Young-Jun Son; Shravan Aras; Janine E. Hinton – Educational Technology Research and Development, 2025
Integrating Mixed Reality (MR) into nursing education and professional practice has recently captured significant interest as a transformative approach. This paper presents a comprehensive exploration and practical insights into designing and implementing an advanced MR training platform to provide nursing students with immersive experiences…
Descriptors: Nursing Education, Educational Improvement, College Faculty, Pilot Projects
Türkan Karakus Yilmaz; Zafer Yilmaz; Ömer Arpacik – Journal of Educational Computing Research, 2025
This study compares museum-related knowledge, museum learning experiences and cognitive load based on task types presented via a mobile application during a museum virtual tour. The study involved three experiments, each examining the effects of different task types. In the first experiment, tasks varied by difficulty (easy vs. difficult), in the…
Descriptors: Cognitive Ability, Museums, Computer Simulation, Information Technology
Mohan Honnagudi Gururaj; Nandish Malleshappa; Sankhya Nagesh Nayak; Devaraj Fakkirappa Vadenapur; Benak Patel Medugondanahalli Puradaswamy – Education and Information Technologies, 2024
A Study with undergraduate engineering students was conducted in order to evaluate whether cognitive and comprehending ability can be improved by incorporating the tool based learning. The simulator tools and virtual labs were used to represent tool based learning. The study was conducted on three different years of students. In the first stage…
Descriptors: Undergraduate Students, Engineering Education, Evaluation, Comprehension
Nurul Ashikin Izhar; Wendy Ven Ye Teh; Anita Adnan – Journal of Information Technology Education: Innovations in Practice, 2025
Aim/Purpose: This study investigates the key factors influencing the adoption and use of artificial intelligence (AI) applications among researchers, focusing on effort expectancy, satisfaction, perceived ease of use, and perceived usefulness, which shaped attitudes and drove AI adoption as a research assistant. Background: AI tools have rapidly…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Technology Integration
Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
Fatimah H. Aldeeb; Omar M. Sallabi; Monther M. Elaish; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: This paper examines the use of augmented reality (AR) as a concept-association tool in schools, with the aim of enhancing primary school students' learning outcomes and engagement. Conflicting findings exist in previous studies regarding the cognitive load of AR-enriched learning, with some reporting reduced load and others indicating…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Carlos Sandoval-Medina; Carlos Argelio Arévalo-Mercado; Estela Lizbeth Muñoz-Andrade; Jaime Muñoz-Arteaga – Journal of Information Systems Education, 2024
Learning basic programming concepts in computer science-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed solutions to the problem can be found in the literature, such as the development of new programming languages and environments, the…
Descriptors: Cognitive Ability, Computer Science Education, Programming, Instructional Materials
Song, Yu; Zhang, Shu; Liu, Bingman – Journal of Educational Research, 2023
Classroom dialogue is widely used in mathematics teaching and learning, and if managed strategically, it will have productive benefits for mathematics achievement. However, dialogic participants often lack awareness of how dialogue could be constructed, and few studies show the characteristics of dialogic patterns in different stages of education.…
Descriptors: Dialogs (Language), Mathematics Instruction, Comparative Analysis, Computer Software
Timothy Rosencrans; Ryan Jones; Daniel Griffin; India Loyd; Anna Grady; Mary Moon; Frederick Miller – Advances in Physiology Education, 2024
Medical students face challenging but important topics they must learn in short periods of time, such as autonomic pharmacology. Autonomic pharmacology is difficult in that it requires students to synthesize detailed anatomy, physiology, clinical reasoning, and pharmacology. The subject poses a challenge to learn as it is often introduced early in…
Descriptors: Pharmacology, Medical Students, Student Attitudes, Web Based Instruction
Yu, Eunjyu – Journal of Educators Online, 2023
Artificial intelligence (AI) is increasingly being used as a cost-effective assistant to human instructors to generate performance feedback for online learners. This study found that AI-generated feedback had a positive impact on students' writing practice in an online learning space. Underperforming students stated that they wanted AI to further…
Descriptors: Artificial Intelligence, Feedback (Response), Electronic Learning, Cognitive Style

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