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Jihae Suh; Kyuhan Lee; Jaehwan Lee – Education and Information Technologies, 2025
Artificial Intelligence (AI) has rapidly emerged as a powerful tool with the potential to enhance learning environments. However, effective use of new technologies in education requires a good understanding of the technology and good design for its use. Generative AI such as ChatGPT requires particularly well-designed instructions due to its ease…
Descriptors: Programming, Computer Science Education, Artificial Intelligence, Technology Uses in Education
Ellen Bobronnikov; Daniel Litwok; Kaitlyn Ciaffone; Anjali Pai – Abt Global, 2025
This study evaluates the Programming the Acceleration of Computing Education (PACE) Framework for Computer Science (CS) Systems Change, developed to promote equitable access to CS education for middle school students. Funded by an Education Innovation and Research (EIR) Early-Phase Grant, the intervention aimed to increase student understanding,…
Descriptors: Middle School Students, Computer Science Education, Equal Education, Access to Education
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Siran Li; Jiangyue Liu; Qianyan Dong – Australasian Journal of Educational Technology, 2025
Recent advancements in generative artificial intelligence (GenAI) have drawn significant attention from educators and researchers. However, its effects on learners' programming performance, self-efficacy and learning processes remain inconclusive, while the mechanisms underlying its efficiency-enhancing potential are underexplored. This study…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Science Education, Programming
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Haoming Wang; Chengliang Wang; Zhan Chen; Fa Liu; Chunjia Bao; Xianlong Xu – Education and Information Technologies, 2025
With the rapid development of artificial intelligence technology in the field of education, AI-Agents have shown tremendous potential in collaborative learning. However, traditional Computer-Supported Collaborative Learning (CSCL) methods still have limitations in addressing the unique demands of programming education. This study proposes an…
Descriptors: Artificial Intelligence, Cooperative Learning, Programming, Computer Science Education
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Ibrahim Abba Mohammed; Ahmed Bello; Bala Ayuba – Education and Information Technologies, 2025
In spite of the emergence of studies seeking to integrate chatbot into education, there is a wide literature gap in the Nigerian contexts. While most studies focus on the design and development of chatbots, there exists a very scarce literature on the effect of ChatGPT chatbot on students' achievement. To address this gap, this study checked the…
Descriptors: Natural Language Processing, Artificial Intelligence, Academic Achievement, Computer Science Education
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Eloho Ifinedo; Diane Burt – Journal of Applied Research in Higher Education, 2025
Purpose: Service-learning (SL) is a widely accepted pedagogy that can enrich the learning experience for students in higher education while they apply their skills in a meaningful community service. This research is part of a larger project that aimed to motivate educational achievement among youths living in a priority neighborhood through SL.…
Descriptors: Service Learning, Information Technology, Computer Science Education, Community Centers
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Deepak Dawar – Information Systems Education Journal, 2024
Learning computer programming is typically difficult for newcomers. Demotivation and learned helplessness have received much attention. Besides the subject's intricacy, low in-class participation has been associated with poor student achievement. This paper presents a follow-up, stage 2 study on the novel instructional technique, Student-Driven…
Descriptors: College Students, Computer Science Education, Required Courses, Elective Courses
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Zhong, Baichang; Xia, Liying; Su, Siyu – Education and Information Technologies, 2022
One of the aspects of programming that novices often struggle with is the understanding of abstract concepts, such as variables, loops, expressions, and especially Boolean operations. This paper aims to explore the effects of programming tools with different degrees of embodiment on learning Boolean operations in elementary school. To this end, 67…
Descriptors: Programming Languages, Programming, Novices, Elementary Education
Fay, Derek; Armstrong, Mark; McEldoon, Katherine; Ridley, Julia – Pearson, 2020
Programming and coding skills are in high demand, and can provide access to employment in growing fields. But a high percentage of undergraduates who enroll in relevant programs do not persist until they achieve competency in the subject and employment in the field. Revel is an interactive learning environment intended to help students prepare for…
Descriptors: Introductory Courses, Programming, Computer Science Education, Electronic Learning
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Dawar, Deepak; Murphy, Marianne – Information Systems Education Journal, 2020
Teaching introductory programming courses to university students who come from a varied set of academic and non-academic backgrounds is challenging. Students who are learning programming for the first time can become easily discouraged leading to procrastination that subsequently can have an unfavorable effect on their learning outcomes, and…
Descriptors: Assignments, Scaffolding (Teaching Technique), Introductory Courses, Programming
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Somyürek, Sibel; Brusilovsky, Peter; Çebi, Ayça; Akhüseyinoglu, Kamil; Güyer, Tolga – International Journal of Information and Learning Technology, 2021
Purpose: Interest is currently growing in open social learner modeling (OSLM), which means making peer models and a learner's own model visible to encourage users in e-learning. The purpose of this study is to examine students' views about the OSLM in an e-learning system. Design/methodology/approach: This case study was conducted with 40…
Descriptors: Student Attitudes, Self Evaluation (Individuals), Peer Evaluation, Electronic Learning
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Celis Rangel, Jakeline G.; King, Melissa; Muldner, Kasia – ACM Transactions on Computing Education, 2020
Learning to program requires perseverance, practice, and the mindset that programming skills are improved through these activities (i.e., that everyone has the potential to become good at programming). In contrast to an entity mindset, individuals with an incremental mindset believe that ability is malleable and can be improved with effort. Prior…
Descriptors: Intervention, Cognitive Structures, Programming, Learning Activities
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Yin, Jiaqi; Goh, Tiong-Thye; Yang, Bing; Xiaobin, Yang – Journal of Educational Computing Research, 2021
This study investigated the impact of a chatbot-based micro-learning system on students' learning motivation and performance. A quasi-experiment was conducted with 99 first-year students taking part in a basic computer course on number system conversion. The students were assigned to a traditional learning group or a chatbot-based micro-learning…
Descriptors: Educational Technology, Technology Uses in Education, Student Motivation, Academic Achievement
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Lu, Owen H. T.; Huang, Anna Y. Q.; Tsai, Danny C. L.; Yang, Stephen J. H. – Educational Technology & Society, 2021
Human-guided machine learning can improve computing intelligence, and it can accurately assist humans in various tasks. In education research, artificial intelligence (AI) is applicable in many situations, such as predicting students' learning paths and strategies. In this study, we explore the benefits of repetitive practice of short-answer…
Descriptors: Test Items, Artificial Intelligence, Test Construction, Student Evaluation
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Ran Wei – Cogent Education, 2024
The utilisation of the RIASEC Theory, based on the Holland Code, has gained substantial popularity in the realm of career planning. Nevertheless, only a limited number of studies have explored the potential influence of the six personality types identified in the Realistic-Investigative-Artistic-Social-Enterprising-Conventional Theory (RIASEC…
Descriptors: Foreign Countries, Undergraduate Students, Educational Theories, Career Choice
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