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Héctor Galindo-Domínguez; Nahia Delgado; María-Victoria Urruzola; Jose-María Etxabe; Lucía Campo – Journal of Computer Assisted Learning, 2025
Background: With the integration of artificial intelligence into educational processes, its impact remains to be discovered. Objective: The aim of the present study was to determine whether, after a 7-month intervention in which a subject of artificial intelligence was taught, students improved their psychological needs for competence, autonomy…
Descriptors: Artificial Intelligence, Adolescents, Student Motivation, Technology Uses in Education
Mohamed Ali Nagy Elmaadaway; Mohamed Elsayed El-Naggar; Mohamed Radwan Ibrahim Abouhashesh – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) made substantial progress with language recognition. Proficiency in spoken English reading is a prerequisite for fluency in written English. However, research on its use, especially for non-native speakers, is lacking despite increased usage. Objectives: This study aimed to enhance the oral reading fluency…
Descriptors: Artificial Intelligence, Reading Fluency, Elementary School Students, Oral Reading
Umar Alkafaween; Ibrahim Albluwi; Paul Denny – Journal of Computer Assisted Learning, 2025
Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…
Descriptors: Automation, Grading, Introductory Courses, Programming
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
Ley, Tobias; Tammets, Kairit; Pishtari, Gerti; Chejara, Pankaj; Kasepalu, Reet; Khalil, Mohammad; Saar, Merike; Tuvi, Iiris; Väljataga, Terje; Wasson, Barbara – Journal of Computer Assisted Learning, 2023
Background: With increased use of artificial intelligence in the classroom, there is now a need to better understand the complementarity of intelligent learning technology and teachers to produce effective instruction. Objective: The paper reviews the current research on intelligent learning technology designed to make models of student learning…
Descriptors: Artificial Intelligence, Technology Uses in Education, Learning Analytics, Instructional Effectiveness
Tobias Kohn – Journal of Computer Assisted Learning, 2025
Background: The recent advent of powerful, exam-passing large language models (LLMs) in public awareness has led to concerns over students cheating, but has also given rise to calls for including or even focusing education on LLMs. There is a perceived urgency to react immediately, as well as claims that AI-based reforms of education will lead to…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Usability
Na Yuan – Journal of Computer Assisted Learning, 2024
Background: In the modern music industry, AI music generators have gained particular importance. The use of AI greatly simplifies the creation of polyphony. In addition, it can increase student motivation and interest. Aims: This study focuses on the AI-assisted creation of polyphonic music. The purpose of this study is to determine how creating…
Descriptors: Artificial Intelligence, Motivation Techniques, Music Education, Technology Uses in Education
Lung-Hsiang Wong; Hyejin Park; Chee-Kit Looi – Journal of Computer Assisted Learning, 2024
Background: The emergence of ChatGPT in the education literature represents a transformative phase in educational technology research, marked by a surge in publications driven by initial research interest in new topics and media hype. While these publications highlight ChatGPT's potential in education, concerns arise regarding their quality,…
Descriptors: Bibliometrics, Artificial Intelligence, Computer Software, Citations (References)
Meina Zhu – Journal of Computer Assisted Learning, 2025
Background: Computer programming learning and education play a critical role in preparing a workforce equipped with the necessary skills for diverse fields. ChatGPT and YouTube are technologies that support self-directed programming learning. Objectives: This study aims to examine the sentiments and primary topics discussed in YouTube comments…
Descriptors: Computer Science Education, Programming, Social Media, Video Technology
Josef Šedlbauer; Jan Cincera; Martin Slavík; Adéla Hartlová – Journal of Computer Assisted Learning, 2024
Background: The emergence of Generative Artificial Intelligence has brought a number of ethical and practical issues to higher education. Solid experimental evidence is yet inadequate to set the functional rules for the new technology. Objectives: The objective of this study is to analyse the experience of undergraduate students' interaction with…
Descriptors: Artificial Intelligence, Higher Education, Undergraduate Students, Interaction
Rashmi Khazanchi; Daniele Di Mitri; Hendrik Drachsler – Journal of Computer Assisted Learning, 2025
Background: Despite educational advances, poor mathematics achievement persists among K-12 students, particularly in rural areas with limited resources and skilled teachers. Artificial Intelligence (AI) based systems have increasingly been adopted to support the diverse learning needs of students and have been shown to enhance mathematics…
Descriptors: Mathematics Achievement, Rural Areas, Artificial Intelligence, Individualized Instruction
Fountoukidou, Sofia; Matzat, Uwe; Ham, Jaap; Midden, Cees – Journal of Computer Assisted Learning, 2022
Background: Though pedagogical artificial agents are expected to play a crucial role in the years to come, earlier studies provide inconsistent results regarding their effect on learning. This might be because their potential for exhibiting subtle nonverbal behaviours we know from human teachers has been untapped. What is more, there is little…
Descriptors: Artificial Intelligence, Assistive Technology, Technology Uses in Education, Nonverbal Communication
Gerti Pishtari; María Jesús Rodríguez-Triana; Luis P. Prieto; Adolfo Ruiz-Calleja; Terje Väljataga – Journal of Computer Assisted Learning, 2024
Background: In the field of Learning Design, it is common that researchers analyse manually design artefacts created by practitioners, using pedagogically-grounded approaches (e.g., Bloom's Taxonomy), both to understand and later to support practitioners' design practices. Automatizing these high-level pedagogically-grounded analyses would enable…
Descriptors: Electronic Learning, Instructional Design, Active Learning, Inquiry
Dabae Lee; Taekwon Son; Sheunghyun Yeo – Journal of Computer Assisted Learning, 2025
Background: Artificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real-time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain. Objectives: The primary objective of this study is to examine whether…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Preservice Teachers
Pham, Son T. H.; Sampson, Pauline M. – Journal of Computer Assisted Learning, 2022
Background: In fact, most schools around the world are not well equipped to have discussions and keep current on the expansion of artificial intelligence (AI) in many aspects of society and economy. They either ignore this conversation, or simply criticize technology, but these resistances are not stopping wide spread of various types of AI…
Descriptors: Artificial Intelligence, Preservice Teacher Education, Educational Change, Technology Integration