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Leonora Kaldaras; Kevin Haudek; Joseph Krajcik – International Journal of STEM Education, 2024
We discuss transforming STEM education using three aspects: learning progressions (LPs), constructed response performance assessments, and artificial intelligence (AI). Using LPs to inform instruction, curriculum, and assessment design helps foster students' ability to apply content and practices to explain phenomena, which reflects deeper science…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, STEM Education, Learning Trajectories
Bin Meng; Fan Yang – International Journal of Web-Based Learning and Teaching Technologies, 2025
This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…
Descriptors: Students, Teachers, Computer Assisted Instruction, Knowledge Representation
Da Teng; Xiangyang Wang; Yanwei Xia; Yue Zhang; Lulu Tang; Qi Chen; Ruobing Zhang; Sujin Xie; Weiyong Yu – Education and Information Technologies, 2025
The swift advancement of artificial intelligence, especially large language models (LLMs), has generated novel prospects for improving educational methodologies. Nonetheless, the successful incorporation of these technologies into pedagogical methods, such as flipped classrooms, continues to pose a challenge. This study investigates the…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Flipped Classroom, Technology Uses in Education
Said A. Salloum; Khaled Mohammad Alomari; Aseel M. Alfaisal; Rose A. Aljanada; Azza Basiouni – Smart Learning Environments, 2025
The integration of artificial intelligence in educational environments has the potential to revolutionize teaching and learning by enabling real-time analysis of students' emotions, which are crucial determinants of engagement, motivation, and learning outcomes. However, accurately detecting and responding to these emotions remains a significant…
Descriptors: Artificial Intelligence, Emotional Response, Psychological Patterns, Individualized Instruction
Pilar Cuevas-Ruiz; Luz Rello; Ismael Sanz; Almudena Sevilla – Annenberg Institute for School Reform at Brown University, 2025
Persistent literacy skills deficits hinder educational attainment, limit labour market opportunities, and exacerbate socioeconomic inequalities. This paper evaluates the causal effect of an AI-driven Computer-Assisted Learning (CAL) program implemented by the Government of Madrid, which features personalised, adaptive content and real-time…
Descriptors: Artificial Intelligence, Individualized Instruction, Reading Skills, Equal Education
Ika Qutsiati Utami; Wu-Yuin Hwang; Uun Hariyanti – Journal of Educational Computing Research, 2024
Recently, automatic question generation (AQG) has been researched extensively for educational purposes. Existing approaches generally lack relevant information on the authentic context and problem diversity with various difficulty levels, so we proposed a new AQG system for generating contextualized and personalized mathematic word problems (MWP)…
Descriptors: Foreign Countries, Elementary School Mathematics, Elementary School Students, Mathematics Instruction
Sinem Aslan; Lenitra M. Durham; Nese Alyuz; Rebecca Chierichetti; Pete A. Denman; Eda Okur; David I. Gonzalez Aguirre; Julio C. Zamora Esquivel; Hector A. Cordourier Maruri; Sangita Sharma; Giuseppe Raffa; Richard E. Mayer; Lama Nachman – British Journal of Educational Technology, 2024
Previous research showed that the parents acknowledged the technology's benefits for their young children's learning, however, they are still worried about the extended screen time, lack of physical activity and lack of social interactions. To address these concerns, we developed Kid Space to enable pedagogically appropriate technology use for…
Descriptors: Parents, Young Children, Artificial Intelligence, Interpersonal Communication
Muhammad Mujtaba Asad; Shafaque Shahzad; Syed Hassan Ali Shah; Fahad Sherwani; Norah Mansour Almusharraf – International Journal of Information and Learning Technology, 2024
Purpose: This paper holds considerable importance in the educational dynamics specifically ChatGPT as generative multimedia in English language writing pedagogy and presents a unique lens, as it uses a narrative literature review to view this cutting-edge topic. This paper compiles the knowledge and information already available regarding the…
Descriptors: English (Second Language), Writing Instruction, Artificial Intelligence, Computer Assisted Instruction
Prapasiri Klayklung; Piyawatjana Chocksathaporn; Pongsakorn Limna; Tanpat Kraiwanit; Kris Jangjarat – Online Submission, 2023
The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper…
Descriptors: Artificial Intelligence, Interaction, Foreign Countries, Technology Integration
Kolchenko, Vasiliy – HAPS Educator, 2018
Artificial intelligence (AI) is transforming many fields, including education. Can modern AI replace teachers? We discuss some popular AI applications for adaptive learning, how they are related to personalized education, what makes these applications "intelligent," and how the quality and quantity of student-generated data changes the…
Descriptors: Artificial Intelligence, Individualized Instruction, Computer Assisted Instruction, Student Reaction
Johann Engelbrecht; Marcelo C. Borba – ZDM: Mathematics Education, 2024
In this paper we review selected significant developments in the use of digital technology in the teaching and learning of mathematics over the last five years. We focus on a number of important topics in this field, including the evolvement of STEAM and critical making as well as the process of redefining learning spaces in the transformation of…
Descriptors: STEM Education, Art Education, COVID-19, Pandemics
Rogerson-Revell, Pamela M. – RELC Journal: A Journal of Language Teaching and Research, 2021
This viewpoint essay considers the current status of computer-assisted pronunciation training (CAPT) before examining some of the current issues and future directions in the field. The underlying premise is the pedagogic potential of CAPT systems and resources for teaching and learning, and the need for greater synergy between technological design…
Descriptors: Computer Assisted Instruction, Pronunciation Instruction, Individualized Instruction, Feedback (Response)
Lijuan Feng – Journal of Educational Computing Research, 2025
This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
Galiya Ldokova; Svetlana Frumina; Suad Abdalkareem Alwaely – Smart Learning Environments, 2025
The aim of the study is to examine the influence of students' psychotypes on their learning using digital educational technologies within the Metaverse. In the course of the longitudinal experimental study, the results of the initial testing of 79 students during their undergraduate studies and the re-testing of 75 of these students during their…
Descriptors: Undergraduate Students, Graduate Students, Psychological Characteristics, Brain
Wu Xiaofan; Nagaletchimee Annamalai – Contemporary Educational Technology, 2025
This investigation utilized a phenomenological approach to investigate the experience of English language educators in employing artificial intelligence (AI) tools into English language learning. The study used purposive sampling and 20 participants were interviewed. The data analysis was guided by Bronfenbrenner's (1979) ecological systems…
Descriptors: Technology Uses in Education, Artificial Intelligence, Educational Technology, Second Language Learning