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Yaqian Zheng; Deliang Wang; Junjie Zhang; Yanyan Li; Yaping Xu; Yaqi Zhao; Yafeng Zheng – Education and Information Technologies, 2025
Generating personalized learning pathways for e-learners is a critical issue in the field of e-learning as it plays a pivotal role in guiding learners towards the successful achievement of their learning objectives. The existing literature has proposed various methods from different perspectives to address this issue, including learner-based,…
Descriptors: Individualized Instruction, Electronic Learning, Academic Achievement, Student Educational Objectives
The Impact of Visualizations with Learning Paths on College Students' Online Self-Regulated Learning
Xiaoqing Xu; Wei Zhao; Yue Li; Lifang Qiao; Jinhong Tao; Fengjuan Liu – Education and Information Technologies, 2025
The success of online learning relies on college students' self-regulated learning. The common visualizations (e.g., presentation learning behaviors' frequency and duration) are widely used to enhance online self-regulated learning. But most college students still have difficulty in accurately understanding their learning patterns and…
Descriptors: Individualized Instruction, Electronic Learning, College Students, Visualization
Youngjin Lee – Education and Information Technologies, 2025
This study investigates the development and evaluation of a Retrieval-Augmented Generation (RAG)-based statistics tutor designed to assist students with quantitative analysis methods. The RAG approach was employed to address the well-documented issue of hallucination in Large Language Models (LLMs). A computer tutor was developed that utilizes…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Teachers, Students
Guoqian Luo; Hengnian Gu; Xiaoxiao Dong; Dongdai Zhou – Education and Information Technologies, 2025
In the realm of e-learning, supporting personalized learning effectively necessitates recommending sequences of learning items that maximize learning efficiency while minimizing cognitive load, all tailored to the learner's goals. These recommendations must account for the prerequisite relationships among learning items and the learner's…
Descriptors: Electronic Learning, Individualized Instruction, Sequential Learning, Learning Processes
Hao Zhang; Shihan Chen; Sen Zheng – Education and Information Technologies, 2025
Based on the instructional interaction principles outlined by Chen and Wang (2016) in third-generation distance learning, this study employs a recursive logical perspective on the evolution of the theory of interaction in distance education. It constructs a structural equation model to measure the mediating utility path of the learner's proactive…
Descriptors: Personality Traits, Assertiveness, Interaction, Distance Education
Seongyune Choi; Hyeoncheol Kim – Education and Information Technologies, 2025
Attention to programming education from K-12 to higher education has been growing with the aim of fostering students' programming ability. This ability involves employing appropriate algorithms and computer codes to solve problems and can be enhanced through practical learning. However, in a formal educational setting, it is challenging to provide…
Descriptors: Foreign Countries, High School Freshmen, Programming, Artificial Intelligence
Feifei Wang; Alan C. K. Cheung; Ching Sing Chai; Jin Liu – Education and Information Technologies, 2025
As learners are able to perceive interactivity when interacting with instructors or peer learners in traditional learning environments, learners are similarly able to perceive interactivity when interacting with artificial intelligence (AI) in AI-supported learning environments. Advancements in AI, such as generative AI including ChatGPT and…
Descriptors: Test Construction, Test Validity, Interaction, Artificial Intelligence
Wenjuan Ma; Wenjing Ma; Yongbin Hu; Xinyu Bi – Education and Information Technologies, 2025
The integration of technology in higher education is constantly evolving, and the recent emergence of generative artificial intelligence (AI), particularly AI-based chatbots, presents both opportunities and challenges. This rapid advancement raises crucial questions about the effective and appropriate implementation of these tools in learning and…
Descriptors: Literature Reviews, Higher Education, Technology Uses in Education, Educational Technology
Huan Kang; Hong Chen – Education and Information Technologies, 2025
This study investigates the effects of online instructors' use of initiation and maintenance rapport-building strategies (RBS) on Chinese EFL learners' CALL motivation and cognitive load management. Mixed methods research was used to concurrently triangulate different strands of data on the effects of RBS on 86 randomly sampled EFL learners. The…
Descriptors: English (Second Language), Second Language Learning, Teacher Student Relationship, Cognitive Processes
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
Xi Cao; Yu-Jia Lin; Jia-Hui Zhang; Yi-Ping Tang; Meng-Ping Zhang; Hao-Yue Gao – Education and Information Technologies, 2025
This cross-sectional study explores Chinese college students' perceptions of ChatGPT in higher education, focusing on their attention, interest, and attitude. Students (N = 476) were surveyed from 67 universities and colleges in 17 provinces and municipalities in China. Students were generally positive about the use of ChatGPT. They recognized…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Attitudes, Educational Benefits
MiJeong Kim; JaMee Kim; WonGyu Lee – Education and Information Technologies, 2025
In the digital age, computational thinking (CT)-based problem-solving skills have emerged as essential competencies. Particularly, students with intellectual disabilities need equal educational opportunities and high-quality informatics education to cultivate CT-based problem-solving skills. However, research on the enhancement of CT-based…
Descriptors: Intellectual Disability, Programming, Computation, Thinking Skills
Chee-Kit Looi; Fenglin Jia – Education and Information Technologies, 2025
Since the advent of chatbots enabled by Generative AI such as ChatGPT, their application in the domain of education has been linked to promises of personalizing learning (PL). Through a study of conversational interactions of graduate students with such chatbots, this paper provides an empirical study of how current ChatGPT technologies can enable…
Descriptors: Individualized Instruction, Artificial Intelligence, Technology Uses in Education, Educational Technology
Ji Hyun Yu; Devraj Chauhan – Education and Information Technologies, 2025
This paper presents a comprehensive analysis of the major themes in Natural Language Processing (NLP) applications for personalized learning, derived from a Latent Dirichlet Allocation (LDA) examination of top educational technology journals from 2014 to 2023. Our methodology involved collecting a corpus of relevant journal articles, applying LDA…
Descriptors: Natural Language Processing, Individualized Instruction, Educational Technology, Emotional Intelligence
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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