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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Rui Wang; Haili Ling; Jie Chen; Huijuan Fu – International Journal of Distance Education Technologies, 2025
This study adopted the Latent Dirichlet Allocation (LDA) to extract learners' needs based on 70,145 reviews from online course designed for software design and development in China and then applied Quality Function Deployment (QFD) to map learners' differentiated needs into quality attributes. Taking national first-class courses as the…
Descriptors: Educational Improvement, Student Needs, Computer Science Education, Foreign Countries
Paiheng Xu; Jing Liu; Nathan Jones; Julie Cohen; Wei Ai – Annenberg Institute for School Reform at Brown University, 2024
Assessing instruction quality is a fundamental component of any improvement efforts in the education system. However, traditional manual assessments are expensive, subjective, and heavily dependent on observers' expertise and idiosyncratic factors, preventing teachers from getting timely and frequent feedback. Different from prior research that…
Descriptors: Educational Quality, Educational Assessment, Teacher Effectiveness, Natural Language Processing
Tianlong Zhong; Gaoxia Zhu; Chenyu Hou; Yuhan Wang; Xiuyi Fan – Education and Information Technologies, 2024
The significance of interdisciplinary learning has been well-recognized by higher education institutions. However, when teaching interdisciplinary learning to junior undergraduate students, their limited disciplinary knowledge and underrepresentation of students from some disciplines can hinder their learning performance. ChatGPT's ability to…
Descriptors: Influences, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Eman Abdullah AlOmar – ACM Transactions on Computing Education, 2025
Large Language Models (LLMs), such as ChatGPT, have become widely popular for various software engineering tasks, including programming, testing, code review, and program comprehension. However, their impact on improving software quality in educational settings remains uncertain. This article explores our experience teaching the use of Programming…
Descriptors: Coding, Natural Language Processing, Artificial Intelligence, Computer Software
Jae Q. J. Liu; Kelvin T. K. Hui; Fadi Al Zoubi; Zing Z. X. Zhou; Dino Samartzis; Curtis C. H. Yu; Jeremy R. Chang; Arnold Y. L. Wong – International Journal for Educational Integrity, 2024
The application of artificial intelligence (AI) in academic writing has raised concerns regarding accuracy, ethics, and scientific rigour. Some AI content detectors may not accurately identify AI-generated texts, especially those that have undergone paraphrasing. Therefore, there is a pressing need for efficacious approaches or guidelines to…
Descriptors: Artificial Intelligence, Investigations, Identification, Human Factors Engineering
Md. Rabiul Awal; Asaduzzaman – Higher Education, Skills and Work-based Learning, 2024
Purpose: This qualitative work aims to explore the university students' attitude toward advantages, drawbacks and prospects of ChatGPT. Design/methodology/approach: This paper applies well accepted Colaizzi's phenomenological descriptive method of enquiry and content analysis method to reveal the ChatGPT user experience of students in the higher…
Descriptors: Student Experience, Technology Uses in Education, Artificial Intelligence, Natural Language Processing
Areej ElSayary – Journal of Computer Assisted Learning, 2024
Background: The widespread use of information and communication technology (ICT) has led to significant changes in societal aspects, resulting in the emergence of a "knowledge society." However, students and teachers have faced challenges in adapting to this digitalization. In the United Arab Emirates (UAE), transitioning to a…
Descriptors: Teacher Attitudes, Artificial Intelligence, Information Technology, Barriers