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Joaquín Rodríguez-Ruiz; Inmaculada Marín-López; Raquel Espejo-Siles – Education and Information Technologies, 2025
The present study aimed to analyse if self-control, self-esteem and self-efficacy are related to the use of artificial intelligence tools. These tools are being incorporated to educational practices, but there is a lack of empirical evidence about the relation between artificial intelligence use by students and their personal and psychological…
Descriptors: Artificial Intelligence, Self Control, Self Esteem, Self Efficacy
Mark Feng Teng – European Journal of Education, 2025
The present study explored EFL students' perceptions and experiences in utilising ChatGPT to seek feedback for writing. The present study also examined how levels of metacognitive awareness (MA) influenced these perceptions and experiences. Utilising a mixed-method research design, the study collected data from a total of 40 EFL undergraduates…
Descriptors: English (Second Language), Student Attitudes, Feedback (Response), Writing (Composition)
Mouna Ben Said; Yessine Hadj Kacem; Abdulmohsen Algarni; Atef Masmoudi – Education and Information Technologies, 2024
In the current educational landscape, where large amounts of data are being produced by institutions, Educational Data Mining (EDM) emerges as a critical discipline that plays a crucial role in extracting knowledge from this data to help academic policymakers make decisions. EDM has a primary focus on predicting students' academic performance.…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
Raoyu Qiu; Zequn Lin; Zican Yang; Liang Gao – Journal of Chemical Education, 2024
Machine learning (ML) is extensively applied in chemistry, particularly in vibrational spectroscopy. However, few teaching examples effectively demonstrate the capabilities of ML in classifying polymeric materials, exhibiting subtle spectral differences that elude visual discrimination. This study presents a teaching example specifically tailored…
Descriptors: Artificial Intelligence, Classification, Undergraduate Study, Chemistry
Harry Barton Essel; Dimitrios Vlachopoulos; Henry Nunoo-Mensah; John Opuni Amankwa – British Journal of Educational Technology, 2025
Conversational user interfaces (CUI), including voice interfaces, which allow users to converse with computers via voice, are gaining wide popularity. VoiceBots allow users to receive a response in real-time, regardless of the communication device. VoiceBots have been explored in fields such as customer service to automate repetitive queries and…
Descriptors: Foreign Countries, Artificial Intelligence, Program Effectiveness, Undergraduate Students
Hyunkyoung Yoon; Jihye Hwang; Kyungwon Lee; Kyeong Hah Roh; Oh Nam Kwon – ZDM: Mathematics Education, 2024
In this exploratory study, we investigate undergraduate students' engagement with generative Artificial Intelligence (genAI) in proving mathematical statements. We selected six mathematical statements to conduct interviews with three students. We present the emergent framework, Students' Interactive Proving Experience with AI (SIPE-AI), which…
Descriptors: Artificial Intelligence, Computer Uses in Education, Mathematical Logic, Ethics
Arzu Deveci Topal; Asiye Toker Gökçe; Canan Dilek Eren; Aynur Kolburan Geçer – Journal of Learning and Teaching in Digital Age, 2025
This study aims to adapt to Turkish the "Scale for the assessment of non-experts: AI literacy" developed by Laupichler et al. (2023a). The scale consists of 31 items with three sub-dimensions: technical understanding, critical thinking, and practical applications. The data required for the validity and reliability study of the scale were…
Descriptors: Artificial Intelligence, Technological Literacy, Measures (Individuals), Foreign Countries
Yao Qu; Michelle Xin Yi Tan; Jue Wang – Smart Learning Environments, 2024
The rapid development of generative artificial intelligence (GenAI) technologies has sparked widespread discussions about their potential applications in higher education. However, little is known about how students from various disciplines engage with GenAI tools. This study explores undergraduate students' GenAI knowledge, usage intentions, and…
Descriptors: Undergraduate Students, Learner Engagement, Technology Uses in Education, Artificial Intelligence
Tian Song; Hang Zhang; Yijia Xiao – IEEE Transactions on Learning Technologies, 2024
High-quality programming projects for education are critically required in teaching. However, it is hard to develop those projects efficiently and artificially constrained by the lecturers' experience and background. The recent popularity of large language models (LLMs) has led to a great number of applications in the field of education, but…
Descriptors: Artificial Intelligence, Education, Intellectual Disciplines, Undergraduate Students
Xiaojing Duan; Bo Pei; G. Alex Ambrose; Arnon Hershkovitz; Ying Cheng; Chaoli Wang – Education and Information Technologies, 2024
Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this…
Descriptors: Academic Achievement, Artificial Intelligence, Prediction, Models
Sue Lim; Ralf Schmälzle – Communication Teacher, 2024
Courses: Health Communication, Public Communication Campaigns, Public Relations, Introduction to Communication. Objectives: By the end of this workshop, students will be able to: (1) understand how artificial intelligence--based large language learning models work and be able to explain core concepts such as word embeddings, neural networks, and…
Descriptors: Artificial Intelligence, Communication Skills, Introductory Courses, Workshops
Eui-Chul Jung; Meile Le – IAFOR Journal of Education, 2024
Interpreting and incorporating machine learning technology from a human perspective helps define the role of product designers in the era of artificial intelligence. With this background, this study developed a 7-week design course about machine learning-based product design. Subsequently, in Fall 2023, a class with seven undergraduate students…
Descriptors: Curriculum Development, Man Machine Systems, Artificial Intelligence, Merchandise Information
Hua-Xu Zhong; Jui-Hung Chang; Chin-Feng Lai; Pei-Wen Chen; Shang-Hsuan Ku; Shih-Yeh Chen – Education and Information Technologies, 2024
Artificial intelligence (AI) education is becoming an advanced learning trend in programming education. However, AI subjects can be difficult to understand because they require high programming skills and complex knowledge. This makes it challenging to determine how different departments of students are affected by them. This study draws on…
Descriptors: Undergraduate Students, Artificial Intelligence, Programming, STEM Education
Kamali N. Sripathi; Rosa A. Moscarella; Matthew Steele; Rachel Yoho; Hyesun You; Luanna B. Prevost; Mark Urban-Lurain; John Merrill; Kevin C. Haudek – Journal of Mixed Methods Research, 2024
Assessing student knowledge based on their writing using traditional qualitative methods is time-consuming. To improve speed and consistency of text analysis, we present our mixed methods development of a machine learning predictive model to analyze student writing. Our approach involves two stages: first an exploratory sequential design, and…
Descriptors: Artificial Intelligence, Mixed Methods Research, Student Writing Models, Biology
Pablo Antonio Archila; Brigithe Tatiana Ortiz; Anne-Marie Truscott de Mejía; Jorge Molina – Information and Learning Sciences, 2024
Purpose: In November 2022, the commercial company, OpenAI, launched ChatGPT. Since then, university students have rapidly become regular users of this artificial intelligence (AI) platform. One reason for this is the powerful capability of this generative AI tool to produce textual content, which in many cases, is almost indistinguishable from…
Descriptors: Foreign Countries, Bilingual Education, English, Spanish