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Seong-Won Kim; Youngjun Lee – Education and Information Technologies, 2024
In this study, the influence of socio-cultural factors on attitudes toward artificial intelligence (AI) was investigated. In total, 1,677 Korean middle school students were selected to participate, and a test tool was used to measure the attitude toward AI. As a result, according to socio-cultural factors, middle school students' attitudes toward…
Descriptors: Foreign Countries, Middle School Students, Artificial Intelligence, Sociocultural Patterns
Zhi Liu; Huimin Duan; Shiqi Liu; Rui Mu; Sannyuya Liu; Zongkai Yang – Educational Technology & Society, 2024
Conversational agents (CAs) primarily adopt knowledge scaffolding (KS) or emotional scaffolding (ES) to intervene in learners' knowledge gain and emotional experience in online learning. However, the ill-defined design for KS and ES, as well as insufficient understanding of their interactive effects on learning outcomes, have hindered the…
Descriptors: Electronic Learning, Achievement Gains, Knowledge Level, Emotional Experience
Zi Xiang Poh; Ean Teng Khor – International Journal on E-Learning, 2024
Machine learning and data mining techniques have been widely used in educational settings to identify the important features that tend to influence students' learning performance and predict their future performance. However, there is little to no research done in the context of Singapore's education. Hence, this study aims to fill the gap by…
Descriptors: Learning Analytics, Goodness of Fit, Academic Achievement, Online Courses
Tahereh Firoozi; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…
Descriptors: Turkish, Writing Evaluation, Essays, Accuracy
Boxuan Ma; Li Chen; Shin’ichi Konomi – International Association for Development of the Information Society, 2024
Generative artificial intelligence (AI) tools like ChatGPT are becoming increasingly common in educational settings, especially in programming education. However, the impact of these tools on the learning process, student performance, and best practices for their integration remains underexplored. This study examines student experiences and…
Descriptors: Artificial Intelligence, Computer Science Education, Programming, Computer Uses in Education
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
Ali Al Ghaithi; Behnam Behforouz – Journal of Educators Online, 2024
The current study attempted to measure the impact of using an interactive WhatsApp bot designed using Python language programming in grammar learning. To this end, sixty Omani pre-intermediate English proficiency learners were the sample population of this study to act as a control and experimental group, with an equal number of students in each…
Descriptors: Grammar, Programming Languages, English (Second Language), Second Language Learning
Jia, Jiyou; He, Yunfan – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this study is to design and implement an intelligent online proctoring system (IOPS) by using the advantage of artificial intelligence technology in order to monitor the online exam, which is urgently needed in online learning settings worldwide. As a pilot application, the authors used this system in an authentic…
Descriptors: Artificial Intelligence, Supervision, Computer Assisted Testing, Electronic Learning
Ali Al Ghaithi; Behnam Behforouz; Hassan Isyaku – Turkish Online Journal of Distance Education, 2024
This study tried to design a WhatsApp bot to be implemented in English language vocabulary learning context in Oman. 150 Omani English as a Foreign Language (EFL) students from three different proficiency levels were selected based on random sampling. To measure the effectiveness of the treatment, pretests, posttests, and delayed posttests were…
Descriptors: Computer Software, Teaching Methods, Computer Assisted Instruction, Student Attitudes
So, Joseph Chi-ho; Wong, Adam Ka-lok; Tsang, Kia Ho-yin; Chan, Ada Pui-ling; Wong, Simon Chi-wang; Chan, Henry C. B. – Journal of Technology and Science Education, 2023
The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic…
Descriptors: Pattern Recognition, Artificial Intelligence, Higher Education, College Students
Anna Y. Q. Huang; Jei Wei Chang; Albert C. M. Yang; Hiroaki Ogata; Shun Ting Li; Ruo Xuan Yen; Stephen J. H. Yang – Educational Technology & Society, 2023
To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…
Descriptors: Academic Achievement, Tutoring, Artificial Intelligence, Individualized Instruction
Srour, F. Jordan; Karkoulian, Silva – International Journal of Social Research Methodology, 2022
The literature provides multiple measures of diversity along a single demographic dimension, but when it comes to studying the interaction of multiple diversity types (e.g. age, gender, and race), the field of useable measures diminishes. We present the use of decision trees as a machine learning technique to automatically identify the…
Descriptors: Diversity, Decision Making, Artificial Intelligence, Correlation
Tsai, Chih-Cheng; Cheng, Yuh-Min; Tsai, Yu-Shan; Lou, Shi-Jer – Education Sciences, 2021
In this study, experimental teaching was conducted through the artificial intelligence of things (AIOT) practical course, and the 4D (discover, define, develop, deliver) double diamond shape was used to design the course and plan the teaching content to observe the students' self-efficacy and learning anxiety. The technology acceptance model (TAM)…
Descriptors: High School Students, Student Satisfaction, Value Judgment, Usability
Weragama, Dinesha; Reye, Jim – International Journal of Artificial Intelligence in Education, 2014
Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Programming Languages
Panovics, Janos – Journal of Information Technology Education: Innovations in Practice, 2012
The theory and practice of search algorithms related to state-space represented problems form the major part of the introductory course of Artificial Intelligence at most of the universities and colleges offering a degree in the area of computer science. Students usually meet these algorithms only in some imperative or object-oriented language…
Descriptors: Foreign Countries, Programming, Artificial Intelligence, Programming Languages
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