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Sha, Lele; Rakovic, Mladen; Lin, Jionghao; Guan, Quanlong; Whitelock-Wainwright, Alexander; Gasevic, Dragan; Chen, Guanliang – IEEE Transactions on Learning Technologies, 2023
In online courses, discussion forums play a key role in enhancing student interaction with peers and instructors. Due to large enrolment sizes, instructors often struggle to respond to students in a timely manner. To address this problem, both traditional machine learning (ML) (e.g., Random Forest) and deep learning (DL) approaches have been…
Descriptors: Computer Mediated Communication, Discussion Groups, Artificial Intelligence, Intelligent Tutoring Systems
Chengming Zhang; Florian Hofmann; Lea Plößl; Michaela Gläser-Zikuda – Education and Information Technologies, 2024
Reflective practice holds critical importance, for example, in higher education and teacher education, yet promoting students' reflective skills has been a persistent challenge. The emergence of revolutionary artificial intelligence technologies, notably in machine learning and large language models, heralds potential breakthroughs in this domain.…
Descriptors: Foreign Countries, Higher Education, Reflection, Student Writing Models
Conijn, Rianne; Kahr, Patricia; Snijders, Chris – Journal of Learning Analytics, 2023
Ethical considerations, including transparency, play an important role when using artificial intelligence (AI) in education. Explainable AI has been coined as a solution to provide more insight into the inner workings of AI algorithms. However, carefully designed user studies on how to design explanations for AI in education are still limited. The…
Descriptors: Ethics, Writing Evaluation, Artificial Intelligence, Essays
Yung-Hsiang Hu; Jo Shan Fu; Hui-Chin Yeh – Interactive Learning Environments, 2024
Artificial intelligence aims to restructure and process re-engineering education and teaching processes and accelerate the evolution of the whole education system from information to intelligence. Robotic Process Automation (RPA) robots learn by observing people at work, analyzing user processes repeatedly, and adjusting or correcting automated…
Descriptors: Intelligent Tutoring Systems, Robotics, Automation, Instructional Effectiveness
Premlatha, K. R.; Dharani, B.; Geetha, T. V. – Interactive Learning Environments, 2016
E-learning allows learners individually to learn "anywhere, anytime" and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to…
Descriptors: Electronic Learning, Profiles, Automation, Classification
Tsai, Min-hsiu – Action in Teacher Education, 2012
This study investigates the consistency between human raters and an automated essay scoring system in grading high school students' English compositions. A total of 923 essays from 23 classes of 12 senior high schools in Taiwan (Republic of China) were obtained and scored manually and electronically. The results show that the consistency between…
Descriptors: Foreign Countries, High School Students, Writing (Composition), Essays
Rus, Vasile; Lintean, Mihai; Azevedo, Roger – International Working Group on Educational Data Mining, 2009
This paper presents several methods to automatically detecting students' mental models in MetaTutor, an intelligent tutoring system that teaches students self-regulatory processes during learning of complex science topics. In particular, we focus on detecting students' mental models based on student-generated paragraphs during prior knowledge…
Descriptors: Data Analysis, Prior Learning, Cognitive Structures, College Students
Ozpolat, Ebru; Akar, Gozde B. – Computers & Education, 2009
A desirable characteristic for an e-learning system is to provide the learner the most appropriate information based on his requirements and preferences. This can be achieved by capturing and utilizing the learner model. Learner models can be extracted based on personality factors like learning styles, behavioral factors like user's browsing…
Descriptors: Cognitive Style, Classification, Measures (Individuals), Measurement Techniques
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers

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