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Ethan Prihar; Manaal Syed; Korinn Ostrow; Stacy Shaw; Adam Sales; Neil Heffernan – International Educational Data Mining Society, 2022
As online learning platforms become more ubiquitous throughout various curricula, there is a growing need to evaluate the effectiveness of these platforms and the different methods used to structure online education and tutoring. Towards this endeavor, some platforms have performed randomized controlled experiments to compare different user…
Descriptors: Educational Trends, Electronic Learning, Educational Experience, Educational Experiments
Ding, Xinyi; Larson, Eric C. – International Educational Data Mining Society, 2019
Knowledge tracing allows Intelligent Tutoring Systems to infer which topics or skills a student has mastered, thus adjusting curriculum accordingly. Deep Knowledge Tracing (DKT) uses recurrent neural networks (RNNs) for knowledge tracing and has achieved significant improvements compared with models like Bayesian Knowledge Tracing (BKT) and…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Models, Skills
Nikola M. Luburic; Luka Z. Doric; Jelena J. Slivka; Dragan Lj. Vidakovic; Katarina-Glorija G. Grujic; Aleksandar D. Kovacevic; Simona B. Prokic – IEEE Transactions on Learning Technologies, 2025
Software engineers are tasked with writing functionally correct code of high quality. Maintainability is a crucial code quality attribute that determines the ease of analyzing, modifying, reusing, and testing a software component. This quality attribute significantly affects the software's lifetime cost, contributing to developer productivity and…
Descriptors: Intelligent Tutoring Systems, Coding, Computer Software, Technical Occupations
Seongyune Choi; Yeonju Jang; Hyeoncheol Kim – Interactive Learning Environments, 2024
Intelligent Personal Assistants (IPAs) are becoming more prevalent in daily and educational contexts, increasing the possibility of using them as learning partners that can provide more personalized and learner-centric learning opportunities. However, research has primarily focused on educational advantages that IPAs may provide, overlooking…
Descriptors: Intelligent Tutoring Systems, Foreign Countries, Technology Uses in Education, Independent Study
Elif Polat; Yunus Emre Bastug; Sinan Hopcan; Simge Cepdibi Sibiç; Nazli Ceren Isikligil – Journal of Learning and Teaching in Digital Age, 2024
This study investigates the primary school teachers' perceptions towards the Intelligent Material System (IMS), which was developed to enhance the quality of inclusive environments and support the academic skills of students with Special Educational Needs (SEN). Within this scope, IMS training was conducted with 84 classroom teachers who worked at…
Descriptors: Teacher Attitudes, Elementary School Teachers, Inclusion, Special Education
Shreya Singhal; Andres Felipe Zambrano; Maciej Pankiewicz; Xiner Liu; Chelsea Porter; Ryan S. Baker – International Educational Data Mining Society, 2024
Education is increasingly taking place in learning environments mediated by technology. This transition has made it easier to collect student-generated data including comments in discussion forums and chats. Although this data is extremely valuable to researchers, it often contains sensitive information like names, locations, social media links,…
Descriptors: MOOCs, Privacy, Confidential Records, Student Records
Dang, Steven C.; Koedinger, Kenneth R. – International Educational Data Mining Society, 2020
Effective teachers recognize the importance of transitioning students into learning activities for the day and accounting for the natural drift of student attention while creating lesson plans. In this work, we analyze temporal patterns of gaming behaviors during work on an intelligent tutoring system with a broader goal of detecting temporal…
Descriptors: Learner Engagement, Intelligent Tutoring Systems, Student Behavior, Student Motivation
Mangera, Elisabet; Supratno, Haris; Suyatno – Pegem Journal of Education and Instruction, 2023
This studied focus on the relationship between transhumanist and artificial intelligence in the Education Context; Particularly Teaching and Learning Process at private university in Makassar, South Sulawesi, Indonesia. Anchored by a qualitative analysis and participated by five teachers, the data were analyzed in-depth interview. It was designed…
Descriptors: Humanism, Artificial Intelligence, Learning Processes, Postsecondary Education
Wan, Haipeng; Yu, Shengquan – Interactive Learning Environments, 2023
Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Artificial Intelligence, Cognitive Mapping
Wijaya, Adi; Setiawan, Noor Akhmad; Shapiai, Mohd Ibrahim – Electronic Journal of e-Learning, 2023
This study aims to provide a comprehensive overview of the current state and potential future research in learning style detection. With the increasing number and diversity of research in this area, a quantitative approach is necessary to map out current themes and identify potential areas for future research. To achieve this goal, a bibliometric…
Descriptors: Bibliometrics, Cognitive Style, Diagnostic Tests, Content Analysis
Troussas, Christos; Chrysafiadi, Konstantina; Virvou, Maria – Education and Information Technologies, 2021
Personalized computer-based tutoring demands learning systems and applications that identify and keep personal characteristics and features for each individual learner. This is achieved by the technology of student modeling. One prevalent technique of student modeling is stereotypes. Furthermore, individuals differ in how they learn. So, the way…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style, Stereotypes
Arguedas, Marta; Daradoumis, Thanasis – Journal of Computer Assisted Learning, 2021
There is a lack of studies that examine the role of a pedagogical agent on student development in a specific learning situation that involves psychological and cognitive preparatory activities in high school settings. We examined the effectiveness of pedagogical agent (APT) cognitive and affective feedback on learner motivation and well-being. We…
Descriptors: High School Students, Feedback (Response), Learning Motivation, Well Being
Yilmaz, Gizem Karaoglan; Tepgeç, Mustafa; Müftüoglu, Cennet Terzi; Sulak, Sema; Sahin, Muhittin; Aydin, Furkan; Yilmaz, Ramazan; Yurdugül, Halil – International Association for Development of the Information Society, 2021
Massive Open Online Courses (MOOCs) have become widespread all around the world since their conceptualization, both in terms of the number of students enrolled and the number of courses available. Some issues or learner needs in these environments, such as accreditation, quality of assessment and scaffolding for left-behind learners, have also…
Descriptors: Student Attitudes, Preferences, Online Courses, Educational Technology
Zeyad Alshaikh – ProQuest LLC, 2021
Programming skills are a vital part of many disciplines but can be challenging to teach and learn. Thus, the programming courses are considered difficult and a major stumbling block. To overcome these challenges, students could benefit from extensive individual support such as tutoring, but there are simply not enough qualified tutors available to…
Descriptors: Questioning Techniques, Teaching Methods, Intelligent Tutoring Systems, Coding
Sarsa, Sami; Leinonen, Juho; Hellas, Arto – Journal of Educational Data Mining, 2022
New knowledge tracing models are continuously being proposed, even at a pace where state-of-the-art models cannot be compared with each other at the time of publication. This leads to a situation where ranking models is hard, and the underlying reasons of the models' performance -- be it architectural choices, hyperparameter tuning, performance…
Descriptors: Learning Processes, Artificial Intelligence, Intelligent Tutoring Systems, Memory

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