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Marcela Pessoa; Marcia Lima; Fernanda Pires; Gabriel Haydar; Rafaela Melo; Luiz Rodrigues; David Oliveira; Elaine Oliveira; Leandro Galvao; Bruno Gadelha; Seiji Isotani; Isabela Gasparini; Tayana Conte – IEEE Transactions on Learning Technologies, 2024
Game designers and researchers have sought to create gameful environments that consider user preferences to increase engagement and motivation. In this sense, it is essential to identify the most suitable game elements for users' profiles. Designers and researchers must choose strategies to classify users into predefined profiles and select the…
Descriptors: Educational Environment, Game Based Learning, Classification, Learner Engagement
Huang, Tao; Hu, Shengze; Yang, Huali; Geng, Jing; Liu, Sannyuya; Zhang, Hao; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
The global outbreak of the new coronavirus epidemic has promoted the development of intelligent education and the utilization of online learning systems. In order to provide students with intelligent services, such as cognitive diagnosis and personalized exercises recommendation, a fundamental task is the concept tagging for exercises, which…
Descriptors: Educational Technology, Prediction, Electronic Learning, Intelligent Tutoring Systems
Chih-Hsuan Chen; Chia-Ru Chung; Hsuan-Yu Yang; Shih-Ching Yeh; Eric Hsiao-Kuang Wu; Hsin-Jung Ting – IEEE Transactions on Learning Technologies, 2024
Possible symptoms of intellectual disability (ID) include delayed physical development that becomes more pronounced as the disability progresses, delayed development of gross and fine motor skills, sensory perception problems, and difficulty grasping the integrity of objects. Although there is no cure or reversal, research has shown that extensive…
Descriptors: Intellectual Disability, Disability Identification, Simulated Environment, Computer Simulation
Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
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
Zheng, Yafeng; Gao, Zhanghao; Shen, Jun; Zhai, Xuesong – IEEE Transactions on Learning Technologies, 2023
A text semantic classification is an essential approach to recognizing the verbal intention of online learners, empowering reliable understanding, and inquiry for the regulations of knowledge construction amongst students. However, online learning is increasingly switching from static watching patterns to the collaborative discussion. The current…
Descriptors: Semantics, Classification, Electronic Learning, Computer Mediated Communication
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Andre, Maverick; Mello, Rafael Ferreira; Nascimento, Andre; Lins, Rafael Dueire; Gasevic, Dragan – IEEE Transactions on Learning Technologies, 2021
Social presence is an essential construct of the well-known Community of Inquiry (CoI) model, which is created to support design, facilitation, and analysis of asynchronous online discussions. Social presence focuses on the extent to which participants of online discussions can see each other as "real persons" in computer-mediated…
Descriptors: Communities of Practice, Interpersonal Relationship, Computer Mediated Communication, Asynchronous Communication
Sun, Bo; Zhu, Yunzong; Yao, Zeng; Xiao, Rong; Xiao, Yongkang; Wei, Yungang – IEEE Transactions on Learning Technologies, 2020
Reading comprehension tasks are commonly used for developing students' reading ability. In order to adaptively recommend reading comprehension materials to students engaged in computerized testing, the information in an item bank (a collection of test items stored in a dataset) must be effectively indexed. Familiarity with the topics present in…
Descriptors: Automation, Indexing, Item Banks, Classification
Sahu, Archana; Bhowmick, Plaban Kumar – IEEE Transactions on Learning Technologies, 2020
In this paper, we studied different automatic short answer grading (ASAG) systems to provide a comprehensive view of the feature spaces explored by previous works. While the performance reported in previous works have been encouraging, systematic study of the features is lacking. Apart from providing systematic feature space exploration, we also…
Descriptors: Automation, Grading, Test Format, Artificial Intelligence
Mandal, Sourav; Naskar, Sudip Kumar – IEEE Transactions on Learning Technologies, 2021
Solving mathematical (math) word problems (MWP) automatically is a challenging research problem in natural language processing, machine learning, and education (learning) technology domains, which has gained momentum in the recent years. Applications of solving varieties of MWPs can increase the efficacy of teaching-learning systems, such as…
Descriptors: Classification, Word Problems (Mathematics), Problem Solving, Arithmetic
Neto, Valter; Rolim, Vitor; Pinheiro, Anderson; Lins, Rafael Dueire; Gasevic, Dragan; Mello, Rafael Ferreira – IEEE Transactions on Learning Technologies, 2021
This article investigates the impact of educational contexts on automatic classification of online discussion messages according to cognitive presence, an essential construct of the community of inquiry model. In particular, the work reported in the article analyzed online discussion messages written in Brazilian Portuguese from two different…
Descriptors: Foreign Countries, Computer Mediated Communication, Discussion, Content Analysis
Atapattu, Thushari; Falkner, Katrina; Thilakaratne, Menasha; Sivaneasharajah, Lavendini; Jayashanka, Rangana – IEEE Transactions on Learning Technologies, 2020
The substantial growth of online learning, and in particular, through massively open online courses (MOOCs), supports research into nontraditional learning contexts. Learners' confusion is one of the identified aspects which impact the overall learning process, and ultimately, course attrition. Confusion for a learner is an individual state of…
Descriptors: Electronic Learning, Online Courses, Psychological Patterns, Learning Processes
Polyzou, Agoritsa; Karypis, George – IEEE Transactions on Learning Technologies, 2019
Developing tools to support students and learning in a traditional or online setting is a significant task in today's educational environment. The initial steps toward enabling such technologies using machine learning techniques focused on predicting the student's performance in terms of the achieved grades. However, these approaches do not…
Descriptors: Prediction, Academic Achievement, Low Achievement, Classification
Camacho, Vicente Lopez; de la Guia, Elena; Olivares, Teresa; Flores, M. Julia; Orozco-Barbosa, Luis – IEEE Transactions on Learning Technologies, 2020
Increasing school dropout rates are a problem in many educational systems, with student disengagement being one significant factor. Learning analytics is a new field with a key role in educational institutions in the coming years. It may help make strategic decisions to reduce student disengagement. The use of technology in educational…
Descriptors: Learning Analytics, Learner Engagement, Measurement Equipment, Technology Uses in Education