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Huaiya Liu; Yuyue Zhang; Jiyou Jia – IEEE Transactions on Learning Technologies, 2024
Intelligent tutoring systems (ITSs) aim to deliver personalized learning support to each learner, aligning with the educational aspiration of many countries, including China. ITSs' personalized support is mainly achieved by providing individual prompts to learners when they encounter difficulties in problem-solving. The guiding principles and…
Descriptors: Intelligent Tutoring Systems, Mathematics Achievement, Individualized Instruction, Foreign Countries
Yu Bai; Jun Li; Jun Shen; Liang Zhao – IEEE Transactions on Learning Technologies, 2024
The potential of artificial intelligence (AI) in transforming education has received considerable attention. This study aims to explore the potential of large language models (LLMs) in assisting students with studying and passing standardized exams, while many people think it is a hype situation. Using primary education as an example, this…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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
Hershcovits, Haviv; Vilenchik, Dan; Gal, Kobi – IEEE Transactions on Learning Technologies, 2020
This paper studies students engagement in e-learning environments in which students work independently and solve problems without external supervision. We propose a new method to infer engagement patterns of users in such self-directed environments. We view engagement as a continuous process in time, measured along chosen axes that are derived…
Descriptors: Electronic Learning, Problem Solving, Independent Study, Factor Analysis
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Whitehill, Jacob; Movellan, Javier – IEEE Transactions on Learning Technologies, 2018
We propose a method of generating teaching policies for use in intelligent tutoring systems (ITS) for concept learning tasks [1], e.g., teaching students the meanings of words by showing images that exemplify their meanings à la Rosetta Stone [2] and Duo Lingo [3]. The approach is grounded in control theory and capitalizes on recent work by [4],…
Descriptors: Intelligent Tutoring Systems, Second Language Learning, Educational Policy, Comparative Analysis
Ayedoun, Emmanuel; Hayashi, Yuki; Seta, Kazuhisa – IEEE Transactions on Learning Technologies, 2020
This article proposes a computer-based approach to effectively enhance second language learners' willingness to communicate in the target language. To do so, we implemented a conversational agent embedding a dialogue management model based on two conversational strategies (i.e., communication strategies and affective backchannels), serving as…
Descriptors: Scaffolding (Teaching Technique), Teaching Methods, Second Language Learning, Second Language Instruction
VanLehn, Kurt; Wetzel, Jon; Grover, Sachin; van de Sande, Brett – IEEE Transactions on Learning Technologies, 2017
Constructing models of dynamic systems is an important skill in both mathematics and science instruction. However, it has proved difficult to teach. Dragoon is an intelligent tutoring system intended to quickly and effectively teach this important skill. This paper describes Dragoon and an evaluation of it. The evaluation randomly assigned…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Skill Development
VanLehn, Kurt; Zhang, Lishan; Burleson, Winslow; Girard, Sylvie; Hidago-Pontet, Yoalli – IEEE Transactions on Learning Technologies, 2017
This project aimed to improve students' learning and task performance using a non-cognitive learning companion in the context of both a tutor and a meta-tutor. The tutor taught students how to construct models of dynamic systems and the meta-tutor taught students a learning strategy. The non-cognitive learning companion was designed to increase…
Descriptors: Metacognition, Learning Strategies, Nonverbal Communication, High School Students
Gomez, Jorge E.; Huete, Juan F.; Hernandez, Velssy L. – IEEE Transactions on Learning Technologies, 2016
The dynamics of the world today demands a change in traditional education paradigms to enable the creation of more efficient learning environments, where students will learn more effectively and will play a more active role in their education. They should interact with the knowledge at anytime-anywhere. In order to tackle this problem we should…
Descriptors: Active Learning, Telecommunications, Handheld Devices, Intelligent Tutoring Systems
Calvo, R. A.; O'Rourke, S. T.; Jones, J.; Yacef, K.; Reimann, P. – IEEE Transactions on Learning Technologies, 2011
Academic writing, individual or collaborative, is an essential skill for today's graduates. Unfortunately, managing writing activities and providing feedback to students is very labor intensive and academics often opt out of including such learning experiences in their teaching. We describe the architecture for a new collaborative writing support…
Descriptors: Architecture, Teaching Methods, Feedback (Response), Collaborative Writing