Article
Computer Science, Artificial Intelligence
Amin Zammouri, Abdelaziz Ait Moussa, Sylvain Chevallier
Summary: In the context of learning environments, this study introduces a new architecture using a multi-agent-based approach to assist learners, generating adaptive learning content and interactions based on electroencephalogram. The study also presents an unsupervised approach to estimate and recognize the learner's cognitive load by analyzing brain rhythms. Experimental results demonstrate the accuracy of the approach in describing the learner's mental efforts and cognitive load.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Chemistry, Multidisciplinary
Vladimir Bradac, Pavel Smolka, Martin Kotyrba, Tomas Prudek
Summary: The article discusses the construction of an intelligent tutoring system for distance learning and combined forms of studies. The proposed model emphasizes the individual needs of students through an expert system and adaptation mechanisms. The focus on the individuality of students is considered an innovative approach that can be achieved on a large scale.
APPLIED SCIENCES-BASEL
(2022)
Article
Mathematics
Xiushan Zhang
Summary: This paper proposes an improved collaborative filtering recommendation algorithm with enhanced user model. By normalizing user rating data and introducing time forgetting weight, the algorithm improves recommendation accuracy. The similarity calculation method is also improved. Experimental results demonstrate better performance of the proposed algorithm in terms of recommendation accuracy and efficiency.
JOURNAL OF MATHEMATICS
(2022)
Review
Education & Educational Research
Luiz Rodrigues, Filipe Dwan Pereira, Marcelo Marinho, Valmir Macario, Ig Ibert Bittencourt, Seiji Isotani, Diego Dermeval, Rafael Mello
Summary: This article fills the research gap by reviewing the methods, characteristics, and applications of math ITSs compatible with handwritten input. The study found that all ITSs depend on receiving handwritten input from a touchscreen interface, and most ITSs focus on similar audiences, subjects, and applications. To enable equitable access to ITSs, the authors propose the concept of "ITS Unplugged" and present a research agenda for developing such systems.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Computer Science, Artificial Intelligence
Shengyingjie Liu, Zongkai Yang, Sannyuya Liu, Ruxia Liang, Jianwen Sun, Qing Li, Xiaoxuan Shen
Summary: Intelligent tutoring systems (ITS) analyze user behavior to customize personalized learning strategies. However, existing methods cannot effectively model ITS data due to the discrete user evolution. This study introduces the concept of a discrete evolution graph (DEG) and proposes the DEGE method to embed ITS data in a hyperbolic space, outperforming other baselines in question annotation and performance prediction.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Education & Educational Research
Arief Ramadhan, Harco Leslie Hendric Spits Warnars, Fariza Hanis Abdul Razak
Summary: One of the developments in Information and Communication Technology (ICT) for learning is the combination of Intelligent Tutoring System (ITS) with gamification. This study presents a Systematic Literature Review (SLR) that synthesizes the characteristics of ITS + G, revealing its potential in both STEM and non-STEM subjects. The main game elements used in ITS + G are levels, points, and progress bars, which have been found to have positive impacts.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Computer Science, Information Systems
Pablo Arnau-Gonzalez, Ana Serrano-Mamolar, Stamos Katsigiannis, Turke Althobaiti, Miguel Arevalillo-Herraez
Summary: Math Word Problem (MWP) solving is often used in Intelligent Tutoring Systems (ITS) to teach mathematics. Encoding potential solutions for each supported problem is a drawback of ITS. This study proposes a method to automatically convert a new MWP into the internal representation of an ITS, simplifying the task of adding new problems. Pre-trained language models are used to translate the problem into Python code, which can be easily imported into an ITS. Experimental results show the effectiveness of this approach, with expected improvement as language models advance.
Article
Computer Science, Artificial Intelligence
Cristina Conati, Oswald Barral, Vanessa Putnam, Lea Rieger
Summary: The research shows that providing explanations increases students' trust in hints, perceived usefulness, and intention to use them again. Students' access and learning gains from explanations are modulated by multiple user characteristics, providing insights on personalizing explanations.
ARTIFICIAL INTELLIGENCE
(2021)
Review
Education & Educational Research
Elham Mousavinasab, Nahid Zarifsanaiey, Sharareh R. Niakan Kalhori, Mahnaz Rakhshan, Leila Keikha, Marjan Ghazi Saeedi
Summary: This study focused on the variant characteristics of Intelligent Tutoring systems (ITSs) developed in different educational fields, mainly utilizing artificial intelligent techniques such as action-condition rule-based reasoning, data mining, and Bayesian network. These techniques enable personalized guidance, assessment of learners, and adaptive instruction in ITSs.
INTERACTIVE LEARNING ENVIRONMENTS
(2021)
Article
Education & Educational Research
Yun Huang, Peter Brusilovsky, Julio Guerra, Kenneth Koedinger, Christian Schunn
Summary: This study highlights the importance of skill integration in learning technologies and demonstrates the effectiveness of ITS technology in computing education. It also provides general implications for designing learning technologies to foster robust learning.
JOURNAL OF COMPUTER ASSISTED LEARNING
(2023)
Review
Computer Science, Interdisciplinary Applications
Galina Deeva, Daria Bogdanova, Estefania Serral, Monique Snoeck, Jochen De Weerdt
Summary: Real-time teacher feedback is crucial for learners' knowledge and skills acquisition. Recent technological advancements have enabled the development of computer tutoring systems that provide personalized feedback, supporting learners in various domains and settings.
COMPUTERS & EDUCATION
(2021)
Article
Education & Educational Research
Priynka Sharma, Mayuri Harkishan
Summary: This paper introduces the architectural design of Intelligent Tutoring Systems, with a focus on the core implementation of user interaction. The proposed Programming-Tutor system aims to provide learning support and immersive learning experience for students in the Pacific through online programming courses. It is hypothesized that Intelligent Tutoring Systems can facilitate the learning of programming and improve students' learning efficiency.
EDUCATION AND INFORMATION TECHNOLOGIES
(2022)
Article
Computer Science, Interdisciplinary Applications
Yiyang Le, Zhongting Chen, Shuo Liu, Weiguo Pang, Ciping Deng
Summary: The study found that positive emotional design can alleviate cognitive overload and improve learning performance in situations of ego depletion. Results support the viewpoint that implementing emotional design methods can prevent learning impairment, and also discuss the impact of learners' affective states on cognitive load.
COMPUTERS & EDUCATION
(2021)
Article
Neurosciences
Mark H. Myers
Summary: The study uses AutoTutor data and data mining methods to identify key frequent item sets that can predict student emotional states. Various feature extraction techniques, such as multilayer-perceptron and naive Bayes, were utilized to classify emotional states. Among all emotions, "Flow" and "Frustration" were the most accurately classified.
Article
Engineering, Electrical & Electronic
Fehaid Alqahtani, Stamos Katsigiannis, Naeem Ramzan
Summary: This study proposes the use of physiological signals and machine learning to detect a learner's affective state during test taking. The experiments show a relation between acquired signals and the examined tasks, demonstrating the potential of this approach for enhancing ITS.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Interdisciplinary Applications
Elise Ameloot, Tijs Rotsaert, Thomas Ameloot, Bart Rienties, Tammy Schellens
Summary: This study investigates the impact of using learning analytics to support students' autonomy and competence needs in a blended learning environment. The findings show that teachers' adaptation based on learning analytics positively influences students' satisfaction with the adapted learning environment. However, students' basic psychological needs vary depending on the face-to-face workshop subject. The study emphasizes the importance of thoughtful blended learning course design and provides recommendations for effective learning analytics utilization in university settings.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Tzu-Chi Yang, Zhi-Shen Lin
Summary: Computational thinking is essential in the current era and learning programming is the most effective way to develop it. Introducing computational thinking and programming at an early age is recommended. Graphic organizers serve as a bridge between students' existing knowledge and new learning, enhancing their learning process. The study found that using graphic organizers improved elementary school students' computational thinking, programming skills, and learning experiences.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Yuqin Yang, Kaicheng Yuan, Gaoxia Zhu, Lizhen Jiao
Summary: The study finds that the design of collaborative analytics-enhanced reflective assessment can promote conducive epistemic emotions to knowledge building among undergraduates, and enriches our understanding of the relationships between metacognition, epistemic emotions, and knowledge building practices.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Vishal Kiran Kuvar, Jeremy N. Bailenson, Caitlin Mills
Summary: Recent research suggests that students' minds often wander off-task during learning, regardless of the learning modality. This study explores the potential of virtual reality (VR) to reduce task-unrelated thoughts (TUT) and finds that learning with VR leads to lower TUT and better performance.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Yiming Liu, Jeremy Tzi Dong Ng, Xiao Hu, Zhengyang Ma, Xiaoyan Lai
Summary: This study examines teachers' usage intention and behavior towards the Game Learning Analytics (GLA) system in K-12 classrooms. The study found that personal, environmental, and technological factors influenced teachers' intention and behavior, and that technostress moderated the intention-behavior relationship. The study also identified the heterogeneity of GLA usage among teachers with different individual characteristics.
COMPUTERS & EDUCATION
(2024)
Article
Computer Science, Interdisciplinary Applications
Romina Cachia, Artur Pokropek, Nikoleta Giannoutsou
Summary: This article introduces a shortened version of the European Commission's SELFIE tool for measuring the digital capacity of schools. Two shorter measurement instruments, called midi-SELFIE and mini-SELFIE, are proposed based on the original tool. The validity and uses of these shortened versions are explored through various cases and compared to the complete instrument. The results suggest that the shortened versions of SELFIE are reliable alternatives for specific purposes.
COMPUTERS & EDUCATION
(2024)