Article
Computer Science, Artificial Intelligence
Doaa Mohamed Elbourhamy, Ali Hassan Najmi, Abdellah Ibrahim Mohammed Elfeky
Summary: Modern approaches in education technology, such as electronic books, infographics, and mobile applications, are being used to improve education quality and learning levels. Educational data mining is a popular method for predicting student performance and monitoring progress. A model was developed to inform students about their performance in a computer networks course, and the effectiveness of infographics for teaching was proven.
PEERJ COMPUTER SCIENCE
(2023)
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, 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.
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
Computer Science, Information Systems
Albert Rego, Pedro Luis Gonzalez Ramirez, Jose M. Jimenez, Jaime Lloret
Summary: The study introduces an intelligent system based on reinforcement learning and deep learning for smart home environments to improve user experience. Experimental results show that this system outperforms traditional algorithms and can increase user QoE.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
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, 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)
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
Yanqing Wang, Shaoying Gong, Yang Cao, Yueru Lang, Xizheng Xu
Summary: Affective pedagogical agent (PA) is a character embedded in multimedia lessons that can influence learners' emotions and learning performance. Previous studies on affective PA have yielded inconsistent findings. This study conducted four meta-analyses and found that affective PA can increase positive emotions, intrinsic motivation, and learning performance. Additionally, moderator analysis revealed that characteristics of affective PA and learning materials can influence its effects. Overall, affective PA can enhance students' happiness and motivation in multimedia learning environments.
EDUCATIONAL RESEARCH REVIEW
(2023)
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
Computer Science, Artificial Intelligence
Zhaoxing Li, Lei Shi, Jindi Wang, Alexandra I. Cristea, Yunzhan Zhou
Summary: The continuous application of artificial intelligence technologies in online education, particularly in Intelligent Tutoring Systems and learning management systems, has shown significant progress. Customisation of learning trajectories through student modelling has been proven to enhance students' learning experiences and outcomes. However, training intelligent tutoring systems that can customise learning trajectories is still challenging due to various issues.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Education & Educational Research
Chunsheng Yang, Feng-Kuang Chiang, Qiangqiang Cheng, Jun Ji
Summary: Machine learning-based modeling technology has shown effectiveness in developing models for intelligent education systems, but there are challenges in creating high-performance student models from educational data. Our proposed systematic and comprehensive methodology addresses fundamental modeling issues and has proven useful and feasible in developing models for various intelligent education systems.
JOURNAL OF EDUCATIONAL COMPUTING RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Taewoong Ryu, Unil Yun, Chanhee Lee, Jerry Chun-Wei Lin, Witold Pedrycz
Summary: Utility pattern mining is a branch of data mining that extracts valid patterns by considering the quantity and weight of the items. This article proposes a novel mining approach, HUOMI, which performs quickly on an increasing database and demonstrates better performance compared to other state-of-the-art algorithms.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Engineering, Manufacturing
Martin Dahl, Christian Larsen, Endre Eros, Kristofer Bengtsson, Martin Fabian, Petter Falkman
Summary: This paper presents an interactive and iterative framework to address new challenges in future intelligent automation systems. The framework supports simultaneous preparation of model-based control systems, 3D geometries, robot positioning, and tool design. The workflow allows for real-time addition of resources and constraints and analysis of control system failures.
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY
(2022)
Article
Education & Educational Research
Daryn A. Dever, Nathan A. Sonnenfeld, Megan D. Wiedbusch, S. Grace Schmorrow, Mary Jean Amon, Roger Azevedo
Summary: Self-regulated learning is essential for learning, but learners often struggle with accurately using cognitive and metacognitive self-regulated learning strategies, leading to poor learning outcomes. Intelligent tutoring systems aim to address this issue by prompting and scaffolding learners to engage in self-regulated learning. This study collected data from 117 undergraduate students using MetaTutor, an intelligent tutoring system, and found that learners who received prompts from pedagogical agents had better learning outcomes and higher frequencies of strategy use.
METACOGNITION AND LEARNING
(2023)
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)