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)
Review
Construction & Building Technology
Min Hu, Bingjian Wu, Wenbo Zhou, Huiming Wu, Gang Li, Jing Lu, Gang Yu, Yuan Qin
Summary: This paper analyzes the control functions of shield machines and proposes the definition and grading of self-driving shields. Inspired by the theory of human performance models, a Shield Automatic Intelligent Control System (SHIELD_AICS) is designed, which combines a data-driven and a knowledge-driven approach. The system was successfully applied to a traditional shield, transforming it into an intelligent self-driving shield named Zhiyu shield. Field tests demonstrated that the self-driving shield can perform automatic continuous tunneling without manual intervention, meeting the engineering requirements.
AUTOMATION IN CONSTRUCTION
(2022)
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)
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.
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
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)
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
Engineering, Marine
Sulemana Nantogma, Keyu Pan, Weilong Song, Renwei Luo, Yang Xu
Summary: The research focuses on addressing the coordinated autonomous control and decision-making challenges of unmanned autonomous vehicles in complex environments. A modular framework is proposed to aid in realizing intelligent control systems, with a behavior-driven artificial immune-inspired fuzzy classifier system approach presented to optimize agents' behaviors and actions in a multi-agent environment.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
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
Jingting Zhang, Chengzhi Yuan, Cong Wang, Wei Zeng, Shi-Lu Dai
Summary: This paper introduces an intelligent adaptive learning control framework for discrete-time nonlinear uncertain systems operating under multiple environments, which combines offline and online learning methods to ensure system stability and adaptability. The framework consists of offline learning for locally-accurate identification and storage of system dynamics, as well as online adaptive learning control mechanisms and a learning-based recognition mechanism for real-time control and environment recognition.
Article
Education & Educational Research
Hoang Tieu Binh, Nguyen Quang Trung, Bui The Duy
Summary: This paper introduces a new student responsive model for supporting students using Intelligent Tutoring Systems, proposes a weighted-based model for estimating and suggesting learning materials, conducts empirical research, and demonstrates the effectiveness of the proposed model in ITS.
EDUCATION AND INFORMATION TECHNOLOGIES
(2021)
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)
Article
Computer Science, Information Systems
Dong Li, Zai Luo, Bo Cao
Summary: Blockchain technology is an indisputable ledger technology storing transactions securely in chains of blocks; Federated learning is a new paradigm to enhance accuracy in data mining while ensuring privacy and security; Utilizing blockchain technology in intelligent learning can significantly impact information security and privacy, leading to advancements in data science and AI.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Engineering, Civil
Fuli Qiao, Jun Wu, Jianhua Li, Ali Kashif Bashir, Shahid Mumtaz, Usman Tariq
Summary: This paper proposes a distributed trustworthy storage architecture with reinforcement learning in ITS, which dynamically stores data and improves resource scheduling and storage space allocation. In addition, a trapdoor hashing based identity authentication protocol is introduced to secure transportation network access. Simulation results demonstrate that the proposed architecture outperforms compared ones in terms of trustworthiness and efficiency.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Marine
Dean Sumic, Lada Males, Marko Rosic
Summary: This paper presents a proof of principal for on-board fire monitoring and extinguishing software agents that may be used to upgrade present systems and contribute to an autonomous ship design, reducing the risks of human error and increasing maritime safety.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Ani Grubisic, Branko Zitko, Angelina Gaspar, Daniel Vasic, Arta Dodaj
Summary: Various approaches to text simplification have been proposed to increase readability, but balancing linguistic simplicity, naturalness, and informativeness is crucial. Simplified texts may improve reading comprehension with shorter sentences and limited vocabulary, but often lack coherence and style. Future research should focus on addressing these trade-offs.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Lada Males, Dean Sumic, Marko Rosic
Summary: This paper presents a review of the current state of implementation of multi-agent systems for performing the functions of unmanned surface vessels, based on the analysis of 24 relevant papers.
Article
Computer Science, Software Engineering
Ani Grubisic, Slavomir Stankov, Branko Zitko, Ines Saric-Grgic, Angelina Gaspar, Emil Brajkovic, Daniel Vasic
Summary: This paper describes and evaluates the performance of a semi-automatic authoring tool (SAAT) for knowledge extraction in the AC & NL Tutor. The study compares automatic annotation tasks to a gold standard and includes human-error analysis for improving error identification and correction. The main contributions of this research are an integrated approach to text preprocessing, knowledge extraction, and visualization, as well as a comprehensive evaluation of natural language processing tasks and knowledge extraction output.
JOURNAL OF UNIVERSAL COMPUTER SCIENCE
(2023)
Article
Education & Educational Research
Nikola Balic, Ani Grubisic, Andrina Granic
Summary: This research analyzes the self-perception of teachers and students regarding their digital readiness and attitudes towards digital and distance learning, as well as the potential influence of other factors. The findings indicate significant digital readiness gaps, considering gender and the field of study. The study emphasizes the disconnect between expectations and reality in terms of the digital transformation of the learning environment, highlighting the need to reduce existing gaps and improve the digital teaching and learning environment.
TECHNOLOGY KNOWLEDGE AND LEARNING
(2023)
Article
Education, Scientific Disciplines
Ivan Peraic, Ani Grubisic
Summary: The purpose of this study is to predict the academic performance of students in a Programming class course by analyzing data from the Moodle learning platform. Six machine learning classification techniques were used on two datasets, and multiple similar prediction models were found to perform best in binary and three-level grade categorization. The study highlights the impact of feature selection on prediction results.
INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Ivan Peraic, Ani Grubisic
Summary: This paper presents the development and evaluation of the learning analytics dashboard for students (LAD-S), which provides feedback to students and teachers. The survey results show a high level of student satisfaction with various aspects of the LAD-S, as well as willingness to use and perceive its usefulness.
HCI INTERNATIONAL 2022 - LATE BREAKING PAPERS: INTERACTION IN NEW MEDIA, LEARNING AND GAMES
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Lada Males, Dean Sumic, Marko Rosic
Summary: This paper presents a simulation model for testing agent based on board firefighting system, aiming to address ship fire accidents. By developing appropriate simulation environments, we can conduct tests for automated firefighting systems and evaluate the results.
2022 8TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT'22)
(2022)
Article
Computer Science, Theory & Methods
Ines Saric-Grgic, Ani Grubisic, Branko Zitko
Summary: This research investigates the impact of note-taking practice on the learning process in Tutomat, an intelligent tutoring system. The analysis reveals that student interaction with Tutomat varies based on their note-taking practice, which can be detected using learning analytics variables and predicted with an accuracy of 85% through clustering.
APPLIED COMPUTER SYSTEMS
(2021)
Article
Engineering, Marine
Dean Sumic, Lada Males, Marko Rosic
Summary: This paper presents a model of agent-based architecture for fighting fires on ships, aiming to achieve safe autonomous vessels. The introduction of agent technology can exclude the human factor, reducing injuries and losses. Additionally, agent-based technology offers easy interoperability with other automated systems.
TRANSACTIONS ON MARITIME SCIENCE-TOMS
(2021)
Article
Engineering, Multidisciplinary
Daniel Vasic, Branko Zitko, Hrvoje Ljubic
Summary: This paper presents a novel approach to automatic question generation using semantic role labeling for morphologically rich languages, focusing on Croatian. It can be divided into two stages: the development of a new SRL model for Croatian and the implementation of this model in an AQG system. The results show high accuracy in argument classification and positive expert evaluation for educational purposes.
TEHNICKI VJESNIK-TECHNICAL GAZETTE
(2021)
Article
Education, Scientific Disciplines
Tonci Dadic, Vlado Glavinic, Marko Rosic
INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION
(2020)
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)
