Article
Robotics
Weiyuan Li, Ruoxin Hong, Jiwei Shen, Liang Yuan, Yue Lu
Summary: Substantial progress has been made in embodied visual navigation based on RL, but the presence of interactable objects in real cluttered scenes poses a challenge for the ego-centric visual agent. To address this, the authors propose a transformer-based memory to empower agents with historical interactive information and utilize a surrogate objective to predict the next waypoint, facilitating representation learning and bootstrapping RL.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
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, 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)
Article
Computer Science, Artificial Intelligence
Changyin Sun, Wenzhang Liu, Lu Dong
Summary: This article explores reinforcement learning algorithms for cooperative multiagent systems with multiple tasks, proposing a method to decompose reward signals for each agent to learn optimal policies. The simulation results demonstrate the effectiveness of the proposed algorithms in both discrete and continuous problems.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
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
Automation & Control Systems
Jia Guo, Dongyu Li, Bo He, Shuzhi Sam Ge
Summary: In this article, an intelligent collaborative system for robotic navigation and control (CNaC) governed by the Euler-Lagrange equation is proposed. A state reconstruction based on neural networks navigation (SR-NNN) law is designed to estimate the current position of the robot for intelligent CNaC. The system has been demonstrated by simulation tracking sample and real experiments, which verifies its effectiveness.
IEEE TRANSACTIONS ON CYBERNETICS
(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
Engineering, Electrical & Electronic
Yue Hu, Xu Li, Xuan Dong, Dong Kong, Qimin Xu, Yizhou Sun
Summary: In this article, a multisensor cooperative fusion positioning methodology is proposed to achieve reliable position in NLOS environments. The methodology includes NLOS identification, NLOS mitigation using multilayer perceptron (MLP), and adaptive fuzzy factor graph fusion. Real vehicle experiments demonstrate the effectiveness of the proposed methodology.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Computer Science, Information Systems
Yuehua Wang, Shulan Lu, Derek Harter
Summary: The current pandemic has significantly impacted educational practices, leading to the importance of remote learning and digital platforms. However, students are facing challenges in learning and performance due to the sudden shift to online teaching and e-learning.
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
Education & Educational Research
Yue Wang, Tessa H. S. Eysink, Zhili Qu, Zhijiao Yang, Huaming Shan, Nan Zhang, Hai Zhang, Yining Wang
Summary: This research investigated the impacts of using IRS in an ILE on students' academic performance, cognitive load, and satisfaction with the lesson. The findings showed that students in the experimental group had higher academic performance, lower cognitive load, and higher satisfaction with the lesson compared to the control group.
JOURNAL OF EDUCATIONAL COMPUTING RESEARCH
(2022)
Article
Automation & Control Systems
Jia Guo, Dongyu Li, Bo He
Summary: This article proposed intelligent collaborative navigation and control (CNaC) to improve tracking accuracy by using neural networks to reconstruct states and free control frequency from USBL limitations. Through simulation and real experiments, CNaC showed an improvement in tracking accuracy by 81.96% compared to mechanically combining traditional navigation and control algorithms.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Engineering, Civil
Zhihan Lv, Yuxi Li, Hailin Feng, Haibin Lv
Summary: The study aims to enhance the security performance of digital twins in the Cooperative Intelligent Transportation System in a deep learning environment. By combining Convolutional Neural Network with Support Vector Regression, a model is constructed and analyzed through simulation experiments. Results show that the proposed algorithm has significant advantages in security performance and data transmission speed.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
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
Monther M. Elaish, Liyana Shuib, Gwo-Jen Hwang, Norjihan Abdul Ghani, Elaheh Yadegaridehkordi, Siti Zaidah Zainuddin
Summary: Technology-mediated learning, especially mobile learning, has become an important tool for promoting education in the English language classroom. However, there has been limited attention given to key aspects such as experimental group size, duration of study, and suitability of assessment methods. This study analyzed 151 articles published between 2010 and 2017 and found that these aspects significantly varied based on language acquisition problems, types of participants, and targeted English skills. Questionnaires and tests were identified as the most commonly used assessment methods. The findings of this study can inform the design of experimental studies to enhance the effective use of mobile learning in English language learning.
COMPUTER ASSISTED LANGUAGE LEARNING
(2023)
Article
Psychology, Multidisciplinary
Vimala Balakrishnan, Kee Seong Ng, Wandeep Kaur, Zhen Lek Lee
Summary: This study aims to synthesize existing literature on the psychological outcomes of people in Southeast Asia during the COVID-19 pandemic and identify risk factors. The study found that there was an elevated prevalence of adverse mental effects, with Malaysia and Philippines reporting higher rates. Mental decline was more common among the general population compared to healthcare workers and students. The dominant risk factors identified were younger age, female sex, higher education, low coping skills and social/family support, and poor reliability of COVID-19 related information.
CURRENT PSYCHOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Wandeep Kaur, Vimala Balakrishnan, Kok-Seng Wong
Summary: This paper examines the weighted information gain method for improving text classification accuracy. The proposed algorithm is trained and tested using a corpus from Facebook pages, and incorporates the weighted information gain feature selection technique with a co-trained Naive Bayes classification algorithm. The results show an improvement in classification to 61%.
MALAYSIAN JOURNAL OF COMPUTER SCIENCE
(2022)
Article
Computer Science, Cybernetics
Vimala Balakrishnan, See Kiat Ng
Summary: This study investigates the impact of users' personality traits and emotions expressed through textual communications on YouTube to detect cyberbullying. The results show that both personality traits and emotions significantly improve the identification of cyberbullying presence, with accuracy and F-score values of more than 95%. Further analysis reveals that anger and openness have a more profound effect compared to other emotions and personalities, and neurotic individuals tend to engage in cyberbullying due to joy, disgust and fear.
BEHAVIOUR & INFORMATION TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Lokabhiram Dwarakanath, Amirrudin Kamsin, Liyana Shuib
Summary: The ability to post short text and media messages on social media platforms plays a huge role in the exchange of information following a mass emergency event. While social media can be helpful, posts related to the disaster often get lost in the overwhelming amount of data, hindering the emergency relief effort. Research in emergency coordination via social media has focused on machine learning-based models to separate disaster-related posts from non-disaster related ones.
INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY
(2023)
Review
Green & Sustainable Science & Technology
Fayez Nahedh Alsehani, Ainuddin Wahid Bin Abdul Wahab, Liyana Shuib
Summary: Enterprises are increasingly investing in sustainability due to social and ecological trends and rapidly changing environments. The impact of the environment on achieving sustainability is a major challenge for organizations. Social media has become a driving force in addressing environmental challenges, as it has a large number of users. Organizations use social media to achieve various goals such as information sharing, building connections, brand development, raising awareness, and gathering customer insights. This study explores the use of social media in organizational sustainability performance and found that there is limited research in this area.
Article
Computer Science, Artificial Intelligence
Vimala Balakrishnan, Vithyatheri Govindan, Kumanan N. Govaichelvan
Summary: This study uses a corpus of Tamil comments collected from YouTube to detect offensive language patterns. The research compares supervised and unsupervised machine learning approaches, and finds that unsupervised clustering is more effective in detecting offensive language in under-resourced languages.
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
(2023)
Review
Biochemistry & Molecular Biology
Vimala Balakrishnan, Yousra Kehrabi, Ghayathri Ramanathan, Scott Arjay Paul, Chiong Kian Tiong
Summary: Biomarker-based tests can improve tuberculosis diagnosis, treatment initiation, and outcomes. Machine learning approaches show promising results in detecting TB using biomarkers.
PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY
(2023)
Review
Health Care Sciences & Services
Vimala Balakrishnan, Kok Khuen Yong, Chiong Kian Tiong, Nicholas Jian Shen Ng, Zhao Ni
Summary: This scoping review examines the extent of research on knowledge, awareness, perceptions, attitudes, and risky behaviors related to sexually transmitted infections (STIs) in Southeast Asia (SEA), indicating low levels across various cohorts. The review highlights the impact of cultural, societal, economic, and gender inequality on people's behaviors. It calls for increased investment in educating vulnerable populations, especially in less-developed countries/regions of SEA, to prevent STIs.
Article
Education & Educational Research
Maria Ijaz Baig, Elaheh Yadegaridehkordi, Liyana Shuib, Hasimi Sallehuddin
Summary: This research aimed to identify the determinants of big data adoption (BDA) in the education sector. The findings highlighted compatibility, IT infrastructure, management support, financial resources, security and privacy, and government guidelines as important determinants of BDA. These results can assist higher education commissions, big data facilitators, and university managements in providing safe and successful BDA in university campuses.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Review
Computer Science, Artificial Intelligence
Vimala Balakrisnan, Mohammed Kaity
Summary: This paper conducts a systematic literature review on scholarly publications from 2011 to 2022 that focus on using machine learning to detect cyberbullying incidents. The findings highlight the dire consequences of cyberbullying across different demographics and provide insights on machine learning algorithms, features, and performance measures in cyberbullying detection. The paper also discusses research challenges and future directions for further exploration.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Information Systems
Vimala Balakrishnan, Ghayathri Ramanathan, Siyi Zhou, Chee Kuan Wong
Summary: This study developed and optimized a machine learning model to predict the treatment duration for Tuberculosis patients in Malaysia using a real-life patient dataset. The Support Vector Regression model performed the best in predicting treatment duration with the lowest error rates. Comparison with data from other countries confirmed the consistent performance of the optimized model.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Health Care Sciences & Services
Wandeep Kaur, Vimala Balakrishnan, Ian Ng Zhi Wei, Annabel Yeo Yung Chen, Zhao Ni
Summary: This scoping review collected current literature on the knowledge, awareness, and perception of STIs/STDs among women in Asia. The results showed consistently low levels of knowledge and awareness across Asia, particularly among vulnerable groups such as sex workers, transgender women, pregnant women, and rural housewives. The study emphasizes the need for educational initiatives to target these groups and prevent STIs/STDs.
Article
Education & Educational Research
Farhan Bashir Shaikh, Ramesh Kumar Ayyasamy, Vimala Balakrishnan, Mobashar Rehman, Shadab Kalhoro
Summary: This study examines the factors influencing cyberbullying behavior among Malaysian tertiary students. A model combining Social Cognitive Theory and the Theory of Planned Behavior is used, and the data from a survey of 428 students is analyzed using a two-step Structural Equation Modeling (SEM) -Artificial Neural Networks (ANN) approach. The results show that the intention to engage in cyberbullying is the most influential factor, influenced by variables such as image, moral disengagement, perceived behavioral control, university climate, subjective norms, peer relationships, and attitude towards cyberbullying. The ANN results further reveal that image is the strongest predictor of cyberbullying intention, followed by moral disengagement, cyberbullying attitude, perceived behavioral control, and university climate. These findings offer valuable insights into the underlying factors of cyberbullying among Malaysian tertiary students and provide guidance for addressing this issue in the country.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Computer Science, Artificial Intelligence
Vimala Balakrishnan, Hii Lee Zing, Eric Laporte
Summary: The use of content features, especially textual and linguistic, in detecting fake news has not been sufficiently studied, despite evidence suggesting their potential contribution. This study explores various content features, such as word bigrams and part of speech distribution, for improved fake news detection. The experiments conducted on a new dataset collected during the COVID-19 pandemic using different machine learning algorithms show that Random Forest performs the best, followed closely by Support Vector Machine. Overall, both textual and linguistic features enhance fake news detection when used separately, but combining them into a single model does not significantly improve the results. Differences in performance are also observed between word bigrams and part of speech tags. This study demonstrates the successful utilization of textual and linguistic features in detecting fake news with traditional machine learning approaches compared to deep learning.
MALAYSIAN JOURNAL OF COMPUTER SCIENCE
(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)