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8th International Visual Informatics Conference, IVIC 2023

作者： Khoirunnisa, Azizah Nurul Munir Dewi, Laksmi Rasim Azizah, Nissa Nur Alivia, Zsalzsa Puspa Curriculum Development Study Program Indonesia University of Education Bandung Indonesia Computer Science Education Study Program Indonesia University of Education Bandung Indonesia

ISBN: (纸本)9789819973385

Autism spectrum disorder (ASD) is a neurobiological developmental disorder that affects communication and social interaction. Autistic children often have difficulty communicating effectively, both verbally and nonverbally. Good verbal and nonverbal communication skills help children with autism participate in social interactions. In this paper, we present a systematic literature review focused on analyzing AR/VR/Mixed reality technologies used to improve communication skills in children with ASD based on research published over the last ten years and available in relevant scientific databases. We reviewed 22 studies showing target area communication, how AR/VR/Mixed reality is used in the context of communication skills in ASD children, user experience and accessibility, technology limitations, and findings. This systematic review of the literature shows that the majority of the communication areas targeted are verbal and nonverbal simultaneously. Overall, the use of AR/VR/Mixed reality can be an alternative to improve children’s communication. Technologies that can facilitate the different abilities and emotions of children with ASD are considered in developing AR/VR/Mixed reality in the future. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Augmented reality

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Deep learning and genomic strategies for ocean literacy development

AIMS Environmental Science

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AIMS Environmental science 2025年第3期12卷 461-477页

作者： Munandar, Rifki Risma Hidayat, Topik Sanjaya, Yayan Riza, Lala Septem Program of Science Education Faculty of Mathematics and Science Education Indonesia University of Education Bandung City Indonesia Program of Biology Education Faculty of Mathematics and Science Education Indonesia University of Education Bandung City Indonesia Program of Computer Science Education Faculty of Mathematics and Science Education Indonesia University of Education Bandung City Indonesia

Indonesia, as a nation with rich marine biodiversity, faces significant challenges in fostering ocean literacy due to the limited integration of ecological and technological content in formal education. In this study, we aimed to evaluate ocean literacy among university students through a project-based learning program incorporating deep learning and genomic data for fish species identification. The initiative responded to the urgent need for educational reform that supports sustainable ocean conservation practices. Using a quantitative approach, the program engaged 36 undergraduate biology students in various activities, including marine problem analysis, field-based fish species identification via the Fishiden platform, phylogenetic tree construction using genomic data, and public outreach through social media advocacy. Pretest and post-test evaluations measured changes in ocean literacy, while Likert-scale questionnaires assessed student engagement and perception. The results showed a significant increase in post-test scores, with a mean improvement from 58.11 to 71.88, and a moderate N-Gain of 0.30. Students who demonstrated positive responses to the program also achieved higher gains in ocean literacy, indicating a strong correlation between engagement and learning outcomes. The highest evaluation scores reflected students’ enhanced awareness, inquiry skills, and attitudes toward biodiversity conservation. Technological tools such as deep learning and genomic databases effectively support interactive and data-driven learning. These findings highlight the transformative potential of integrating technology into ocean literacy education. This research bridges technology, pedagogy, and marine conservation, emphasizing the integration of innovative educational strategies for sustainability. In the future, researchers should address study limitations and improve the accuracy of deep learning models. © 2025 the Author(s), licensee AIMS Press.

关键词： Students

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Exploring the Potential of Artificial Intelligence in Special education: A Bibliometric Analysis to Support Educators and Students with Autism Spectrum Disorder (ASD) 54

Exploring the Potential of Artificial Intelligence in Specia...

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54th IEEE Frontiers in education Conference, FIE 2024

作者： Silveira, Lisiane Corrêa Gomes De Alvarenga, Patricia Warnke Ribeiro, Luis Otoni Meireles Gonçalves, Eder Mateus Vicari, Rosa Barwaldt, Regina Federal Institute Sul-rio-grandense Postgraduate Program in Education Pelotas Brazil Federal University of Rio Grande Postgraduate Program in Science Education Rio Grande Brazil Federal University of Rio Grande Computer Science Center of Furg Rio Grande Brazil Federal University of Rio Grande Rio Grande Brazil Federal University of Rio Grande do Sul Computer Science Center Porto Alegre Brazil Federal University of Rio Grande Computer Science Center Rio Grande Brazil

ISBN: (纸本)9798350351507

This full paper describes a complete article in the research category. This work presents a Bibliometric Review that aims to characterize the current scenario of academic research in Artificial Intelligence in education to support educators in the teaching and learning processes in Special education in different contexts, becoming a tool with potential use in cases of students with Autism Spectrum Disorder (ASD). In this sense, this work aims to contribute to a better understanding of research associated with the area of Artificial Intelligence aimed at educational processes involving students with autism. To do this, we used the EndNote reference manager, an online tool designed to support researchers in conducting Literature Reviews, following the bibliometric protocol proposed by Guedes and Borschiver (2005). From the definition of search strings, ('artificial intelligence') AND ('autism' OR 'ASD' OR 'autism spectrum disorder') AND ('education' OR 'teaching'), scientific databases were explored like Web of science (WoS), Scopus, ERIC, Emerald, Scielo, Portal CAPES, and IEEE, to locate existing studies on the topic, between 2019 and 2024. As a result, 298 articles were mapped and 20 scientific works were selected that address the aforementioned specific theme, written by 89 authors belonging to 50 institutions in 19 countries on four continents, enabling the creation of a significant theoretical basis. By analyzing the information contained in scientific publications in this specific field, it was possible to infer that research is divided into distinct areas of concentration: 1) the exploration of algorithms and data analysis based on Artificial Intelligence for analytical-predictive issues in the field of special education;2) the use of robots in the teaching and learning processes of students with autism;3) the development of personalized educational intervention models for learning pedagogical, social and communication skills. The data show that research on th

关键词： Students

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Physics-informed neural networks for modeling water flows in a river channel

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第3期5卷 1001-1015页

作者： Nazari, Luis Fernando Camponogara, Eduardo Seman, Laio Oriel Department of Mathematics Federal Institute of Education Science and Technology Catarinense Rio do Sul89160-202 Brazil Department of Automation and Systems Engineering Federal University of Santa Catarina Florianopolis88040-900 Brazil Program in Applied Computer Science Universidade Do Vale Do Itajai Itajai88302-901 Brazil

The impacts incurred by floods regularly affect the planets population, inflicting social and economic problems. Optimal control strategies based on reservoir management may aid in controlling floods and mitigating the resulting damage. To this end, an accurate dynamic representation of water systems is needed. In practice, flood control strategies rely on hydrological forecasting models obtained fromconceptual or data-drivenmethods. Encouraged by recent works, this research proposes a novel surrogate model for water flow in a river channel based on physics-informed neural networks (PINNs). This approach achieved promising results regarding the assimilation of real-data measurements and the parameter identification of differential equations that govern the underlying dynamics. This article investigates PINN performance in a simulated environment built directly from a configuration of the Saint-Venant equations. The objective is to create a suitable model with high prediction accuracy and scientifically consistent behavior for use in real-Time applications. The experiments revealed promising results for hydrological modeling and presented alternatives to solve the main challenges found in conventional methods while assisting in synthesizing real-world representations. Impact Statement-The research seeks to contribute to the hydrological modeling area with a surrogate model based on physicsinformed neural networks (PINNs) to water flow in a watershed. In practice, thesemodels use conceptual or *** models to reach the precision provided by themethodology use large numbers of physical parameters. These parameters can demand deep knowledge about the environment and are possibly hard to identify in a complex basin. On the other hand, while data-driven methods do not require such knowledge about the dynamic system, they depend on a reliable and useful database to guarantee the accuracy of system *** introduce PINNs as a viable solution for

关键词： Floods

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Enhancing Computational Thinking Based on Virtual Robot of Artificial Intelligence Modeling in the English Language Classroom 1

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International Conference on Data Analytics and Management, ICDAM 2023

作者： Muthmainnah Obaid, Ahmad J. Al Yakin, Ahmad Brayyich, Mohammed Teacher Training and Education Faculty Civic Education Study Program Universitas Al Asyariah Mandar Polewali Mandar Indonesia Faculty of Computer Science and Mathematics University of Kufa Najaf Iraq National University of Science and Technology Thi-Qar Iraq

ISBN: (数字)9789819965502

ISBN: (纸本)9789819965496

There has been a lack of both educational focus on computational thinking (CT) and research into effective methods of assessing CT competence. This research takes a comprehensive look at the methods used to grade CT in higher education. This study examines the use of educational robotics (ER) as a teaching strategy in higher education, with particular attention to how undergraduate students might respond differently to this kind of learning. Students collaborate using artificial intelligence to find out how to program robots (start installing, interact, sharing information, feedback, and evaluate). Of 181 undergraduates’ students from Indonesia, Saudi Arabia, Riyadh, Pakistan, the Philippines, Egypt, Algeria, Lesoto, Cameron, Bangladesh, Sudan, Uganda, Portugal, Ukraine, Pakistan, and England make up the study groups. These students are enrolled in the first semester of the 2022 academic year. In this work, researchers employed a quantitative method technique. During the exercise, the participants were closely monitored to assess their performance in relation to the core CT constructs in the robotics class. These constructs include confidence in dealing with complexity, persistence in problem-solving, tolerance for ambiguity, ability to handle open-ended problems, effective communication skills, and teamwork abilities. In order to enhance the implementation of strategic initiatives. To facilitate more strategic learning, this study found that the use of visual robotics of artificial intelligence helped to developing CT and the respondents strong believe it to increase students’ confidence in dealing with complexity, persistence in working through difficult questions, tolerance for ambiguity, ability to handle open problems, communication skills, and teamwork. It is thought that this study would be valuable to academics, curriculum designers, and teachers because students who play artificial intelligence games exhibit considerably greater cognitive flexibility than b

关键词： Students

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Development of Web-Based Learning Environment to Promote Problem Solving on Problem Solving in Computational science for Secondary School 5th

Development of Web-Based Learning Environment to Promote Pro...

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5th International Conference on Innovative Technologies and Learning, ICITL 2022

作者： Phoosamrong, Anutra Samat, Charuni Vongtathum, Pornsawan Master of Education Program in Science and Technology Education Faculty of Education Khon Kaen University Khon Kaen Thailand Division of Computer Education Faculty of Education Khon Kaen University Khon Kaen Thailand

ISBN: (纸本)9783031152726

The objectives of this research were to develop a networked learning environment that promoted solving problem and to study solving problem of learners who learned this research in Computational science for secondary school, grade 7. The target group of this research was 34 students of grade 7 in semester 2, academic year 2021. This research used the Development Research by using basic statistical in analysis mean (x¯ ) and standard deviation (S.D.). The research showed that 1. There are 6 components of the result of design and develop a networked learning environment in Computational science for secondary school, grade 7 namely 1) problem situation, 2) resource, 3) collaboration, 4) analytical solving problem room, 5) scaffolding and 6) coaching. 2. The result of student who learned about this research showed that 34 students who had solving problem passing the criteria 60%, representing 100% in total number of students. The average mean (x¯ ) was 28.27 and standard deviation (S.D.) was 1.08 which was higher than specified criteria at 60%. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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Enhanced Keypoint-Based Approach for Identifying Copy-Move Forgery in Digital Images 7

Enhanced Keypoint-Based Approach for Identifying Copy-Move F...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Bisht, Girish Singh Jain, Arpit Bansla, Vandna Sharma, Khemraj Bhutia, Rudramani Kumar, Vikas Tula's Institute Department of Computer Science & Engineering Dehradun248001 India Koneru Lakshamaiah Education Foundation Department of Computer Science & Engineering A.P. Vadessahwaram India Shivalik Engineering College Dehradun248001 India Nanhua University Doctoral Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering A.P. India Dev Bhoomi Uttrakhand University School Engineering and Computing Uttrakhand Dehradun India

ISBN: (纸本)9798350350067

Copy-move forgeries often exploit homogeneous regions in images with large-scale attacks to either highlight or conceal target objects. These manipulations are simple to execute but challenging to notice. Forgery detection techniques like Copy-Move Forgery Detection (CMFD) cannot detect these forged documents because they are unable to identify a sufficient number of effective keypoints in homogeneous areas, leading to inaccurate and inefficient results. SURF stands for Speeded-Up Robust Features and is used in this paper along with A-KAZE and Scale-Invariant Feature Transforms. According to our experiment, A-KAZE offers superior detection performance under diverse attacks, especially when it comes to large-scale attacks targeting homogeneous regions. A-KAZE is found to be more accurate than SIFT, SURF, and A-KAZE when applied to the NB-CASIA dataset, achieving detection accuracies of 89.2%, 93.9% and 98.98%.) © 2024 IEEE.

关键词： Image analysis

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Interactive Multimedia Kolb Experiential Learning Model Using Logistic Regression Algorithm to Improve Student Cognitive

Interactive Multimedia Kolb Experiential Learning Model Usin...

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7th International Conference on Advances in Visual Informatics, IVIC 2021

作者： Khoirunnisa, Azizah Nurul Munir Rasim Rahman, Eka Fitrajaya Dewi, Laksmi Curriculum Development Study Program School of Postgraduate Studies Indonesia University of Education Bandung Indonesia Computer Science Education Study Program Department of Computer Science Education Indonesia University of Education Bandung Indonesia

ISBN: (纸本)9783030902346

The differences of each student become a challenge for educators in delivering learning materials. More often than not, students often find it difficult to process study materials. Conventional study-based learning may not always have a profound impact on students. Consideration of interactive multimedia as a tool for student-centered learning has not been widely discussed in scientific research. In this paper, the authors investigate interactive multimedia using Kolb’s experiential learning model in improving students’ cognitive abilities. This study uses a pre-experimental method and one-group pre-and post-test design type with the research population in class XI RPL and a sample of SMK students in Bandung. The results show that the application of interactive multimedia using Kolb’s experiential learning model is effective in improving students’ cognitive abilities. On the other hand, it is found that combining abstract learning materials with interactive visuals and activities that involve students’ participation could create exceptionally positive feedback from students. © 2021, Springer Nature Switzerland AG.

关键词： Students

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The Second Workshop on Child-Centered AI Design (CCAI)

The Second Workshop on Child-Centered AI Design (CCAI)

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2024 CHI Conference on Human Factors in Computing Sytems, CHI EA 2024

作者： Atabey, Ayça Wang, Ge Johnston, Samantha-Kaye Lin, Grace C. Wilson, Cara Urquhart, Lachlan D Zhao, Jun School of Law Centre for Data Culture & Society University of Edinburgh United Kingdom Department of Computer Science University of Oxford United Kingdom Scheller Teacher Education Program - the Education Arcade The Massachusetts Institute of Technology United States Centre for Research in Digital Education University of Edinburgh United Kingdom Edinburgh Law School University of Edinburgh United Kingdom

ISBN: (纸本)9798400703317

AI-powered solutions are increasingly woven into the fabric of children's digital worlds. They're found in interactive toys, home automation systems, everyday apps, and various online services that young users engage with. As we look ahead, it's almost certain that the prevalence of AI in tools and platforms designed for kids will grow, given AI's ability to offer rich, tailored, and dynamic experiences. However, the nuances of how these AI-centric platforms cater to children and how they can be optimized to meet the unique needs of younger users remain largely underexplored. Building on the momentum from our inaugural CCAI workshop at CHI 2023, our aspirations for this year's workshop include: (1) deepening the discourse on the essence of AI that prioritizes children, (2) focusing on actionable ethical strategies to operationalise child-centered AI design principles into practice, and (3) cultivating an ever-growing collective of professionals passionate about the future of child-focused AI innovations. © 2024 Owner/Author.

关键词： Automation

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An Improved Particle Swarm Approach for Energy-Aware Location-Aided Routing in Mobile Ad-Hoc Network 7

An Improved Particle Swarm Approach for Energy-Aware Locatio...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Kumar, Sandeep Sharma, Khemraj Ashok Kumar, P.M. Jain, Arpit Bhagat, Sukesh Kumar Singh, Pranita Tula's institute U.K Dehradun India Nanhua University Doctoral Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Koneru Lakshmaiah Education Foundation Department of Computer Science Engineering AP Vaddeswaram522502 India Uttaranchal University Department of Computer Science & Engineering Uttarakhand Dehradun India Roorkee Institute of Technology Department of Computer Science and Engineering Uttarakhand Roorkee India

ISBN: (纸本)9798350350067

A network with no infrastructure, multiple hops, and dispersed nodes called a MANET. Nodes can communicate directly or through intermediaries without the need for permanent infrastructure. In dynamic networks like MANETs, routing procedures enhance the overall appearance of the network by ensuring Quality of Service (QoS). A routing protocol may use a composite routing measure to determine the best path for transferring data. Optimal location-based routing for MANETs based on energy-awareness is presented in this paper. Optimal routes are selected using this fast algorithm. Particle swarm optimization (PSO) is used instead of location-aided routing to select the normal data transmission route. Last but not least, the network is tested by simulating its packet delivery ratio, its energy level, its delay, and its overhead. © 2024 IEEE.

关键词： Adversarial machine learning

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