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1	AI for Learning	ABS-3
Exploring Tourism Students^ Perceptions of ChatGPT in English Language Learning Novasa Adiyani, Fanissa Narita, Febryawan Yuda Pratama Politeknik Jatiluhur Abstract The rapid development of artificial intelligence has introduced new opportunities in language learning, including the use of ChatGPT as an interactive learning assistant. In tourism education, English proficiency is important for communication with international visitors. This study aims to investigate tourism students^ perspectives of utilizing ChatGPT in learning English for tourism fields. The study used a descriptive qualitative approach involving tourism students enrolled in an English for Tourism course. Data were collected through semi-structured interviews to examine students^ experiences in using ChatGPT to support tourism-related language learning activities, such as making tour guiding scripts, practicing dialogues with tourists, and generating tourism-related vocabulary. The findings show that most students perceive ChatGPT as a useful tool that helps them generate ideas, increase vocabulary related to tourism, and practice English communication more confidently. Students also reported that ChatGPT gives quick explanations and practical examples that support independent learning, additionally some students noted limitations based on the need to verify the accuracy of the information and avoid overreliance on AI tools. Overall, the findings suggest that ChatGPT can serve as a supportive learning tool in English for Tourism when used critically and under teacher guidance. The study provides insights into the potential integration of AI tools in tourism-related English language learning. Keywords: Artificial intelligence, ChatGPT, English for tourism, language learning, students^ perceptions. Share Link | Plain Format | Corresponding Author (Novasa Adiyani)

2	AI for Learning	ABS-4
Exploring the Use of Artificial Intelligence in Learning: A Phenomenological Study of Students^ Critical Thinking Experiences Sopa Siti Marwah, Ani Siti Anisah, Nenden Munawaroh, Ade Holis Universitas Garut Abstract The development of Artificial Intelligence (AI) in the field of education has transformed the way students access information, understand learning materials, and complete academic tasks. The use of AI in learning not only functions as a source of information but also has the potential to influence students^ critical thinking processes. This study aims to explore students^ experiences in using Artificial Intelligence in learning and to understand the meaning of its use in relation to their critical thinking processes. The study employs a qualitative approach with a phenomenological method to investigate students^ lived experiences in utilizing AI during the learning process. Research informants were selected through purposive sampling, namely students who actively use Artificial Intelligence in their academic activities. Data were collected through in-depth interviews, observations, and documentation. Data analysis was conducted through the processes of data reduction, coding, theme categorization, and interpretation of experiential meanings to identify the essence of the phenomenon under study. The findings of this study are expected to provide a deeper understanding of how the use of Artificial Intelligence in learning influences students^ ways of analyzing information, evaluating arguments, and constructing critical understanding of learning materials. Furthermore, the results are expected to serve as a basis for developing learning strategies that utilize Artificial Intelligence more wisely and reflectively to support the development of students^ critical thinking skills in the digital era. Keywords: Artificial Intelligence, learning, critical thinking, students, phenomenology. Share Link | Plain Format | Corresponding Author (Sopa Marwah)

3	AI for Learning	ABS-7
Artificial Intelligence in Science Education for Sustainability: A Systematic Review of AI Interventions and SDG-Aligned Learning Outcomes Rizky Agassy Sihombing, Noviansyah Kusmahardhika, Shiang-Yao Liu, Chun-Yen Chang Graduate Institute of Science Education, National Taiwan Normal University Abstract The rapid advancement of artificial intelligence (AI) presents new opportunities and challenges in science education, particularly in supporting sustainability-oriented learning. This study employs a systematic literature review to examine the implementation of AI interventions in science education and their contribution to Sustainable Development Goals (SDG)-aligned learning outcomes. Thirty peer-reviewed studies published between 2020 and 2025 were analyzed across various educational levels and learning contexts. The findings reveal diverse AI-based interventions, including adaptive learning systems, generative AI tools, AI-supported instruction, immersive technologies such as AI combined with VR/AR/XR, and AI-driven assessment systems. These interventions contribute to the development of 21st-century competencies, including critical thinking, systems thinking, digital literacy, collaboration, and sustainability awareness. Quantitative approaches, particularly experimental and quasi-experimental designs, dominate the research methods, followed by mixed-methods and qualitative studies. Higher education and secondary school students represent the most frequently examined participants, while primary education and teacher training contexts remain less explored. Geographically, research contributions are widely distributed, with notable activity in China, Turkey, Taiwan, Indonesia, and several European countries. Science content is predominantly focused on environmental and interdisciplinary sustainability issues, although fewer studies address specific disciplinary science domains such as physics, biology, and chemistry. Despite challenges such as uneven technological access and limited pedagogical readiness, AI-supported science education demonstrates strong potential to enhance sustainability competencies. Overall, AI integration serves as a bridge between technological innovation and sustainability education, supporting the development of future learners who are environmentally responsible, digitally competent, and capable of addressing global sustainability challenges. Keywords: Artificial Intelligence- Science Education- Sustainability Education- SDGs- AI Intervention- Systematic Literature Review Share Link | Plain Format | Corresponding Author (Rizky Agassy Sihombing)

4	AI for Learning	ABS-18
Artificial Intelligence Adoption in Higher Education: A Mediation-Based Conceptual Framework for Teaching Innovation and Learning Effectiveness Yousef Mohammad Iriqat Al-Quds Open University Technology and Applied Science Department Jericho Branch, Jericho, Palestine Abstract Artificial Intelligence (AI) is rapidly transforming higher education by enabling innovative teaching practices and enhancing student learning outcomes. Despite the growing adoption of AI technologies in educational institutions, limited research has examined the mechanisms through which AI adoption contributes to improved learning effectiveness. This study addresses this gap by proposing an integrated conceptual framework that explains how technological and institutional factors influence AI adoption and how AI adoption subsequently enhances teaching innovation and learning outcomes. Exploring established theoretical perspectives, including the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study develops a mediation-based model in which AI infrastructure and institutional support drive AI adoption, while teaching innovation mediates the relationship between AI adoption and learning effectiveness. Methodologically, the study proposes the use of Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the direct and mediating relationships among the constructs. The proposed framework suggests that AI infrastructure and institutional support facilitate AI adoption in higher education institutions. AI adoption, in turn, enables innovative teaching practices that enhance learning effectiveness. By integrating technological, organizational, and pedagogical perspectives, this study contributes to the literature by extending technology adoption models and providing a comprehensive framework for understanding the educational value of AI in higher education. Keywords: Artificial Intelligence, Higher Education, AI Adoption, Teaching Innovation, Learning Effectiveness Share Link | Plain Format | Corresponding Author (Yousef Mohammad Iriqat)

5	AI for Learning	ABS-19
CHATGPT VS ACADEMIC SOURCES IN INDONESIAN CHURCH HISTORY LEARNING FOR CRITICAL THINKING Della Gita Van Gobel IAKN Palangka Raya Abstract This study explores the use of ChatGPT as part of AI-based learning to enhance students critical thinking skills in Indonesian Church History Learning. It employs an exploratory qualitative approach combined with a literature review to provide a comprehensive understanding of AI use in learning contexts. Empirical data were derived from classroom observations conducted in 2024, where students used ChatGPT and compared its outputs with academic sources such as scholarly articles and journals. The findings reveal that while ChatGPT offers quick access to information, it often produces inaccuracies, oversimplifications, and unverified historical claims. In contrast, academic sources lead to deeper and more accurate understanding. The comparison activity encourages students to critically evaluate information sources. This study proposes the AI-Manual Comparison Strategy as a pedagogical approach to integrating AI reflectively in learning. Although based on early observations from 2024, the findings remain relevant amid the rapid expansion of AI in education, particularly in history learning that requires accuracy and critical interpretation. Keywords: Academic Sources- AI-Based Learning- ChatGPT- Critical Thinking- Indonesian Church History Share Link | Plain Format | Corresponding Author (Della Gita Van Gobel)

6	AI for Learning	ABS-21
TRANSFORMING INDONESIAN LANGUAGE LEARNING IN HIGHER EDUCATION THROUGH AI ASSISTED PEDAGOGY FOR SUSTAINABLE LITERACY DEVELOPMENT Suryanti1*, Agusalim2, Marwah 3 Universitas Muhammadiyah Buton Abstract The integration of artificial intelligence (AI) in higher education offers new opportunities to transform Indonesian language learning and promote sustainable literacy. This study aims to examine the implementation of AI-based pedagogy in enhancing students^ literacy skills at the university level. A qualitative case study design was employed in an Indonesian language course. Data were collected through classroom observations, semi-structured interviews with lecturers and students, and analysis of AI-supported learning materials. The data were analyzed thematically to identify patterns in teaching practices and student learning experiences. The results show that AI-based pedagogy increases student engagement, supports personalized learning, and improves critical and creative writing skills. The use of AI tools provides immediate feedback, enabling students to refine their language use more effectively. In addition, students demonstrate better ability to relate language learning to social and sustainability contexts. However, challenges such as limited digital competence among lecturers and ethical concerns in AI usage were also identified. In conclusion, AI-based pedagogy has strong potential to transform Indonesian language learning in higher education and to foster sustainable literacy in line with global educational goals. Keywords: Artificial Intelligence- Indonesian language learning- higher education- sustainable literacy- pedagogy Share Link | Plain Format | Corresponding Author (Suryanti suryanti)

7	AI for Learning	ABS-22
Islamic Religious Education as a Foundation for Ethical AI Use Among Indonesian Youth: A Multi-Site Qualitative Study Tyas Prayesti (a*) Widiani Hidayati (b) Anindita Yumnaa Oktaviani (c) a) STIKes Bina Putera Banjar (prayesti.tyas[at]gmail.com) b) Afsheen Learning Center c) SMP Muhammadiyah 3 Wonosobo Abstract The rapid advancement of Artificial Intelligence (AI) has introduced ethical challenges for Indonesian youth in educational settings, including academic dishonesty, misinformation, and privacy violations. Islamic Religious Education (PAI) as a compulsory subject in Indonesian higher education and high schools holds a strategic position in shaping students ethical character toward AI use. This study investigates the role of PAI in building ethical AI use through a multi site qualitative case study, combining systematic literature review, in depth interviews, and document analysis. Participants were purposively selected from multiple universities and high schools across Indonesia. Findings indicate that PAI learning contextualising Islamic values honesty (shidq), responsibility (amanah), and justice (adl) effectively shapes students ethical attitudes toward AI. This study recommends explicit integration of AI ethics into the national PAI curriculum to develop ethical digital citizens in Indonesia. Keywords: Islamic Religious Education- Artificial Intelligence- Digital Ethics- Indonesian Youth- Character Education Share Link | Plain Format | Corresponding Author (Tyas Prayesti)

8	AI for Learning	ABS-23
Enhancing Student Engagement and Emotional Regulation in ASD through Technology-Enhanced Universal Design for Learning in Inclusive Classrooms Tri Gunadi Magister Psikologi, Universitas 17 Agustus 1945 Surabaya Abstract This pilot study examines the effectiveness of technology-enhanced Universal Design for Learning (UDL) in improving academic engagement and emotional regulation among students with Autism Spectrum Disorder (ASD) in inclusive elementary classrooms, aligned with SDG 4 (Quality Education) and SDG 10 (Reduced Inequalities). Students with ASD frequently experience difficulties sustaining engagement and regulating emotions in mainstream classroom settings, necessitating adaptive, technology-integrated instructional approaches. A quantitative quasi-experimental one-group pretest-posttest design was employed. Eight students with ASD (n = 8- ages 7-12- DSM-5-TR Level 1-2) enrolled in inclusive elementary classrooms in Jakarta, Indonesia, were selected through purposive sampling. A priori power analysis (G*Power 3.1) confirmed n = 8 as sufficient to detect large effects (d &#8805- 0.80, &#945- = .05, power = .80). The five-week technology-enhanced UDL intervention integrated AAC applications, visual scheduling software, video modeling platforms, and adaptive learning systems within the three UDL principles. Academic engagement was assessed using an observational rating scale (ICC = .89) and emotional regulation using the Emotion Regulation Checklist (Shields & Cicchetti, 1997- &#945- = .84). Results indicated statistically significant improvements in academic engagement (t(7) = 5.21, p < .001, d = 1.20) and emotional regulation (t(7) = 4.87, p < .001, d = 1.10), with large effect sizes confirmed across all eight participants. These preliminary findings suggest that technology-enhanced UDL effectively supports both learning participation and emotional functioning in students with ASD within inclusive settings, with important implications for Indonesian inclusive education policy and practice. Keywords: autism spectrum disorder- emotional regulation- inclusive education- student engagement- sustainable development goals- technology-enhanced learning- Universal Design for Learning Share Link | Plain Format | Corresponding Author (Tri Gunadi)

9	AI for Learning	ABS-26
AI SUPPORTED LITERACY AND NUMERACY LEARNING: A SYSTEMATIC REVIEW FOR SDGs Kamariah dan M. Saufi 1Department of Information Technology Education, Universitas PGRI Kalimantan, Banjarmasin, Indonesia Abstract The rapid advancement of artificial intelligence (AI) has transformed educational practices by enabling adaptive, personalized, and data-driven learning. AI-supported learning offers significant potential to enhance literacy and numeracy skills, which are essential for achieving quality education as outlined in the Sustainable Development Goals (SDGs). However, existing research on AI in education remains fragmented and lacks comprehensive synthesis. This study aims to systematically review the literature on AI-supported learning in literacy and numeracy education, focusing on its implementation, impact, challenges, and future directions in the context of SDGs. This research employs a Systematic Literature Review (SLR) method following PRISMA guidelines. Relevant articles were collected from reputable databases using predefined keywords and inclusion criteria. The findings indicate that AI-supported learning, including adaptive learning systems, intelligent tutoring systems, and AI-driven analytics, improves students^ literacy and numeracy skills, engagement, and critical thinking abilities. However, challenges such as infrastructure limitations, teacher readiness, and ethical concerns remain. This study highlights the potential of AI in supporting sustainable education and provides directions for future research and practice. Keywords: ai-supported learning- literacy- numeracy- SDGs- systematic literature review Share Link | Plain Format | Corresponding Author (Kamariah Kamariah)

10	AI for Learning	ABS-31
The Impact of Artificial Intelligence on EFL Learning: A Systematic Review of Research Trends and Language Skill Development Fanissa Narita, Novasa Adiyani, Dikka Syahrial Wiguna POLITEKNIK JATILUHUR Abstract The integration of artificial intelligence (AI) in English as a Foreign Language (EFL) learning has generated significant academic interest due to its potential to create interactive and adaptive learning environments. This study aims to identify current research trends on AI in EFL contexts, examine the language skills most influenced by AI, and analyze its overall impact on learners^ development. To achieve these objectives, this study employed a systematic literature review using the PRISMA framework. Data were collected from the Scopus database. The initial search produced 943 records, which were refined to 65 articles through the use of specific keywords. After applying the inclusion criteria, 32 articles were selected for final analysis. The findings indicate that AI has been widely used to support the development of writing, speaking, reading, and grammar skills, while also enhancing learners^ motivation, engagement, confidence, and access to personalized feedback. At the same time, the literature highlights several challenges, including overreliance on AI, reduced critical thinking, limited interpersonal interaction, inaccuracies in AI-generated feedback, and ethical concerns related to academic integrity and algorithmic bias. These findings suggest that AI offers substantial pedagogical benefits for EFL learning, but its implementation should be guided carefully to ensure balanced, ethical, and meaningful educational practice. Keywords: AI, EFL, Language skills Share Link | Plain Format | Corresponding Author (Fanissa Narita)

11	AI for Learning	ABS-33
FROM TRADITIONAL TO DIGITAL: PEDAGOGICAL INNOVATION IN ACHIEVING SUSTAINABLE DEVELOPMENT GOAL 4 Agung Olaf Ridho Rambe, Tengku Thyrhaya Zein, Nurlela Rusdi Noor Rosa University of North Sumatera Abstract The rapid shift from traditional to digital education has become a critical pathway for achieving Sustainable Development Goal 4 (SDG 4), which emphasizes inclusive and equitable quality education. This study aims to examine how pedagogical innovation through technology integration enhances teaching and learning outcomes in higher education. A mixed-method approach was employed, combining quantitative data from student surveys (n=120) and qualitative insights from instructor interviews. The findings reveal that technology-enhanced pedagogies, such as blended learning, interactive digital platforms, and collaborative tools, significantly improve student engagement, accessibility, and learning effectiveness. However, challenges related to digital literacy and infrastructure disparities remain evident. The study concludes that while digital transformation supports the realization of SDG 4, its success depends on institutional readiness, teacher competence, and equitable access to technology. Strategic implementation of innovative pedagogical practices is therefore essential to ensure sustainable and inclusive education in the digital era. Keywords: Please Just Try to Submit This Sample Abstractblended learning- digital pedagogy- educational technology- SDG 4- student engagement- sustainable education Share Link | Plain Format | Corresponding Author (Agung Olaf Ridho Rambe)

12	AI for Learning	ABS-34
EXPLORING THE NOTEBOOKLM PLATFORM AS A VARIED TEACHING MATERIAL IN INDONESIAN LANGUAGE LEARNING (a) Nafri Yanti, (b) Arono, (c) Catur Wulandari, (d) Noermanzah, (e) Safinatul Hasanah Harahap, (f) Diah Eka Sari (a-d) Prodi Pendidikan Bahasa Indonesia, Universitas Bengkulu, Bengkulu, Indonesia- (e-f) Prodi Pendidikan Bahasa Indonesia, Universitas Negeri Medan, Medan, Indonesia Abstract This research is motivated by the need for Indonesian language learning to be more varied, adaptive, and aligned with student needs. In Indonesian language learning, learning variations play a crucial role in creating an engaging learning environment, increasing student engagement, and supporting educators in presenting teaching materials more flexibly. One platform that has the potential to support these needs is NotebookLM. This platform allows users to manage learning resources, summarize material, formulate questions, and develop teaching materials more systematically. This study aims to explore the use of the NotebookLM platform to support the variation of teaching materials in Indonesian language learning. This study used a qualitative approach with descriptive methods. Data were collected through observation, interviews, and documentation of NotebookLM^s use in the context of Indonesian language learning. The data were then analyzed descriptively to identify the platform^s utilization, the variety of learning variations that can be developed, and their relevance in supporting the Indonesian language learning process. Keywords: Teaching Materials- Indonesian Language- NotebookLM- Learning Variations. Share Link | Plain Format | Corresponding Author (Nafri Yanti)

13	AI for Learning	ABS-46
THE URGENCY OF USING DIGITAL LEARNING MEDIA WITH A GENDER EQUALITY PERSPECTIVE FOR GENERATION Z: A LITERATURE REVIEW Nunung Nurjanah Institut Pangeran Dharma Kusuma Abstract Gender inequality creates various problems that cause a domino effect in different areas of life. Efforts to achieve gender equality are one of the goals intended to be accomplished through the SDGs. Technological advancement presents both opportunities and challenges that have the potential to strengthen or weaken gender perspectives. It is important for Generation Z, as digital natives, to have a gender perspective. The use of digital technology as a learning medium is one of the efforts in building students^ gender equality perspectives. This study uses a qualitative approach through a literature review. The results of the study show that the use of learning media plays an important role in shaping students^ gender perspectives. The conclusion of this study is that the development of digital learning media with a gender equality perspective is necessary. Keywords: digital- equality-gender- learning- media- Share Link | Plain Format | Corresponding Author (Nunung Nurjanah)

14	AI for Learning	ABS-53
EXAMINING GENERATIVE AI USE IN HIGHER EDUCATION: LEARNING EFFICIENCY AND TECHNOLOGY DEPENDENCE Maya Karmila Universitas Terbuka Abstract The use of Generative Artificial Intelligence (GenAI) in student learning has increased significantly alongside the advancement of digital technologies in higher education. This study aims to analyze the role of GenAI in improving learning efficiency while examining the risk of technology dependence among students. A quantitative approach with a survey design was employed. Data were collected from 200 university students who actively use GenAI tools, particularly ChatGPT, for academic purposes through purposive sampling. A structured questionnaire was developed based on the Technology Acceptance Model (TAM), incorporating variables such as perceived usefulness, perceived ease of use, learning efficiency, and technology dependence. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships among variables. The results indicate that perceived usefulness and perceived ease of use have a positive effect on GenAI usage, which enhances learning efficiency. However, increased usage also contributes to higher levels of technology dependence, potentially reducing cognitive engagement and independent learning. In conclusion, GenAI plays a dual role as both a facilitator of efficient learning and a source of potential dependency, requiring proper management, digital literacy, and ethical considerations in its implementation. Keywords: generative ai- higher education- learning efficiency- pls-sem- technology dependence Share Link | Plain Format | Corresponding Author (Maya Karmila S.E.,M.E.)

15	AI for Learning	ABS-65
EXPLORING THE ACCURACY AND USABILITY OF AI-GENERATED IMAGES FOR ABSTRACT PHYSICS CONCEPTS IN EDUCATION Yoseph Satria Praka, Malisa Huzaifa, Candi Rahayu Tri Prameswari, Nurul Wahyuni, Ananda Maria Digital Multimedia Engineering, Jakarta State Polytechnic, Depok, Indonesia Abstract Abstract physics concepts are often difficult for students to understand due to their invisible and complex nature, requiring effective visualization. Recent advances in artificial intelligence (AI) enable the rapid generation of educational images- however, their scientific accuracy and usability remain uncertain. This study aims to evaluate the accuracy and usability of AI-generated images for selected abstract physics concepts using Google Gemini with a CLEAR-based prompting approach. This study employed a mixed methods descriptive evaluative design, combining quantitative Likert-scale ratings and qualitative expert feedback. The evaluation involved expert judgment from a physics teacher with 11 years of teaching experience. The results show that the accuracy of AI-generated images is generally high (mean scores: 3.75 for kinetic theory of gases and 3.5 for atomic structure), although limitations were found in representing complex conceptual relationships and maintaining scientific consistency. In contrast, usability scores were higher (4.25 and 4.0), indicating that the images are visually appealing and helpful for learning. The findings suggest that AI-generated images have strong potential as instructional media but require expert validation to prevent misconceptions. Keywords: AI-Generated Images- GenAI in Education- Google Gemini Share Link | Plain Format | Corresponding Author (Yoseph Satria Praka)

16	AI for Learning	ABS-69
Research on the Transformation and Effect of Lifelong Learning Methods Supported by Artificial Intelligence Jie Peng The Open University of Ya^an Abstract With the continuous iteration and in-depth development of artificial intelligence (AI) technology, it has gradually penetrated into the entire process of education and teaching, exerting a profound and long-lasting impact on the form and system structure of lifelong learning. Compared with the traditional learning mode centered on teacher-led and one-way knowledge transmission, AI-supported lifelong learning places greater emphasis on the construction of personalized learning paths, interactive communication among multiple subjects, and real-time feedback on the learning process. This transformation has not only profoundly changed the learning behaviors and cognitive modes of adult learners, but also exerted a significant impact on their learning engagement, learning experience and learning outcomes, while putting forward new challenges and requirements for the optimal operation of the lifelong learning system. In this context, this paper focuses on the core issue of the transformation of lifelong learning methods in the context of AI support, constructs a theoretical analysis framework centered on the transformation of learning methods, clearly defines the connotation and characteristics of the transformation of AI-supported lifelong learning methods from three core dimensions: learning behavior, learning path and learning support, and systematically explores its influence mechanism and action path on learning effects. The research adopts a combination of literature analysis and theoretical combing, systematically sorts out the research results in related fields, constructs a theoretical model of the transformation of AI-supported lifelong learning methods and learning effects, and clarifies the measurement standards and methods of each variable. On this basis, empirical data from front-line adult learners are collected through questionnaire surveys, and quantitative analysis methods such as structural equation modeling (SEM) are used to test and revise the theoretical model, so as to provide a solid empirical basis and scientific theoretical analysis perspective for the optimization and improvement of the lifelong learning mode and the sound development of the lifelong learning system in the context of digital transformation. Keywords: artificial intelligence-lifelong learning-learning mode transformation- Share Link | Plain Format | Corresponding Author (Jie Peng)

17	AI for Learning	ABS-76
LEVERAGING ARTIFICIAL INTELLIGENCE FOR LEARNING ANALYTICS-DRIVEN PERSONALIZED LEARNING TO IMPROVE STUDENT ENGAGEMENT AND LEARNING OUTCOMES Dina Dahliana, Andri, Rahmat Ilahi, Akmal Yandi STAI Solok Nan Indah Abstract The rapid advancement of Artificial Intelligence (AI) has created new opportunities for developing adaptive and personalized learning environments. However, the implementation of AI-based personalized learning in higher education still faces significant challenges, particularly in enhancing student engagement and learning outcomes. This study aims to examine the use of Artificial Intelligence supported by learning analytics in facilitating personalized learning and its impact on student engagement and academic performance. This research employs a quantitative approach with a quasi-experimental design involving university students in an online learning setting. Data were collected through student engagement questionnaires, learning outcome tests, and activity logs obtained from the Learning Management System (LMS). The data were analyzed using both descriptive and inferential statistical techniques. The findings indicate that the use of AI in personalized learning significantly improves student engagement, as reflected in increased active participation, learning time, and interaction with learning materials. Furthermore, a significant improvement in student learning outcomes was observed compared to conventional learning approaches. These results suggest that the integration of AI supported by learning analytics has strong potential as an innovative solution for promoting adaptive and sustainable learning in higher education. This study contributes to the development of technology-enhanced pedagogical models to support the achievement of the Sustainable Development Goals (SDGs) in education. Keywords: Artificial Intelligence, personalized learning, learning analytics, student engagement, learning outcomes Share Link | Plain Format | Corresponding Author (Dina Dahliana)

18	AI for Learning	ABS-79
Designing AI-Supported Ipas Learning With Canva For Cultural Diversity Education In Elementary Schools Sherly Anisa Utami, Ratu Asmaarobiyah, Suryo Prabowo, Mohamad Arif Rahmansyah Terbuka University Abstract The integration of Artificial Intelligence (AI) in education offers significant opportunities to develop innovative, interactive, and student-centered learning in elementary schools. However, IPAS (Integrated Science and Social Studies) learning, particularly on the topic of cultural diversity, is still often delivered through conventional approaches that emphasize memorization rather than meaningful understanding. This results in low student engagement and limited participation in classroom activities. Therefore, this study aims to design an AI-supported learning framework using Canva to facilitate engaging and contextual learning experiences for fourth-grade elementary school students. This study adopts a Design-Based Research (DBR) approach consisting of four stages: needs analysis, design, development, and evaluation. The proposed framework integrates visual learning, collaborative activities, and contextual cultural content supported by Canva^s AI features. The resulting products include lesson plans, teaching materials, student worksheets, and assessment instruments designed to enhance student participation and creativity. The design was validated by two university lecturers and one elementary school teacher, showing a high level of validity and feasibility. The proposed framework provides both conceptual and practical guidance for implementing AI-based learning and contributes to the development of meaningful and student-centered learning environments in elementary school. Keywords: artificial intelligence- canva ai- ipas learning- cultural diversity- elementary school. Share Link | Plain Format | Corresponding Author (Sherly Anisa Utami)

19	AI for Learning	ABS-84
ENHANCING UNDERSTANDING OF LOCAL WISDOM AND SOCIAL ISSUES THROUGH AI AND EDUCATIONAL APPLICATIONS Elsya Fitriani Nuraziziah Utami, Yunus Abidin UNIVERSITAS PENDIDIKAN INDONESIA Abstract Local wisdom-based learning is essential for fostering cultural values and enhancing students^ awareness of social issues. Recent advances in technology, particularly artificial intelligence (AI) and educational applications, provide innovative tools to support interactive and contextually relevant learning. This literature review examines how AI and educational applications contribute to improving students^ understanding of local wisdom and associated social issues. Analysis of recent scholarly articles highlights that these technologies enhance student engagement, conceptual understanding, and critical thinking, while promoting collaborative and experiential learning. Despite these benefits, challenges such as limited access to technology, teacher preparedness, and content quality persist. In conclusion, AI and educational applications offer an effective and innovative approach to strengthen local wisdom-based learning and social issue comprehension, provided that sufficient infrastructure and quality content are ensured. Keywords: artificial intelligence- educational applications- local wisdom- literature review- social issues- innovative learning Share Link | Plain Format | Corresponding Author (ELSYA FITRIANI NURAZIZIAH UTAMI)

20	AI for Learning	ABS-85
ASSESSING THE IMPACT OF TECHNOLOGY-SUPPORTED PEDAGOGICAL INNOVATION ON STUDENT SUSTAINABLE DEVELOPMENT AWARENESS Tarina Nurul Lieza1 - Dede Trie Kurniawan2 UNIVERSITAS PENDIDIKAN INDONESIA Abstract This study examines the impact of technology supported pedagogical innovation on students awareness of sustainable development. The increasing urgency of global sustainability challenges highlights the need for transformative educational approaches that integrate digital technologies with innovative pedagogy. This research aims to assess how technology enhanced learning strategies influence students^ understanding, attitudes, and awareness of sustainable development concepts. A quasi experimental design was employed involving two groups of students in higher education, where the experimental group was exposed to technology supported pedagogical interventions, while the control group received conventional instruction. Data were collected through questionnaires and pre test, post test assessments and analyzed using statistical methods. The findings indicate that students in the experimental group demonstrated significantly higher levels of awareness and engagement with sustainable development issues compared to those in the control group. The results suggest that integrating technology with innovative pedagogical practices can effectively enhance students^ sustainability awareness and foster more meaningful learning experiences. In conclusion, technology supported pedagogical innovation plays a critical role in advancing education for sustainable development and should be widely adopted in educational settings. Keywords: digital learning- pedagogical innovation- sdgs- student awareness- sustainable development- technology integration Share Link | Plain Format | Corresponding Author (Tarina Nurul Lieza)

21	AI for Learning	ABS-93
Cybergogy and Multiliteracy in AI-Mediated Academic English: A Conceptual Study in Islamic Higher Education Arum Putri Rahayu STAI MA^arif Magetan Abstract This conceptual study examines how cybergogy can be used to promote multiliteracy in AI-mediated academic English learning within Islamic higher education. Focusing on the context of the Islamic Religious Education (Pendidikan Agama Islam/PAI) program at STAI Ma^arif Magetan, the article responds to the increasing demand for students to access, interpret, and produce scholarly texts in English in the Society 5.0 era, where digital technologies and artificial intelligence (AI) pervade academic communication. Two questions guide the discussion: how cybergogical principles can be conceptualized and operationalized to support multiliteracy in academic English learning, and what opportunities and challenges arise when cybergogy is used as a framework for fostering multiliteracy and responsible engagement with AI tools. Using a qualitative conceptual approach, the study synthesizes literature on cybergogy, multiliteracy, academic English, AI in education, and Islamic higher education. The analysis shows that cybergogy provides a coherent pedagogical lens that links cognitive, emotional, and social engagement with linguistic, digital, visual, information, and intercultural literacies in AI-rich environments. At the same time, its implementation faces challenges related to lecturer preparedness, risks of cognitive overload, unequal access to digital and AI resources, and tensions around academic integrity and Islamic ethics. The article concludes that cybergogy offers a promising framework for designing academic English courses in PAI programs that are multiliterate, ethically grounded, and aligned with the human-centered vision of Society 5.0, while also highlighting the need for further empirical research and institutional support. Keywords: Artificial Intelligence, Cybergogy, Multiliteracy Share Link | Plain Format | Corresponding Author (arum putri rahayu)

22	AI for Learning	ABS-95
THE USE OF ARTIFICIAL INTELLIGENCE (AI) IN LANGUAGE LEARNING Sutarsih Badan Riset dan Inovasi Nasional Abstract The application of artificial intelligence (AI) in language learning is the topic of this article. As AI coexists with technological advancements, this is inevitable. Language learners often use AI to solve problems related to language learning. Learners and learning outcomes are influenced by the use of AI tools. Therefore, the role of AI in language learning is a research question. Using research articles published in journals and/or proceedings conferences about the application of AI in language learning, this study employs a qualitative descriptive technique based on literature evaluation. The application of AI in language learning was identified, categorised, and interpreted as part of a qualitative data analysis process. The findings demonstrate that AI is now widely used in all language learning activities. AI is recognized as beneficial for language learning, both in completing assignments and in understanding exam or quiz questions. However, learners may become dependent on AI, reluctant to work independently, and demanding quick solutions. Furthermore, there is no guarantee of human identity or the privacy of the resulting thoughts. To mitigate the negative impacts of AI, significant consideration must be given to its use. Keywords: artificial intelligence (AI), language learning, impact, education technology Share Link | Plain Format | Corresponding Author (Sutarsih Sutarsih)

23	AI for Learning	ABS-99
Enhancing Mathematics Learning through AI Chatbots and Scaffolding: A Systematic Literature Review Hasanah Sulistiyah Ningsih (1*), Hepsi Nindiasari (2), Maman Fathurrohman (3), Novaliyosi (4) 1) Mathematics Education Study Program, Universitas Sultan Ageng Tirtayasa Jl. Raya Jakarta Km 4, Pakupatan, Serang 42124, Banten, Indonesia *hasanahsn50[at]gmail.com 2) Mathematics Education Study Program, Universitas Sultan Ageng Tirtayasa Jl. Raya Jakarta Km 4, Pakupatan, Serang 42124, Banten, Indonesia 3) Mathematics Education Study Program, Universitas Sultan Ageng Tirtayasa Jl. Raya Jakarta Km 4, Pakupatan, Serang 42124, Banten, Indonesia 4)Mathematics Education Study Program, Universitas Sultan Ageng Tirtayasa Jl. Raya Jakarta Km 4, Pakupatan, Serang 42124, Banten, Indonesia Abstract The rapid advancement of Artificial Intelligence (AI), particularly in the form of chatbot technologies, has created new opportunities for supporting mathematics learning. However, its pedagogical application, especially when integrated with scaffolding approaches, has not been extensively explored. Therefore, this study aims to systematically review the use of AI chatbots in mathematics learning, examine the role of scaffolding, and evaluate the effectiveness of their integration. This study employs a Systematic Literature Review (SLR) method following PRISMA guidelines. Relevant articles were collected from several academic databases based on predefined inclusion criteria, focusing on recent studies related to AI chatbots, scaffolding, and mathematics education. The findings reveal that AI chatbots are widely utilized as virtual tutors that provide real-time interaction, immediate feedback, and support for self-directed learning. Meanwhile, scaffolding is implemented through step-by-step guidance, prompting strategies, and feedback mechanisms that help students develop a deeper understanding of mathematical concepts. The integration of AI chatbots and scaffolding generally demonstrates positive effects on students^ learning outcomes, motivation, and engagement. However, most studies indicate that scaffolding within chatbot systems is not yet designed in an adaptive and systematic manner aligned with students^ learning needs. These findings suggest that there is still a gap in the development of AI chatbot systems that integrate pedagogically grounded scaffolding. Therefore, future research should focus on designing and evaluating AI-based learning environments that incorporate adaptive scaffolding to support students^ problem-solving skills in mathematics learning. Keywords: AI Chatbots- Scaffolding- Mathematics Learning- Systematic Literature Review- Problem-Solving Skills Share Link | Plain Format | Corresponding Author (Hasanah Sulistiyah Ningsih)

24	AI for Learning	ABS-102
AI Chatbots as Creative Writing Buddies: Stimulating Narrative Writing Skills in Primary School Students Anugrah Agung(a)*,Yusnia (b), Rizqa Dwi Shofiya Maghfira Izzania(b) Yuli Amaliyah (b)Muhammad Habib Ramadhani (b) Universitas Bengkulu, Bengkulu, Indonesia Abstract The rapid integration of Artificial Intelligence (AI) in education presents new opportunities for language pedagogy in primary schools. This preliminary study explores the utilization of AI chatbots as a ^Writing Buddy^ to stimulate narrative writing skills among elementary students. The research is motivated by the common difficulties students face in brainstorming ideas and structuring coherent story plots. Using a descriptive qualitative method, this study analyzes early-stage interactions between students and AI tools during the pre-writing phase. Data were collected through observations and document analysis of student story drafts. The preliminary results indicate that AI chatbots effectively serve as a scaffolding tool that reduces ^writer^s block^ and encourages vocabulary expansion by providing creative prompts. Furthermore, the interaction with AI stimulates students^ imaginative thinking while maintaining their role as the primary authors. In conclusion, while AI cannot replace the teacher^s role, its position as a digital partner offers significant potential to enhance linguistic creativity and confidence in young learners. This study provides a foundational framework for future research on AI-integrated literacy curricula in primary education. Keywords: ai chatbot- language pedagogy- narrative writing- preliminary study- primary education- writing buddy Share Link | Plain Format | Corresponding Author (Anugrah Agung)

25	AI for Learning	ABS-103
Identification of Ethnoscience Potential and GenAI Technology in Disaster Mitigation Learning Rizqa Dwi Shofiya Maghfira Izzania (1*), Anugrah Agung(2), Miftahus Silmi Zohro (3), Yusnia (4), Neza Agusdianita(5) 1,2,3,4,5) Elementary School Teacher Education Study Program, University of Bengkulu Abstract The province of Bengkulu is geographically situated in a zone highly prone to tectonic disasters- however, disaster mitigation understanding at the elementary school level is often theoretical and detached from the local cultural context. This study aims to identify the potential integration of Bengkulu^s cultural ethnoscience and Generative Artificial Intelligence (GenAI) technology as a foundation for developing disaster mitigation learning media in elementary schools. This research represents the initial stage (Analysis) of the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development model. The analysis method was conducted through literature reviews, observations of local wisdom, and curriculum needs analysis for Phase C (Grade V and VI) of the Kurikulum Merdeka (Independent Curriculum). The results of the analysis indicate that: (1) Bengkulu^s culture possesses a wealth of ethnoscience, such as the architecture of Rumah Bubungan Lima, which is adaptive to earthquakes, and local knowledge regarding natural signs that have not been documented in formal teaching materials- (2) The use of GenAI technology holds great potential in transforming abstract ethnoscience narratives into interactive visual media and digital storytelling that align with the cognitive characteristics of elementary school students- (3) This integration is relevant to the Science and Social Studies (IPAS) Learning Outcomes and the strengthening of the Dimensions of the Graduate Profile. The conclusion of this analysis phase recommends the necessity of developing disaster mitigation learning tools that blend Bengkulu^s local wisdom values with the sophistication of AI technology to create contextual, immersive, and meaningful learning experiences for students. Keywords: Ethnoscience- Bengkulu- GenAI- Disaster Mitigation- Elementary School Share Link | Plain Format | Corresponding Author (Rizqa Dwi Shofiya Maghfira Izzania)

26	AI for Learning	ABS-116
Enhancing Student Engagement and Academic Performance through Artificial Intelligence-Based Adaptive Learning Systems Muhammad Aryuda Silfa Universitas Terbuka Abstract The integration of artificial intelligence (AI) in education has significantly transformed teaching and learning processes, particularly in improving student engagement and personalized learning experiences. This study aims to examine the effectiveness of AI-based adaptive learning systems in enhancing student engagement and academic performance in higher education. A quantitative research design was employed using a quasi-experimental approach involving 120 undergraduate students divided into control and experimental groups. The experimental group utilized an AI-driven adaptive learning platform, while the control group engaged in conventional learning methods. Data were collected through pre and post tests, as well as student engagement questionnaires, and analyzed using paired sample t-tests and regression analysis. The results indicate that students exposed to AI-based learning systems showed a statistically significant improvement in both engagement levels and academic achievement compared to the control group. Furthermore, AI personalization features contributed to better learning outcomes by adapting content to individual student needs. In conclusion, AI-based adaptive learning systems offer a promising approach to enhance learning effectiveness and support sustainable educational development. Keywords: Academic Performance- Adaptive Learning- AI- Student Engagement- Sustainable Education Share Link | Plain Format | Corresponding Author (Muhammad Aryuda Silfa)

27	AI for Learning	ABS-122
Reimagining Civic Education through AI-Supported Blended Learning in Indonesia: A Qualitative Inquiry into Policy Awareness, Participation, and Diversity Hastangka, Herlinawati, Benny Widaryanto National Research and Innovation Agency Abstract The ongoing digital transformation of education in Indonesia presents both opportunities and tensions in fostering civic engagement and inclusive policy education. Within the broader agenda of achieving the Sustainable Development Goals (SDGs), there is a growing need to rethink how pedagogical innovation can cultivate critical civic awareness, participation, and respect for diversity. This study explores how artificial intelligence (AI), when integrated into blended learning environments, reshapes the meanings, practices, and experiences of civic education in Indonesia. This research draws on narrative interviews, reflective dialogues, and document analysis involving educators and learners engaged in AI-supported civic learning practices. Rather than focusing on institutional levels, the study centers on lived experiences and meaning-making processes as participants interact with digital tools to explore issues of public policy, social justice, and cultural diversity. This study contributes to the literature by offering (1) a conceptual understanding of AI as a mediating tool in civic meaning-making, (2) empirical insights into AI-supported civic learning in a culturally diverse context, and (3) a critical perspective on the ethical implications of AI integration in education. The findings provide implications for educators and policymakers seeking to align digital transformation with democratic values and the Sustainable Development Goals (SDGs). The findings reveal that AI-supported blended learning environments create dialogic and reflective spaces where civic knowledge is not merely transmitted but co-constructed. Participants reinterpret policy issues through their sociocultural contexts, negotiate diverse perspectives, and develop a more situated understanding of citizenship. At the same time, the integration of AI introduces ethical and epistemic questions, particularly concerning authority, bias, and the role of human judgment in learning. Digital inequality and uneven media literacy also shape how participants engage with these technologies. This study contributes to pedagogical innovation by offering a context-sensitive perspective on the transformative potential of AI in civic education. It highlights the importance of embedding critical, ethical, and culturally responsive approaches in technology-enhanced learning to support inclusive civic participation in Indonesia^s diverse society. The paper provides insights for educators, researchers, and policymakers seeking to align digital transformation with democratic values and sustainable development Keywords: Civic Education, Artificial Intelligence, Blended Learning, Civic Participation, Narrative Inquiry. Share Link | Plain Format | Corresponding Author (Herlinawati Syaukat)

28	AI for Learning	ABS-125
The Impact of Artificial Intelligence On Students^ Thinking Skills In Indonesian Higher Education Adhi Susilo Universitas Terbuka Abstract Across the updated literature, AI shows the strongest positive association with higher-order learning when it is embedded in structured, dialogic, and reflective pedagogies rather than used as a shortcut for answer production. Recent empirical studies and reviews indicate that scaffolded human-AI collaboration can improve critical thinking, collaborative problem-solving, and idea generation, especially when students must justify prompts, compare alternatives, evaluate evidence, and revise outputs. However, the same literature also documents clear risks: passive dependence on generative AI, cognitive offloading, fatigue, reduced evaluative depth, and homogenization of written or creative products. Indonesia-specific studies suggest rapid uptake and substantial student readiness, yet the local evidence base remains thinner and methodologically less mature than the surrounding policy discourse. The central conclusion of the revised review is that the educational impact of AI is not determined by tool adoption alone but by pedagogical framing, assessment redesign, AI literacy, and equitable institutional governance. The manuscript therefore recommends moving from permissive or prohibitive approaches toward responsible, higher-order, human-centered AI integration in Indonesian higher education. Keywords: artificial intelligence- critical thinking- problem-solving- creativity- analytical reasoning- higher education- Indonesia- systematic literature review- PRISMA- cognitive skills Share Link | Plain Format | Corresponding Author (Adhi Susilo)

29	AI for Learning	ABS-127
AI-Scaffolding and Neuropedagogy in Elementary Mathematics: A Scoping Review Sendi Ramdhani, Riandi Marisa, Puryati, Uliya Khoirun Nisa, Amalia Sapriati Universitas Terbuka Abstract Elementary mathematics learning requires instructional designs that foster not only conceptual understanding but also critical reasoning and student autonomy. In the era of artificial intelligence, AI-based scaffolding offers adaptive support for learners, while neuropedagogy provides a brain-informed foundation for designing meaningful learning experiences. However, the integration of these two perspectives in elementary mathematics education remains insufficiently explored. This study aims to map research trends and identify key characteristics of AI-scaffolding and neuropedagogical approaches in elementary mathematics learning. The study employed a scoping review method through the stages of identification, screening, data extraction, and thematic synthesis of relevant scholarly publications. The findings indicate that AI-scaffolding has been increasingly used to provide personalized feedback, adaptive tasks, and learning support, while neuropedagogical principles emphasize attention, emotion, memory, and cognitive readiness in instructional design. The review also shows that both approaches have the potential to strengthen students^ critical reasoning and learning autonomy, although empirical studies at the elementary level remain limited. In conclusion, integrating AI-scaffolding and neuropedagogy offers a promising direction for developing adaptive and human-centered mathematics learning designs in elementary education. Keywords: ai-scaffolding- critical reasoning- elementary mathematics- neuropedagogy- scoping review- student autonomy Share Link | Plain Format | Corresponding Author (Sendi Ramdhani)

30	AI for Learning	ABS-128
A Critical Analysis of Students Use of ChatGPT in Completing Mathematics Assignments Muhammad Habib Ramadhani, Yusnia, Irfan Supriatna, Neza Agusdianita, Anugrah Agung, Rizqa Dwi Shofiya Maghfira Izzania University of Bengkulu Abstract The rapid development of artificial intelligence presents both opportunities and challenges in higher education. ChatGPT, as one of the most widely used AI applications, is increasingly utilized by students to complete academic assignments, including mathematics tasks. This phenomenon raises questions about whether students use ChatGPT critically or simply copy its outputs without proper verification. This study aims to critically analyze how students use ChatGPT in completing mathematics assignments. The research employed a qualitative descriptive approach using document analysis by examining student assignments suspected of utilizing ChatGPT. The findings reveal variations in usage patterns: some students directly copied the responses, others made minor modifications, while a smaller group demonstrated more critical engagement by verifying, adjusting, and adding explanations according to the task context. These findings indicate different levels of students^ critical literacy in utilizing AI technology. This study highlights the importance of strengthening critical and digital literacy, particularly among prospective teachers, so that AI can be used as a supportive tool for meaningful learning without reducing independent thinking skills. Keywords: artificial intelligence, ChatGPT, critical literacy, digital literacy, mathematics education Share Link | Plain Format | Corresponding Author (Muhammad Habib Ramadhani)

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