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All Journal Journal of Applied Data Sciences Foreign Language Instruction Probe SeLEC Sustainable
Dewi Sari Wahyuni
Universitas Sains dan Teknologi Indonesia
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences

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Augmented Reality in Integrated Sustainability Concept for English Language Learning Dewi Sari Wahyuni; T. Sy. Eiva Fatdha
Foreign Language Instruction Probe Vol. 5 No. 1 (2026): Teaching English as a Foreign Language
Publisher : STIT Buntet Pesantren Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54213/flip.v5i1.828

Abstract

This position paper examines the integration of Augmented Reality (AR) into a comprehensive sustainability framework for English Language Learning (ELL) in Indonesian higher education. The exponential growth of immersive learning technologies, coupled with the global imperative articulated through Education for Sustainable Development (ESD) and Sustainable Development Goal 4, has placed unprecedented pressure on language educators to design pedagogies that are simultaneously technologically rich and ethically grounded. However, current literature treats AR-enhanced language learning and sustainability-oriented language education as parallel discourses with limited theoretical convergence. This paper addresses this gap by proposing a conceptual framework that integrates AR affordances with the principles of integrated sustainability, encompassing ecological, social, economic, and pedagogical dimensions. Drawing on a systematic review of 48 Scopus-indexed publications and adopting a conceptual-analytical method of inquiry, the analysis identifies three thematic findings: the fragmentation of AR-ELL and sustainability discourses, the structural conditions that sustain this fragmentation, and the transformative potential of integration. The paper contributes a five-dimensional framework, the AR-ISC model, and offers recommendations for curriculum design, teacher education, and future empirical validation, particularly within Indonesian and broader Global South contexts.
Augmented Reality in English Language Learning: Now and Then Dewi Sari Wahyuni; T. Sy. Eiva Fatdha
Studies in Language, Education, and Culture (SeLEC) Vol. 2 No. 1 (2026): Studies in Language, Education, and Culture (SeLEC)
Publisher : Media Publikasi Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56303/selec.v2i1.1437

Abstract

Augmented Reality has shifted from being a novelty technology in English Language Learning to an established pedagogical infrastructure in fewer than two decades. This position paper This position paper argues that the field is now entering a third generation in which AR's value is no longer derived from the technology itself but from its integration with artificial intelligence, mobile ubiquity, and learner-centered task design. Using a structured narrative review combined with a Scopus bibliometric mapping of 398 documents published between 2007 and 2026, the study traces the evolution of AR-supported English learning across three periods: a foundational period (2007-2016) dominated by marker-based and barcode prototypes, a mainstreaming period (2017-2021) shaped by mobile AR and learning theory, and a convergent period (2022-2026) characterized by an explosive growth of empirical work, with two thirds of all indexed publications appearing in this most recent five-year window. The findings indicate that AR consistently produces moderate-to-large positive effects on linguistic and affective outcomes, but that effects are uneven across skills, age groups, and contexts. The paper takes the position that further research should move beyond demonstrating that AR works, and instead address how AR-enhanced English instruction should be designed, governed, and integrated with generative AI in ways that protect equity, teacher agency, and pedagogical coherence. Implications for curriculum designers, teacher educators, and policymakers in English as a Foreign Language contexts are discussed, with particular attention to low-resource settings such as Indonesia, where mobile-first AR deployment offers a credible pathway to scale immersive English instruction.
MYCD: Integration of YOLO-CNN and DenseNet for Real-Time Road Damage Detection Based on Field Images Helda Yenni; Rometdo Muzawi; Karpen Karpen; M. Khairul Anam; Michel Kasaf; Tjut Rizqi Maysyarah Hadi; Dewi Sari Wahyuni
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1040

Abstract

Road damage such as cracks, potholes, and uneven surfaces poses serious risks to transportation safety, logistics efficiency, and maintenance budgeting in Indonesia. Manual inspection is time consuming, labor intensive, and prone to error, motivating the use of reliable computer vision solutions. This study proposes MYCD, a hybrid and mobile ready architecture that combines the fast detection ability of YOLO with the dense feature reuse of DenseNet, enhanced by the Convolutional Block Attention Module (CBAM) for spatial and channel focus and Spatial Pyramid Pooling (SPP) for multi scale context understanding. The system detects and classifies the severity of road damage into minor, moderate, and severe categories using images captured by standard cameras. MYCD was trained and validated on 1,120 field images using an 80/20 split to simulate realistic deployment. Validation achieved 64 percent accuracy, with the highest per class precision of 0.72 for minor damage and mAP@0.5 = 0.677. The confusion matrix showed that most errors occurred in the moderate category because of visual similarity with minor and severe damage. Unlike earlier studies that extended YOLO with heavy backbones such as ResNet or EfficientNet, MYCD focuses on feature propagation (DenseNet), attention precision (CBAM), and multi scale fusion (SPP) optimized for real time operation on standard hardware. Efficiency profiling confirmed its deployability. After compression, the model size is 46.8 MB and it requires 3.7 GFLOPs per inference at 640×640 resolution. On a mid-range Android device (Snapdragon 778G, 8 GB RAM), MYCD runs at 19 frames per second with 1.2 GB peak memory. Compared with YOLOv8 WD (68 MB; 5.2 GFLOPs), MYCD reduces computation by 31 percent while maintaining similar accuracy. Overall, MYCD achieves a practical balance of speed, accuracy, and efficiency, providing a deployable and reproducible framework for real time road damage detection in resource limited settings.
Climate Action in English for Computer Science Dewi Sari Wahyuni; T. Sy. Eiva Fatdha
Sustainable Vol. 8 No. 2 (2025): Transforming Education: Digital Integration, Strategic Assessment, and Sustaina
Publisher : Lembaga Penjaminan Mutu, IAIN Syaikh Abdurrahman Siddik Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32923/hx8rag64

Abstract

This study examines the integration of climate action concepts, specifically green computing and computing for green, into English language learning for computer science students using the Content and Language Integrated Learning (CLIL) approach. English Language Learners (ELLs), most of whom are non-native English speakers (NNES) in the field of Computer Science, require a language learning model that not only improves linguistic skills but also fosters awareness and active participation in global climate change issues. Through qualitative methods, including a literature review, CLIL classroom observations, and interviews with instructors, this study identifies best practices in designing content-integrated English language curricula that combine language proficiency and ecological literacy. Green computing principles are applied not only in learning materials but also in research methods to reduce carbon footprints. Findings indicate that integrating sustainability topics into English language learning within the context of Computer Science effectively enhances students' language skills and environmental awareness. Students become more motivated to act as agents of change in preserving the environment. The practical implication is that interdisciplinary collaboration and innovative CLIL curriculum design can play a crucial role in preparing Computer Science graduates to be not only technically competent but also linguistically competent, as well as having sustainability awareness.
Co-Authors Anam, M Khairul Helda Yenni Karpen Karpen Michel Kasaf Rometdo Muzawi T. Sy. Eiva Fatdha Tjut Rizqi Maysyarah Hadi