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All Journal Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Pendidikan Progresif
Sari, Salma Rahmadhani Puspita
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Computer Science & IT Education Engineering Medicine & Pharmacology Social Sciences Other

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Integration of the AI-Edu Assistant in an Appreciation-Based Deep Learning Strategy to Enhance the Motivation and Learning Outcomes of Vocational High School Student Sari, Salma Rahmadhani Puspita; Musthafa, Rochman Hadi
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2025: Proceeding ISETH (International Summit on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

This study aims to describe the integration of the AI-Edu Assistant within an appreciation-based deep learning strategy to enhance the motivation and learning outcomes of vocational high school students. Alongside the rapid development of artificial intelligence in education, this research explores how AI can support the provision of personalized feedback, digital appreciation, and adaptive learning recommendations as components of an innovative instructional design aligned with 21st-century educational needs. The study employs a qualitative descriptive approach supported by quantitative data. Data were collected through classroom observations, teacher and student interviews, documentation, and pre- and post-learning assessments. The instructional process implemented four phases of deep learning-exploration, elaboration, application, and reflection which were combined with teacher-provided appreciation and automated appreciation messages generated by the AI-Edu Assistant. Feedback logs and AI-generated recommendations were also analyzed as supporting data. The findings indicate that the integration of the AI-Edu Assistant successfully enhanced students’ learning motivation, as evidenced by increased participation, persistence, and willingness to ask questions and express opinions. Students responded positively to the instant appreciation and adaptive feedback provided by the AI system. Learning outcomes increased from an average score of 68 (pretest) to 80 (posttest), demonstrating a significant academic impact. This study reveals that combining AI-based feedback with an appreciation-based deep learning strategy can create a more personalized, interactive, and motivating learning environment. The findings offer a practical model for integrating AI into pedagogical strategies and contribute new insights into the role of AI in supporting both the cognitive and affective aspects of learning.
Learning Engagement as the Primary Catalyst for Transforming Social Support into Rural Teaching Commitment Among Prospective Teachers Syah, Muhammad Fahmi Johan; Huda, Miftakhul; Utomo, Arief Cahyo; Assidik, Gallant Karunia; Mansor, Mahaliza; Jelita, Hanifah Tria Intan; Salsabila, Alifa; Sari, Salma Rahmadhani Puspita
Jurnal Pendidikan Progresif Vol 16, No 2 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i2.pp773-792

Abstract

This study aims to analyze the prediction of social support role on rural teaching commitment (RTC), with learning engagement as a mediator. The study involved 350 prospective teachers at the undergraduate and professional teacher education (PPG) levels in Indonesia. Data were analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach. The results showed that the majority of respondents had moderate levels of social support, learning engagement, and RTC. Specific findings indicate that emotional support is the most fundamental social support item in forming engagement. The PLS-SEM analysis confirmed the prediction that learning engagement functions as a strong partial mediator. Although social support contributes directly to teaching commitment in remote areas, its influence becomes even more significant when mediated by learning engagement, namely vigor, dedication, and absorption. However, the current RTC component remains dominated by the normative aspect (obligation), indicating a risk of low teacher retention. This study concludes that teacher placement policies cannot rely solely on administrative and normative approaches; they must integrate strengthening the basic capital within prospective teachers with a conducive school and community environment to create a sustainable commitment in rural areas of Indonesia. Furthermore, this study highlights the need for curriculum reform in both undergraduate teacher education and professional teacher education programs. These curricula should be deliberately designed to internalize key dimensions such as social support, learning engagement, and long-term teaching commitment. This can be achieved by integrating structured learning experiences, including community-based teaching practices, reflective activities, mentoring systems, and immersion programs in rural contexts. Such initiatives are expected to not only enhance prospective teachers’ adaptive capacities but also strengthen their emotional attachment, sense of purpose, and resilience in undertaking teaching assignments in underserved areas. Keywords: learning engagement, social support, rural teaching commitment, pre-service teacher, PLS-SEM.
Co-Authors Arief Cahyo Utomo Gallant Karunia Assidik Jelita, Hanifah Tria Intan Mansor, Mahaliza Miftakhul Huda Muhammad Fahmi Johan Syah Musthafa, Rochman Hadi Salsabila, Alifa