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All Journal Edukasia: Jurnal Pendidikan dan Pembelajaran International Journal of Research and Community Empowerment International Journal of Advances in Artificial Intelligence and Machine Learning
Favian Avila Syahmi
Universitas Negeri Surabaya
Chemistry Computer Science & IT Education Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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Pengaruh Project Based Learning terhadap Kreativitas dan Hasil Belajar Pada Mata Pelajaran Animasi 2D dan 3D di SMK Unitomo Favian Avila Syahmi; Mustaji Mustaji; Irena Yolanita Maureen
EDUKASIA: Jurnal Pendidikan dan Pembelajaran Vol. 5 No. 1 (2024): Edukasia: Jurnal Pendidikan dan Pembelajaran
Publisher : LP. Ma'arif Janggan Magetan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62775/edukasia.v5i1.732

Abstract

This study aims to determine the influence of the Project Based Learning learning model on the creativity and learning outcomes of grade XI students at SMK UNITOMO Surabaya, focusing on 2D and 3D Animation subjects and Basic Principles of Making 2D Animation. This research method uses quantitative research methods with a Quasi Experiment design. The sample of this study consisted of 22 grade A students as an experimental class and 22 class B as a control class at SMK UNITOMO, using performance tests and questionnaires as research instruments. The test results showed that the value of the t test results on the posttest value of student creativity was known to be the mean value of the control group 72.31 and the mean value of the experimental group was higher with a score of 84.90. And the results of the t test on the posttest value of student learning outcomes are known to be the mean value of the control group 80.59 and the mean value of the experimental group is higher with a score of 83.77. Thus, it can be concluded that there is a positive influence of the use of the Project Based Learning model on the creativity and learning outcomes of grade XI students at SMK UNITOMO Surabaya in 2D and 3D animation subjects material Basic Principles of Animation Making.
Empowering the Practice-Based Mentoring in Microteaching on Pre-Service ICT Teachers: High and Low Self-Efficacy Analysis Husni Mubarok; Yossiri Yossatorn; Hirnanda Dimas Pradana; Syaiputra Wahyuda Meisa Diningrat; Arqoma Nurveda Carreza; Favian Avila Syahmi
International Journal of Research and Community Empowerment Vol. 4 No. 1 (2026): February 2026
Publisher : Mitra Edukasi dan Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58706/ijorce.v4n1.p14-21

Abstract

Practice-based microteaching is now an important method in pre-service teacher education, particularly in ICT, as it creates a forum to practice teaching skills in a structured setting. However, the success of this depends greatly on the quality of guidance, which has the capacity to deliver timely and critical feedback. Self-efficacy, being the belief that an individual is capable of completing tasks, has been a significant predictor of learning achievement and motivation. The present research aims to examine the pre-service ICT teachers' learning achievement and the learning motivation of high and low self-efficacy individuals within a practice-based microteaching environment supported by mentoring. In experimental design, the subjects (N = 82) were divided into high and low self-efficacy according to a standardized self-efficacy scale. The data analysis in this study employed the t-test and Analysis of Covariance (ANCOVA). The findings of this study indicated there was no difference in learning achievement between the two groups on practice-based mentoring in microteaching for pre-service ICT teachers. Moreover, in intrinsic motivation, it was found that high self-efficacy practice-based mentoring microteaching students have significantly higher intrinsic motivation than low self-efficacy students. In the present study, however, low self-efficacy students for practice-based mentoring microteaching show significantly greater extrinsic motivation than high self-efficacy students. This research offers additional reference to scholars, teachers, and policymakers in investigating the role of self-efficacy in learning activity, learners' accomplishment in learning, and to supporting SDGs 4 and 5 in promoting the quality of education as well as gender equality.
AI-Driven Adaptive Online Digital Modules for Communication Courses Using Learning Analytics and Natural Language Processing Utari Dewi; Andi Kristanto; Atan Pramana; Husni Mubarok; Rizki Fitri Rahima Uulaa; Arqoma Nurveda Carreza; Favian Avila Syahmi; Makibane Daniel Ntlhane
International Journal of Advances in Artificial Intelligence and Machine Learning Vol. 3 No. 2 (2026): International Journal of Advances in Artificial Intelligence and Machine Learni
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijaaiml.v3i2.689

Abstract

Background: The rapid growth of online learning in higher education requires innovative solutions that support independent, scalable, and standardized learning experiences. Artificial Intelligence (AI), particularly Learning Analytics (LA) and Natural Language Processing (NLP), offers opportunities to enhance digital learning through adaptive content delivery, personalized learning pathways, and automated formative feedback.Aims: This study aimed to develop and evaluate an AI-driven adaptive online digital module for Communication courses that supports personalized learning and standardized instruction across higher education institutions using Gemini.Methods: This study employed the ADDIE development model, comprising Analysis, Design, Development, Implementation, and Evaluation. Learning Analytics was used to monitor student engagement and learning progress, while NLP analyzed students' written responses to generate automated formative feedback. The module was validated by instructional design, subject matter, and media experts, followed by individual and small-group trials. Its effectiveness was evaluated using normalized gain (N-Gain) analysis.Results: Expert validation, individual trials, and small-group evaluations indicated that the developed module achieved a "very good" level of feasibility. The effectiveness evaluation produced a high N-Gain score (0.7), indicating a substantial improvement in student learning outcomes. The integration of Learning Analytics and NLP supported adaptive learning, timely feedback, and increased student engagement.Conclusion: The AI-driven adaptive digital module is feasible and effective for supporting online learning in Communication courses. Integrating Learning Analytics and Natural Language Processing enables personalized instruction and data-informed learning support, making the module a promising approach for improving learning quality in higher education.
Co-Authors Andi Kristanto Arqoma Nurveda Carreza Atan Pramana Husni Mubarok Irena Yolanita Maureen Makibane Daniel Ntlhane Mustaji Mustaji Rizki Fitri Rahima Uulaa Syaiputra Wahyuda Meisa Diningrat Utari Dewi Yossiri Yossatorn