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Jurnal Pendidikan Progresif
Published by Universitas Lampung
ISSN : 20879849     EISSN : 25501313     DOI : https://doi.org/10.23960/jpp
Core Subject : Education,
Education
urnal Pendidikan Progresif is an academic journal that published all the studies in the areas of education, learning, teaching, curriculum development, learning environments, teacher education, educational technology, educational developments from various types of research such as surveys, research & development, experimental research, classroom action research, etc. Jurnal Pendidikan Progresif covers all the educational research at the level of primary, secondary, and higher education. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on Educational advancements and establishing new collaborations in these areas. Original research papers, state-of-the-art reviews are invited for publication in all areas of Education. Topics of Interest include, but are not limited to, the following Disaster literacy and Risk Management Education Ethnopedagogy-based STEM Education Integrating technology into the curriculum: Challenges & Strategies Collaborative & Interactive Learning Tools for 21st Century learning Learning Analysis Education Management Systems Education Policy and Leadership Business Education Virtual and remote laboratories Pedagogy Enhancement with E-Learning Course Management Systems Teacher Evaluation Curriculum, Research, and Development Web-based tools for education Games and simulations in Education Learning / Teaching Methodologies and Assessment Counselor Education Student Selection Criteria in Interdisciplinary Studies Global Issues in Education and Research Technology Support for Pervasive Learning Artificial Intelligence, Robotics and Human-computer Interaction in Education Mobile/ubiquitous computing in education Web 2.0, Social Networking, Blogs and Wikis Multimedia in Education Educating the educators Professional Development for teachers in ICT
Arjuna Subject : Ilmu Sosial - Pendidikan
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Search results for "fostering algorithmic thinking through ai-supported stem activities" : 1 Documents clear
Fostering Algorithmic Thinking through AI-Supported STEM Activities: Experimental Study Using Cacao Disease Classification Firma Nur Muttakin; Dafik Dafik; Zainur Rasyid Ridlo; Udaya Sri Kakarla
Jurnal Pendidikan Progresif Vol 16, No 3 (2026): Jurnal Pendidikan Progresif
Publisher : FKIP Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpp.v16i3.pp1679-1703

Abstract

This study investigated the effect of AI-integrated STEM activities using cocoa leaf disease classification materials on undergraduate students’ algorithmic thinking skills. This quasi-experimental study used a non-randomized pretest–posttest comparison design and involved 66 undergraduate students. Data were collected using an algorithmic thinking test and an instrument validation sheet. The instrument demonstrated acceptable content validity, with a mean validation score of 4.57, a feasibility percentage of 91.38%, Aiken’s V coefficient of 0.892, and very high internal consistency (Experimental α = 0.942 and Control α = 0.938 ). The data were analyzed using assumption testing, Welch’s t-tests, gain-score analysis, and ANCOVA. The experimental group achieved a substantially larger mean gain than the control group (d = 1.43) and a higher average normalized gain (〈g〉 = 0.87 versus 0.52), and outperformed the control group on all seven algorithmic thinking indicators (d = 0.72 to 1.60). The ANCOVA indicated a significant group difference in posttest performance, F(1, 63) = 29.302, p < .001, with a higher adjusted mean in the experimental group (M = 76.8) than in the control group (M = 66.5). However, the pretest covariate explained virtually none of the posttest variance, so the covariance adjustment was negligible, and the two intact classes differed significantly at baseline. Because posttest variance was also heterogeneous, interpret the findings with appropriate caution and understand them as associational rather than causal. These results suggest that AI-integrated STEM activities based on cocoa leaf disease classification may support the development of undergraduate students’ algorithmic thinking through structured, iterative, and evidence-based learning processes. Keywords: algorithmic thinking, STEM activities, cacao diseases, classification, undergraduate students.

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