Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal ELINVO (Electronics, Informatics, and Vocational Education)
Admaja Dwi Herlambang
(Scopus ID: 57203202096) Universitas Brawijaya, Indonesia
Computer Science & IT Education Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Optimizing Procedural Knowledge Transfer in AI Chatbot-Enhanced Flipped Learning Models on Computer Programming Course Admaja Dwi Herlambang; Aditya Rachmadi
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 11 No. 1 (2026): May 2026
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v11i1.96278

Abstract

This research investigates whether an AI chatbot can further enhance the effectiveness of the flipped classroom model by facilitating personalized learning in computer programming. A quasi-experimental pretest-posttest with a matched samples control group design was used with a population of 60 in a vocational high school in Indonesia. The experimental treatment group of 30 students received flipped instruction supported by AI chatbot; the 30-student strong control group had traditional flipped instruction. Cognitive test data, psychomotor tests, and self-reported learning questionnaires measured data. Results show that the AI-enhanced flipped classroom outperformed the traditional flipped classroom to a great degree in both personalized learning (adjusted mean difference = 12.30, p < 0.001, partial η² = .335) and procedural knowledge acquisition (mean difference = 9.70, p < 0.001). The effect sizes were large for individualized instruction (Cohen's d = 0.89, 95% CI: 0.75 to 1.03) and medium for procedural knowledge (Cohen's d = 0.62, 95% CI: 0.49 to 0.75). Of particular note was that the experimental group not only did better on coding tasks (d = 1.18), but even more so on debugging efficiency (d = 1.48).
Co-Authors Aditya Rachmadi