The Effect of a Pembelajaran Mendalam (Mindful, Meaningful, and Joyful Learning) Coding and Artificial Intelligence Module on Elementary School Students' Computational Thinking

Starting in the 2025/2026 academic year, Coding and Artificial Intelligence (Koding dan Kecerdasan Artifisial, KKA) was introduced as an elective subject from grade five in Indonesian elementary schools. This quasi-experimental study compared a KKA module based on Pembelajaran Mendalam (mindful, meaningful, and joyful learning)—a pedagogical approach distinct from machine-learning-based deep learning—with application-only instruction. Sixty-five fifth-grade students from two schools in South Tangerang participated (experimental n = 33; control n = 32). Across six 70-minute meetings, the module integrated unplugged activities, Scratch, a simple image-classification tool, and reflection. Computational thinking tests, a learning-experience questionnaire, and observations supplied the data. Posttest mean scores were 76.88 (experimental) and 65.40 (control), t(63) = 4.73, p < .001, d = 1.17; corresponding N-gains were 0.58 and 0.37. Descriptively, the largest indicator gain in the experimental group was decomposition (0.62), while the smallest was abstraction (0.47). In this two-school sample, the module was associated with greater computational-thinking gains than application-only instruction; the design does not establish which component produced the difference.

Authors

Publication Details

Journal
Jurnal Inovasi dan Riset Pendidikan Dasar
Published
2026-11-01
DOI
https://doi.org/10.64421/jirpd.v1i3.130
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Effect of a Pembelajaran Mendalam (Mindful, Meaningful, and Joyful Learning) Coding and Artificial Intelligence Module on Elementary School Students' Computational Thinking

Rina Kartika Sari, Dimas Aditya Pratama, Andayani Andayani, Suryo Prabowo
Jurnal Inovasi dan Riset Pendidikan Dasar
Teaching and Learning Programming
article

The Effect of a Pembelajaran Mendalam (Mindful, Meaningful, and Joyful Learning) Coding and Artificial Intelligence Module on Elementary School Students' Computational Thinking

Rina Kartika Sari, Dimas Aditya Pratama, Andayani Andayani, Suryo Prabowo
article en

Abstract

Starting in the 2025/2026 academic year, Coding and Artificial Intelligence (Koding dan Kecerdasan Artifisial, KKA) was introduced as an elective subject from grade five in Indonesian elementary schools. This quasi-experimental study compared a KKA module based on Pembelajaran Mendalam (mindful, meaningful, and joyful learning)—a pedagogical approach distinct from machine-learning-based deep learning—with application-only instruction. Sixty-five fifth-grade students from two schools in South Tangerang participated (experimental n = 33; control n = 32). Across six 70-minute meetings, the module integrated unplugged activities, Scratch, a simple image-classification tool, and reflection. Computational thinking tests, a learning-experience questionnaire, and observations supplied the data. Posttest mean scores were 76.88 (experimental) and 65.40 (control), t(63) = 4.73, p < .001, d = 1.17; corresponding N-gains were 0.58 and 0.37. Descriptively, the largest indicator gain in the experimental group was decomposition (0.62), while the smallest was abstraction (0.47). In this two-school sample, the module was associated with greater computational-thinking gains than application-only instruction; the design does not establish which component produced the difference.

Jurnal Inovasi dan Riset Pendidikan Dasar
Quality education
Openalex Percentile: Top 7%
Teaching and Learning Programming
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon