Teaching basic data literacy through Python: Integrating basic computer science and Mathematics for lower secondary students

This conceptual paper proposes an interdisciplinary pedagogical approach to teaching basic data literacy to lower secondary students by combining elements from the Basic Computer Science (BCS) and Mathematics syllabi in Malaysia's KSSM curriculum. Motivated by the growing importance of digital skills and real-world data analysis, this conceptual paper aims to address the limited exposure students have to data handling and interpretation in current classroom practice. The proposed method uses Python to introduce concepts such as data preprocessing, data visualization, and basic statistical analysis, with example tasks and hypothetical datasets to demonstrate how the approach can be implemented. Although the approach has not yet been implemented in classroom settings, it is designed to align with syllabus standards and promote cross-curricular connections. No student feedback or empirical results are reported in this paper. Instead, it presents a pedagogical approach that makes data literacy accessible, engaging, and practically relevant for young learners.

Authors

Institutions

Publication Details

Journal
Data Analytics and Applied Mathematics (DAAM)
Published
2026-03-31
DOI
https://doi.org/10.15282/daam.v7i1.13687
Primary Topic
Statistics Education and Methodologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Teaching basic data literacy through Python: Integrating basic computer science and Mathematics for lower secondary students

Ming Hui Lim
Data Analytics and Applied Mathematics (DAAM)
Statistics Education and Methodologies
article

Teaching basic data literacy through Python: Integrating basic computer science and Mathematics for lower secondary students

Ming Hui Lim
article en

Abstract

This conceptual paper proposes an interdisciplinary pedagogical approach to teaching basic data literacy to lower secondary students by combining elements from the Basic Computer Science (BCS) and Mathematics syllabi in Malaysia's KSSM curriculum. Motivated by the growing importance of digital skills and real-world data analysis, this conceptual paper aims to address the limited exposure students have to data handling and interpretation in current classroom practice. The proposed method uses Python to introduce concepts such as data preprocessing, data visualization, and basic statistical analysis, with example tasks and hypothetical datasets to demonstrate how the approach can be implemented. Although the approach has not yet been implemented in classroom settings, it is designed to align with syllabus standards and promote cross-curricular connections. No student feedback or empirical results are reported in this paper. Instead, it presents a pedagogical approach that makes data literacy accessible, engaging, and practically relevant for young learners.

Data Analytics and Applied Mathematics (DAAM)
Universiti Sains Malaysia (MY)
Universiti Sains Malaysia
Quality Education
Openalex Percentile: Top 31%
Statistics Education and Methodologies
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.