Research Article
Needs Assessment for Developing Literacy-Based Teaching Materials with Quantum Teaching in Food and Nutrition Data Analysis
@INPROCEEDINGS{10.4108/eai.16-9-2025.2361087, author={Nila Reswari Haryana and Erni Rukmana and Edy Marjuang Purba and M.Edwin Fransiari and Diah Retno Wahyuningrum}, title={Needs Assessment for Developing Literacy-Based Teaching Materials with Quantum Teaching in Food and Nutrition Data Analysis}, proceedings={Proceedings of the 7th International Conference on Innovation in Education, Science, and Culture, ICIESC 2025, 16 September 2025, Medan, Indonesia}, publisher={EAI}, proceedings_a={ICIESC}, year={2026}, month={3}, keywords={literacy nutrition education needs analysis teaching materials quantum teaching}, doi={10.4108/eai.16-9-2025.2361087} }- Nila Reswari Haryana
Erni Rukmana
Edy Marjuang Purba
M.Edwin Fransiari
Diah Retno Wahyuningrum
Year: 2026
Needs Assessment for Developing Literacy-Based Teaching Materials with Quantum Teaching in Food and Nutrition Data Analysis
ICIESC
EAI
DOI: 10.4108/eai.16-9-2025.2361087
Abstract
This study assesses students' needs for developing literacy-based teaching materials using the Quantum Teaching approach in food and nutrition data analysis courses. Data were collected via a Likert-scale questionnaire (1–5) with 15 closed-ended and 2 open-ended questions, analyzed descriptively across five thematic areas. The overall mean score was 3.81. Specifically, Section A: Knowledge scored 3.8 (Agree); Section B: Skills and Tools 3.5 (Agree); Section C: Learning Methods 4.3 (Agree); Section D: Learning Challenges 3.4 (Neutral); and Section E: Expectations for Quantum Teaching 4.1 (Agree). Students identified the need for more interactive, practical, and engaging materials. Challenges included the theory–practice gap and limited study time. There was a strong desire for integrating Quantum Teaching to boost motivation and learning effectiveness. These results form a vital basis for designing innovative, student-centered materials that promote literacy, practical skills, and engagement in nutrition data analysis.
