Development of software and scientific–methodological tools for researching environmental awareness among young people: architecture, questionnaire and data analysis algorithm in Python
DOI:
https://doi.org/10.51707/2618-0529-2026-36-06Keywords:
environmental awareness, digital research tools, psychometrics, Python, research reproducibility, young people.Abstract
This article presents an original scientific, methodological and curricular framework designed for a comprehensive study of environmental awareness among young people in the context of contemporary social transformations and Ukraine’s post-war reconstruction. The relevance of the study stems from the need to create a coherent, theoretically sound, psychometrically robust and reproducible set of tools capable of ensuring the unity of the conceptual model, empirical data collection procedures and algorithms for their statistical processing. The aim of this work is to develop a scientific and methodological framework for researching young people’s environmental awareness, integrating a system of assessment criteria, the structure of the working questionnaire, a variable code book, data quality assurance procedures and a software algorithm for analysing results in the Python environment. The methodological basis of the study comprises contemporary concepts of environmental worldview, environmentally responsible behaviour, the interaction between humans and nature, individual and collective self-efficacy, constructive hope, as well as international recommendations regarding the development, psychometric validation and standardisation of questionnaire instruments. The study resulted in the creation of a comprehensive set of tools covering four interrelated criteria of environmental consciousness: cognitive, value emotional, reflective regulatory and behavioural-projective. A questionnaire structure comprising 12 thematic sections and 65 content items has been proposed; a code book for 77 variables, a scaling system, data quality control rules, procedures for expert evaluation, cognitive and pilot testing, as well as a thirteen-step algorithm for statistical analysis in Python. The scientific novelty of this work lies in the creation of an integrated methodological platform that combines conceptual modelling, standardised research tools and software for data analysis, ensuring a high level of reproducibility, reliability and practical applicability of the results for empirical research in the fields of environmental education, psychology, sociology, youth policy and sustainable development.
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