Automated systems for assessing geography knowledge and their impact on students' cognitive development
DOI:
https://doi.org/10.31489/3106-9649/2026-3-4.GSD/40-48Keywords:
automated assessment, geography, GIS , spatial thinking, cognitive development, Bloom's taxonomy, intelligent learning systems, self-assessment, feedbackAbstract
The review systematizes empirical data on automated systems for assessing knowledge of geography and their impact on the cognitive development of students. The sample includes 14 studies from 2021-2025 with a combined coverage of more than 15,000 participants. The Geoportti Self-Assessment Tool (Fagerholm et al., 2023) was tested in five geoinformatics courses in Finland (n=11-73/course, 2019-2021) and showed a steady increase in self-assessed competence with a different growth profile depending on the type of course. The Spatial Thinking Ability Test (STAT), applied to 83 students in Portugal (Duarte et al., 2022), recorded a significant increase in spatial thinking after GIS exposure. The Intelligent Learning System (ITS) for 300 schoolchildren in Jordan (Khasawneh, 2024) provided an increase in critical thinking by 5.4 points (p<0.001) in 8 weeks. The automatic classification of Bloom taxonomy test questions achieves 94% accuracy when using SVM with data augmentation (Kumar et al., 2025). A comparison of data from Finland, Portugal, Jordan, Indonesia, and Australia shows that the effectiveness of systems depends on the type of cognitive construct: procedural knowledge is more reliably automated than evaluation and creation.
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