How can initially reluctant beginners become engaged, self-motivated users of QGIS? This presentation introduces a successful, research-informed workflow that uses learner-generated, field-based data as an accessible entry point into GIS thinking.

This QGIS case study presents an effective educational framework to introduce new digital tools to learners who may not be predisposed toward their adoption and to student groups with diverse technical and disciplinary backgrounds. Many students are more familiar with proprietary ecosystems and with the consumption, rather than creation, of data. Under these conditions, conventional tutorials using scaffolded concepts and preconfigured datasets are less engaging and pedagogically ineffective.

To address these challenges, we use a “Findings from the Field” approach that inverts the traditional tutorial model. Rather than beginning with abstract concepts and standardized datasets, students first identify a topic of personal or collective interest and gather geotagged data using mobile photography. Working individually or collaboratively, they document phenomena encountered outside the classroom that interest them, such as public infrastructure, creative works, or commercial artifacts. Students are then introduced to core QGIS functions as they import their geotagged photographs to create point layers and associated attribute tables; they then use the Map Tips feature to display the images interactively. Because the dataset originates from student fieldwork, this process supports deeper reflection on connecting their interests to geocoding practices, spatial representation, analysis, and workflows.

This approach’s relative simplicity makes it an effective entry point for both instructors and novice learners, as well as a foundation for further exploration, while simultaneously reinforcing critical, place-based research skills. Beyond the case study, this presentation contributes to discussions on inclusive and interdisciplinary GIS pedagogy, particularly in contexts with learners initially unaware of or disinterested in geospatial analysis and representation. The workflow we present is grounded in classic learning theories that address motivation and skill acquisition: Self-Determination Theory explains how student-generated data fosters intrinsic motivation through autonomy and relevance (Ryan & Deci, 2000); Cognitive Load Theory informs how simplifying initial technical tasks supports learning (Sweller, Ayres, & Kalyuga, 2011); and the Zone of Proximal Development concept (Vygotsky, 1978) guides the structured introduction of QGIS tools for deeper exploration. At a broader level, the approach aligns with experiential and constructionist learning theories, as students build knowledge through field-based inquiry and the creation of meaningful artifacts (Healey & Jenkins, 2000).

References/resources
Healey, M., & Jenkins, A. (2000). Kolb’s Experiential Learning Theory and Its Application in Geography in Higher Education. Journal of Geography, 99(5), 185–195. https://doi.org/10.1080/00221340008978967
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67. https://doi.org/10.1006/ceps.1999.1020
Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. Springer.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.