The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4/W14
https://doi.org/10.5194/isprs-archives-XLII-4-W14-85-2019
https://doi.org/10.5194/isprs-archives-XLII-4-W14-85-2019
23 Aug 2019
 | 23 Aug 2019

EVALUATING STUDENT MOTIVATION AND PRODUCTIVITY DURING MAPATHONS

C. Green, V. Rautenbach, and S. Coetzee

Keywords: OpenStreetMap, OSM, mapathons, volunteer motivation, volunteered geographic information, VGI

Abstract. During mapathons, volunteers from various backgrounds get together to map a specific area using satellite imagery or aerial photographs. The expertise and motivation of these volunteers generally differ. In this paper, we present our results from an evaluation of university students’ motivation for participating in mapathons and their productivity (i.e. how much data they contributed). To achieve our aim, we hosted four mapathons for final year university students where the participants were asked to complete a short questionnaire to determine their motivations and personal opinions of the mapathon. Afterwards, the productivity for two mapathons was evaluated. Participants indicated that they felt a sense of humanitarianism by contributing to communities in need. Additionally, the social aspect came through with a large percentage of the participants indicating that mapathons are fun and that they learned something new, for example, by improving their digitizing skills or that humanitarian organizations need help. Participants also indicated that the tools (i.e. OSM and iD editor) were easy to use, but that the imagery is sometimes not good enough due to cloud coverage. The general productivity for two mapathons was evaluated and we found that with more experience the participants were generally more productive. The results from this evaluation provided insight and knowledge that can assist mapathon organisers to create a productive environment for participants with the hopes of encouraging the participants to produce high quality data.