Developing geographic computer modeling competencies in higher education

Dados Bibliográficos

ID11954822
AutoresRieke Ammoneit (0000-0003-1016-8336, Department of Geography Education, Philipps-University Marburg, Marburg, Germany, autor correspondente), Christoph Reudenbach (0000-0002-7476-3663, Department of Spatial Modeling and Remote Sensing, Philipps-University Marburg, Marburg, Germany), Carina Peter (0000-0002-2293-0220, Department of Geography Education, Philipps-University Marburg, Marburg, Germany)
Ano2023
Volume48
Fascículo3
Páginas345-367
Data de publicação2023-08-30
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoJournal of Geography in Higher Education (JOURNAL)
Identificadores do periódicoISSN: 0309-8265 • E-ISSN: 1466-1845
EditoraTaylor & Francis (PUBLISHER • GB)
DOI10.1080/03098265.2023.2250991
OpenAlexW4386275068
IdiomaEN
Citações recebidas2
Referências citadas58

Modeling is a key scientific practice and is usually computer-implemented, but it is challenging to teach because it seems high on presuppositions, for example, coding. This design-based research study presents a geography course offered during the 2019/20 winter semester in computer modeling, with no prior coding knowledge. It was implemented in two elective classes: one in the Bachelor of Science program and one in the teacher program. Interviews were conducted to monitor the students' development, and the final reports showed their competencies at the end of the course. Since there were no noticeable differences between the Bachelor of Science students and the teacher trainees in terms of competence acquisition, four learning types could be described based on analysis of the interviews and final reports, which are important for the planning and adaptation of the course concepts. In summary, our results show four key findings: (1) mere reproduction of learning content is of no value for the development of geographic modeling skills; (2) the ability to access conceptual thinking patterns is crucial; (3) process-level understanding is a fundamental prerequisite for advanced geographic modeling understanding; and (4) poor programming skills hinder but do not prevent at least basic modeling understanding.KEYWORDS: Scientific thinkingNetLogoteacher educationcomputational thinkingmodeling competenciesdigital modeling AcknowledgementsThe author would like to thank the participating students as well as the editors and anonymous reviewers.Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementhttps://doi.org/10.17192/fdr/63 & https://github.com/ammrie/ModelingCompetenceAdditional informationFundingThis research received no external funding

Bachelor · Coding (social sciences · Competence (human resources · Geography · Mathematics education · Pedagogy · Sociology · Computer Science · Educational Games and Gamification · Geography Education and Pedagogy · Psychology · Science Education and Pedagogy