Developing Computational Methods to Measure and Track Learners' Spatial Reasoning in an Open-Ended Simulation

Autor/inn/en	Mallavarapu, Aditi; Lyons, Leilah; Shelley, Tia; Minor, Emily; Slattery, Brian; Zellner, Moria
Titel	Developing Computational Methods to Measure and Track Learners' Spatial Reasoning in an Open-Ended Simulation
Quelle	In: Journal of Educational Data Mining, 7 (2015) 2, S.49-82 (34 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2157-2100
Schlagwörter	Spatial Ability; Urban Areas; Neighborhoods; Conservation (Environment); Data Analysis; Environmental Education; Teaching Methods; Natural Disasters; Computer Assisted Instruction; Computer Simulation; Feedback (Response); Formative Evaluation; Problem Based Learning; High School Students; Undergraduate Students; Regression (Statistics); Instructional Effectiveness; Statistical Analysis; Monte Carlo Methods; Multivariate Analysis + Suchen Sie Ihr Suchwort? Räumliches Vorstellungsvermögen; Urban area; Stadtregion; Neighbourhoods; Nachbarschaft; Conservation; Environment; Konservierung; Bewahung; Umwelt; Auswertung; Umweltbildung; Umwelterziehung; Umweltpädagogik; Teaching method; Lehrmethode; Unterrichtsmethode; Natural disaster; Naturkatastrophe; Computer based training; Computerunterstützter Unterricht; Computergrafik; Computersimulation; Problem-based learning; Problemorientiertes Lernen; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Regression; Regressionsanalyse; Unterrichtserfolg; Statistische Analyse; Monte-Carlo-Methode; Multivariate Analyse
Abstract	Interactive learning environments can provide learners with opportunities to explore rich, real-world problem spaces, but the nature of these problem spaces can make assessing learner progress difficult. Such assessment can be useful for providing formative and summative feedback to the learners, to educators, and to the designers of the environments. This work adds to a growing body of research that is applying EDM techniques to more open-ended problem spaces. The open-ended problem space under study here was an environmental science simulation. Learners were confronted with the real-world challenge of effectively placing green infrastructure in an urban neighborhood to reduce surface flooding. Learners could try out different 2D spatial arrangements of green infrastructure and use the simulation to test each solution's impact on flooding. The learners' solutions and the solutions' performances were logged during a controlled experiment with different user interface designs for the simulation. As with many open-problem spaces, analyzing this data was difficult due to the large state space, many good solutions, and many alternate paths to those good solutions. This work proposes a procedure for reducing the state space of solutions defined by 2D spatial patterns while maintaining their critical spatial properties. Spatial reasoning problems are a problem class not extensively examined by EDM, so this work sets the stage for further research in this area. This work also details a procedure for discovering effective 2D spatial strategies and solution paths, demonstrates how this information can be used to give formative feedback to the designers of the interactive learning environment, and speculates about how it could be used to provide formative feedback to learners. (As Provided).
Anmerkungen	International Working Group on Educational Data Mining. e-mail: jedm.editor@gmail.com; Web site: http://www.educationaldatamining.org/JEDM/index.php/JEDM/index
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01