TaskTimeTrackerA tool for temporal analysis of the problem solving process

  1. Pla-Castells, Marta 1
  2. García-Fernández, Ignacio 2
  1. 1 Departament de Didàctica de la Matemàtica. Universitat de València. España
  2. 2 Departament d'Informàtica. Universitat de València. España
Revista:
Investigación en Entornos Tecnológicos en Educación Matemática: iETEM

ISSN: 2792-9019

Año de publicación: 2020

Número: 1

Páginas: 9-15

Tipo: Artículo

DOI: 10.7203/IETEM.1.16280 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Investigación en Entornos Tecnológicos en Educación Matemática: iETEM

Resumen

The analysis of the problem solving process in mathematics can shed light on the learning process. However, the analysis of this process is a difficult task that has to face the complexity and non linearity of the process itself. In this work we present the TTT software tool aimed to facilitate the registration and graphical representation of the steps that are followed by a group of students during the resolution of a problem, together with the time extension of these steps. This tool is based upon, and extends, the representation schemes presented by Arleback(2009), and can be applied to any problem resolution process (either mathematical or not) that can be divided into phases or categories along time.

Referencias bibliográficas

  • Albarracın, L., Arleback, J., Civil, E., & Gorgorio, N. (2019). Extending modelling activity diagrams as a tool to characterise mathematical modelling processes. The Mathematics Enthusiast, 16(1), 211–230.
  • Arleback, J. B. (2009). On the use of realistic fermi problems in introducing mathematical modelling in upper secondary mathematics. The Mathematics Enthusiast, 6(3).
  • Berry, J., & Sahlberg, P. (2006). Accountability affects the use of small group learning in school mathematics. Nordic Studies in Mathematics Education, 11(1), 5–31.
  • Borromeo Ferri, R. (2006). Theoretical and empirical differentiations of phases in the modelling process. ZDM, 38(2), 86–95.
  • Brandell, J. R. (2010). Theory & practice in clinical social work. Sage.
  • Bransford, J. D., & Stein, B. S. (1984). The ideal problem solver. a guide for improving thinking, learning, and creativity. Freeman.
  • Brown, J. P. (2003). An insight into student understanding of functions in a graphing calculator environment [Master’s thesis]. Department of Education, The University of Melbourne.
  • Gillies, R. M. (2003). Structuring cooperative group work in classrooms. International Journal of Educational Research, 39(1), 35 - 49.
  • Goos, M., & Galbraith, P. (1996). Do it this way! metacognitive strategies in collaborative mathematical problem solving. Educational studies in mathematics, 30(3), 229–260.
  • Pearl, J. (1984). Heuristics: intelligent search strategies for computer problem solving. Addison-Wesley Pub. Co., Inc., Reading, MA.
  • Polya, G. (1945). How to solve it; a new aspect of mathematical method. US: Princeton University Press.
  • Puig Espinosa, L. (1996). Elementos de resoluci´on problemas. Comares.
  • Reas, C., & Fry, B. (2007). Processing: A programming handbook for visual designers and artists. MIT Press. Schoenfeld, A. H. (1985). Mathematical problem solving. Academic Press: Orlando, FL.
  • Schoenfeld, A. H. (1992). On paradigms and methods: What do you do when the ones you know don’t do what you want them to? issues in the analysis of data in the form of videotapes. Journal of the Learning Sciences, 2(2), 179-214. doi: Versi´on 0.1, August 27, 201910.1207/s15327809jls0202_3
  • Scott, N., & Stacey, K. (2000). Orientation to deep structure when trying examples: a key to successful problem solving. Hergue.
  • Vygotsky, L. S. (1980). Mind in society: The development of higher psychological processes. Harvard university press.
  • Wilson, J. W., Fernandez, M. L., & Hadaway, N. (1993). Mathematical problem solving. Research ideas for the classroom: High school mathematics, 57, 78.