Probabilities and Predictions: Modeling the Development of Scientific Problem-Solving Skills

Autor/inn/en	Stevens, Ron; Johnson, David F.; Soller, Amy
Titel	Probabilities and Predictions: Modeling the Development of Scientific Problem-Solving Skills
Quelle	In: Cell Biology Education, 4 (2005) 1, S.42-57 (16 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1536-7509
DOI	10.1187/cbe.04-03-0036
Schlagwörter	Majors (Students); Undergraduate Students; Problem Solving; Genetics; Problem Sets; Molecular Biology; Probability; Gender Differences; Skill Development; Internet; Computer Simulation; Science Education; Markov Processes; Models; Teaching Methods + Suchen Sie Ihr Suchwort? Problemlösen; Humangenetik; Problemstellung; Molekularbiologie; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Geschlechterkonflikt; Kompetenzentwicklung; Qualifikationsentwicklung; Computergrafik; Computersimulation; Naturwissenschaftliche Bildung; Markowscher Prozess; Analogiemodell; Teaching method; Lehrmethode; Unterrichtsmethode
Abstract	The IMMEX (Interactive Multi-Media Exercises) Web-based problem set platform enables the online delivery of complex, multimedia simulations, the rapid collection of student performance data, and has already been used in several genetic simulations. The next step is the use of these data to understand and improve student learning in a formative manner. This article describes the development of probabilistic models of undergraduate student problem solving in molecular genetics that detailed the spectrum of strategies students used when problem solving, and how the strategic approaches evolved with experience. The actions of 776 university sophomore biology majors from three molecular biology lecture courses were recorded and analyzed. Each of six simulations were first grouped by artificial neural network clustering to provide individual performance measures, and then sequences of these performances were probabilistically modeled by hidden Markov modeling to provide measures of progress. The models showed that students with different initial problem-solving abilities choose different strategies. Initial and final strategies varied across different sections of the same course and were not strongly correlated with other achievement measures. In contrast to previous studies, we observed no significant gender differences. We suggest that instructor interventions based on early student performances with these simulations may assist students to recognize effective and efficient problem-solving strategies and enhance learning. (Contains 6 tables and 8 figures.) (As Provided).
Anmerkungen	American Society for Cell Biology. 8120 Woodmont Avenue Suite 750, Bethesda, MD 20814-2762. Tel: 301-347-9300; Fax: 301-347-9310; E-mail: ascbinfo@ascb.org; Website: http://www.ascb.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10