The Construction of Causal Schemes: Learning Mechanisms at the Knowledge Level

Abstract

This work uses microgenetic study of classroom learning to illuminate (1) the role of preinstructional student knowledge in the construction of normative scientific knowledge, and (2) the learning mechanisms that drive change. Three enactments of an instructional sequence designed to lead to a scientific understanding of thermal equilibration are used as data sources. Only data from a scaffolded student inquiry preceding introduction of a normative model were used. Hence, the study involves nearly autonomous student learning. In two classes, students developed stable and socially shared explanations ("causal schemes") for understanding thermal equilibration. One case resulted in a near-normative understanding, while the other resulted in a non-normative "alternative conception." The near-normative case seems to be a particularly clear example wherein the constructed causal scheme is a composition of previously documented na€ ıve conceptions. Detailed prior description of these naive elements allows a much better than usual view of the corresponding details of change during construction of the new scheme. A list of candidate mechanisms that can account for observed change is presented. The non-normative construction seems also to be a composition, albeit of a different structural form, using a different (although similar) set of naïve elements. This article provides one of very few high-resolution process analyses showing the productive use of na€ ıve knowledge in learning.

Exploring students’ epistemological knowledge of models and modelling in science: results from a teaching/learning experience on climate change

“…Carey & Smith, 1993;Pluta, Chinn, & Duncan, 2011) and fostering productive epistemologies of science (Gilbert S.W., 1991;Schwarz & White, 2005). Further studies highlight the benefits of modelling for developing fundamental life skills, such as awareness of the semantic relation between theory and phenomena (Gilbert J.K., 2004;Greca & Moreira, 2000), metaphorical competencies which underlie every language (Lakoff & Johnson, 1980) and analogical causal reasoning (diSessa, 2014;Harrison & Treagust, 2000). Additionally, many model-centred tools and educational software (e.g.…”

“…More specifically, research has revealed the following issues (Besson, De Ambrosis, & Mascheretti, 2010;: (i) infrared emission of bodies is usually not taken into account as an energy-loss mechanism, (ii) emittance, when considered, is often confused with reflectance, (iii) students tend to give absolute meaning to properties like transparency, absorptivity and emissivity, rather than seeing them as interactive properties, (iv) radiation is often confused with heat, and (v) students tend to apply a temporal or linear causal reasoning (Rozier & Viennot, 1991) for explaining processes instead of causal schemes based on balancing and equilibration (diSessa, 2014). These tendencies lead students to interpret the greenhouse effect with the naïf metaphor of "trapping" (Besson et al, 2010) which is not only misleading but also ineffective for grasping concepts such as feedback.…”

Relationship of the cognitive functions of prospective science teachers and their knowledge, knowledge levels, success and success levels

“…Low success might be a result low student interest. Motivation can be used in knowledge level mechanisms (Di Sessa, 2014). The low level of knowledge might be a result of low teacher motivation.…”

Introducción a un método para la conducción y análisis de diálogos didácticos basado en la evaluación de modelos mentales

“…A esta estructura cognitiva Pask la llama Conversación (la mayúscula pretende atribuir al término este sentido técnico). El concepto Conversación (el sistema cognitivo aprende «diciéndose» a sí mismo) puede proporcionar fundamento al autoaprendizaje, un fenómeno bien conocido en la literatura didáctica (Chi, 2000;Wong, Lawson y Keeves, 2002;Gutiérrez, 2003;Craig et al, 2006;Ainsworth y Burcham, 2007;Van den Boom et al, 2007;Fonseca y Chi, 2011;diSessa, 2014). Hay que advertir que, así como el concepto de autoaprendizaje («self-learning») se define nítidamente en la teoría de Pask, en su aproximación didáctica este término puede referirse a diferentes tipos de aprendizaje.…”