Identifying implicit assumptions to support learning

By Heather King - April 2013


Talanquer, Vicente (2009). On Cognitive Constraints and Learning Progressions: The case of "structure of matter". International Journal of Science Education, 31(15), 2123–2136.

This paper provides an interesting insight into how educators can support learners in coming to understand the nature of matter. Whilst the specific focus is on students’ implicit assumptions and reasoning strategies in a particular domain, the broader discussion exploring the differences between novice and expert thinking is relevant to all educators seeking to support learners to engage with new content.

The paper begins with a summary of current thinking about how the mind operates. Some researchers have argued that learners possess ‘explanatory frameworks’ that organise their thinking (see Vosniadou, 1994). Others have proposed that learners possess more fragmented knowledge systems based on intuitive knowledge and some ideas about phenomena—essentially ‘knowledge in pieces’ (cf. diSessa, 1993). For proponents of ‘explanatory frameworks’, learning occurs as individuals revise and replace their naïve mental models, whilst for advocates of the ‘knowledge in pieces’ tradition, learning involves the reorganisation and integration of available knowledge. As the author of this paper notes, either way, it is important for educators to understand and acknowledge learners’ background assumptions or implicit presuppositions. Such assumptions have been termed ‘cognitive constraints’: they constrain the learner, but also guide the cognitive process. Identifying the cognitive constraints in any one domain makes educators better able to help learners achieve greater expertise in that domain. Thus, the aim of this study was to identify the constraints shaping students’ thinking and reasoning about the structure of matter.

The article’s detailed review of the literature compiles a comprehensive inventory of studies on students’ thinking, alternative conceptions and models regarding the structure of matter. This review is then used to identify generalisations about areas or dimensions along which students’ ideas evolve with learning and development.

Such generalisations are arguably useful to educators who seek to select appropriate analogies and explanations, learning experiences and assessment tools. Indeed, the author argues that ‘focusing on the underlying implicit assumptions that constrain student thinking in a given domain is a more fruitful educational approach than trying to address the myriad of specific alternative ideas and mental models held by learners during a specific task’ (p. 2133).

For ISEs, this paper offers support specifically on teaching material science. More generally, it points to the value of identifying typical assumptions of novices and experts in any particular domain in order to create appropriate teaching experiences that respond to learners’ progression along a continuum of implicit notions or cognitive constraints.


diSessa, A. A. (1993). Towards an epistemology of physics. Cognition and Instruction, 10, 165–255. Vosniadou, S. (1994). Capturing and modeling the process of conceptual change. Learning and Instruction, 4, 45–69.