Modeling competence in science education

Abstract

Research on the understanding of the nature of models and modeling processes in science education have received a lot of attention in science education. In this article, we make five claims about the research on modeling competence in science education. The five claims are (1) the development of modeling competence in practice is essential to scientific literacy for twenty-first century citizens, (2) further research is needed to build a holistic and theoretical understanding of models and modeling knowledge (MMingK), (3) providing a modeling-based scaffolding framework for meaningful and active authentic learning is to enhance student's engagement of scientific practice, (4) appropriate formative assessment instruments and evaluation rubrics to assess students' modeling processes and products within the context of modeling practice should be developed, and (5) research on learning progression in modeling competence needs to be intertwined with MMingK and modeling practice. Implications for student learning and teacher professional development will be drawn from existing literature.

Learning through modelling in science: Reflections by pre-service teachers

“…They claimed, in line with previous studies (Aktan, 2016;Torres & Vasconcelos, 2017;Yenilmez Turkoglu & Oztekin, 2016), that the use of models in school would make science more exciting and enjoyable and would involve pupils directly in the teaching and increase their urge to further explore. This experience supports Oh and Oh's (2011) suggestions that cyclic modelling can improve teaching practices and that modelling-based scaffolding frameworks can enhance engagement in scientific practice (Chiu & Lin, 2019).…”

“…Being exposed to different modelling-based activities made the PSTs consider how they might include such activities in a classroom with pupils, which is important for all science teachers (Oh & Oh, 2011). As developing modelling competence is essential to scientific literacy for 21st-century citizens (Chiu & Lin, 2019) and is part of modern science education (NDET, 2019;OECD, 2019), modelling practices must be included in teacher education to make teaching more process-oriented (Nielsen & Nielsen, 2019;Oh & Oh, 2011). Olufsen et al (2017) found that PSTs who were educated with an emphasis on the connection between subject knowledge, education strategies and practice included teaching…”

“…In a position paper on modelling competence in science education, Chiu and Lin (2019) state that the development of modelling competence is essential to scientific literacy for 21st-century citizens and that a modelling-based scaffolding framework can provide an authentic learning experience and enhance students' engagement in scientific practice. Emphasising the connection between subject knowledge, education strategies and practice in teacher education has been found to aid PSTs in including teaching strategies learnt on campus in their own teaching (Olufsen, Karlsen and Ødegaard, 2017).…”

“…Recent research concerning pre-service and in-service science teachers' experiences with using models and modelling Many studies have investigated teachers' knowledge and use of models and modelling. As curricula around the world begin to further emphasise the development of 21st-century skills, this topic has become increasingly more relevant, yet it still requires much research (Chiu & Lin, 2019). Some of the latest research related to models and modelling in teacher education will be summarised here.…”

Project-based learning to improve scientific literacy for primary education postgraduate students in science subject

“…Someone who has scientific literacy is willing to engage in reasoning discourse on science and technology. It requires competence explains scientific phenomena so that they recognize, offers and evaluates explana-tions for various natural and technological phenomena; evaluating and designing scientific research to describe and assess scientific investigations, and to propose ways of handling scientific questions; and interpreting data and scientific evidence to analyze and evaluate data, claims, and arguments in various representations and draw appropriate scientific conclusions (Chiu & Lin, 2019). All competencies also require students' abilities in terms of collaborating, communicating, thinking critically, and evaluative.…”