Models and Modelling: Routes to More Authentic Science Education

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Defining Computational Thinking for Mathematics and Science Classrooms (2016, background): “…power of computational models comes not just from students using existing models, but also from enabling students to design, build, and assess models of their own (Brady et al. 2015; Gilbert 2004; Penner 2000; White 1993; Wilensky 1995, 2003; Wilensky and Reisman 2006; Wilkerson-Jerde et al. 2015).”
Epilogue: Plotting a Research Agenda for Multiple Representations, Multiple Modality, and Multimodal Representational Competency (2010, background): “We are not convinced about the value of using the label mental models for private and personal mental ideas and images ( Gilbert 2004 ).”
A review of research on augmented reality in education: Advantages and applications (2015, background): “Students commonly find Science subjects to be abstract, requiring a depth of understanding and visualization skills (Gilbert, 2004). When students have difficulties in understanding the concept well, it leads to misconceptions. According to Palmer (2001), misconception among students has to be taken”