Learning and expertise with scientific external representations: an embodied and extended cognition model

被引:0
作者
Prajakt Pande
机构
[1] Roskilde University,Department of People and Technology
[2] Roskilde University ,Centre for Virtual Learning Technologies
来源
Phenomenology and the Cognitive Sciences | 2021年 / 20卷
关键词
Representation; Embodied; Science education; Mathematics education; Expertise; Mental abacus;
D O I
暂无
中图分类号
学科分类号
摘要
This paper takes an embodied and extended cognition perspective to ER integration – a cognitive process through which a learner integrates external representations (ERs) in a domain, with her internal (mental) model, as she interacts with, uses, understands and transforms between those ERs. In the paper, I argue for a theoretical as well as empirical shift in future investigations of ER integration, by proposing a model of cognitive mechanisms underlying the process, based on recent advances in extended and embodied cognition. I present this new model in contrast to the still dominant classical cognitivist (information processing) approaches to ER integration, and the educational technology intervention designs such approaches inspire. I then exemplify this distinction between the information processing model and the new model through a case of arithmetic problem solving. Corroborative neuroscience evidence presented in relation to this case provides empirical support for the new model by showing how bodily actions (sensorimotor mechanisms) are critical to ER integration and learning. Finally, as educational implications of the new model, I demonstrate the need for: (i) re-viewing the development of ER integration and expertise as fine-tuning of the learner's action or sensorimotor system, and (ii) a shift of focus in new-media intervention design principles based on this newer understanding of ER integration in science, technology, engineering and mathematics.
引用
收藏
页码:463 / 482
页数:19
相关论文
共 177 条
  • [21] Nersessian NJ(2003)Neural correlates underlying mental calculation in abacus experts: A functional magnetic resonance imaging study NeuroImage 19 296-307
  • [22] Chandrasekharan S(2004)Dynamic visualizations and learning: Getting to the difficult questions Learning and Instruction 14 343-351
  • [23] Osbeck L(1995)How a Cockpit Remembers Its Speeds Cognitive Science 19 265-288
  • [24] Chen F(2014)The cultural ecosystem of human cognition Philosophical Psychology 27 34-49
  • [25] Hu Z(2004)Fixation location and fixation duration as indices of cognitive processing The Interface of Language, Vision, and Action: Eye Movements and the Visual World 217 105-133
  • [26] Zhao X(1890)The perception of reality Principles of Psychology 2 283-324
  • [27] Wang R(2018)Immersive VR and Education: Embodied Design Principles That Include Gesture and Hand Controls Frontiers in Robotics and AI 5 81-379
  • [28] Yang Z(1982)Macro and microchemistry School Science Review 64 377-83
  • [29] Wang X(1991)Why is science difficult to learn? Things are seldom what they seem Journal of Computer Assisted Learning 7 75-268
  • [30] Tang X(1997)Chemistry teaching, science or alchemy? Journal of Chemical Education 7 262-19