Computational apprenticeship: Cognitive apprenticeship for the digital era

Abstract

The conceptualization of Computational Thinking as a cross-cutting skill with relevance across disciplines has ushered in wide-ranging efforts to increase computational education in all facets of education. However, the majority of initiatives for integrated computing education have focused on K-12 settings, as has most education research around computational thinking. At the postsecondary level, computing education remains largely siloed within specific programming courses and has not been well-integrated throughout the STEM curriculum. Current instructional approaches often leave students poorly prepared to transfer their computing knowledge to solve new real-world problems. Additionally, there is limited education research into how best to develop computational thinking among postsecondary students. In fact, education research into computational thinking remains undertheorized and is often definitional in nature. Here, we integrate computational thinking with the educational psychology concept of adaptive expertise. Finally, we contextualize computational thinking within constructivist learning theories by introducing computational apprenticeship, an application of cognitive apprenticeship to computing. Computational apprenticeship provides a research and practice model for supporting the development of computational adaptive expertise.

Supporting Computational Apprenticeship through educational and software infrastructure. A case study in a mathematical oncology research lab

“…Computational Apprenticeship is a newly proposed theoretical framework and a type of cognitive apprenticeship for computational disciplines [24]. Biology and engineering, like most other academic disciplines, are often taught through traditional instructional methods heavily featuring didactic lectures.…”

“…In these disciplinary contexts, there is typically a heavy emphasis on the technical aspects of computational topics. However, education research suggests that a narrow focus on technical competency typically provides students with routine expertise, but lacks the adaptive expertise needed to solve computational problems in real world settings [24][25][26]. For example, students attempting to develop computational models of cellular and molecular biological systems report challenges with higher-order computational thinking skills such as abstraction and problem decomposition, rather than coding or mathematics [10,27,28].…”

“…The Computational Apprenticeship framework adapts this model to computational domains and provides a theoretical basis for creating curated learning experiences with graduated challenges in terms of difficulty and diversity. The framework also provides direction for the use of emerging technological practices such as code commenting and Jupyter notebooks to deliver pedagogical scaffolding and other elements of the sequencing and method dimensions of learning [24].…”

Supporting Computational Apprenticeship Through Educational and Software Infrastructure: A Case Study in a Mathematical Oncology Research Lab

“…Computational Apprenticeship is a newly proposed theoretical framework and a type of cognitive apprenticeship for computational disciplines [ 12 ]. Biology and engineering, like most other academic disciplines, are often taught through traditional instructional methods heavily featuring didactic lectures.…”

“…In these disciplinary contexts, there is typically a heavy emphasis on the technical aspects of computational topics. However, education research suggests that a narrow focus on technical competency typically provides students with routine expertise, but lacks the adaptive expertise needed to solve computational problems in real world settings [ 6 , 12 , 22 ]. For example, students attempting to develop computational models of cellular and molecular biological systems report challenges with higher-order computational thinking skills such as abstraction and problem decomposition, rather than coding or mathematics [ 38 , 61 , 64 ].…”