Computational practices in introductory science courses

Abstract

Nowadays computation is considered to be one of the pillars of modern science. This is reflected in the fact that much scientific research and industry work relies heavily on technology and computation. As university educators we need to equip graduates with the tools to help them succeed in their discipline. The study reported here is part of a larger project which aims to identify computational practices used by faculty from across the College of Science in an R1 Irish university in their disciplines and research, in order to inform the design of a computational science course intended for first-year undergraduate students. This paper reports on findings from one-to-one interviews with fourteen faculty from across six schools in the college. Their understanding of the nature of computational thinking and their views on the role that computation does/can play in the undergraduate science curriculum, and specifically in teaching and learning within their disciplinary program are presented. Concerns and challenges related to the embedding of computation in undergraduate science programs voiced by participants are presented here. Finally, implications of the findings for the design of the first year computational science course are discussed.

Creating a computational playground in high school physics

“…In order for computational thinking to be effectively introduced to students as an interdisciplinary practice of using computers to understand STEM-related concepts [1][2][3][4][5][6], it must be integrated across disciplinary subjects [7,8]. The physics education community has taken up this charge [9,10] by creating activities that develop computational thinking in a physics context [6,11,12] and that use computation to further develop students' conceptual understanding of physics [13][14][15][16]. While significant progress has been made in integrating computation into the undergraduate physics experience [17], the high school context has seen much less development.…”

Student Representations of Computation in the Physics Community

“…Students can use computation to simulate physical systems, conduct advanced analysis of experimental data, create insightful visualizations, explore analytically intractable problems, and bridge the gap between mathematical problems and experimental activities [1][2][3][4][5][6][7][8][9][10]. Upon graduating, students find that computation is prevalent in all fields of physics research and STEM industry [10][11][12][13], with faculty mentors and employers expecting well-developed computational skills in their research mentees and new hires [8,[14][15][16][17]. Integrating computation into the undergraduate experience provides students with research-and industry-relevant skills [13,17,18] while helping them develop an appropriate view of building models and implementing them with a computer [19].…”

“…Upon graduating, students find that computation is prevalent in all fields of physics research and STEM industry [10][11][12][13], with faculty mentors and employers expecting well-developed computational skills in their research mentees and new hires [8,[14][15][16][17]. Integrating computation into the undergraduate experience provides students with research-and industry-relevant skills [13,17,18] while helping them develop an appropriate view of building models and implementing them with a computer [19]. Computation enables students to pursue creative solutions [20,21], more directly engage in sense-making [5,6,22,23], and test a variety of model-based predictions [9,21,24,25].…”

“…Computation enables students to pursue creative solutions [20,21], more directly engage in sense-making [5,6,22,23], and test a variety of model-based predictions [9,21,24,25]. Such activities equalize student mathematical backgrounds [26][27][28], promote deeper learning [13,21,29,30], and support underrepresented groups [9,[31][32][33]. In physics and beyond, computational thinking has become its own suite of learning objectives, including data practices, modeling and simulation practices, computational problem solving practices, and systems thinking [9,10,13,29,30,[34][35][36].…”

“…What aspects of programming do students need to understand in order to learn by working with a computational model? How can we properly scaffold a diverse set of programming skills alongside the preexisting objectives of the physics curriculum, and how do we make room for computa-tion in the already-packed curriculum [2,10,13,51]? How can departments negotiate varying levels of faculty proficiency with computation?…”