Teaching computer programming to science majors by modelling

Abstract

This study reports the design and implementation of a modelling‐based programming instruction for science majors and its effectiveness on programming and science learning. A modelling approach was proposed to provide guidance to students in implementing solutions for scientific problems in computer programming. This modelling approach includes five stages: (1) phenomenon description, (2) data modelling, (3) algorithmic modelling, (4) coding, and (5) verification and debugging. Authentic scenarios for science learning were adopted in teaching materials and problems to inspire students to learn both the scientific and programming aspects of the underneath phenomena. An empirical experiment to examine the effectiveness of the proposed instruction was conducted in a general education course at a university, and the results showed that students who engaged more in the modelling approach performed better in both the program implementation test and their final projects. In addition, students' feedback agreed with what we had expected the modelling approach would benefit students: they could connect abstract, real‐world phenomena to programming variables and logic by visualizing the phenomena in simulation and animation. Data modelling and algorithmic modelling also helped them analyze the variables in the problem space and propose a solution before coding. Because the proposed instruction provided opportunities to experience the capability of programming in solving scientific problems, high‐programming‐performance students also showed a greater interest in exploring science after the class.

The transfer effects of computational thinking: A systematic review with meta‐analysis and qualitative synthesis

“…Most of the studies focusing on science subjects examined the CT transfer effects in biology ( n = 6) (Arık & Topçu, 2022; Irgens et al, 2020; Nguyen & Santagata, 2021; Peel et al, 2019; Peel & Friedrichsen, 2018; Rachmatullah & Wiebe, 2022), physics ( n = 5) (Aksit & Wiebe, 2020; Hutchins et al, 2020; Orban et al, 2018; Svensson et al, 2020; Vieira et al, 2018) and integrated science contexts ( n = 5) (Basu et al, 2017; Guven et al, 2020; Lin et al, 2021; Sáez‐López et al, 2019; Sengupta et al, 2013). In addition, two studies assessed the effects in a chemistry context ( n = 2) (Bortz et al, 2020; Chongo et al, 2021).…”

“…First, students can actively engage in learning activities by peer collaboration and discussion (e.g., Bortz et al, 2020;Chongo et al, 2021;Irgens et al, 2020;Rodríguez-Martínez et al, 2020). Second, immediately using and applying the information in the intervention activities can also facilitate a deeper understanding and help students to solve reallife problems (e.g., Aksit & Wiebe, 2020;Arık & Topçu, 2022;Chen et al, 2020;Città et al, 2019;Lin et al, 2021;Orban et al, 2018).…”

Current trends and developments in the application of digital tools and implementation of environmental awareness and sustainability in PBL-based STEM education: a dual systematic literature review

“…For beginners and young students, block-based programming is the best -Scratch is the most popular of these, based on the articles studied (Century et al, 2020;Weng et al, 2022). Nevertheless, for example, complex scientific phenomena can also be modeled by programming -usually using text-based programming languages, like Python (Lin, YT et al, 2020).…”

“…It is the case for all robotics projects, where the robot has to be "made" to do something (Major et al, 2021;Cui et al, 2021;Wang et al, 2021;Shahin et al, 2021;Sisman et al, 2022;Bhuyan et al, 2020;Kim et al, 2021). However, it also includes programming tasks (Weng et al, 2022;Century et al, 2020;Lin, YT et al, 2020), computer games (Juric et al, 2021), andvirtual reality (Darayathna et al, 2020).…”

“…It is either achieved by having to solve the task together, for example, in robotics cases (Major et al, 2021;Cui et al, 2021;Wang et al, 2021;Shahin et al, 2021;Sisman et al, 2022;Bhuyan et al, 2020;Kim et al, 2021) and the science simulation programming task (Lin, YT et al, 2020). Or it can be implemented by making the simultaneous work transparent and assessable, as in the case of the interactive online whiteboard (Ng et al, 2020) c) supports learning (provides an environment that helps understand the subject content)…”