Paper Info
Title
Teaching Programming to Science Majors by Modelling.
Abstract
Programming is playing an increasingly important role in various fields, including science. However, traditional programming instruction tends to use small-scale and general examples to explain syntax and semantic meaning of the code, which cannot foster students' programming ability of solving real-world problems. This research was intended to develop a modelling-based instruction for scientific programming to guide students to solve programming problems based on the modelling process (phenomenon description, data modelling, algorithmic modelling, coding, and verification and debugging). A learning platform based on the proposed modelling process was also developed to assist science-major students to learn how to solve real-world scientific problems by programming. An empirical study was conducted on thirty-two science-major college students to prove the effectiveness of the modelling-based scientific programming. The experiment results show that students who engaged more in modelling had higher programming performance. The modelling-based instruction actually helps students to write programs for solving scientific problem by using both of data and algorithmic models.
Year
DOI
Venue
2020
10.1145/3328778.3372688
SIGCSE
DocType
ISBN
Citations 
Conference
978-1-4503-6793-6
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Hsin-Ling Hsieh100.34
Yu-Tzu Lin23711.11