Name
Abstract | ||
|---|---|---|
The widespread of data science programming languages and libraries have raised new interest in teaching computational science coding in ways that leverage the capabilities of both single-computer and cluster-based computation infrastructures. Some of the programming patterns and idioms are converging, yet there are specialized uses and cases that require learners to switch from one to another. In this paper, we report on the experience in action research with more than ten cohorts of mixed background students in postgraduate level data science classes. We first discuss the key mental models found to be essential to understanding solution design, and then review the three fundamental paradigms that students must face when coding data manipulation and their interrelation. Finally, we discuss some insights on additional elements found important in understanding the specificities of current practice in data analysis tasks. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-22750-0_33 | COMPUTATIONAL SCIENCE - ICCS 2019, PT V |
Keywords | Field | DocType |
Computational science, Education, Data science, Programming, Mental models | Programming patterns,Programming paradigm,Computer science,Coding (social sciences),Computational science,Action research,Computation | Conference |
Volume | ISSN | Citations |
11540 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miguel-Ángel Sicilia | 1 | 479 | 61.55 |
| Elena GarcíA-Barriocanal | 2 | 422 | 51.53 |
| Salvador Sánchez Alonso | 3 | 193 | 29.09 |
| Marçal Mora Cantallops | 4 | 0 | 0.34 |