Lesson #3

Back to the Methods of Teaching Data Science course

Back to Technion Data Science Education website
  • Continuation of the discussion about the interdisciplinarity of data science and the pedagogical challenges that this characteristic of data science presents.
  • The following issues were discussed (questions on several of these issues were included in the preliminary questionnaire distributed to the students prior to the onset of the course):
    • The interconnection between data science, computer science, and statistics. While in the first lesson, we presented the students with their own answers to this question, in this lesson, our purpose was to highlight the interdisciplinarity of data science.
    • Specifically, we discussed the relationship between data science and the application domain, and addressed the following two points:
      • The variety of fields from which data can be brought
      • The domain neglect cognitive bias and the importance that should be attributed to the application domain
    • Project-based learning (PBL) and the interdisciplinarity challenge (see also Mike, Nemirovsky-Rotman, and Hazzan, 2020)
    • Presentation of the asynchronous task about the interdisciplinarity of computer science (see Table ‎2 in Grading policy)