The Methods of Teaching Data Science (MTDS) Course

Back to Technion Data Science Education website

A full-semester course that meets 3 hours a week for 13 weeks.
The description is based on our experience teaching the course at the Faculty of Education in Science and Technology at the Technion during the Spring semester 2021-2022.
The course was taught as a hybrid course: two hours were taught synchronously via Zoom and one hour was taught asynchronously.
The course online learning platform was Moodle.

LT1: The students become familiar with the Israeli high school data science curriculum.
LT2: The students experience a full data science workflow in Python.
LT3: The students become familiar with learning theories, pedagogical approaches, and teaching methods suitable for data science education in general, and specifically for the data science workflow.

Data analysis with Python
The Israeli data science curriculum and teaching methods suitable for teaching data science on the high school level
Relevant technologies for teaching and learning data science
Challenges of teaching data science, e.g., the interdisciplinarity of data science , and the variety of populations studying data science
Methods for teaching data science
Teaching data science skills
Carrying out a research project in data science that examines an educational topic (since the teachers’ application domain is education).

See the grading policy and submission page, including the course assignments and asynchronic tasks.

Notes:

The MTDS course schedule (including references to our book Hazzan, O. and Mike, K. (2023). Guide to Teaching Data Science: An Interdisciplinary Approach, Springer).
Detailed descriptions of each lesson (without references to the book sections/chapters) appear below. Descriptions are in English; Slides are either in English/Hebrew