[0302 Morning · Team 2] New maths materials for teaching college-level data science

Prompt: New maths materials for teaching college-level data science

Please share your notes/comments here.

Logic model for “math prep for DS programme for college students”

Purpose

  • Ensure a common level of math competence for students who continue with the DS programme.

Inputs

  • Access to computing resources for teachers and students
  • Curricular materials
  • Real world case studies, data sets, templates, exercises.

Constraints/Barriers

  • Can only assume familiarity with grade X level math
  • Class size > 60 < 200
  • Inhomogeous training in math (for incoming students)
  • Instructors need to come in with exposure to DS.
  • Concurrent course load of the students
  • Basic English proficiency
  • Operations support

Activities

  • Ongoing formative assessment towards improving learning trajectory.
  • Collaborative capstone project and presentations.
  • Peer instruction opportunities
  • Real world case studies

Outputs

  • Students familiar with Sets, Counting, Probability, basic Statistics, Linear algebra.
  • Students able to apply probability to inference problems.
  • Can formulate problems as probabilistic processes?
  • Students complete the DS programme successfully given the math prep. (i.e. dropout rate)

Effects

  • Students not intimidated by mathematical formulations of data problems.
  • Students ask pertinent questions about new data-related situations presented to them.
  • DS instructors are able to do deeper coverage of topics with students.

Context

  • Students joined a DS programme and need to be prepped to handle the math they’ll encounter in the programme.

Research questions

  • RQ1: Are students who’ve gone through the prep course intimidated by mathematical formulations of data problems?

  • RQ2: Is the fear students have of mathematics affecting their learning?

  • RQ3: Is “time to first action” a good proxy for gaining a sense of student fear?

    • Sampling criterion - students with self reported fear of math in pre-test.
  • RQ4: Are timed tests indicative of student performance in subsequent DS courses?

Highlights from the in-person discussion:

  • Fear and degree of intimidated are hard to measure

    • People do this in other fields
    • Perhaps useful to collaborate
  • Ethics issues (e.g, for doing RCTs on your students and such)

  • The questions are not inter-connected, but this happens (e.g, one of the RQs might be about incoming students, one might be about outgoing ones; and they might seem unrelated but are all important).