# Instructor Insights

Instructor Insights pages are part of the OCW Educator initiative, which seeks to enhance the value of OCW for educators.

## Instructor Insights

Rahul Bhargava in the MIT Media Lab.

Below, Rahul Bhargava describes various aspects of how he teaches CMS.631 Data Storytelling Studio: Climate Change.

- A Compass-Led Course
- Misconceptions about Data Storytelling
- Thinking with Climate Data
- Tips for Making Teamwork Work Well
- Using a Class Blog for Learning
- Making Things Local

## Student Insights

Making the data ‘alive’ through non-quantitative means makes the concept much more relatable and personable. The audience understands this at an organic level, and they are drawn to learning more. It's much more engaging. Long story short, it is much more memorable. And in many cases, that's the entire point.

— Felipe Lozano-Landinez, Undergraduate

Below, students in the course describe the data storytelling techniques they found particularly compelling, offer advice to future students, and share tips with educators interested in facilitating a similar learning experience.

- Compelling Data Storytelling Techniques
- Advice for Students
- Tips for Educators

## Curriculum Information

### Prerequisites

None

The course is open to all technical levels and backgrounds. Students with a strong background in one or more of the following areas are prioritized: journalism, software development, data analysis, documentary, and visual and performing arts.

### Requirements Satisfied

GIR

HASS

### Offered

Every spring semester

## The Classroom

- ### Studio

  Studio sessions were held in a classroom with moveable tables and chairs, sliding chalkboards, and an AV system.

## Assessment

### Grade Breakdown

The students' grades were based on the following activities:

20% Participation, peer-assistance and paper reviews 15% Assignments 45% Technique sketches 20% Final project

## Student Information

### Breakdown by Year

Both undergraduates and graduate students

### Breakdown by Major

Computer science, business, biology, mechanical engineering, writing, and the arts

### Enrollment Cap

Enrollment is capped at 30 so that the instructor has adequate time to support each student as they experiment with data storytelling techniques.

## How Student Time Was Spent

During an average week, students were expected to spend 12 hours on the course, roughly divided as follows:

## In Class

3 hours per week

- Met 2 times per week for 1.5 hours per session; 27 sessions total.
- Class sessions involved hands-on activities, teamwork, and critique sessions.

## Out of Class

9 hours per week

- Students completed assignments and readings, contributed to the class blog, and worked on their final projects outside of class.

## Semester Breakdown

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No classes throughout MIT
Class meeting
Student presentations
No class session scheduled
Critique sessions
Open work time