Course Assignments

  • Attendance (5 points)

  • Class Contributions (70 points)

  • 13 Reading Responses (5 points each; 65 total)

  • 1 Article Presentation (50 points)

  • 4 Jupyter Notebook Exercises (25 points for #1-3, 30 points for #4; 105 total)

  • 2 Project Proposals (25 points for Round 1, 75 points for Round 2)

  • 1 Annotated Bibliography (25 points)

  • 1 Project Presentation (80 points)

Due Date

Assignments

Description

Points out of 500

Course Goals

Other Goals

-

Attendance

Students will be deducted .04% of their final grade for each unexcused absence

5

(1) learn what, why, and how, (2) survey selected topics

preparing for class, organizing schedule

-

Class Contributions (Participation)

Students can contribute to class sessions by: asking questions, answering questions, adding comments, thoughts, or opinions to the discussion, helping classmates, offering ideas or suggestions, etc.

70

(2) survey selected topics, (4) work collaboratively to “fit” models to data

communicating ideas, preparing for class, critical thinking

-

Article Presentation

Students will sign up to present one research article and lead the class discussion

50

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing discussion questions

2/2

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

2/9

Jupyter Notebook Exercise 1

Students will complete a coding exercise on model fitting

25

(3) write code for data science, (4) work collaboratively to “fit” models to data, (6) gain richer understanding of computational models

problem solving through coding, developing algorithmic critical thinking, working with others on projects

2/9

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

2/16

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

2/25

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

3/2

Jupyter Notebook Exercise 2

Students will complete a coding exercise on non-social reinforcement learning

25

(3) write code for data science, (4) work collaboratively to “fit” models to data, (6) gain richer understanding of computational models

problem solving through coding, developing algorithmic critical thinking, working with others on projects

3/16

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

3/18

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

3/23

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

3/25

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

3/25

Jupyter Notebook Exercise 3

Students will complete a coding exercise on social reinforcement learning

25

(3) write code for data science, (4) work collaboratively to “fit” models to data, (6) gain richer understanding of computational models

problem solving through coding, developing algorithmic critical thinking, working with others on projects

4/20

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

4/22

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

4/27

Jupyter Notebook Exercise 4

Students will complete a coding exercise on social inference

30

(3) write code for data science, (4) work collaboratively to “fit” models to data, (6) gain richer understanding of computational models

problem solving through coding, developing algorithmic critical thinking, working with others on projects

4/27

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

4/29

Project Proposal - Round 1

Students will submit a 250-300 word abstract describing their interests and set up a meeting with Shawn to determine a final project idea

25

(1) learn what, why, and how, (2) survey selected topics, (6) gain richer understanding of computational models

synthesizing research study ideas, receiving feedback

5/4

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

5/6

Annotated Bibliography

Students will choose 7-10 research articles and summarize their behavioral methods, findings, and relevance to final project

25

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results, (6) gain richer understanding of computational models

summarizing research articles

5/6

Reading Response

Students will submit a 1-page response to the reading(s)

5

(1) learn what, why, and how, (2) survey selected topics, (5) interpret results

reading and presenting research articles, preparing for class, critical thinking, preparing discussion questions

5/12

Project Proposal - Round 2

Students will submit a 2 page project proposal (NSF GRFP format) on a hypothetical research study

75

(1) learn what, why, and how, (2) survey selected topics, (6) gain richer understanding of computational models

synthesizing research study ideas and writing a NSF GRFP style research proposal, incorporating feedback

5/12

Project Presentation

Students will present their project proposal on a hypothetical research study to the class

80

(1) learn what, why, and how, (2) survey selected topics, (6) gain richer understanding of computational models

presenting new ideas in the context of established studies, preparing discussion questions, answering questions, incorporating feedback