Course outline

Who you are when you are at your best, and what gets in the way.

• Week 1

  The mind is a muscle

  Psychology

  Positive psychology, intentional actions, and shifting your positivity ratio. Why mindset matters for learning and growth.

  Data science

  The data science pipeline, end to end.

  Communication

  Storytelling, and what narrative does to attention, memory, and belief—applied to your own positive introduction.

• Week 2

  Motivation and strengths

  Psychology

  Types of motivation, putting your character strengths to work, and getting out from under procrastination.

  Data science

  Where data comes from, and first visualizations of a survey run in an intro computer science class.

  Communication

  Judging sources with a trustworthiness checklist, the six research designs in the evidence hierarchy, and finding peer-reviewed work through Google Scholar and the MIT Libraries.

• Week 3

  Stress and resilience

  Psychology

  Resilience, the thinking traps that undercut it—catastrophizing, mind reading, tunnel vision—and the tools that counter them.

  Data science

  How to prompt large language models, and how to judge what comes back.

  Communication

  Sharing positive introductions in small groups, with the practice on the listening side.

Attention, goals, habits, and the long arc of getting good at something.

• Week 4

  Attention and active learning

  Psychology

  Managing attention, cutting distraction, active learning techniques, and time management.

  Data science

  Statistical significance and effect size, on MIT subject evaluation data.

  Communication

  The three kinds of presenting—entertain, educate, persuade—aimed at your poster session, plus in-the-moment techniques for managing performance stress.

• Week 5

  Goals and satisficing

  Psychology

  The stages of goal achievement, and when "good enough" is the right standard.

  Data science

  Unsupervised learning and clustering, in the context of the Stroop test.

  Communication

  Where feedback comes from, how to ask for it, and how to give it so someone can act on it.

• Week 6

  Habits, social media, and spaced learning

  Psychology

  How habits form, and how to build one on purpose.

  Data science

  Finding correlations between features, using video-watching data from a blended learning class.

  Communication

  First poster session, presenting a data visualization you built.

• Week 7

  Deliberate practice

  Psychology

  What separates practice from deliberate practice, the role of grit, and whether to chase meaning, purpose, or pleasure.

  Data science

  Classification with training and test sets, predicting grit and finding which features drive it.

  Communication

  The science of learning and teaching, applied to your own explanations.

Connection, teams, and the values underneath how you work with people.

• Week 8

  Relationships

  Psychology

  Building high-quality connections quickly, and what makes long-term relationships hard.

  Data science

  Clustering and principal component analysis on a five-factor personality survey.

  Communication

  Informational interviews: active listening, open-ended questioning, and examining your findings for selection, confirmation, representativeness, and overconfidence bias.

• Week 9

  Teams, collaboration, and conflict

  Psychology

  Psychological safety, what it does for a team, and how to handle conflict inside one.

  Data science

  Linear regression on MIT data about students working together on problem sets.

  Communication

  Writing collaboratively with Diátaxis, in preparation for the group project.

• Week 10

  Identity and values

  Psychology

  Values, icebergs, and refining your own sense of who you are.

  Data science

  Survey and questionnaire design, and what qualitative and quantitative collection each buy you.

  Communication

  Second poster session, telling a story across several visualizations.

Making it stick, and putting the whole pipeline together on a question of your own.

• Week 11

  Rest, sleep, and learning

  Psychology

  Why rest and sleep are load-bearing, and how to actually change a sleep schedule.

  Data science

  Logistic regression predicting outcomes from student behaviors.

  Communication

  Receiving feedback well, and turning it into a revision.

• Week 12

  PERMA and sustaining positive behavior

  Psychology

  The PERMA model of well-being, and gratitude as a practice rather than a mood.

  Data science

  Exploring a student-activities dataset and presenting what you find.

  Communication

  Making an abstract idea concrete with a story an audience can feel.

• Week 13

  Case studies

  Psychology

  Positive psychology at organizational scale, with industry examples.

  Data science

  Group project work.

  Communication

  Analyzing how different leaders' communication strategies land.