MIT's Department of Electrical Science and Engineering offers 6.C31 (Hack Yourself), a course that helps students build a personal toolkit of over 60 positive habits using computing tools, thereby markedly improving their college experience. Developed by senior lecturer Ana Bell, ESG visiting instructor Carter Jernigan, and senior lecturer Paola Rebusco, the class is part of the Common Ground initiative of the MIT Schwarzman College of Computing, which blends computing with other disciplines.\ \ The course treats well‑being and learning as systems problems: gather meaningful data, decompose a big question into manageable parts, test interventions, and evaluate outcomes. Students learn the full data‑science pipeline—designing surveys, conducting interviews, accounting for bias and measurement error—human‑centered skills that remain valuable regardless of future technologies.\ \ Collected data are diverse, with recurring themes such as reducing smartphone use, regular sleep, work habits, and transition to the workplace. Rather than seeking a single "best" intervention, the class encourages students to assemble a personalized toolkit. Teamwork assignments use research‑backed tricks—e.g., replacing small talk with "Tell me something good happening in your life" or conducting a pre‑mortem where a group imagines a project has already failed and works backward to prevent issues. Reading assignments are collaborative via Perusall, reinforcing shared annotation.\ \ A tangible element of the toolkit is the "Intention cards": professionally printed, playing‑card‑sized collectibles that distill a habit or strategy into a few words and an AI‑generated image. Students earn several each week, ending the semester with more than 60 cards stored in a booklet. As they reorganize and revisit cards, they unintentionally practice spaced repetition and recall—key learning principles discussed in class.\ \ Student examples illustrate impact:\
- Sarah Hopp used a 2001 assignment by Laura King to envision her "best possible future self" for 20 minutes, then wrote a letter to that future self, clarifying goals and focusing on positives.\
- Amitoj Singh applied a flow‑state discussion to restructure his schedule into longer, uninterrupted blocks, and explored "satisficing"—knowing when an outcome is good enough instead of endlessly optimizing.\ \ The curriculum also incorporates large language models, requiring students to critically evaluate both prompts and AI responses. The goal is not fluency with current AI but the ability to assess any future tool.\ \ Hack Yourself deliberately avoids becoming another machine‑learning class; instead, it emphasizes the data‑science pipeline itself—collecting useful data, asking good questions, designing small experiments—mindsets that scale as technology evolves.\ \ Review