The NEET Experience

Instructor's Guide

This is a first-year course.

• The lecture time per week is 60 minutes.
• The out-of-class time per week is 120 minutes.
• There are no prerequisites.

Subject Description

SP.248 gives first-year students an opportunity to explore various interdisciplinary domains, or threads: autonomous machines, climate and sustainability systems, digital cities, and living machines, all of which are a part of the New Engineering Education Transformation (NEET) program. Students gain knowledge and skills in those domains through interactions with NEET faculty, instructors, and students, and exercise their algorithmic, creative, and systems thinking through team-based challenges taken from those domains.

Connection with the MIT New Engineering Education (NEET) Program

This subject is not required for joining the NEET program, and enrolling in this subject does not obligate you to join the program. Passing this subject will provide you with early access to the NEET program application in spring 2026.

The NEET Program

The NEET program was launched in 2017 to reimagine engineering education at MIT. A hands-on, experiential learning program, NEET is a cross-departmental endeavor focused on integrative, project-centric learning. NEET cultivates the essential skills, knowledge, and qualities to address the formidable societal challenges posed by the 21^st century. Students join NEET in their sophomore year, and in the usual four years earn a degree in their chosen major and a NEET Certificate in one of four cross-departmental threads: Autonomous Machines, Climate and Sustainability Systems, Digital Cities, and Living Machines.

Learning Objectives and Outcomes

By the end of the course, students are expected to do the following:

1. Be exposed to basic concepts in autonomous machines, climate and sustainability systems, digital cities, and living machines.
2. Become familiar with the NEET program and its four threads.
3. Understand basic concepts in algorithmic thinking, creative thinking, and systems thinking.
4. Be able to apply algorithmic thinking, creative thinking, and systems thinking techniques to problems.

Course Assignments

There will be three types of assignments:

1. Preparation (Note: an instructor solution is provided for every Preparation assignment.)
   • This is an individual and out-of-class assignment.
   • Students will read a short article about a topic related to a specific way of thinking or problem-solving concept and submit a short quiz in preparation for a challenge.
   • The assignment is expected to be completed in 30 minutes.
   • Using generative AI is allowed only when preparing for the quiz, not for taking it.
2. Application
   • This assignment is mostly done in teams and both inside and outside of class.
   • Students will apply a way of thinking to a given challenge adapted from one of the NEET threads.
   • The assignment is expected to be completed in 30 minutes.
   • Using generative AI is allowed only when following the instructor’s guidance and reporting on how AI was used.
3. Reflection
   • This is an individual and out-of-class assignment.
   • Students will self-rate on a specific way of thinking and provide a real-life example for it.
   • The assignment is expected to be completed in 15 minutes.
   • Using generative AI is NOT allowed.

Assignments ID’s and Titles

• P1: Preparation 1 - Algorithmic Thinking
• P2: Preparation 2 - Systems Thinking
• P3: Preparation 3 - Creative Thinking 
• P4: Preparation 4 - Ill-Structured Problems 
• A1: Application 1 - Algorithmic Thinking in Autonomous Machines: Formulate a search strategy 
• A2: Application 2- Algorithmic Thinking in Autonomous Machines: Improve your search strategy 
• A3: Application 3 - Systems Thinking in Living Machines: Design a microfluidic device for a drug delivery experiment 1
• A4: Application 4 - Systems Thinking in Living Machines: Design a microfluidic device for a drug delivery experiment 2
• A5: Application 5 - Systems Thinking in Climate & Sustainability Systems: Describe a renewable energy system 
• A6: Application 6 - Systems Thinking in Climate & Sustainability Systems: Improve the design of a renewable energy system
• A7: Application 7 - Creative Thinking in Digital Cities: Formulate your problem statement 
• A8: Application 8 - Creative Thinking in Digital Cities: Generate ideas* 
• A9: Application 9 - Creative Thinking in Digital Cities: Refine your ideas 
• A10: Application 10 - Synthetic Thinking: Problem case, problem statement, and usefulness criteria 
• A11: Application 11 - Synthetic Thinking: Generate ideas* 
• A12: Application 12 - Synthetic Thinking: Refine your ideas 
• A13: Application 13 - Making: Mold and Cast a Figurine 
• R1: Reflection 1 - Algorithmic Thinking 
• R2: Reflection 2 - Systems Thinking 
• R3: Reflection 3 - Creative Thinking

* Application assignments 8 and 11 are each divided into four sub-assignments.

Challenges and Recommended Teaching Sequences

Challenges

Challenge 1 (C1)* 

• Assigned in week 2
• Use algorithmic thinking to formulate a search strategy for a minibot looking for balls on a grid (in no-code platform, Scratch).
• A1, A2

Challenge 2 (C2)**

• Assigned in week 2
• Use systems thinking to design a microfluidic device for drug delivery experiments.
• A3, A4

Challenge 3 (C3)

• Assigned in week 2
• Use systems thinking to describe and suggest improvements to the design of a clean/renewable energy system.
• A5, A6

Challenge 4 (C4)

• Assigned in week 2
• Use creative thinking to generate and refine ideas for making Cambridge more cycle-friendly.
• A7, A8, A9

Challenge 5 (C5)

• Assigned in week 3
• Use creative and systems thinking to conceive and design a method or tool to help first-year MIT students choose the right major.
• A10, A11, A12

Challenge 6 (C6)

• Assigned in week 1
• Mold and cast a wooden figurine in plaster
• A13

* Before teaching this challenge, go through “Algorithmic Thinking in Autonomous Machines - Instructor Guide.” ** Instructor solutions exist for both Application assignments 3 and 4.

Recommended Teaching Sequence for Each Challenge

From well-defined to ill-defined

• C1: R1 → R2 → R3 → P1 → A1 → A2 → R1
• C2: P2 → A3 → A4
• C3: A6 → A6 → R2
• C4: P3 → A7 → A8a1 → A8a2 → A8b1 → A8b2 → A9 → R3
• C5: P4 → A10 → A11a1 → A11a2 → A11b1 → A11b2 → A12 → R1 → R2 → R3
• C6: A13

Recommended teaching sequence: Modular / Standalone

• C1: R1 → P1 → A1 → A2 → R1 
• C2: R2 → P2 → A3 → A4 → R2 
• C3: R2 → P2 → A5 → A6 → R2 
• C4: R3 → P3 → A7 → A8a1 → A8a2 → A8b1 → A8b2 → A9 → R3 
• C5: R1 → R2 → R3 → P4 → A9 → A10 → A11a1 → A11a2 → A11b1 → A11b2 → A12 → R1 → R2 → R3 
• C6: A13

References

[Note: These references are not required readings. They are a list of publications on which some of the course materials are based.]

1. Maital, S. & Lavi, R. (2019). Can effective creative thinking be taught to and implemented by students? Poster presented in the 41st International School Psychology Association conference, Basel, Switzerland, July 9–12, 2019.
2. Lavi, R., Bathe, M., Hosoi, A., Mitra, A., & Crawley, E. (2021). The NEET Ways of Thinking: Implementing them at MIT and assessing their efficacy. Advances in Engineering Education, 9(3), 1–19. doi.org/10.18260/3-1-1153-14557.
3. Lavi, R., Marti, D., & Crawley, E. (2023). Creating analogies for design problem-solving: Initial evaluation of an engineering faculty workshop. Proceedings of the VII IEEE World Engineering Education Conference (EDUNINE2023), Bogotá, Colombia.
4. Lavi, R., & Brogaard Bertel, L. (2024). The System Architecture-Function-Outcome framework for fostering and assessing systems thinking in first-year STEM education and Its potential applications in case-based learning. Education Sciences, 14(7), 720.
5. Lavi, R. Paz, A., & Berman, C. (2024). Defining real-world problems with the D.I.S. method: Describe, inquire, state. MIT OpenCourseWare.
6. Lai, Y. & Lavi, R. (2025). Problem structuring in urban science education: Why, what, and how. Frontiers of Urban and Rural Planning, 3(13). doi.org/10.1007/s44243-025-00064-3.