About

The New Engineering Education Transformation (NEET) program aims to reimagine and rethink undergraduate engineering education—what students learn and how they learn—in a fundamental way across MIT.

A student-focused endeavor, NEET is based on four principles:

  • An engineering education should focus on the new machines and systems students will build in the 21st century.
  • Students should be prepared to act as makers and discoverers, with fundamentals as a foundation for careers in research and practice.
  • An education should be built around the way our students learn best by engaging them in their learning and finding the best balance of classroom, project, and digital learning.
  • The NEET Ways of Thinking are conceived specifically to help students thrive in an atmosphere of rapid scientific and technological development.

New Machines and Systems

Simply put, new machines and systems are things that engineers build— including mechanical, molecular, biological, informational, and energetic constructs. These are the things that our graduating students will build during their careers after they leave MIT.

What makes these machines new, and NEET’s approach relevant, is the degree, nature, and pace of change in modern science and technology. Very few of today’s practicing engineers received training in a whole range of fields that will define the careers of our graduates. For example, the new machines of tomorrow are likely to be facilitated by:

  • Machine learning
  • Internet of Things
  • Autonomous and robotic systems
  • Novel materials design and manufacturing systems
  • Smart grids, cities, and urban infrastructure
  • Sustainable materials and energy systems
  • AI-driven healthcare diagnostics and therapeutics

The organization and structure of most engineering programs, especially in the US, is around siloed disciplines (civil, mechanical, electrical, chemical, etc.) and their machines. Reinforced by the accreditation process, this curricular structure is very repeatable, prescriptive, and good at generating certain “types” of engineers—a situation that is then reinforced by many companies that use the labels to inform their hiring practices. The established professional organizations (ASME, IEEE, etc.) further perpetuate the silos.

Preparing young people to design a “new machine” means approaching their overall training very differently. We must work energetically to overcome academic inertia, conservative influences in accreditation and professional societies, and the hiring practices of major companies.

In the future, students must be able to work on machines and systems that are complex, highly networked and part of larger systems of systems, have higher levels of autonomy, and are supportive of a sustainable environment.

Makers and Discoverers

A second principle of NEET is that we should help our students prepare for careers on a spectrum that spans from making to discovering. Makers are people who will have careers conceiving, designing, implementing, and operating systems and products that deliver value. Discoverers will perform research that reveals the underlying principles, mechanisms, and truths that drive our world.

Undergraduate students are often unsure of the exact routes their careers will take, but they should have the option to prepare themselves to work anywhere along this spectrum. NEET gives students the tools and training that affords them a foundation for a lifetime of managing new technologies, new theories, new models, and new methods for making and discovering.

Flexibility along the spectrum from making to discovering is achieved by allowing students to choose projects that suit their interest, and by designing an appropriate structure of supporting coursework that gives them the fundamental knowledge they need. Whether it’s a maker-based project or a student research experience (e.g., SuperUROP), NEET provides flexibility and choice on this axis. Ideally, this flexibility allows students to defer their choice of major to the middle or even end of their second year.

The Way Our Students Learn Best

NEET is built around the idea that we should teach students in the ways they most want to learn—engaging them and making them active collaborators in their learning. NEET rigorously documented the best practices, benchmarking, and evidence from stakeholders and institutions around the world in a global undergraduate education benchmarking study that was released in 2018. Based on these findings NEET understands the ways to prepare today’s engineer for the careers of tomorrow.

We have structured our program around ideas and practices that increase the use of the approaches that have been proven to work—more regular and active engagement with students in the classroom, more project-based learning, creative and relevant uses of digital learning, and professional experiences and training, to name a few.

The way our students are learning is rapidly changing. Today, they employ increasingly diverse combinations of learning strategies in any given class. NEET strives to better understand how students are learning so it can be factored into the program.

NEET Students

NEET Ways of Thinking

Given the modern pace of scientific and technological development—and the high probability of sustained or even increasing rate of growth in this area—NEET takes it as a fundamental principle that students need to know how to learn effectively by themselves. Our approach to this challenge is the NEET Ways of Thinking

Based on cognitive approaches and skills used by successful technical professionals, the NEET Ways of Thinking empower students, allowing them to have a greater impact, to be more effective, and to thrive in academic and workplace environments after graduation. These cognitive approaches help them think and learn on their own throughout their lifetimes.

We have identified a framework of twelve NEET Ways of Thinking; this framework also formed the basis for getting inputs and gathering evidence from a range of stakeholders, including thought leaders, industry, alumni, students and faculty.

THINKING DESCRIPTION
Learning how to learn Cognitive approaches such as those listed below that can help students think and learn on their own initiative.
Making Inventing and creating artifacts that have never before been in existence: Conceiving (understanding needs and technology, and creating concept), designing, implementing, and operating products and systems that deliver value.
Discovering Advancing the knowledge of our society and world by exploring, identifying, and generating new knowledge, often by conducting research that leads to new fundamental discoveries and technologies.
Interpersonal skillsEngaging with and understanding other people: communicating, listening, emotional intelligence, working in and leading teams, collaboration and networking, advocacy and leading change.
Personal skills and attitudes Initiative, judgment, and decision making; responsibility and urgency; flexibility and self-confidence; acting ethically and with integrity; social responsibility; dedication to lifelong learning.
Creative thinking Forming something new and valuable by focusing thought and incubating new ideas, illuminating and articulating them in conscious awareness, and verifying them.
Systems thinkingPredicting emergence of a whole by examining inter-related entities in context in the face of complexity and ambiguity; for both homogeneous systems and systems that integrate multiple technologies.
Critical and metacognitive thinkingAssessing the worth or validity of a concept, product, or process by analyzing and evaluating information gathered from observation, experience, or communication.
Analytical thinking Working systematically and logically to break down facts and resolve problems; identifying causation and anticipating results by applying theory, modeling, and mathematical analysis.
Computational thinking Using computation to understand physical, biological, and social systems by applying the fundamental constructs of computer programming (abstractions, modularity, recursion), data structures, and algorithms.
ExperimentalConducting experiments to obtain data: selecting measurements, determining procedures to validate data, formulating and testing hypotheses.
Humanistic Developing a broad understanding of society and its traditions and institutions: knowledge of human cultures, human systems of thought, modes of expression in the arts, and the social, political, and economic frameworks of society.

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