How can the MIT community leverage generative ai to support learning and work on campus and beyond?
At MIT's 2024 Festival of Learning, faculty and instructors, students, staff, and alumni shared perspectives on the digital tools and innovations they are experimenting with in the classroom. Panelists agreed that generative ai should be used to support, not replace, learning experiences.
This annual event, co-sponsored by MIT Open Learning and the Office of the Vice Provost, celebrates innovations in teaching and learning. Introducing new teaching and learning technologies, panelists highlighted the importance of iteration and teaching students how to develop critical thinking skills while leveraging technologies like generative ai.
“The Festival of Learning brings together the MIT community to explore and celebrate what we do every day in the classroom,” said Christopher Capozzola, senior associate dean for open learning. “This year’s deep dive into generative ai was thoughtful and practical – another remarkable example of ‘mind and hand’ here at the Institute.”
Incorporating generative ai into learning experiences
MIT professors and instructors are not only willing to experiment with generative ai; some believe it is a necessary tool to prepare students to be competitive in the world of work. “In the future, we will know how to teach skills with generative ai, but we need to take iterative steps to get there rather than waiting,” said Melissa Webster, professor of management communication at MIT Sloan School of Management.
Some educators are reviewing the learning objectives of their courses and redesigning assignments so that students can achieve desired outcomes in an ai world. Webster, for example, previously combined written and oral tasks to help students develop ways of thinking. But he saw an opportunity to teach experimentation with generative ai. If students use tools like ChatGPT to help produce writing, Webster asked, “how can we include the thinking part?”
One of the new assignments Webster developed asked students to generate cover letters through ChatGPT and critique the results from the perspective of future hiring managers. Beyond learning how to refine generative ai prompts to produce better results, Webster shared that “students are thinking more in their mindset.” Reviewing her ChatGPT-generated cover letter helped students determine what to say and how to say it, which supported their development of higher-level strategic skills such as persuasion and audience understanding.
Takako Aikawa, a senior lecturer in MIT's Section of Languages and Global Studies, redesigned a vocabulary exercise to ensure that students developed a deeper understanding of the Japanese language, rather than just right or wrong answers. Students compared short sentences written by themselves and ChatGPT and developed broader vocabulary and grammatical patterns beyond the textbook. “This type of activity not only improves their language skills but stimulates their metacognitive or analytical thinking,” Aikawa said. “They have to think in Japanese for these exercises.”
While these panelists and other Institute professors and instructors are redesigning their assignments, many MIT undergraduate and graduate students in different academic departments are leveraging generative ai for efficiency: creating presentations, summarizing notes, and quickly retrieving specific ideas from long documents. But this technology can also creatively personalize learning experiences. Its ability to communicate information in different ways allows students with different backgrounds and abilities to adapt course material in a way specific to their particular context.
Generative ai, for example, can help with student-centered learning at the K-12 level. Joe Diaz, program director and STEAM educator for MIT pK-12 at Open Learning, encouraged educators to foster student-owned learning experiences. “Take something that kids care about and are passionate about and they can discern where (generative ai) might not be correct or unreliable,” Diaz said.
Panelists encouraged educators to think about generative ai in ways that go beyond a course policy statement. When incorporating generative ai into assignments, the key is to be clear about your learning objectives and be open to sharing examples of how generative ai could be used in ways that align with those objectives.
The importance of critical thinking
Although generative ai can have positive impacts on educational experiences, users must understand why large language models can produce incorrect or biased results. The professors, instructors, and student panelists emphasized that it is essential to contextualize how generative ai works. “(The instructors) try to explain what happens on the back end and that really helps my understanding when I read the responses I get from ChatGPT or Copilot,” said Joyce Yuan, a senior computer science major.
Jesse Thaler, a professor of physics and director of the Institute for artificial intelligence and Fundamental Interactions at the National Science Foundation, cautioned against relying on a probabilistic tool to give definitive answers without bands of uncertainty. “The interface and the output should be in the form of there being pieces that you can check or things that you can cross-check,” Thaler said.
When introducing tools like calculators or generative ai, professors and instructors on the panel said it is essential for students to develop critical thinking skills in those particular academic and professional contexts. Computer science courses, for example, could allow students to use ChatGPT to help with their assignments if the problem sets are large enough that generative ai tools don't capture the full answer. However, introductory students who have not developed an understanding of programming concepts should be able to discern whether the information ChatGPT generated was accurate or not.
Ana Bell, professor of the Department of Electrical and Computer Engineering and MITx A digital learning scientist, he dedicated a class toward the end of the semester of Course 6.100L (Introduction to Computer Science and Programming with Python) to teach students how to use ChatGPT for programming questions. He wanted students to understand why setting up generative ai tools with the context of programming problems, entering as much detail as possible, would help achieve the best possible results. “Even after I give you an answer, you have to be critical of that answer,” Bell said. By waiting until this stage to introduce ChatGPT, students were able to look at generative ai responses critically because they had spent the semester developing the skills to be able to identify whether problem sets were incorrect or not working in all cases.
A scaffold for learning experiences
The panelists' conclusion during the Learning Festival was that generative ai should provide scaffolding for engaging learning experiences in which students can still achieve their desired learning objectives. The MIT undergraduate and graduate student panelists found it invaluable for educators to set course expectations about when and how it is appropriate to use ai tools. Informing students about learning objectives allows them to understand whether generative ai will help or hinder their learning. The student panelists asked for confidence that they would use generative ai as a starting point or treat it like a brainstorming session with a friend for a group project. Teacher and instructor panelists said they will continue to iterate on their lesson plans to better support student learning and critical thinking.
Panelists from both sides of the room discussed the importance of generative ai users being responsible for the content they produce and avoiding automation bias, implicitly trusting the technology's response without thinking critically about why it produced that response and whether it is accurate. . But because generative ai is built by people who make design decisions, Thaler told students, “You have the power to change the behavior of those tools.”
