ChatGPT Has Mastered the Principles of Economics. Now What?

Dirk Mateer is a professor of instruction at the University of Texas at Austin and author of Economics in the Movies, Essentials of Economics, and Principles of Economics. Dirk has been featured in the “Great Teachers in Economics” series and he was also the inaugural winner of the Economic Communicator Contest. While he was at Penn State, he received the George W. Atherton Award, the university’s highest teaching award, and was voted the best overall teacher in the Smeal College of Business. He received the Kenneth Elzinga Distinguished Teaching Award from the Southern Economic Association in 2021. 

Wayne Geerling is a professor of instruction at the University of Texas at Austin. He has taught more than 40,000 undergraduate students in his career, specializing in large undergraduate courses of up to 1,000 students. Wayne’s contribution to innovation and teaching excellence has been recognized with several teaching awards at the department, faculty, university and national levels in Australia and America. 

Dirk Mateer
Image Credit: Dirk Mateer
Wayne Geerling
Image Credit: Wayne Geerling

We have taught principles of economics to 80,000 students over the last 30 years in small classes, large lecture halls, hybrid courses, and massive online courses. Our passion is helping students develop the intuition and vocabulary that economists use to explain the world around us. Now, like so many instructors, we’re faced with a strange reality: ChatGPT has mastered the principles of economics. How do we know this? As cited in our recent paper in SSRN, we had ChatGPT take a standardized post-test that has been in use for the last 50 years. The results floored us. ChatGPT scored in the 91st percentile in microeconomics and the 99th percentile in macroeconomics when compared to economics students.

ChatGPT is a natural language processing model that can generate conversational-style responses to user inputs. While it does not have an intuitive understanding of economics, it can harvest the power of the internet to produce “educated” answers. For our human students, mastering the economic way of thinking often takes considerable time, effort, and thoughtfulness. While we believe that this is a worthwhile endeavor, our students are wondering: Why should we learn economics when you can ask ChatGPT?

For instructors in the modern age, it’s useful to reflect on how technology has pushed us to evolve our teaching strategies. Our story begins in the 1990s when the internet was in its infancy. Classroom instruction relied mostly on a chalkboard. Being innovative meant loading a VCR with a tape to show a clip from a movie or documentary in class. Instructors curbed cheating by requiring students to use Blue Books.

Today, this picture is vastly different: we use a course management system to communicate; give online homework that is automatically graded; play Kahoot! games in class to discern in real-time how well students understand what is being taught; write on a document camera or tablet instead of a chalkboard; and we can access online databases with thousands of educational clips to effectively reinforce key learning points. Teaching and learning economics are easier than they have ever been because of technology.

But the rise of artificial intelligence in higher education, specifically natural language processing models like ChatGPT, presents a new challenge. While antiplagiarism tools can compare a student’s work with existing sources, ChatGPT can generate original content in seconds, making it almost impossible to detect plagiarism. Furthermore, ChatGPT has several advantages over non-AI forms of cheating: it is free, simple to use, and generates content much quicker than earlier methods.

Faculty do their best to limit academic integrity violations, but there is only so much that can be done when students take assessments online. Cheating is now the lowest-cost way to earn a high grade. Or in the jargon of economics, the dominant short-run strategy is to cheat, and students who take exams or write essays on their own merits are likely to do worse than their counterparts who do not. Economists describe this type of game as a prisoner’s dilemma. In a prisoner’s dilemma, each student can secure the best possible course grade by cheating, but the best possible outcome for society at large (which is honesty) happens less often.

One way to reduce the amount of cheating is to give in-person, proctored exams. And while AI’s impact on exams is of vital importance, we believe the impact on written assessment is even greater. You can give the bot a prompt and have an essay in a few seconds. We should require students to critique and evaluate written material rather than simply replicate and rehash what they’ve read. Our goal is to make cheating so challenging that most students will rationally decide that their time is better spent studying instead of finding ways to cheat.

We’ve been helping students learn economics for many years. We’d like to continue for many more, but the emergence of AI presents a significant challenge to traditional assessment methods. We are not naïve enough to think that large lectures and massive online courses are suddenly going to go away: universities and K-12 schools have invested so much in scaling education that they cannot afford to go back—and when it comes to teaching methods, neither can we.

As we know, it is not possible to evaluate students’ intellectual ability through artificial intelligence, as it only reflects their ability to access information. Therefore, it is crucial to rethink assessment strategies to include both traditional methods, such as proctored exams or in-class writing assignments, and experiential learning. Assessments that evaluate higher-level thinking skills like analysis, evaluation, and creation can help engage students in meaningful learning experiences while making it more difficult for ChatGPT to circumvent the process.

Economic education must embrace this technological disruptor in order to better prepare our students for the jobs of the future. While it’s not exactly clear how this field will evolve over time, as these machine-learning driven systems become more advanced and capable of replicating a broader range of humanlike traits, there will be a greater acceptance of their use in shaping the education landscape of the 21st century. Our job is to stay ahead of the curve.

Watch the recording of our workshop, “Chat GPT Has Mastered the Principles of Economics: Now What?“, hosted by Dirk Mateer and Wayne Geerling here.

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