A recent phenomenon within sociotechnology is the overwhelming confidence placed in artificial intelligence (AI). Society, as a whole, has come to believe that AI has the right answer, all that is needed is to ask the right question. This has even lead to a new career field called, ”prompt engineering,” where individuals not only learn how to ask questions, but how to adjust the position or pretext of the question to create a context that would render the most correct response. What if teachers had the same faith in their students?
In 1968 a study was conducted by researchers Robert Rosenthal and Lenore Jacobson that did just this. The study sought to investigate the effects of teachers’ expectations on students’ academic performance. In the study, teachers were deceived into believing that an average group of students were, ”growth sputters,” exhibiting amazing academic potential and ability for rapid intellectual growth. (Rosenthal and Jacobson 1968). As expected, the teachers pushed these students to learn more aggressively and the students did exceptionally well.
Although this study was based on earlier work by R.K. Merton in 1948, and of course, Greek poetry where Pygmalion experiences the original version of this phenomenon (Good, Sterzinger, and Lavigne 2018), it has been well-tested in a variety of settings. Over the next 20 years, the Pygmalion in the Classroom (PC) concept has been used in almost every facet of life, from bootcamp (Eden and Shani 1982) to retail stores (Sutton and Woodman 1989), and has been found to be quite accurate.
The effectiveness of the Rosenthal study was not merely in abstract expectations from the students, but in the teachers’ actual behavior. Teachers who thought their students were average or below average would not follow-up on wrong student answers provided in the classroom. Why would they? Why would you question a dull student who provided a dull answer? On the contrary, teachers who held the belief that their students were intelligent and capable responded differently when confronted with a wrong answer, asking, ”why do you think that?” This is because if a teacher has high expectation of a student, they will look beyond the student’s response, especially when it is incorrect. They will take time to investigate how the question may have been incorrectly phrased, or how the context may have been misinterpreted, to cause that student’s particular error—just as is seen in the use of Artificial Intelligence.
In this short academic commentary, the concentration involves the social behavior surrounding interrogation of AI systems, and how proper questions can generate proper answers. This is a small step beyond the benefits of immediate access to a global system that provides intelligible answers to natural human language queries.
Moreover, it extends beyond the issues arising from AI delivering inaccurate information due to flawed curation or programmed biases. It involves a shift in our social construct, where humans have greater expectations of AI than in that of their fellow human’s true intelligence. It is important to remember that AI is regurgitating a statistical response from the writings of humans in the past. Humans still have the ability to create and innovate with new ideas and accomplishments.
For educators, understanding dependence on AI may go beyond setting higher expectations in the classroom, it may involve an overall faith in humanity. If teachers believe that AI is the pinnacle of intellectual achievement, then this belief will also be silently conveyed to students in the classroom. Students will then grow into adults feeling that their own humanity and opinions are secondary to a statistical database with natural language processing. Although there are many exegeses of Proverbs 23:7, a persistent interpretation is that a person’s heartfelt belief shapes who they are beyond our conscious thought.
”For as he thinks in his heart, so is he. ’Eat and drink!’ he says to you, but his heart is not with you.” (The Holy Bible: World English Bible 2021, Proverbs 23:7).
Despite, or perhaps due to, these factors, AI has the potential to usher in an educational renaissance. Teachers who are willing to reshape questions, learn contextual positioning, and study prompt engineering to use AI for work and at home, may be more likely to understand the importance of pedagogy in the classroom. Rephrasing the question and altering context for AI may, inadvertently, shape teachers’ ability to question students, and also improve the way they convey information for the course materials. While there remains a concern about the potential dehumanization resulting from increased reliance on AI, there are also valuable classroom lessons to be learned from how expectations are placed on it, and how contextual thinking must be adapted for its proper application.
-Paul Poteete, PhD
References
Eden, Dov, and Abraham B Shani. 1982. “Pygmalion goes to boot camp: Expectancy, leadership, and trainee performance.” Journal of Applied Psychology 67 (2): 194.
Good, Thomas L, Natasha Sterzinger, and Alyson Lavigne. 2018. “Expectation effects: Pygmalion and the initial 20 years of research”. Educational Research and Evaluation 24 (3-5): 99–123.
Rosenthal, Robert, and Lenore Jacobson. 1968. “Pygmalion in the classroom”. The urban review 3 (1): 16–20.
Sutton, Charlotte D, and Richard W Woodman. 1989. “Pygmalion goes to work: The effects of supervisor expectations in a retail setting.” Journal of Applied Psychology 74 (6): 943.
The Holy Bible: World English Bible. 2021. ebible.org. https://ebible.org/eng-web/.
Opinions expressed in the Geneva Blog are those of its contributors and do not necessarily represent the opinions or official position of the College. The Geneva Blog is a place for faculty and contributing writers to express points of view, academic insights, and contribute to national conversations to spark thought, conversation, and the pursuit of truth, in line with our philosophy as a Christian, liberal arts institution.
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