ChatGPT and Teacher Education
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by Jacob Pleasants & Jeffrey Radloff
On November 30, 2022, OpenAI released the ChatGPT chatbot to the public, unleashing a torrent of attention and commentary. The underlying technologies it employs – natural language processing and language models (OpenAI, 2023) – are not new. Over a decade ago, IBM’s Watson used those AI approaches to win the Jeopardy! challenge (Baker, 2012). Language models are used in many public-facing technologies, such as personal assistants (e.g., Amazon’s Alexa, Apple’s Siri, and Google) and chatbots companies use for customer service (Adamopoulou & Moussiades, 2020). They have also entered educational spaces through essay scoring systems (Ramesh & Sanampudi, 2022; Schneider et al., 2022) and automated feedback systems (Chen et al., 2020).
However, ChatGPT nevertheless represents a significant departure from its predecessors. For one, it is publicly available, at least at the time of writing. More striking is its ability to parse natural language prompts and provide a wide array of human-like responses. It can provide reasonable answers to a great variety of questions (though certainly not all; Christian, 2023) and even more impressively compose entire essays in an array of styles (e.g., rap lyrics in the style of Snoop Dogg; Zahn, 2022). Moreover, much to the consternation of many educators, the text it generates gives few overt signs that a machine created it. ChatGPT might not employ radically new AI processes, but it does demonstrate what can happen when a truly enormous amount of computing resources and a staggering amount of data are brought to bear.
Since its release, ChatGPT has garnered a great deal of attention in education circles. Much of the initial discourse focused on the possibility of students using the chatbot to cheat (Rosenblatt, 2022). Its capabilities led some scholars to herald the death of English education (Herman, 2022) and essay writing (Marche, 2022) as we know it. For their part, colleges and universities scrambled to take action (Huang, 2023), and school districts such as New York City have banned ChatGPT outright (Elsen-Rooney, 2023). These conversations and developments are the latest entries in what seems like an ever-escalating and dichotomous arms race of ‘academic dishonesty’ on one side and ‘methods of detection and deterrence’ on the other. As technologies have given students novel ways to evade the mental workload of school (e.g., using the internet to search for information, using software to solve mathematical problems), new technologies have also been developed to surveil and constrain them (e.g., Respondus, 2023) – though often with problematic results (Flaherty, 2020, 2021; Grajek, 2020). True to form, ChatGPT is already spawning its own new wave of countermeasures (GPTZero, 2023; Rosalsky & Peaslee, 2023).
The initial panic has calmed (somewhat), and educators have begun to write about ways ChatGPT can be employed for more positive educational purposes (e.g., Ferlazzo, 2023; Shields, 2023). Rather than simply focusing on positive and negative use cases, important critical perspectives have also been brought to bear (e.g., Singer, 2023). For instance, in a recent blog post, Autumn Caines addressed critical ethical questions about students’ use of ChatGPT, providing suggestions for how to engage students in critical conversations about what it means to use the technology responsibly. Unfortunately, such nuanced and critical perspectives remain rare in the educational discourse.
As teacher educators working with pre-service and in-service public school teachers, we have watched this discourse unfold uneasily. We are not particularly concerned about how our teacher education students might use ChatGPT in our classes. Nevertheless, that does not mean that we should ignore it. Even though ChatGPT is unlikely to remain freely accessible, it will not be the last generative AI of its kind. Therefore, we need to think carefully about how to prepare teachers for an educational landscape in which AI technologies, from generative chatbots to scoring algorithms, will continue to be made more powerful and ubiquitous.
When working with teachers, we want to avoid conveying that ChatGPT threatens the integrity of education, against which a defense must be mounted. Treating it this way feeds into reactive conversations about the cheating/detection arms race, which will likely be of little lasting value. At the same time, we do not want to simply outline different ways to use ChatGPT for more positive educational purposes. Doing so would imply that it is just a “neutral tool” that can be put to various uses. Instead, we consider ChatGPT an opportunity to develop teachers’ critical thinking abilities about novel educational technologies. The provocative nature of ChatGPT creates a valuable and timely invitation to conduct critical inquiries into educational technology that are all too rare in teacher education programs (Bradshaw, 2017; Heath et al., 2023; Krutka et al., 2019, 2022).
Technical Capabilities and Uses is a Starting Point, not an Ending Point
· If you ask ChatGPT a question, how accurate is its response?
· What kinds of questions does it answer well, and which does it answer poorly?
· What genres of writing can it compose, and how well?
· To what extent are its responses distinguishable from a human's?
When we encounter new educational technologies, we often begin with these kinds of questions. We consider them tools and ask about their technical capabilities and potential uses (Selwyn, 2010). For example, we might imagine how a student could use ChatGPT when completing school tasks such as homework assignments or essays. Naturally, this provokes anxiety given that ChatGPT is not just assistive but can efficiently complete many assignments for the student. However, we can also imagine more positive use cases: a student could use it as an editor and collaborator rather than a surrogate writer or as a starting point to learn about a new topic (Ferlazzo, 2023; Pavlik, 2023).
Assessing a technology's technical capabilities and use cases is a fine place to begin. Unfortunately, all too often, this is as far as analyses of educational technologies go before judgments are made, and actions are taken (Selwyn, 2010). In the case of ChatGPT, the response has generally been to react to the harmful use cases (cheating) by constraining its use (Elsen-Rooney, 2023) or adjusting assignment and assessment protocols (Huang, 2023). The issue is that viewing technologies (educational or otherwise) merely as value-neutral tools with ‘good’ and ‘bad’ uses is a profoundly limiting perspective (Martin et al., 2020; Pleasants et al., 2019; Spector, 2016). Understanding a technology's uses and technical capabilities is necessary but woefully insufficient to understand its effects (Bonk & Wiley, 2020).
One crucial idea that the “tool” perspective misses is how, in using any technology, we are changed by it in ways that are unintended, unexpected, and often unnoticed (Carr, 2014; Ihde, 1990, 1998; Verbeek, 2005). Communication technologies from smartphones to email reshape work and social life in rarely anticipated ways (Newport, 2021; Turkle, 2012). Even “mundane” technologies change how we perceive and act in the world. When we sit behind the wheel of an automobile, we can seemingly become an entirely different person, often one who is more belligerent and impatient. Other people, especially those on bicycles, become little more than obstacles and impediments (Delbosc et al., 2019). Paradoxically, the technical capabilities of cars to move us around more rapidly are often accompanied by heightened feelings that we are never moving as fast as we want to be (Burkeman, 2021).
Also missing from the “tool” perspective is the recognition that technologies are part of broader social and technical systems. As elements of those systems, technologies inevitably interact with social values and beliefs, strongly influencing what those technologies do and their effects (Feenberg, 2010; Kranzberg, 1986; Van de Pol & Kroes, 2014). Those interactions with broader social systems cause the benefits and costs of seemingly neutral technologies to be distributed inequitably and disproportionately (Benjamin, 2019; O’Neil, 2017). For instance, critical studies of computer algorithms have shown how they reinscribe and reinforce societal biases and inequities, despite their ostensible impartiality (Bogina et al., 2021; Buolammini & Gebru, 2018; Eubanks, 2017; Noble, 2018).
In general, what is true for technology is also true for educational technologies. When educational technologies are introduced into a classroom, the changes they bring are both additive and ecological (Garcia & Nichols, 2021; Nichols & Garcia, 2022). Not all of those changes will be intentional, and while some might be desirable, others will be less so (Ciccone, 2022; Dixon-Román et al., 2020; Macgilchrist, 2021). They encourage and facilitate specific interactions and learning activities while discouraging others (Manolev et al., 2019; Teräs et al., 2020; Witzenberger & Gulson, 2021). Many of the complex ecological effects fail to be anticipated because educational technologies are not recognized as belonging to broader social and technical systems. The values embedded in those systems influence how developers design educational technologies, how they are utilized, and their effects on students and teachers (Garcia & Nichols, 2021; Selwyn & Bulfin, 2016; Watters, 2020). Even if unintended, educational technologies will be shaped by, and often reinforce, inequities embedded in those broader systems (Heath & Segal, 2021; Heath et al., 2023; Raji et al., 2020; Resta et al., 2018).
These are the kinds of understandings that we need to instill in our current and future teachers. To slightly modify the words of historian of technology Melvin Kranzberg (1986), teachers need to see that “[Educational] technology is neither good nor bad; nor is it neutral” (p. 545).
Enter ChatGPT
In many ways, ChatGPT provides an ideal object of study and point of entry into the broader and more perceptive ways of thinking about educational technology described above. The primary reason why ChatGPT is so well suited for this task is that its effects on education are anything but subtle. In the case of more mundane, everyday educational technologies such as PowerPoint or iPads, the ecological impacts on the classroom environment are potentially harder to recognize. While it may not be entirely clear what ChatGPT will do to education, it is much more apparent that its effects will be substantial and far-reaching. The fact that it has already spurred changes in so many classrooms (Huang, 2023) is evidence of its potential to transform teaching and learning (and not necessarily in desirable ways).
Yet even though the power of ChatGPT is evident, much of the discourse around it remains confined to “tool” perspectives. In holding up ChatGPT as an object of inquiry, we need to help teachers think about it in ways that go beyond listing its potential use cases. We especially need to help teachers go beyond merely discussing how to react to the specter of ChatGPT-based cheating. Below are some questions that could be used to initiate conversations about ChatGPT that give attention to those ideas:
1. Even if ChatGPT is free to use (for now), what costs are associated with using it? Who bears those costs?
2. What kinds of uses does ChatGPT encourage? Which does it make more difficult?
3. If students were to frequently use ChatGPT when completing assignments, how might that change the way they engage with school tasks more generally? How might it change the way that they interact with teachers and classmates?
4. How might using ChatGPT change the way that students and teachers think about the nature of writing? About the nature of knowledge? About the nature of learning?
5. What are some of the characteristics of our educational systems that make ChatGPT so threatening? How could those systems be set up so that ChatGPT would not be so threatening?
6. What and whose values are reflected in how ChatGPT was designed?
7. What societal values and biases are likely to exist in the data on which ChatGPT was trained? How might those values and biases manifest themselves when using it?
8. What educational biases and inequities might ChatGPT reinforce?
9. What would an AI system look like that was more aligned with your values as an educator?
10. What societal inequities does ChatGPT support or perpetuate, and how can its fairness and transparency be improved?
These questions are only starting points for deeper critical conversations about ChatGPT. Although many questions take a skeptical stance (Krutka et al., 2022), this does not necessarily mean that the inquiries will result in pessimistic or negative evaluations. Only some of the transformative changes that ChatGPT might bring are undesirable. It can, for instance, force educators to rethink their educational objectives and assessments. If the culminating assignment for a class is something that ChatGPT can complete, what does that say about the assignment? What does that say about the educational goals of that class? By rendering certain classroom tasks trivial, it can actually reveal a triviality that was already present. When we prepare students to merely complete the kinds of tasks that ChatGPT can do, we do little more than train those students to be machines (and be machined).
ChatGPT, though, is just a single point of entry into conversations and inquiries that ought to be had about any educational technology. We should help teachers apply the ways of thinking that they used for ChatGPT to other influential educational technologies. Teachers might, for instance, analyze other AI systems that have made their way into educational spaces. AI-powered “intelligent tutoring systems” (Ma et al., 2014) continue to be promoted as tools for individualized learning (Chen et al., 2020; Tetzlaff et al., 2021). Instead of narrowly examining their technical capabilities, teachers might analyze the values and beliefs built into those systems. Clearly, personalized AI tutors were not designed from sociocultural perspectives on learning (e.g., Rogoff, 2003; Vygotsky, 1978). They instead employ a behaviorist view of learning, one that imagines it to be a reinforcement-driven process of knowledge and skill acquisition, which can presumably be made more efficient via the use of data to employ “effective” teaching techniques (Biesta, 2010; Watters, 2021; Witzenberger & Gulson, 2021). They are tied to larger social systems that foreground data as an educational value (Nichols & Garcia, 2022; Selwyn, 2015; Selwyn et al., 2021). Recognizing those systems and values will raise teachers’ awareness of the kinds of impacts these technologies might bring.
Critical examinations need not and should not be limited to “cutting-edge” AI technologies. More everyday educational technologies, from whiteboards to learning management platforms to classroom furniture, are worthy of critical examination (Nichols & Garcia, 2022; Selwyn, 2023; Smith et al., 2005). As teacher educators, our goal is not to focus only on the latest educational technologies but to provide teachers with the conceptual tools to think critically and make informed decisions about educational technologies in general (Bradshaw, 2017; Heath et al., 2023; ISTE, 2018; Krutka et al., 2022). AI technologies like ChatGPT and others (e.g., facial recognition software and art generators) are starting points, not ending points, for critical thinking.
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