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What do AI chatbots really mean for students and cheating?

October 31, 2023 By

Carrie Spector

The launch of ChatGPT and other artificial intelligence (AI) chatbots has triggered an alarm for many educators, who worry about students using the technology to cheat by passing its writing off as their own. But two Stanford researchers say that concern is misdirected, based on their ongoing research into cheating among U.S. high school students before and after the release of ChatGPT.

Here, Lee and Pope discuss the state of cheating in U.S. schools, what research shows about why students cheat, and their recommendations for educators working to address the problem.

What do we know about how much students cheat?

Pope: We know that cheating rates have been high for a long time. At Challenge Success we’ve been running surveys and focus groups at schools for over 15 years, asking students about different aspects of their lives — the amount of sleep they get, homework pressure, extracurricular activities, family expectations, things like that — and also several questions about different forms of cheating.

For years, long before ChatGPT hit the scene, some 60 to 70 percent of students have reported engaging in at least one “cheating” behavior during the previous month. That percentage has stayed about the same or even decreased slightly in our 2023 surveys, when we added questions specific to new AI technologies, like ChatGPT, and how students are using it for school assignments.

So AI isn’t changing how often students cheat — just the tools that they’re using?

Lee: The most prudent thing to say right now is that the data suggest, perhaps to the surprise of many people, that AI is not increasing the frequency of cheating. This may change as students become increasingly familiar with the technology, and we’ll continue to study it and see if and how this changes. But I think it’s important to point out that, in Challenge Success’ most recent survey, students were also asked if and how they felt an AI chatbot like ChatGPT should be allowed for school-related tasks. Many said they thought it should be acceptable for “starter” purposes, like explaining a new concept or generating ideas for a paper. But the vast majority said that using a chatbot to write an entire paper should never be allowed. So this idea that students who’ve never cheated before are going to suddenly run amok and have AI write all of their papers appears unfounded. What would you suggest to school leaders who are concerned about students using AI chatbots?

Pope: Even before ChatGPT, we could never be sure whether kids were getting help from a parent or tutor or another source on their assignments, and this was not considered cheating. Kids in our focus groups are wondering why they can't use ChatGPT as another resource to help them write their papers — not to write the whole thing word for word, but to get the kind of help a parent or tutor would offer. We need to help students and educators find ways to discuss the ethics of using this technology and when it is and isn't useful for student learning.

Lee: There’s a lot of fear about students using this technology. Schools have considered putting significant amounts of money in AI-detection software, which studies show can be highly unreliable. Some districts have tried blocking AI chatbots from school wifi and devices, then repealed those bans because they were ineffective. AI is not going away. Along with addressing the deeper reasons why students cheat, we need to teach students how to understand and think critically about this technology. For starters, at Stanford we’ve begun developing free resources to help teachers bring these topics into the classroom as it relates to different subject areas. We know that 3 teachers don’t have time to introduce a whole new class, but we have been working with teachers to make sure these are activities and lessons that can fit with what they’re already covering in the time they have available.

I think of AI literacy as being akin to driver’s education: We’ve got a powerful tool that can be a great asset, but it can also be dangerous. We want students to learn how to use it responsibly.

Available from: < https://ed.stanford.edu/news/what-do-ai-chatbots-really-mean-students-and-cheating>. Access: 08 Dec., 2023. Adapted. 

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    Building on the professional consensus that no method could claim supremacy, Prabhu (1990) asks why there is no best method. He suggests that there are three possible explanations: (1) different methods are best for different teaching / learning circumstances; (2) all methods have some truth or validity; and (3) the whole notion of what is a good or a bad method is irrelevant. Prabhu argues for the third possibility and concludes that we need to rethink what is “best” such that classroom teachers and applied linguists can develop shared pedagogical perceptions of what real-world classroom teaching is.

    H.D. Brown (2002), in his critique of methods, adds the following two observations: (1) so-called designer methods seem distinctive at the initial stage of learning but soon come to look like any other learner centered approach; and (2) it has proven impossible to empirically (i.e., quantitatively) demonstrate the superiority of one method over another. Brown (2002) concludes that classroom teachers do best when they ground their pedagogy in “well-established principles of language teaching and learning” (p.17).

    So what are these well-established principles that teachers should apply in the post methods era? One of the early concrete proposals comes from Kamaravadivelu (1994), who offers a framework consisting of 10 macro strategies, some of which are summarized below:

    – Maximize learning opportunities. The teacher’s job is not to transmit knowledge but to create and manage as many learning opportunities as possible.

    – Facilitate negotiated interaction. Learners should initiate classroom talk (not just respond to the teacher’s prompts) by asking for clarification, by confirming, by reacting, and so on, as part of teacher-student and student-student interaction.

    – Activate intuitive heuristics. Teachers should provide enough data for learners to infer underlying grammatical rules, since it is impossible to explicitly teach all rules of the L2.

    – Integrate language skills. The separation of listening, reading, speaking, and writing is artificial. As in the real-world, learners should integrate skills: conversation (listening and speaking), note-taking (listening and writing), self-study (reading and writing), and so on.

    – Raise cultural consciousness. Teachers should allow learners to become sources of cultural information so that knowledge about the culture of the L2 and of other cultures (especially those represented by the students) becomes part of classroom communication.

    – Ensure social relevance: acknowledge that language learning has social, political, economic, and educational dimensions that shape the motivation to learn the L2, determine the uses to which the L2 will be put, and define the skills and proficiency level needed in the L2.

(Celce-Murcia, M. 2001. Adaptado)