Radically rethinking teaching methodologies Transforming education with artificial intelligence necessitates a nuanced blend of traditional and innovative approaches. Returning to basics, such as reinstating in-class essays, could ensure that every word reflects a student’s personal opinion, devoid of AI assistance. Some educators, including myself, have already embraced AI in their curricula. Students are permitted to use the tool, but transparency is mandatory, potentially elevating the quality of homework while simultaneously complicating assessment and the intrinsic value of assigned work. The radical overhaul of teaching methodologies, such as flipped classrooms – where lessons are learned at home and assignments completed in class – may offer a proven solution to this current quandary. Transforming reading sessions into in-class group discussions allows students to share perspectives in real time, thereby fostering a richer learning environment. Integrating AI, rather than opposing it, can serve as a valuable learning tool, enabling students to contrast their analysis with those generated by AI and identify both similarities and differences. Assignments could be reimagined to emphasise critical thinking, encouraging students to debate AI analysis or create content inspired by their readings, including plays, poems and short stories. Moreover, traditional assignments such as problem-solving exercises, quizzes and other assessment methods are undergoing significant transformations. Problem-solving – a fundamental skill taught across disciplines – is experiencing a revolution. Historically, it reflected a student’s ability to analyse, break down and devise solutions to complex challenges. Today, it faces the ascendancy of AI titans. GPT4 can now solve problems with a finesse that rivals our students. This LLM can access databases and real-time information with increased accuracy, making errors rare and often indistinguishable when the problem is already known. Traditional verification methods quickly become obsolete, raising serious questions about academic integrity. In response to this shifting landscape, there are several strategies that educators might care to consider: reverting to fundamental, in-class assessments where students are observed solving problems, potentially normalising such practices; grappling with the ethical and practical challenges of banning AI; or integrating AI into pedagogical methods, allowing students to use it as a tool along with the required transparency. This could enhance classroom discussions but also raise evaluation questions. Ultimately, adopting active learning methods, where students tackle problems in class using resources that include AI, might emerge as a viable solution to reinvent education for the modern era. Banning AI outright presents a tempting, albeit challenging, option due to the difficulty in defining and controlling it in a world in which reliance on digital technology is growing almost daily. The primary motivation for implementing AI detection tools is, in my opinion, to maintain a ‘business-as-usual’ state of affairs and prevent or restrict another learning experience transformation as occurred in the wake of the Covid pandemic. Students’ reliance
on generative AI would be strictly prohibited in instances where there is proof of its use. This is one of the gravest errors that an academic institution (particularly one of higher learning) can commit, given that this technology is already influencing the work of millions of people and our relationship with information. Detection dilemmas and educational enhancements To assess the complexity of a given text, AI detection algorithms quantify the degree to which the selected words elicit astonishment. Texts containing frequent English words with a low perplexity score are more likely to be identified as AI-generated. Meanwhile, texts containing intricate or fantastical vocabulary are assigned a greater perplexity score, thereby enabling their classification as human-authored. Due to the biases of these tools, the work of non-native English speakers, who frequently employ uncomplicated words, may be erroneously identified as AI-generated. Moreover, negative effects on the mental health of pupils may result from AI detectors producing false positives, inducing excessive stress, anxiety and demotivation. They may also develop a sense of mistrust or unjust judgment, which can diminish their confidence and interest in the learning process. To transform pedagogy with the integration of artificial intelligence, particularly leveraging LLM tools such as ChatGPT or Google Gemini, educators can adopt a multi-faceted approach that enriches learning experiences and cultivates critical thinking skills. Role-playing simulations facilitated by LLMs can offer students in fields such as psychology or
26 | Ambition | MAY 2024
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