Using AI Tutors to Flip Your Classroom (Ethan Mollick); Examining the Efficacy of Inquiry-based Approaches to Education (David M Scott, Cameron Smith, Man-Wai Chu, and Sharon Friesen); Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning (David Baidoo-Anu, Leticia Owusu Ansah)
Using AI Tutors to Flip Your Classroom
Ethan Mollick’s discussion of AI tutors in a flipped classroom model offers insights into the evolving nature of education, particularly in relation to active learning and student agency. His argument that AI will not replace teachers but instead transform instructional methods is particularly resonant and is supported by my experience in the classroom and in my research. Traditional lecture-based teaching, which often reinforces passive learning, is increasingly out of step with the cognitive demands of today’s learners. Mollick notes that while a well-delivered lecture can be effective, too often lectures fail to engage students in meaningful ways. Instead, flipped learning provides a far more effective model.
Mollick highlights how AI tutors might enhance the flipped classroom by providing personalised learning experiences outside of class. He observes that AI-driven learning tools can allow students to interact dynamically with content, answering their questions and adapting instruction based on individual needs. This means students arrive with foundational knowledge already in place, allowing for richer in-class discussions and collaborative work. AI-powered instruction is not just about content delivery; it is about scaffolding learning so that students can engage meaningfully with complex ideas. The goal is not for students to passively receive information but to critically engage with historical narratives, sources, and perspectives.
One of Mollick’s most compelling points is that AI tutors allow educators to move beyond the constraints of one-size-fits-all teaching. He notes that AI can analyse student performance to detect misconceptions and gaps in understanding, allowing teachers to tailor their instruction accordingly. Rather than struggling to differentiate instruction within a limited class period, teachers can use AI-generated insights to identify where students are excelling or struggling. This complements my research into the role of technology in history classrooms, particularly in how it can be used to develop student agency. Inquiry-driven learning, which is foundational to my pedagogical approach, requires students to not only access historical information but to actively question, interpret, and construct meaning from it. AI tutors, when used effectively, can help facilitate this process by ensuring students are well-prepared to engage in complex historical thinking tasks during class time.
Mollick also discusses the role of AI simulations in education, illustrating how they can create immersive learning experiences that allow students to explore historical and scientific phenomena dynamically. He references an AI-generated simulation that enabled students to engage with historical scenarios in ways that encouraged creativity and problem-solving. This aligns with my own work in developing AI-driven historical simulations in my blog’s Chatbot Sandbox. These simulations are not designed to replace traditional research methods but to complement them, allowing students to interact with historical concepts in ways that encourage deeper engagement and critical thinking.
The implications for teacher education are profound. If AI tutors and flipped learning are to be integrated successfully, educators must be trained not only in how to use these technologies but in how to design learning experiences that maximise their potential. Mollick points out that AI can alleviate some of the workload associated with lesson planning, allowing teachers to focus on creating richer, more interactive classroom experiences. This aligns with a broader need to rethink pedagogical approaches in the digital age, ensuring that emerging technologies reinforce, rather than replace, the fundamental principles of good teaching.
Mollick’s work underscores a key tenet of my own research: technology, when thoughtfully implemented, has the potential to enhance rather than diminish student learning and agency. Flipped learning, supported by AI, offers a way to move beyond rote memorisation and passive content consumption, instead creating classrooms that prioritise inquiry, collaboration, and deep engagement with knowledge. The challenge now is not whether to integrate AI into education, but how to do so in a way that truly empowers both students and educators.
Examining the Efficacy of Inquiry-based Approaches to Education
Inquiry-based learning has long been a contentious topic in educational discourse, with critics often conflating it with discovery learning – an unstructured approach that offers little guidance to students. However, a careful reading of the research suggests that this is a misrepresentation. This article provides a crucial clarification: criticisms of inquiry-based learning are largely directed at discovery learning, which indeed has limited educational value. In contrast, guided inquiry and problem-based learning -when structured effectively – offer significant pedagogical affordances that align with both traditional education and authentic learning movements. In an age where generative AI is becoming ubiquitous, these distinctions become critical.
One of the most compelling arguments put forward in the article is the necessity for educational policymakers and practitioners to actively engage with critics who mis-characterise inquiry-based learning. The authors argue that education authorities should explicitly differentiate between flawed minimally guided “discovery learning” approaches and structured inquiry approaches that incorporate scaffolding, direct instruction, and iterative feedback. These approaches are typical of history classrooms. This is particularly relevant as education systems worldwide navigate curriculum reforms and pedagogical shifts in response to emerging technologies. Inquiry learning, when implemented effectively, is not in opposition to direct instruction but rather works in tandem with it, leveraging its strengths while fostering deeper student engagement and understanding.
For history educators, especially those adopting technology-infused pedagogies, this article offers important insights. Inquiry approaches are consistent in history classrooms with the flipped classroom model. For instance, students in such classrooms engage with foundational knowledge before class, allowing in-person sessions to focus on higher-order thinking, discussion, and inquiry. The structured nature of flipped learning mirrors the principles of guided inquiry – students are not left to ‘discover’ content unguided but rather work through carefully designed tasks that encourage analytical thinking and interpretation. This is particularly pertinent when integrating AI into history education. Generative AI tools like ChatGPT can provide instant access to historical information, but without a structured inquiry framework, students risk engaging passively with AI-generated content rather than critically interrogating it.
By embedding guided inquiry into AI-enhanced learning environments, history educators can ensure that students move beyond merely consuming AI-generated responses. Instead, students can engage in processes akin to historical reasoning – evaluating sources, cross-referencing perspectives, and constructing well-substantiated arguments. This aligns with the authentic education movement, which prioritises real-world problem-solving and meaningful student engagement. As the article suggests, well-designed inquiry approaches offer not only cognitive benefits but also help students develop agency, a crucial skill in navigating an AI-driven future.
As generative AI continues to disrupt traditional learning paradigms, I believe that the research reaffirms the enduring importance of inquiry-based learning. Inquiry-based learning that is true to its Deweyan origins in that it is structured, guided, and purposefully designed. By aligning these inquiry approaches with flipped learning and AI integration in the history classroom, educators can create environments that foster deep learning, critical thinking, and student agency. The challenge now is not whether to adopt AI in education but how to ensure that its use reinforces, rather than undermines, foundational pedagogies that promote genuine understanding.
Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning
Baidoo-Anu and Owusu Ansah, in 2023, were quick to explore the transformative role of generative AI, particularly ChatGPT, in shaping the future of education. They argue that as AI becomes increasingly embedded in professional and societal spaces, schools must adapt by integrating generative AI tools into classrooms. They argue that teaching students how to use these technologies constructively and safely is not just an educational imperative but a critical step in preparing them for an AI-dominated workforce. Educators, rather than resisting these advancements, could harness models like ChatGPT to support student learning, offering new ways to personalize instruction, foster engagement, and enhance critical thinking skills.
The study highlights several potential benefits of AI in education, including its capacity to provide personalised tutoring, automate assessments, and facilitate interactive and adaptive learning. ChatGPT can act as an always-available tutor, responding to individual student needs, offering explanations, and adapting to different learning levels. In assessment, AI can support teachers by automating grading, generating formative feedback, and even assisting in creating exam questions, allowing educators to focus on higher-order pedagogical tasks. Another advantage lies in accessibility, as AI-powered translation and text-generation tools can support non-native speakers and students with disabilities, helping to bridge gaps in educational equity. Additionally, generative AI can enhance teacher efficiency by streamlining lesson planning, summarizing complex texts, and developing instructional resources, ultimately allowing teachers to dedicate more time to student engagement.
Despite its potential, the study also acknowledges several challenges and limitations. One significant concern is the lack of human interaction in AI-driven learning. While ChatGPT can provide immediate responses, it cannot replicate the nuanced guidance, mentorship, and emotional intelligence that human teachers bring to the learning process. Another issue is bias within AI models, as generative AI is trained on large datasets that may inadvertently reinforce stereotypes or inaccuracies. This extends to misinformation, where ChatGPT has been shown to generate false or misleading content, including fabricated references. Without careful oversight, students may internalize incorrect information, highlighting the need for AI literacy and verification skills in education.
The question of equity also emerges as a pressing issue. While AI has the potential to democratize education by providing access to high-quality learning resources, there is also a risk that it could deepen the digital divide. Students and schools with limited access to advanced technology may be left behind, further exacerbating existing educational disparities. Ethical and privacy concerns add another layer of complexity, as AI tools process vast amounts of user data, raising important questions about how student information is stored, used, and protected. Additionally, over-reliance on AI may hinder students’ creativity and critical thinking, as generative models, while powerful, do not truly understand context or produce original thought. If not carefully managed, AI integration could lead to passive rather than active engagement with knowledge.
Given these opportunities and challenges, the study poses several urgent questions for educators, policymakers, and researchers. How can AI tools like ChatGPT be leveraged to support student learning without diminishing the role of teachers or critical inquiry? Should schools implement formal training for teachers and students on responsible AI usage? What role should AI play in teacher education programs to ensure that pre-service teachers are prepared to integrate these technologies effectively into their classrooms? Perhaps most significantly, will generative AI serve as a bridge to greater educational accessibility, or will it widen the gap between well-resourced and under-resourced schools?
The challenge ahead is not simply technological but pedagogical: how to use AI to empower students while preserving the essential human elements of learning.
Disrupted History 