Step into any faculty meeting or office today, and you’ll likely hear discussions about artificial intelligence (AI). Some educators are embracing it eagerly, while others approach it with caution or reluctance. Most are grappling with how to integrate this potential shift without compromising the essence of their teaching.<\/p>\n
In the early stages of AI in education, a familiar trend is apparent. Faculty are leveraging AI to create quizzes, draft emails, prepare slides, and summarize text readings. These applications are useful as they alleviate the ongoing challenges of time management and routine administrative duties faced by faculty. However, these improvements in efficiency often do not translate into transformative changes in student learning experiences.<\/p>\n
This pattern is not unprecedented. Historically, educational technology has enhanced efficiency without fundamentally altering instruction. In many classrooms, technology improves the output\u2014quizzes, worksheets, presentations\u2014while leaving the student learning process unchanged. Generative AI could alter this, but only with a creative and different approach. Instead of asking, “How can I use AI?” the focus should be, “How can AI facilitate a transformative, student-centered learning experience?”<\/p>\n
The efficiency trap is widespread. Consider a basic example: quizzes that were once handwritten or sourced are now generated by AI in seconds. The process is quicker, but the instructional model remains unchanged. Research on technology integration reveals that many innovations support existing practices rather than transforming them (Cuban, 2018; De Leon, Martinez, Diaz, & Whitacre, 2019; Tondeur, Van Braak, Ertmer, & Ottenbreit-Leftwich, 2017). This is not due to an inherent resistance to change by instructors. Teaching is complex, and new tools must align with time constraints, institutional expectations, and ingrained pedagogical beliefs. Moreover, staff development is crucial for teachers to understand and incorporate innovations that have not existed throughout most of their careers.<\/p>\n
AI often enters classrooms initially as a productivity tool. Yet, its true value lies in its ability to support all students’ learning and reach those on the fringes of the classroom. How can AI help educators foster student-centered environments that empower and engage students? Achieving this requires a pedagogy-first approach.<\/p>\n
A useful reminder when working with instructional technology is to avoid equating technology integration with mere student device use. The focus should be on pedagogy. This concept is central to the TPACK Framework (Koehler & Mishra, 2009), which posits that transformative instruction occurs at the intersection of teacher knowledge in content, pedagogy, and technology. Technology is beneficial when it supports and enhances sound instructional goals, not when it’s an add-on. Similarly, the SAMR Model (Puentedura, 2012) offers a practical means to assess technology use. Initially, technology substitutes existing practices; at its most transformative, it enables previously impossible learning experiences.<\/p>\n
Neither framework requires instructors to be theorists. Instead, they prompt a simple reflective question: Is technology making learning different, or just more efficient? With this focus, here are three practical methods for using AI to support student-centered learning experiences.<\/p>\n
First, use AI for differentiation, not just generation. AI’s capacity to tailor learning materials for diverse learners is one of its strengths. Instead of assigning the same readings or tasks to all students, instructors can use AI to adapt complex texts, create podcasts, visual aids, and video summaries, provide vocabulary support, generate alternative explanations, and create stratified assignment versions. AI tools enable this kind of differentiation, allowing teachers to select modalities, reading levels, and vocabulary tiers suited to their students’ diverse needs.<\/p>\n
Try this: Begin with one reading per week. Employ AI platforms to create alternative versions such as leveled texts, podcasts, or video summaries, and offer them as options. Allow students to choose what aids their learning best. This approach enhances not just efficiency but also access and equity.<\/p>\n
Second, turn AI into a thinking partner. A common concern is that AI might replace critical student thinking. This risk is real but hinges on assignment design and modeling. When students use AI for final answers, learning may cease. However, using AI as a dialogue partner can deepen learning.<\/p>\n
Examples include history students interviewing AI versions of historical figures, business students debating AI-generated ethical dilemmas, education students analyzing classroom realities through AI-created cases, science students testing hypotheses with an AI “Lab Assistant,” and students exploring environmental standards through interactive AI. These interactive spaces and simulations promote student-centered pedagogy by encouraging analysis, reflection, and critique.<\/p>\n
Try this: Require students to submit a brief reflection detailing what AI got right, what it oversimplified or got wrong, and how the interaction influenced their viewpoint. Here, AI becomes a catalyst for critical thinking rather than a shortcut.<\/p>\n
Lastly, use AI to design enhanced learning experiences. While many instructors use AI to generate materials, fewer employ it to design learning experiences. This may be where the greatest value lies for student-centered realities. AI can help instructors generate discussion questions at various cognitive levels, create real-world scenarios for problem-based learning, develop layered formative assessments, and explore alternative activity formats.<\/p>\n
The key is to center student needs in your design. Try this: In lesson planning, ask AI for three ways students can explore a concept through discussion, collaboration, or problem-solving. Adapt the output to suit your context, expanding your teaching approach.<\/p>\n