How to Educate First-Year Science Students to Thrive with Critical Human Skills in the Age of AI?
Reform curriculum and build cross-sector partnerships in the community that we live in!
Preamble
Artificial intelligence (AI) is a disruptive technology with dichotomic impact on humanity across several societal dimensions. It displaces jobs but boosts productivity. It empowers some people with unimaginable power but can erode social relationships. Used poorly, AI risks miseducating students by replacing rigor and depth with shortcuts and convenience. But used wisely, it can personalize learning and democratize access to complex knowledge. On the other front, our society is increasingly challenging colleges to prioritize student-centered, career-relevant, and affordable education.
Under this societal context, I ask the question: How do we educate first-year science students to thrive with critical human skills in the age of AI? As a small example towards this grand challenge, I would like to share my current view as:
Why first-year science curriculum must be transformed.
How to initiate the transformation by design.
I selected the first-year curriculum as an initial testbed of AI infusion into science education, as I interact with first-year students everyday as their biology teacher and am responsible for biology and chemistry curricula and faculty hiring and development as Department Chair at my school. In brief, I hypothesize that this transformation requires building cross-sector partnerships among educators, founders, philanthropic funders, and corporate sponsors in the community that we live in. Note that this story represents a snapshot of my current thinking, which will undoubtedly and rapidly evolve with advances in AI.
Why Our Students and Our Community Need to Change Together
Every year, I see irreversible behavioral trends in first-year students in my classroom – exemplified by shorter attention span, less engagement, more focus on earning points, etc. I think the behavioral changes are not due to my students’ increasing laziness or lack of ability, but rather are shaped by digital media in which content is flashy, feedback is immediate, and depth is optional. For sure, my own attention span is usually not any longer than my students’ unless I am in my yoga class.
Yet I observe every year, too, remarkable growth of these same students when we discuss their results from capstone senior research projects. Students, when challenged and supported in the right ways, undergo incredible growth as confident learners, critical thinkers, and problem-solvers. Clearly, students need a nurturing environment that activates and cultivates their full potential.
However, as I will explain soon, the change to enhance the nurturing environment with AI, cannot rely on ad hoc classroom innovation alone due to AI’s dichotomic nature. I propose that the change must be designed into the curricular, institutional, and community levels. But how do we design the change to be safe, ethical, accessible, scalable, affordable, and accepted by our community?
Inspired by Two Visionaries: Envisioning Education with AI
Two recent books have deeply influenced how I now think about the future of science education. In Who Needs College Anymore?, Kathleen deLaski challenges us to imagine new institutional models – that prioritize learners and innovation over tradition. She offers a compelling vision with practical recommendations in transforming higher education for career relevance, personalization, skill-building, accessibility, and affordability. I agree with her that we must tackle these difficult challenges. I also think that AI provides many new opportunities to solve some of these challenges.
Equally influential is Stephen Kosslyn’s Learning to Flourish in the Age of AI, where he introduces the idea of using generative AI as a "cognitive amplifier." He invites us to harness AI, not to bypass thinking, but to elevate. With this use of AI, we can guide students to clarify goals, revise strategies, refine ideas, and practice higher-order thinking skills – analyzing, evaluating, and creating in accordance with Bloom’s taxonomy.
Critical Human Skills Enhanced by AI for Careers in Science
Taken together, Kossyln and deLaksi provide both the pedagogical foundation and practical guidance to envision a new kind of science education that can be enhanced with AI infusion. A practical outcome of such new curriculum is for students to acquire and practice critical human skills that cannot be easily automated, but actually enhanced by AI.
For scientific careers, I think the critical human skills are:
Scientific judgment that requires critical thinking and ethical reasoning.
Problem-solving that requires human interaction, collaboration, communication, and leadership.
Research skills rooted in hands-on laboratory experience.
Why Target Curriculum, Not Individual Courses First?
Over the past year, I’ve shared a personal journey exploring how generative AI might reshape my own teaching in an introductory biology course at my university. In my first Substack post, I described the impact of guided AI use on student motivation in the biology course. Learning introductory biology can be quite challenging and boring for many students due to significant memory barriers to overcome before being able to visualize, comprehend, and integrate high-level concepts in real-life context. Most students quickly lose interest in learning biology deeply, despite its relevance and importance in our daily lives.
For the past two semesters, I used ChatGPT-based AI Assistant for students to experience inquiry-based learning of high-level concepts in connection to real-world challenges. For example, students were asked to assess the AI Assistant-generated design of a scientific study relating to gene-edited chickens for avian flu resistance and the safety of eating such chicken from technical, ethical, and societal perspectives. Initial data, as reported in my previous story from Fall 2024 and reproduced in Spring 2025, suggest that the guided use of AI Assistant can certainly enhance student motivation.
However, as promising as my individual effort with AI may be, my experience invited many questions, for example:
I observed that first-year students have varying literacy, interest, and proficiency levels of generative AI. Obviously, I cannot use biology class time to provide basic training on generative AI. How do we provide basic AI training and infrastructure to all students – access, governance, and support - for safe, equitable, and meaningful AI use?
How much should students understand a concept (e.g., gene-editing) before they are asked to analyze an application derived from the concept (e.g., gene-edited chicken for avian flu resistance) using AI Assistant? In this example, AI Assistant was used to motivate students to learn about the topic, but not necessarily by design for them to develop critical thinking, problem-solving, and ethical thinking skills. How much time should I set side to go deeper on certain application topics in an introductory course? Who decides?
How do we meaningfully support every student’s unique learning path with AI use while maintaining academic standards? But, traditional courses – standardized and rigid often driven by available textbooks – have not kept pace and often disconnected from rapid technological and societal changes. How closely do we need to follow standards? Who decides?
These questions may reflect what a faculty member wrestles with daily adoption (or consideration) of AI in teaching and guiding students. I think these questions can more holistically be answered from the perspective of designing a curriculum that is more aligned with real-world careers that our students are motivated to pursue and are preparing for. Therefore, AI’s true potential will remain limited or even may be counter-productive unless we begin to think about its infusion at the curricular level.
A Hypothetical First-Year Science Curriculum
For AI infusion into the science curriculum, I think designing the first-year experience is the most critical and consequential theater. This is when students begin to form not only their scientific understanding, but also their sense of purpose and identity. In my recent Substack story on career role models, I described how introducing real-world professionals working in various sectors of our local economy, e.g., industrial scientists from pharmaceutical companies, clinicians practicing in medical centers, biotech entrepreneurs, patent lawyers, corporate executives, private equity consultants, science teachers, etc., into the classroom can make scientific careers real to our first-year students. These encounters are used to motivate, inspire, and challenge students to assess career pathways, think about options, and learn to develop a career plan that is aligned with a study plan. Starting this fall, we plan to ask:
Working professionals, as career role models, to share how AI impacts their workplaces and offer practical advice on appropriately leveraging AI in their career paths.
Students to critically examine and articulate their own perspectives on AI's role in their academic studies and future careers.
This career pathway seminar course anchors the AI-infused curriculum envisioned for real-world careers. The curriculum is to be modular, hybrid, stackable, accessible, and affordable. Core and inter-connected elements of the curriculum are:
AI-enhanced human skills for scientific careers – Career exploration, research method practicum, and ethical thinking and decision-making.
Computer science – Application of coding, AI/ML, generative AI for scientific problem-solving.
Biology I and II – AI-infused, project-, inquiry-, team-, and lab-based experiential learning
Chemistry I and II – AI-infused, project-, inquiry-, team-, and lab-based experiential learning.
Plus – Mathematics, physics, writing, communication, and humanity.
Plus - Externships and micro-internships
For example, Biology I is being brainstormed for hybrid modality, consisting of:
Synchronous online (1 credit) – AI-assisted, inquiry- and team-based learning through capstone projects.
Synchronous online (2 credits) – Self-paced and AI-powered learning of foundational concepts connected to capstone projects.
In person lab (1 credit) – 1-week immersive experience, complemented with asynchronous online pre- and post-lab work.
This kind of hybrid learning experience can help students develop and practice critical human skills: collaborative problem-solving through critical and ethical thinking, connection to and exploration of concepts, and developing hands-on skill through in person lab experience. And yet, self-paced and AI-powered learning provides accessibility and affordability.
This hybrid modality cannot be implemented today at my university due to incompatibility with our institutional model. However, it could be offered as dual-enrollment course modules for pre-college students, especially for homeschooled students. Also, I envision the offering of these modules as micro-credentials to serve pre-college students in our local community by creating a nonprofit, hybrid learning center through cross-sector partnership with high schools, colleges, philanthropic investors, and corporate sponsors.
Changing Roles of College Educators
Under the hypothetical curriculum, we can also reimagine the roles of educators in future. It will certainly demand a lot more than knowledge transfer. We must transform ourselves to function as:
Trusted human guides. We serve as human guides who students trust for human interactions and interventions grounded in subject matter expertise.
Creative designers. We design authentic learning activities that resonate with students and their changing learning habits. For example, I described how I produced my first interactive instructional video in under one hour using AI tools. I anticipate that AI can help educators become more creative and productive.
Technology integrators. We integrate multimedia tools and AI platforms and are willing to provide continuous human support and feedback, as needed, to students.
This isn’t about replacing teaching jobs - it’s about elevating our roles, expanding our toolbox, and re-centering our function in the emerging age of AI. The promise of AI-infused education will only be fulfilled if we, the educators, lead the endeavor.
Can We Build a Community?
As Kathleen deLaski argues in Who Needs College Anymore?, the future of higher education must prioritize personalization, skills-based learning, accessibility, affordability, and above all, adaptive institutional models. The transformation of higher education will not come from a collection of heroic individual efforts, however inspiring they may be.
Success of the transformation will come from:
Institutions that commit to innovation.
Local communities that invest in students’ future.
Educational ecosystems that are willing to evolve.
Importantly, AI infusion must propagate to local communities by building cross-sector partnerships with high schools, community colleges, tech founders, philanthropic investors, and corporate sponsors. These partnerships provide both societal relevance and support structure that make new educational practice to become sustainable, scalable, accepted, and trusted.
While this story reflects one educator’s evolving perspective, it also points to the scale and complexity of what lies ahead. If we are serious about transforming science education for the age of AI starting with first year curriculum, we will need more than good ideas. What’s needed now are experimental pilots, shared infrastructure, and new models of learning that can be explored, tested, and improved together. I hope this story encourages others to join and brainstorm in building together a new community, wishfully from New Jersey’s Hudson county where I work.
If we were to build this community today, I would name this community, “ExploreABC,” i.e., Explore AI, Biology, and Chemistry!