Learning to Surf: Supporting a Campus’s AI Needs – Faculty Focus

Many colleges and universities have struggled to prepare for generative AI on campus, for instance, by providing guiding policies or pedagogical support. Centralized responses can be helpful but they are typically slow and expensive. To fill immediate gaps, smaller academic programs, such as Critical Thinking Initiatives and Centers for Teaching and Learning, can help campus communities begin engaging with generative AI thoughtfully while fostering student success and workplace readiness.   

To tame their anxieties about AI, faculty and administrators might embrace Howard Kabat-Zinn’s maxim, “You can’t stop the waves, but you can learn to surf.”  It’s time to get in the water. 

Three camps 

On most campuses, faculty fall into three camps:  those who want to “lock and block” AI (just stay out of the water!), those who encourage students to use AI freely in their writing processes (open-ocean swimmers), and, finally, those who want to embrace AI with guardrails (learning to surf). Open-ocean swimmers have argued that their strategy might equalize the playing field for students or mimic workplace writing processes. But experimenting with generative AI (GAI) teaches us that this casual approach might work for experts, but that it might rob students of the critical thinking skills granted by the writing process. Such a practice might also convince administrations that certain departments are unnecessary. At the other end of the spectrum, “lock and block-ers” have banned students’ GAI use altogether. Besides denying students the critical AI skills they may need in the workplace, this approach has often relied upon AI chatbot detectors, which have been proven unreliable and biased (Liang et al., 2023).  

Discord between these three camps, combined with slow university governance procedures, could force the AI waves to a Himalayan height. What can be done?    

Surfing lessons:  Integrating GAI support into an academic program 

I’ve led the Writing Across the Curriculum (WAC) program at CSUF—a large HSI, public land-grant university in Orange County, CA—since 2017. An experience that, when combined with teaching composition and serving as an academic senator, has informed my fathoming of the AI tides approaching higher education’s shores.   

What follows is a case study that can be adapted by a wide range of academic programs, such as faculty development centers, university learning centers, and writing centers. 

Testing the water:  AI boot camps 

As a low-stakes, first step, programs can offer AI-familiarizing experiences during summer or winter breaks.  At CSUF, the WAC program facilitated a summer “ChatGPT/LLM Boot Camp,” which delivered an accessible, open enrollment “GAI Faculty Resources” Canvas site to the campus.  Representatives from CSUF’s eight colleges, the DEI committee, our Instructional Designers team, our Office of Institutional Effectiveness and Assessment, and our Writing Center built the site together while testing the powers and limitations of the Large Language Models (LLMs) that power AI chatbots.  Faculty were paid a small stipend for their participation. Featuring general and college-specific annotated bibliographies, teaching resources, and syllabi guidance, among other things, the site has been consulted by over 500 CSUF faculty, staff, and administrators. 

With a stipend and cross-campus representation, other academic programs can support AI literacy on campus with similar immersive, community-building experiences. 

Riding the first wave:  Proposing AI-infused academic programs 

A boot camp is a solid start, but colleges need more expansive outreach to buoy faculty whose anxiety and burnout on many campuses are palpable. Faculty need empathetic support as they adapt to the technologies encroaching upon their familiar pedagogies. To support them, I proposed connecting writing and AI pedagogies in a new “WAC LIAISONS” program. 

As a writing program administrator, I often deploy “Design Thinking” in my problem solving, which borrows liberally from rhetorical theory. As disciplinary experts, we sometimes rush into the first solution that our expertise suggests to us. Design Thinking (DT) reminds us instead to begin with audience analysis: the first step in DT is to consider your “users’” needs (Raz 2018).  

Directors crafting proposals for new AI-infused programs must first consider their students’ needs, their faculty’s’ needs, and their institution’s needs. “User” needs relevant to CSUF’s WAC LIAISONS program break down into three categories, which exist at many campuses: 

  1. Research-informed GAI policies 
  2. Professional development and community building for adapting to AI in the classroom 
  3. Assessment of student and faculty AI applications 

Next, leaders can propose activities that meet users’ needs while also satisfying their own program’s outcomes.  For our LIAISONS program, these activities included:   

  • Need #1: Advising university senate committees as they draft campus AI-use policies.  
  • Need #2: 
    • Offering professional development workshops on interrogating and integrating AI in the classroom, including a series on developing AI-informed writing intensive courses.  
    • Facilitating a WAC LIAISONS Faculty Learning Community (FLC) who, besides liaising for their colleges, will produce model writing intensive syllabi with suggested AI policies as well as activities that invite students to engage critically with AI.     
    • Facilitating an annual summer GAI Boot Camp which will respond to future technologies, including opportunities and limitations.   
  • Need #3: Assessing the impact of faculty and student use of AI. 

Performing a needs analysis will help program directors identify suitable strategies for specific campus communities and departments.  Directors might, for instance, facilitate an FLC dedicated to updating general education learning goals or design a workshop series for developing AI literacy in tandem with critical thinking skills.     

Budgeting: New program proposals must request funds to stipend members of intensive faculty professional development projects. Directors can expand their program’s outreach by collaborating with other units. For instance, deans may pay additional faculty members’ stipends or support a community-building “AI Café,” at which faculty can celebrate or critique the steps along their AI-ready transitions. Program directors should propose appropriate salary increases or rank changes as well, because this work adds rapid updating of currency in GAI’s developments to directors’ established duties.   

Scanning the horizon:  Assessing AI-supportive programs 

In 2024, I will continue teaching faculty and students the value of “writing to learn” even as we explore how AI might impact that important cognitive process. In addition, I will support faculty as they design authentic assessments that incorporate AI. Universities must assess AI use, not just in the academic programs directly addressing it, but also in classrooms.  A simple example of the former would be determining the percentage of faculty who write “AI-ready” syllabi after using a campus’s AI professional development resources.  An example of the latter would consider students’ needs and achievements.  For instance, because ethical communication is a general education learning goal at CSUF, I can partner with our GE Assessment Committee to gauge students’ achievement of this goal before and after faculty integrate responsible AI-use curricula into their classes.   

Sharing our boards 

Many academic programs will benefit from AI-informed retoolings like these. Directors revamping programs should first ask what their “users” need, then study how they might serve those needs while meeting their programs’ performance outcomes. To increase the chances of budgetary support, directors should provide evidence for the campus need and explain how they will assess the impact of their interventions.   

The ways humans write and research are changing, as they did when the internet was introduced. I could tell you how my students and I are currently using AI, but I can’t predict what writing processes will look like in ten years, or even in five. I may not like the changes, but there’s likely no going backwards: Duolingo and Khan Academy customize tutoring for students with AI, and Microsoft’s 365 AI “Copilot” integrates AI into the entire Office suite. In my mind, it is an ethical obligation to prepare every instructor and student to write and learn critically with AI. Linking AI to our academic programs can help campus communities surf the AI waves, rather than founder in them.   


Leslie Bruce earned her PhD in English from USC and her BS in Zoology from CSU Long Beach.  She’s taught composition and literature in California State University, Fullerton’s Department of English since 2007. She’s been honored with CSUF’s “Outstanding Lecturer Award” (2022) and has received an NIH grant for interdisciplinary curricular development (2012-15).  In 2017, she inaugurated CSUF’s Writing Across the Curriculum (WAC) Program, which she transformed into the “WAC LIAISONS” program in 2023.  Leslie’s professional development cultivates faculty’s ability to teach with writing and to adapt to AI’s presence in education.

References 

Liang, Weixin, Mert Yüksekgönül, Yining Mao, Eric Q. Wu, and James Zou. 2023. “GPT Detectors Are Biased against Non-Native English Writers.” Patterns 4 (7): 100779. https://doi.org/10.1016/j.patter.2023.100779.  Accessed Jan. 3, 2024. 

Raz, Ariel. 2018. “Get Started with Design Thinking — Stanford d.School.” Stanford d.School. February 7, 2018. https://dschool.stanford.edu/resources/getting-started-with-design-thinking.  Accessed Jan. 3, 2024. 

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