2026 Poster Sessions

Outcomes 

• Helping educational leaders understand how to better-serve Latinx students, especially in white-dominated contexts 

Description 

In 2021, I interviewed 54 Latinx high school graduates from 19 different Marin County high schools who attended high school between 1996 and 2021. During the interviews, I asked them all to share recommendations on what they thought schools could do to make Marin County high schools a more accessible and hospitable place for future generations of Latinx students. I would like to share my findings about their answers, ranging from school staff recommendations, curriculum/electives suggestions, immigrant students' suggestions, and much more. I would like to share a 5 to 10-minute pre-recorded (asynchronous) Zoom poster session on these findings in hope that they are helpful to current and future educators.

Outcomes

• Identify course design strategies for weaving AI literacy into writing and ESL instruction. 

• Describe how thematic anchors like digital wellness and technological integrity can build critical thinking in a language course. 

• Consider a culminating reflective project — like an AI manifesto — as a tool for learner agency in tech-integrated courses. 

• Reflect on equity-centered design that prepares diverse community college students for a tech-driven workforce.

Description

Many ESL students at community colleges are already using AI tools to navigate daily life; translating documents, drafting emails, decoding bureaucratic language, yet few have been invited to think critically about those tools or claim authority over them. Writing with Digital Tools at CCSF was designed to change that.

Designing this course meant sitting with a real contradiction: AI tools can level the playing field for multilingual writers, or they can quietly undermine the very language development ESL students need most. Rather than ban AI or uncritically embrace it, this course asks students to interrogate it. Through themes of digital wellness, global leadership, and technological integrity, the course fosters personal, academic, and career growth for students navigating a tech-driven workforce.

The course culminates in a personal AI manifesto, a document in which each student articulates, in their own voice, what they believe about AI, how they will and won't use it, and why. It is part ethical statement, part career vision, part act of authorship. For many students, it is the first time they have been asked to hold an opinion about a technology already shaping their lives.

This session offers an honest reflection on designing this course — including what worked, what was surprising, and what remains an open question. It is an invitation to think together about what equity-centered AI literacy can look like in the community college writing classroom.

Outcomes

• Apply lessons learned from the pilot to develop professional development structures or mentoring frameworks.  

• Develop actionable strategies to strengthen belonging and professional growth. 

Description

This session presents the results and emerging insights from the Faculty Women of Color Peer Mentoring research study, an equity centered pilot designed to foster community, connection, and professional growth for faculty navigating online institutional contexts. Building on the initial implementation, this follow up from the session presented at Peralta in 2024, highlights how structured peer mentorship served as a catalyst for strengthening belonging, enhancing leadership pathways, and improving faculty experiences in virtual academic environments. Drawing from participant feedback and reflective narratives the session will share which components of the mentoring model yielded the greatest impact. 

Participants will leave with practical tools for applying lessons learned from the pilot to their own settings, including how to design or adapt professional development structures that center the needs of historically underrepresented faculty.

This session is ideal for those committed to building inclusive, supportive ecosystems for faculty in online environments.

Outcomes

• Describe ways AI tools in hiring and advising can reproduce human and institutional biases with consequences for student equity and career pathways. 

• Identify specific course  and program level practices that help students critically examine AI, manage biases and assumptions, and reduce institutional barriers in online learning contexts. 

• Propose at least one concrete teaching or support strategy that integrates intercultural and global competence into AI related learning and career preparation.

Description

Artificial intelligence (AI) increasingly shapes both how students learn and how they access future employment. This prerecorded digital poster session examines how AI mediated tools in hiring, advising, and educational technologies can function as both gatekeepers and gateways for online learners, with a focus on equity minded pedagogy. Drawing on brief case examples, the session highlights how human biases, institutional assumptions, and structural barriers are encoded into AI systems.

The poster emphasizes practical strategies for instructors and academic support professionals to: make AI and equity explicit topics of inquiry; identify and interrupt biases and institutional barriers that disadvantage marginalized students; and integrate intercultural and global competence into assignments, examples, and discussions about work and professionalism. Viewers are invited to reflect on their own contexts through three guiding questions and to identify one concrete change they will pilot in a future term. The overarching aim is to position AI not as a neutral add on, but as a critical site of ongoing equity, pedagogical, and global learning work.

Outcomes

• Identify how Universal Design for Learning guidelines can be incorporated into the way online discussions are created.    

• Describe the benefits of allowing students choices in what they post and how they engage in discussions. 

Description

For faculty who use online discussions, this poster will describe how to create inclusive discussions using Universal Design for Learning principles for engagement, representation, and action and expression. Choices are the hallmark of UDL so that each student can find the learning path that works best for them. Clear examples of choices in content and format for online discussions will be provided, as well as a template for offering choices as part of the discussion prompt. In addition, how each choice supports the UDL principles will be explained, along with an explanation of the benefits, including engagement, creativity, equity, student performance, and instructor satisfaction. 

Outcomes

• Explore student perspectives on how the implementation of educational technology may reproduce or challenge existing social inequalities present in higher education through an investigation that explored the ecosystem of technologies that low-income, first-generation students use, their navigation of systemic challenges, and the assets and resilience strategies they employ.

Description

This session will present findings from a qualitative study that investigated how low-income, first-generation students navigate the digital landscape of higher education. Grounded in the frameworks of Critical Studies of Educational Technology and Community Cultural Wealth, the study explored the ecosystem of digital tools that low-income, first-generation students curate for their learning and the navigational capital they develop to overcome systemic challenges. The presentation will provide a student-centered description of technology-mediated learning and offer a roadmap for aligning campus technology infrastructures with the existing cultural wealth of diverse student bodies.

Outcomes

• Identify at least three practical ways AI can be used to reduce barriers and support Universal Design for Learning in online courses.   

• Apply simple AI prompting strategies to improve accessibility, clarity, and inclusive course design without increasing instructor workload.

Description

Artificial intelligence is rapidly changing how we teach and design courses, but many educators are still asking a practical question: How can AI actually help my students right now? This session offers a concise, hands-on walkthrough of ways instructors can use AI tools to reduce barriers, strengthen Universal Design for Learning (UDL), and increase equity in online and hybrid courses—without adding significant workload.

Participants will explore simple, realistic strategies for using AI to support accessibility and inclusive course design. Examples include generating clearer instructions, drafting alt text and captions, and quickly revising materials for readability and accessibility. The session will also highlight ways AI can help instructors anticipate learner needs, offer multiple pathways for engagement, and make course content more flexible and inclusive.

Rather than focusing on complex tools or technical expertise, this session emphasizes practical applications educators can implement immediately. Attendees will leave with concrete ideas, sample prompts, and a mindset for using AI as a supportive design partner—helping create more accessible, human-centered online learning environments for all students.

Outcomes

• Identify and refine faculty development opportunities for equity in online teaching that recognize real-life faculty constraints.

Description

This poster session discusses a tool for developers to use before launching a workshop, series, or initiative that supports equity-based online teaching. The goal is not to lower expectations—but to design for equity in teaching in ways that recognize real-life faculty constraints. This tool is designed for individual or team use. It works best when revisited iteratively and treated as a design constraint (ie action)—not only as reflective exercise alone (ie thinking).

Outcomes

• Explain how displaying bias scores to learners influences trust, confidence, and decision-making, based on empirical evidence from a controlled behavioral study.  

• Analyze the role of bias disclosure in shaping learner perceptions of fairness, credibility, and responsibility in AI-supported environments.  

• Apply research-informed guidelines to decide whether, when, and how bias information should be shared with students in online or AI-enhanced courses.

Description

As artificial intelligence becomes increasingly embedded in online learning environments, concerns about bias, fairness, and equity have moved from theoretical discussions to practical classroom decisions. One emerging approach to addressing these concerns is bias transparency, the practice of displaying bias scores or labels alongside AI-generated content. However, little empirical evidence exists on whether this transparency actually improves equity outcomes for learners. This research presents findings from a behavioral study examining how the visibility of AI bias scores influences users’ trust, confidence, and decision-making in different scenarios. Participants explored a set of AI-generated prompts that vary in bias level and compared outcomes between conditions where bias scores are shown versus hidden. The results highlight both the potential benefits and unintended consequences of bias disclosure, including cases where transparency may increase awareness and accountability, as well as situations where it may not be helpful for certain learners. The session will situate these findings within broader conversations about online equity and responsible AI use in education. Participants will be guided through practical considerations for deciding if, when, and how bias information should be shared with students in AI-supported courses. The goal is to move beyond simple calls for transparency and toward evidence-informed, equity-centered design choices for online learning environments.

Outcomes

• Describe how AI tools can be used to support multilingual writers in online composition courses while maintaining student authorship and academic integrity.  

• Identify instructional strategies that help multilingual students analyze academic language conventions such as tone, vocabulary, and rhetorical structure.  

• Apply classroom activities that use AI as a tool for reflection and language awareness in order to promote linguistic equity in online writing instruction.

Description

Discussions about artificial intelligence in writing instruction often focus on academic integrity and concerns that students may rely on AI to generate their work. In courses serving multilingual writers, however, AI also raises deeper questions about language, voice, and linguistic equity. This pre-recorded asynchronous presentation examines how AI can be used thoughtfully in online composition courses to support multilingual students as they develop confidence in academic writing.

Many English language learners arrive in college with complex ideas and strong rhetorical awareness but encounter difficulty navigating the conventions of standardized academic English. In online learning environments, where opportunities for conversation and immediate feedback may be limited, these challenges can become even more pronounced. Rather than viewing AI primarily as a threat to authentic writing, instructors can use it as a tool to help students analyze how academic language functions.

Drawing on experience teaching ESL composition, this presentation shares classroom practices that position AI as a tool for reflection and language awareness. In guided activities, students draft their own responses and then compare their writing with AI-generated text, examining differences in tone, vocabulary, and rhetorical structure. These comparisons help students see academic English as a set of conventions that can be studied and navigated rather than a fixed standard they must simply imitate.

Framing AI in this way shifts the focus from surveillance to linguistic equity. Multilingual writers gain greater awareness of academic discourse while maintaining ownership of their ideas and voice.

Outcomes

•  Identify key components of a Digital Learning Equity Analysis protocol for reviewing online courses.   

• Describe three equity-centered design practices (pedagogy of care, culturally responsive teaching, and open education pedagogy) that support nontraditional online learners.   

• Recognize opportunities and risks of AI tools when applied to equity-centered course design.

Description

As artificial intelligence rapidly enters higher education, instructors face a pressing question: Will AI tools expand equity in online learning—or deepen existing gaps?

This video poster presents a concise case story from the Digital Learning Equity Analysis Project, a collaborative self-study conducted by faculty members Sarah Straub and Rachel Jumper at a regional public university serving many nontraditional and working adult learners. Inspired by training from Every Learner Everywhere, the researchers applied a structured equity review protocol to two fully online courses—an undergraduate social studies methods course and a graduate introductory human sciences course.

Using tools such as the Social Justice Syllabus Design Tool, Universal Design for Learning rubric, Peralta Equity Rubric, and inclusive assessment checklists, the faculty examined course syllabi, communication strategies, assessments, and institutional supports through an equity lens. The process emphasized reducing extraneous cognitive load, strengthening community of inquiry, and embedding pedagogy of care into course design.

In this session, presenters extend the original project by considering how emerging AI tools can support—or complicate—equity-centered course design. For example, AI can help instructors audit syllabi for clarity, generate multiple formats of course content, and scaffold feedback for students. At the same time, uncritical AI use may reproduce bias, increase cognitive overload, or obscure human connection in online spaces.

This brief presentation highlights practical insights from the project and reflections on AI integration, offering educators a framework for using new technologies responsibly while maintaining a commitment to human-centered digital learning equity.

Outcomes

• Identify "automation-resistant" human traits—such as critical empathy and ethical nuance—to prioritize in course design.  

• Apply the Community of Inquiry (CoI) framework to transition an existing assignment from a product-based to a process-based assessment.  

• Develop specific social and cognitive presence strategies (e.g., structured peer review or multi-stage tasks) to ensure academic integrity in the age of AI.

Description

As generative AI becomes a permanent fixture in higher education, our role as educators must evolve from information gatekeepers to intentional architects of human-centric learning. This "BUILD" workshop introduces the AI-Resistant Pedagogy Studio, a practical framework for redesigning assessments to prioritize uniquely human capacities—critical empathy, ethical nuance, and original synthesis—that resist automation.

Grounded in the Community of Inquiry (CoI) framework, this session moves beyond theoretical discussion into practical application. Participants will be guided through a transition away from traditional, product-based assignments (which are increasingly vulnerable to LLM generation) toward process-based assessments that celebrate and validate the uniquely human journey of learning.