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    <title>Seth Bernstein</title>
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            <a href="#home">Home</a>
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            <a href="#research">Research</a>
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            <a href="assets/Seth_Bernstein_CV_april-18-26.pdf" target="_blank" rel="noopener noreferrer">CV</a>
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            <div class="intro">
                <img src="assets/headshot.png" alt="Seth Bernstein" class="profile-pic" />
                <div class="intro-text">
                    <h1>Seth Bernstein</h1>
                    <p>PhD Student, University of Michigan<br>School of Information<br>NSF Graduate Research Fellow</p>
                    <p><strong>Research:</strong> HCI & Computing Education</p>
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            <div id="announcement" class="announcement fade-in">
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            <div class="announcement-text">
                <strong>Announcement:</strong><br>
                Check out my recent paper
                <a href="https://dl.acm.org/doi/abs/10.1145/3769994.3770036"
                target="_blank"
                rel="noopener noreferrer">
                <em>“Beyond the Benefits: A Systematic Review of the Harms and Consequences of Generative AI in Computing Education”</em>
                </a>
                from <span class="blue">Koli Calling 2025</span>!
            </div>
            </div>
            <section id="about" class="fade-in">
                <h2>About</h2>
                <p>
                    I’m interested in making computing education more accessible and personally meaningful through
                    Human-Computer Interaction (HCI) and AI. My interest in computing began in seventh grade when I
                    started programming on my TI-84 calculator. At Temple University, I began researching
                    how to help novice students understand programming concepts.
                </p>
                <p>
                    My work currently explores how large language models (LLMs) can generate analogies, explanations,
                    and learning
                    materials that reflect students' interests and backgrounds. I am passionate about making computing
                    more inclusive,
                    especially for students who don’t yet see themselves represented in technical spaces.
                </p>
                <p>
                    In the fall of 2025, I began my PhD at the <span class="blue">
                        University of Michigan School of Information.
                        Go blue!
                    </span>
                </p>

            </section>

            <section id="research" class="fade-in">
                <h2>Research</h2>
                <p>
                    My research focuses on using LLMs to personalize learning in computing education. I study how
                    AI-generated
                    explanations and analogies can be adapted to align with students’ interests, cultural backgrounds,
                    and learning
                    needs.
                <p>
                    I combine LLMs with perspectives from HCI to better understand how to support intrinsic motivation
                    and deliver adaptive feedback.
                    This includes building interactive tools, analyzing student responses, and evaluating how
                    personalized
                    support affects comprehension. I’m focused on making sure these systems help students learn, not
                    replace or
                    mislead them.
                </p>
            </section>


            <section id="publications" class="fade-in">
                <h2>Publications</h2>
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                    Sort by:
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                    <div class="pub-card" data-year="2025"
                        data-title="Beyond the Benefits: A Systematic Review of the Harms and Consequences of Generative AI in Computing Education">

                        <a class="pub-title" href="https://dl.acm.org/doi/10.1145/3769994.3770036" target="_blank">
                            Beyond the Benefits: A Systematic Review of the Harms and Consequences of Generative AI in Computing Education
                        </a>
                        <div class="pub-meta"><b>Seth Bernstein</b>, Ashfin Rahman, Nadia Sharifi, Ariunjargal Terbish, Stephen MacNeil<br>Preprint: Koli Calling 2025</div>
                    </div>
                    <div class="pub-card" data-year="2024"
                        data-title="like a nesting doll: analyzing recursion analogies generated by cs students using large language models">
                        <a class="pub-title" href="https://doi.org/10.1145/3649217.3653533" target="_blank">Like
                            a
                            Nesting Doll: Analyzing Recursion Analogies Generated by CS Students using Large
                            Language
                            Models</a>
                        <div class="pub-meta"><b>Seth Bernstein</b>, Paul Denny, Juho Leinonen, Stephen MacNeil, et
                            al.<br>ITiCSE 2024</div>
                    </div>

                    <div class="pub-card" data-year="2024"
                        data-title="analyzing students' preferences for llm-generated analogies">
                        <a class="pub-title" href="https://doi.org/10.1145/3649405.3659504" target="_blank">Analyzing
                            Students' Preferences for LLM-Generated Analogies</a>
                        <div class="pub-meta"><b>Seth Bernstein</b>, Paul Denny, Juho Leinonen, Stephen MacNeil, et
                            al.<br>ITiCSE 2024</div>
                    </div>
                    <div class="pub-card" data-year="2026"
                        data-title="assessing the role of diversity in llm explanations for enhancing student understanding">
                        <a class="pub-title" href="https://doi.org/10.1145/3770761.3777320" target="_blank">Assessing the Role of Diversity in LLM Explanations for Enhancing Student Understanding</a>
                        <div class="pub-meta">Kush Patel, <b>Seth Bernstein</b>, Rayhona Nasimova, Paul Denny, Juho Leinonen, Stephen MacNeil<br>SIGCSE TS 2026</div>
                    </div>
                    <div class="pub-card" data-year="2022"
                        data-title="generating diverse code explanations using the gpt-3 large language model">
                        <a class="pub-title" href="https://doi.org/10.1145/3501709.3544280" target="_blank">Generating
                            Diverse Code Explanations using the GPT-3 Large Language Model</a>
                        <div class="pub-meta">Stephen MacNeil, Andrew Tran, Dan Mogil, <b>Seth Bernstein</b>, et
                            al.<br>ICER
                            2022</div>
                    </div>
                    <div class="pub-card" data-year="2023"
                        data-title="comparing code explanations created by students and large language models">
                        <a class="pub-title" href="https://doi.org/10.1145/3587102.3588785" target="_blank">Comparing
                            Code Explanations Created by Students and Large Language Models</a>
                        <div class="pub-meta">Juho Leinonen, Paul Denny, Stephen MacNeil, Sami Sarsa, <b>Seth Bernstein</b>, et
                            al.<br>ITiCSE 2023</div>
                    </div>
                    <div class="pub-card" data-year="2023"
                        data-title="the implications of large language models for cs teachers and students">
                        <a class="pub-title" href="https://doi.org/10.1145/3545947.3573358" target="_blank">The
                            Implications of Large Language Models for CS Teachers and Students</a>
                        <div class="pub-meta">Stephen MacNeil, Joanne Kim, Juho Leinonen, Paul Denny, <b>Seth Bernstein</b>, et
                            al.<br>SIGCSE 2023</div>
                    </div>
                    <div class="pub-card" data-year="2024"
                        data-title="decoding logic errors: a comparative study on bug detection by students and large language models">
                        <a class="pub-title" href="https://doi.org/10.1145/3636243.3636245" target="_blank">Decoding
                            Logic Errors: A Comparative Study on Bug Detection by Students and Large
                            Language
                            Models</a>
                        <div class="pub-meta">Stephen MacNeil, Paul Denny, Andrew Tran, Juho Leinonen, <b>Seth Bernstein</b>,
                            et al.<br>ACE 2024</div>
                    </div>
                    <div class="pub-card" data-year="2023"
                        data-title="experiences from using code explanations generated by large language models in a web software development e-book">
                        <a class="pub-title" href="https://doi.org/10.1145/3545945.3569785" target="_blank">Experiences
                            from Using Code Explanations Generated by Large Language Models in a Web
                            Software
                            Development E-Book</a>
                        <div class="pub-meta">Stephen MacNeil, Andrew Tran, Arto Hellas, Joanne Kim, Sami
                            Sarsa,
                            Paul
                            Denny, <b>Seth Bernstein</b>, et al.<br>SIGCSE 2023</div>
                    </div>
                    <div class="pub-card" data-year="2023"
                        data-title="automatically generating cs learning materials with large language models">
                        <a class="pub-title" href="https://doi.org/10.1145/3545947.3569630"
                            target="_blank">Automatically Generating CS Learning Materials with Large
                            Language
                            Models</a>
                        <div class="pub-meta">Stephen MacNeil, Andrew Tran, Juho Leinonen, Paul Denny,
                            Joanne
                            Kim,
                            Arto
                            Hellas, <b>Seth Bernstein</b>, et al.<br>SIGCSE 2023</div>
                    </div>
                    <div class="pub-card" data-year="2023"
                        data-title="prompt middleware: mapping prompts for large language models to ui affordances">
                        <a class="pub-title" href="https://arxiv.org/abs/2307.01142" target="_blank">Prompt
                            middleware:
                            Mapping prompts for large language models to UI affordances</a>
                        <div class="pub-meta">Stephen MacNeil, Andrew Tran, Joanne Kim, Ziheng Huang, <b>Seth Bernstein</b>,
                            Dan Mogil<br>arXiv 2023</div>
                    </div>
                </div>
            </section>
            <!-- <section id="service" class="fade-in"> -->
            <!-- <h2>Service</h2>
                <p>
                    Most of my service work has been rooted in the Temple HCI Lab, where I took on a leadership role
                    mentoring newer students, facilitating reading groups, and organizing collaborative workshops. I
                    helped structure onboarding processes, provided feedback on projects, and worked closely with
                    faculty to ensure that students felt supported and engaged. An important aspect was creating an
                    environment where everyone
                    could contribute meaningfully—regardless of prior experiences.
                </p>
                <p>
                    Outside the lab, I served as President of Temple’s ACM chapter. I worked with a small team to host
                    employer visits, technical workshops, student socials, and
                    events designed to bring the department together. I wanted ACM to feel like a space where students
                    could grow.
                </p>
                <p>
                    I also directed OwlHacks, Temple’s annual hackathon, reviving the event after a two-year hiatus. We
                    organized two hackathons in under a year, growing participation by over 100 students and ending with
                    the largest hackathon in Temple’s history, with more than 250 attendees. I focused on building a
                    beginner-friendly experience that encouraged collaboration and learning.
                </p>
                <p>
                    I’ve also mentored undergraduate researchers through the NSF REU program. My focus there was on
                    building a near-peer mentorship model where students felt comfortable asking questions and learning
                    research practices. I aimed to reduce the power distance between faculty and students by fostering a
                    supportive and conversational research environment.
                </p>
            </section> -->


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