Statement of career interest
My long-term career objective is to become a research faculty member whose work bridges a college of education and a department of computer science, ideally through a joint or courtesy appointment that allows me to contribute meaningfully to both. I want to lead a research program that examines how students learn computing in collaborative, inquiry-based environments, and how generative artificial intelligence (AI) can be designed into those environments in ways that strengthen, rather than replace, students' reasoning, self-efficacy, and sense of belonging. I see this dual home as essential to the work itself. Questions about how novice programmers learn cannot be answered well from either discipline alone: the learning sciences contribute theories of cognition, motivation, and collaboration, while computer science supplies the disciplinary knowledge, course contexts, and faculty partners where those theories must be tested.
This goal grows directly out of the path that brought me to doctoral study. I began my career as a full-stack web developer and business analyst, and more than six years in industry gave me a practitioner's understanding of the work computing graduates go on to do. I then moved into higher education as an instructor and program coordinator in computer science at Florida A&M University (FAMU), where I taught more than fourteen distinct computer science and information systems courses, chaired the undergraduate Assessment Committee, coordinated the program curriculum, and served as the department's accreditation coordinator for ABET. I also taught working adult learners at Saint John's College School of Professional Studies in Belize. As a Co-PI on an NSF-funded project investigating active learning strategies in multi-institution online synchronous computing courses, I gained my first experience designing and conducting funded computing education research. Today, as an instructional designer in Florida State University's Office of Digital Learning, I partner with faculty across disciplines to design high-quality online courses. Across these roles, I came to see that well-designed active and collaborative learning helps students persist, particularly students from groups historically underrepresented in computing, yet the field has little evidence about how AI tools are reshaping those learning dynamics. That gap is what I intend my research career to address.
My research sits at the intersection of computing education, active and collaborative learning design, AI in education, and equity in STEM. In the Instructional Systems and Learning Technologies (ISLT) program, advised by Dr. Secil Caskurlu, I am building this agenda through several connected projects. With computer science faculty at FAMU, I am co-authoring a paper on students' use of AI within Process Oriented Guided Inquiry Learning (POGIL)–style activities in which AI tasks are deliberately built into the inquiry process; we plan to submit this work to both ICER and AERA, reflecting the two research communities I intend to serve. Building on that paper, I will conduct a scholarship of teaching and learning (SoTL) action research study in FAMU's introductory programming course (COP3014C) in 2027–2028, examining how students engage with AI across the inquiry cycle and how the instructor redesigns activities and her own role in response. My dissertation will extend this line of inquiry to CS1 at Florida State, investigating how AI mediation relates to students' self-efficacy and motivation in introductory programming, in partnership with faculty in the Department of Computer Science. Alongside these studies, I am developing a methodological project that uses the Community of Inquiry framework to compare how AI and human coders identify teaching, social, and cognitive presence, and I have completed a scholarship of teaching and learning study on scenario-based mastery exams that assess object-oriented design thinking in CS2.
To reach this goal, I have organized my doctoral training around four areas that faculty search committees in both fields value. Methodological depth: I will develop expertise in quantitative and qualitative methods, including the measurement of self-efficacy and motivation, design-based and action research, and the responsible use of AI in qualitative analysis, so that I can independently lead mixed-methods studies. A cross-disciplinary publication record: I will publish in computing education venues such as SIGCSE, ICER, and ACM Transactions on Computing Education, as well as in educational research and learning technology venues such as AERA and peer-reviewed learning technology journals; a record that is legible to both communities is what makes a joint appointment viable. Funding readiness: drawing on my prior Co-PI experience, I will seek opportunities to contribute to grant proposals during my program and will use my dissertation findings as preliminary data for a proposal to federal or foundation programs that support computing education research. Sustained partnerships with computer science faculty: my dissertation is being developed in collaboration with FSU's Department of Computer Science, and my ongoing work with FAMU faculty gives me experience negotiating the roles, data access, and shared authorship that cross-departmental research requires.
I also intend to remain an active teacher and community builder, because research has its greatest impact when it reaches practitioners. As co-lead of the POGIL Project's inclusivity initiative, I help build learning communities for faculty at institutions serving historically marginalized groups; my analysis of program participation data showed that recruitment, rather than retention, was the primary gap, an insight that now shapes how I approach broadening participation. Through service such as Posters Co-Chair for SIGCSE 2026, I have learned to connect research with the daily realities of teaching. In the future, I hope to launch the Caribbean Classroom Project, a technology-enriched faculty development initiative for educators across the Caribbean. I will continue this translational work, including a planned 2027 workshop at the University of Florida AI Summit on cultivating critical thinkers in AI-augmented inquiry classrooms. As a faculty member, I would teach courses that prepare future educators and instructional designers to use AI thoughtfully, and contribute to the preparation of computer science graduate students and teaching assistants in evidence-based pedagogy.
In sum, my goal is to become a research faculty member who connects the learning sciences and computer science in both appointment and practice. My industry background, my years teaching and leading curriculum in computer science, and my current work in instructional design give me an unusual vantage point on how computing is learned and taught. My doctoral program is the bridge that will turn that experience into a rigorous, fundable, and equity-centered research program, one that helps institutions use AI to make computing education more collaborative, more inquiry-driven, and more welcoming to every student.
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