About

I am an Instructional Associate Professor of Computer Science at the Herbert Wertheim College of Engineering, University of Florida. My research focuses on Computer Science Education and Learning Analytics where I study the effectiveness of different formative learning approaches on students' learning outcomes and performance in introductory programming courses. My Masters thesis work was on cultivating computational reasoning skills and mental simulation ability in K-12 students using Microsoft's Kodu Game Lab. I was fortunate to be advised by Christina Gardner-McCune (UF) and David Touretzky (CMU).

Research topics

• Computer Science
• Mathematics education
• Psychology
• Artificial Intelligence
• Political Science
• Sociology
• Management science
• Medicine
• Multimedia
• Engineering
• Medical education
• Social psychology
• Data science

Selected publications

• Aligning the Goals of Learning Analytics with its Research Scholarship

  Journal of Learning Analytics · 2023 · 10 citations

  • Computer Science
  • Computer Science
  • Political Science

  To promote cross-community dialogue on matters of significance within the field of learning analytics (LA), we as editors-in-chief of the Journal of Learning Analytics (JLA) have introduced a section for papers that are open to peer commentary. An invitation to submit proposals for commentaries on the paper was released, and 12 of these proposals were accepted. The 26 authors of the accepted commentaries are based in Europe, North America, and Australia. They range in experience from PhD students and early-career researchers to some of the longest-standing, most senior members of the learning analytics community. This paper brings those commentaries together, and we recommend reading it as a companion piece to the original paper by Motz et al. (2023), which also appears in this issue

  DOI

• How do Undergraduate Students Reason about Ethical and Algorithmic Decision-Making?

  Proceedings of the 53rd ACM Technical Symposium on Computer Science Education · 2022 · 6 citations

  1st authorCorresponding
  • Computer Science
  • Computer Science
  • Artificial Intelligence

  As the effectiveness of algorithms to make decisions improves and as the use of algorithms in domains, which can have a significant impact in determining one's life prospects increases, it is important to understand undergraduate students' perceptions of algorithmic decision making and reasoning behind that perception. We conducted a study to understand engineering students' perception about algorithmic decision making in two different scenarios using a trolley problem at the end of an introductory programming course. The motivation to conduct this study was to gain insights on how they reason about the ethical use of algorithms. Data of eighty-two undergraduate engineering students was analyzed to not only understand their decisions in two different contexts but also their qualitative reasoning behind their decisions. This paper presents a thematic analysis of these decisions and how they differed in the two contexts. Further, classification of their reasoning into different known philosophical frameworks is discussed, which helps in understanding the major underpinnings of these decisions. We believe that the results of this study can help educators understand how students reason about algorithms which may influence how 'ethics' as a topic is integrated in computer science courses, especially in introductory programming courses.

  DOI

• Evaluating the Use and Effectiveness of Ungraded Practice Problems in an Introductory Programming Course

  2020 · 10 citations

  Senior authorCorresponding
  • Computer Science
  • Computer Science
  • Mathematics education

  Educational researchers have been interested in finding out factors which are pivotal in a students' success within any course. However, less is known about students' engagement with optional course content and its effect on learning outcomes. Optional content is any ungraded component of the course available to students for additional practice. In our context, it is ungraded quizzes based on concepts discussed in an introductory programming course. In this paper, we present the methodology, analysis, and results of a study concerned with how students engage with optional quizzes and what effects this content may have on students' learning. We find that before the midterm exam, over half of all students completed at least one quiz of the four available, while a third of students completed all available quizzes. Leading up to the midterm exam, we observed a large increase in submissions. During the second half of the semester, overall participation decreased slightly. Again, leading up to the final exam, students' submissions became more frequent. When investigating correlations between quiz completion and student performance, notable differences were observed between the highest and lowest levels of quiz completion. The results of this study will help computer science educators in understanding how students utilize optional content similar to ours and further guide in improving the effectiveness of such content, especially in the context of introductory programming courses. These insights will help to guide the creation and implementation of optional practice problems, with the goal to improve the student's overall experience of the course.

  DOI

Frequent coauthors

• G. Pitts

  University of Florida

  11 shared

• Christina Gardner‐McCune

  Clemson University

  11 shared

• Sarah Rajkumari Jayasekaran

  Texas A&M University

  9 shared

• Saira Anwar

  University of Florida

  9 shared

• David S. Touretzky

  Carnegie Mellon University

  6 shared

• Renske Weeda

  Radboud University Nijmegen

  3 shared

• Cruz Izu

  University of Adelaide

  3 shared

• Quintin Cutts

  University of Glasgow

  3 shared

Labs

• Computational Reasoning GroupPI

Education

• Ph.D., Computer Science Education and Learning Analytics

  University of Florida

• M.S., Computer Science

  University of Florida

• B.S., Computer Science

  University of Florida

Awards & honors

• Teacher of the Year Award, Department of Engineering Educati…
• Affordability Access Award, Center for Teaching Excellence,…
• Teacher of the Year Award, Department of Engineering Educati…
• Alec Courtelis Award, Best International Graduate Student, U…
• Presidential Service Award, University of Florida, 2016, 201…

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