Discrete mathematics is a foundational course in the undergraduate computer science curriculum. Despite its long history in the curriculum, the literature and our student surveys show that students find the topics of proofs and discrete probability significantly more difficult than other topics in the course. The need for pedagogical interventions is pronounced yet the current body of literature largely consists of instructor experience reports with interventions, creating a significant gap in the literature for student voice and data-driven design. To address this gap in the literature, I propose a mixed-methods study designed in three phases: (1) compare student, instructional faculty, and literature perceptions; (2) a quasi-experimental design involving two data- and pedagogically-based interventions; and (3) an analysis and additional focus group with students designed to understand and track student motivations and perceptions of the course and the efficacy of contextualizing discrete mathematics in computer science. The findings of this dissertation research are expected to contribute to the inclusion of student voice into the DM research literature and a comparative mapping of student and instructional faculty DM perceptions, two scalable data-designed interventions, empirical evidence for the efficacy of the interventions, and evidence-based guidance on the creation of curricula pieces in discrete mathematics for computer science majors.

Discrete mathematics has been a topic taught in the undergraduate computer science curriculum for decades. Most research publications that are focused on discrete mathematics focus on the teacher's perspective of the course and the students. They also suggest that students struggle in the course due to a lack of mathematical maturity or motivation without presenting much empirical evidence. This paper fills the gap in research by focusing on what students think of discrete mathematics, including the concepts that they find easier and the ones that challenge them the most. We collected survey data from 132 computing students at a large public university. We analyzed the data utilizing descriptive statistics and open coding. We found that students identify proof writing as the most difficult concept to learn due to its difference from mathematics that they are most used to. Students also suggest that their challenge is not that they find the course as a whole irrelevant, which could cause a lack of motivation, but rather that specific topics were hard to understand or connect to computer science. We discuss these findings and discuss the implications and possible future directions for research in the area of discrete mathematics in the computer science curriculum.

Maker-based learning and Computational Thinking (CT) have increased in popularity in formal educational settings over the past decade. Particularly, the combination of CT and making seem to hold promise for providing opportunities for students to learn and use computing concepts outside of computing courses. This paper presents findings from a two year study of the integration of computational making into 5th and 6th grade science classrooms. Students participated in computational making interventions in which they programmed Arduino microcontrollers to create scientific models of concepts that aimed to help them engage with the science content while learning CT and making skills. In this paper, we explore the differences between the desired computing learning progressions, students' performance on assessments, and perceptions of computer science to answer: To what extent are middle school students able to learn computing through computing integrated science curriculum? We observed that the programming concepts taught were largely dependent on the needs of the science and making project. Our findings suggest that while students had opportunities to learn and use programming concepts, their performance on assessments was between 15% and 78% correct for conceptual and applied questions and their programming self-efficacy and their perceptions of computer science were lower than desired. We discuss the implications of these findings and the factors that impact the integration of CT in core disciplines and the challenges this presents as we aim to use integration approaches to effectively teach computing outside of computing courses and to broaden participation in computing.

In this poster, we present the design of a browser-based Arduino programming tool, CASMM, to support computational thinking and making in science classrooms. This tool allows for unique integration of research tools, lesson planning, and scaffolding for learning computational thinking concepts and block-based programming. This poster will describe four key features of a block-based LMS: (1) reduced-scoped programming toolbox, (2) block locking, (3) lesson plans and starter code templates; and (4) low-tech code replay for researchers. Through discussion of this tool, we aim to catalyze conversations about integrating new scaffolding techniques into block-based programming environments to better support classroom use and research.

This paper presents the design of a browser-based Arduino programming tool and learning management system (LMS), CASMM, that offers end-to-end support for learners utilizing Chromebooks in a classroom environment. This tool aims to support learners through the entire process of coding and using Arduinos in group projects at scale in formal classrooms. The novelty of this tool and its discussion for the VL/HCC community lies in the design and customization of this tool to meet real world constraints of formal classrooms. In addition, it encourages expansion of who we consider users and requires inclusion of where and how learning takes place to truly support human-centered development of programming tools. In this paper, we shift the focus from individual users to multiple groups of student users and 1–3 teachers/mentors in a classroom environment. In particular, this paper aims to make explicit the unique needs of teachers and students who may have limited technology expertise both in coding and using Arduinos in formal classroom environments, the human and technological constraints of a formal classroom and features we've designed into CASMM to address these needs. Through this paper, we aim to spark discussion about the human-centered requirements of these users and how tools that support learners end-to-end in the development process may be necessary to truly provide accessible programming languages and environments for a wide range of novices (i.e., students, classroom teachers, and college mentors/volunteers).