First Computing Education Research NSF CAREER Awards from CISE

The Computer and Information Sciences and Engineering (CISE) directorate of the National Science Foundation (NSF) has been giving early CAREER awards for decades, but this is the first year that they actively sought computing education awards.  Kristy Boyer and Ben Shapiro are awardees — our first CISE-side NSF CAREER awardees in computing education!  This is a big step towards establishing computing education within CS departments.

Photo by Shuchi Grover

Here are pieces of their project summaries, to give you a sense of what they’re doing.  Thanks to both of them for providing me with these, and CONGRATULATIONS!  They’ve done a great service to our community by helping to explain computing education to the CISE community.

Kristy Boyer: A rich body of evidence suggests that collaborative learning holds many benefits for computer science students, yet there is growing recognition that neither collaborative learning itself, nor the innovative curricula in which it may be situated, are “magic bullets” capable of single-handedly solving the computing pipeline problem. In contrast to being a one-size-fits-all solution, collaborative learning is highly dependent upon characteristics of the collaborators and on fine-grained interactions.

Intellectual Merit : The overarching research question of the CS-CLIMATE project is, “How can we identify and support the facets of collaborative dialogue that are particularly effective for fostering learning,sense of identity, motivation, and continued engagement for diverse computer science learners?” The project will investigate this question through three thrusts:

1. Collect a rich set of computer science collaborative learning data. The project will leverage the ASCEND learning environment, built in the PI’s lab, which supports remote collaboration with textual natural language dialogue, synchronized code editing, and integrated repository control for two or more collaborators. Partnering with three participating institutions: North Carolina State University, Meredith College (an all-women’s institution), and Florida A&M University (a minority-serving university with 90% African American enrollment), the full suite of collected data will also include student characteristics of gender, race/ethnicity, personality profile, and achievement goal orientation, while measures of outcomes include learning, sense of computing identity, motivation, and engagement.

2. Examine the fine-grained facets of collaborative dialogue that are particularly effective for diverse computer science learners. By leveraging machine-learning frameworks for dialogue analysis developed within the PI’s lab, the project will see the creation of fine-grained, theoretically informed models that capture collaborative dialogue and problem solving phenomena associated with learning, identity development, motivation, and engagement.

3. Implement and evaluate evidence-based pedagogical support for fostering effective collaborative dialogue. The project will extract a set of evidence-based pedagogical strategies for fostering effective collaborative dialogue tailored to student characteristics. These evidence-based pedagogical supports will be evaluated through quasi-experimental studies. It is hypothesized that CS-CLIMATE pedagogical support will significantly improve learning, sense of identity, motivation, and continued engagement for students overall, and for women and African American students in particular. In addition to testing this primary hypothesis, the project will produce fine-grained sequential analyses and rich qualitative findings that further the state of knowledge about how diverse students learn computing.

Broader Impacts : The project’s central goal is to foster effective collaboration for underrepresented groups in computing, focusing on women and African American students. The project partners with a 100% women’s college and a HBCU that is 90% African American, partnerships grounded in and facilitated by the STARS Alliance for which Boyer is a founding Executive Steering Committee member. The project will make substantial impact by building research capacity: Boyer has a track record of mentoring diverse graduate and undergraduate students. The project’s software and data, including the ASCEND learning environment and the CS-CLIMATE pedagogical support suite, will be released to the community. Finally, it is anticipated that the project will produce significant theoretical and practical advances that lead to a deeper understanding of how diverse students learn computing. Serving as the foundation for many future years of the PI’s faculty career, the project has the potential to transform the way collaboration is incorporated into computer science education.

Ben Shapiro:Constructing Modern and Inclusive Trajectories for Computer Science Learning

Research in computer science education and software engineering points to three acute problems:

1. Programmers, even experienced ones, struggle to reason about and correctly implement systems that include parallel and/or distributed computing.
2. A severe lack of diversity: Women, African-Americans, and Latinos are grossly under-represented.
3. A striking disconnect between the systems and communities that have been successfully engineered to engage broad populations in computing (e.g., Scratch) and the tools and practices of university, industry, and open-source computing.

These problems raise the following question: How can we create new ways into computer science for distributed computing, broaden participation, and support transitions into mainstream computer science?

I propose to investigate this broad question through the following activities:

1. Inventing life-relevant ways into distributed computing for youth. Middle and high school students will solve problems by building networks of cyber-physical systems that communicate with each other.
2. Investigating how distributed computing can broaden participation in CS. Under-Represented Minority (URM) students will be our partners in co-design (Druin, 1999, 2002; Yip et al., 2012) of the tools and curriculum, as well as participants in design-based research on learning (Collins et al., 1989; Edelson, 2002; DiSessa and Cobb, 2004). My students and I will investigate the effects of URMs’ participation on their interest, self-efficacy, and projective identity within computer science.
3. Enabling trajectories into mainstream computer science practices. We will construct a toolkit and curriculum (see Section 4) to support youths’ transitions from using beginner-specific programming environments into techniques and tools that are commonly found in university-level computer science education and in industry and open-source community practice.

To do so, I will draw upon my interdisciplinary background in both learning sciences educational research and in computer science, as well as many years of experience on Chicago’s South Side and in Pittsburgh’s Hill District creating new media arts and technology learning environments for African-American youth, to build a software platform and curriculum that enable URM youth to collaboratively design and program distributed systems. I will study their learning, including how they transition from our beginner-specific tools into general-purpose programming languages and practices, and assess whether these activities build participants’ interest and self-efficacy in computer science.