A Machine Learning Student Behavior Model to Identify Struggling Students in Introductory Computer Science Courses

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This project, administered by Rutgers University New Brunswick, builds capacity in STEM Education Research (SER) through the investigator’s participation in intensive professional growth experiences and application of their new knowledge in the design and implementation of a SER study. The investigator will build proficiency in mixed methods research by engaging in focused coursework, professional conferences, and mentoring by SER experts over the life of the project. In tandem with professional development efforts, the investigator will design and test a machine learning tool tailored to assess student progress in real time in computer science coursework. Once the project goals are realized, the developed tool holds potential for improving student outcomes in computer science, an area of critical need in the United States workforce. The tool will be adaptable for use across disciplines to support student STEM outcomes overall, while the researcher will be prepared to further advance the knowledge base in effective STEM education practices.The project investigator’s professional growth activities, customized via a gap assessment, will focus on qualitative research methods, learning theory, and learning analytics. Through scholarly study that includes regular formative meetings with experts in SER and engagement in focused coursework and professional experiences, the investigator will build expertise to enable the development of a machine learning tool employing behavioral models that predict student success in computer science courses. Detection of student struggles enroute will promote the timely use of intervention strategies to enhance success across demographic groups, thereby improving representation in vital STEM disciplines such as the computer sciences. This project is supported by the ECR Building Capacity in STEM Education Research competition of the EHR Core Research (ECR) program. ECR funds fundamental STEM education research projects that focus on STEM learning and learning environments, broadening participation in STEM fields, and STEM professional workforce development.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.