PRIME: Engaging STEM Undergraduate Students in Computer Science with Intelligent Tutoring Systems

The PRIME project has the overarching objective of transforming introductory computing for STEM majors by creating an intelligent tutoring system that provides individualized problem-solving and motivational support. The project will tackle the issue of courses that introduce computing to non-computer science majors in STEM undergrad. Effectively introducing computing to STEM students holds enormous potential for shaping the way students develop the computational problem-solving abilities that will be critical throughout their careers.

During the four-year span of the project, more than 11,000 undergraduate students will benefit from PRIME. The project will address people from diverse backgrounds through the use and evaluation of PRIME at a Historically Black University, Florida A&M University. PRIME will be made available to computer science educators and the computer science education research community to promote broad adoption. It is anticipated that PRIME will fundamentally improve undergraduate STEM students’ computing abilities and their attitudes toward computing.

Reports

PRIME Technical Report 1: The Development and Validation of the Computer Science Concepts Assessment for Undergraduate Students (UG-CSCA): Preliminary Results

Funders

National Science Foundation

Partners

Teams

Selected Resources

Report – PRIME Technical Report 1: The Development and Validation of the Computer Science Concepts Assessment for Undergraduate Students (UG-CSCA): Preliminary Results

The Undergraduate Computer Science Concept Assessment (UG-CSCA) is intended to assess STEM undergraduate students’ understanding of basic computer science and programming concepts – variables, conditionals, loops, and algorithms. The validation process of this assessment was guided and informed by a Focal Knowledge, Skills, and Abilities (FKSAs) Framework proposed by Grover and Basu (2017) and the K-12 CS Framework (K–12 Computer Science Framework, 2016). Block-based programming is used as the context for each item in the UG-CSCA. Several studies suggest that block-based programming is effective and appropriate computer programming for novices (Grover, Pea, & Cooper, 2015; Weintrop & Wilensky, 2015), and thus aligns with the intention of this assessment. The current version of the UG-CSCA was written for undergraduate students who are novices in computer science and programming. We believe that this assessment will be useful to instructors who teach introductory computer science and programming courses, as well as computer science education researchers. The instrument was designed for use in pre-intervention-post or longitudinal contexts, as well as for a diagnostic tool. We suggest providing 30-35 minutes for students to complete the assessment which consists of 26 multiple-choice questions.