IMPLEMENTATION PROJECT: ASCEND-Advancing STEM Competencies and Enhancing New Discoveries- with AI-Assisted Learning Analytics

Implementation Projects in the Historically Black Colleges and Universities - Undergraduate Program (HBCU-UP) provide support to design, implement, study, and assess comprehensive institutional efforts to increase the numbers of students and the quality of their preparation by strengthening science, technology, engineering, and mathematics (STEM) education and research. This project directed by faculty at Langston University, is designed to strengthen undergraduate STEM education through the formal investigation of an integrated educational model known as Competence Performance Recording for Learning (CPR-L), that combines collaborative problem solving, structured explanation of scientific reasoning, and the responsible use of artificial intelligence to strengthen student learning and success. Additional activities include expanded pre-semester academic workshops, year-long undergraduate research experiences in partnership with nationally recognized biomedical research laboratories, and development of an interdisciplinary innovation laboratory and data visualization center. The project’s integrated learning experiences are designed to strengthen critical thinking, scientific reasoning, communication skills, confidence, and persistence while preparing students for graduate education and careers in science, technology, engineering, and mathematics. The knowledge generated through this activity will contribute to strengthening the nation's science, technology, engineering, and mathematics workforce by expanding evidence-based educational practices that improve student success and expand participation in these fields. Research project results will be disseminated through conference presentations, scholarly publications, faculty development activities, and openly accessible instructional resources to facilitate adoption by other colleges and universities. The primary activity of this project is a research element that will study the effectiveness of the CPR-L instructional model that integrates collaborative problem solving and structured explanation of scientific reasoning with responsible artificial intelligence-assisted formative assessment to improve students’ retention of information and understanding of course concepts while maintaining the integrity of the problem-solving process and exorcising bad learning habits. The investigation will employ a mixed-methods, quasi-experimental design in examining student outcomes in introductory level STEM courses. Students’ audiovisual explanations of problem-solving processes will be evaluated with rubrics designed to assess higher-order cognitive learning objectives. Artificial intelligence will support transcription, rubric-based analysis, and timely formative feedback while maintaining faculty oversight of instructional decisions and student assessment. Quantitative evidence (e.g., course grades, course completion rates, grade point averages, and retention and persistence rates) will be combined with qualitative evidence (e.g., surveys, focus groups, classroom observations) to identify factors influencing CPR-L’s effectiveness and scalability. Additional project activities include expanded collaboration with the Oklahoma Medical Research Foundation, an enhanced two-week pre-semester Workshop, and increased utilization of the Data Visualization Hub. The project expects to generate validated evidence of the CPR-L’s effect on achievement and retention in gateway science courses, a replicable AI-enabled Self-Regulated Learning Model adaptable to other disciplines, and improved DFW and GPA rates among participants. 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.