The remarkable expansion of science and technology into our society over the last several decades have created an exciting landscape of career opportunities for students trained in science, technology, engineering, and mathematics (STEM). During this time, STEM graduate education has continued to rely largely on traditional learning models. These learning models historically have not emphasized professional skills development and career exploration, now recognized as key to long-term career success in STEM fields. Many institutions encourage students to address career and professional development needs through optional extra-curricular opportunities. The sporadic nature of these opportunities makes it difficult for students and faculty to learn about programs and to use them for effective learning. Moreover, when professional development and career exploration are not intentionally built into the arc of graduate training and assessed for effectiveness, graduate programs risk poor use of resources and an inconsistent training experience. This National Science Foundation Innovations in Graduate Education (IGE) award to the University of Michigan will develop an adaptive professional training (APT) system that will gather opportunities across the institution from different levels (e.g. department, college, university, external) into a single system. The data and knowledge gained from the system will help to guide skill development for graduate students.

This project will test the idea that providing a structured learning framework for professional development guided by formative mentor feedback and artificial intelligence-directed recommendations will enable more effective professional skill-building and student career success. The proposed platform, the Adaptive Professional Training (APT) learning management system (LMS) will integrate the following key innovations: (1) a user-friendly online hub of learning opportunity listings across the institution and beyond linked with defined by core professional skill competencies, (2) adaptive and iterative learning recommendations tailored to individual needs and interests based on both mentor and trainee input, (3) portfolio building, and (4) program assessment capabilities to enable evidence-based educational policy and resource optimization. This APT LMS represents a new flexible learning paradigm by which diverse professional training opportunities can be intentionally integrated into STEM graduate education. We will test whether use of the APT LMS by a test student cohort, compared to a control student cohort, will promote more intentional time investment in professional development and more uniform improvement in defined competencies, like science communication and increased awareness of learning resources. We predict that this innovative educational approach will integrate student and mentor input, enabling planning, documentation, and engagement in a systematic manner, leading to more effective acquisition of the professional skills associated with student career success.

The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community.

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.

National Science Foundation (NSF)
Division of Graduate Education (DGE)
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Daniel Denecke
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Regents of the University of Michigan - Ann Arbor
Ann Arbor
United States
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