This work in progress innovative practice paper describes a novel curriculum and pedagogy used in a systems engineering graduate program that provides ethical, innovative and sustainable solutions to important, complex societal problems using convergent transdisciplinary, collaborative, team-based approaches. Convergent engineering approaches have been applied to the program itself to foster collective learning through iterative rapid integration and testing in real world scenarios. This paper presents the motivation, approach, program, pedagogy, and curriculum for the Convergent Systems Engineering master program which supports three major systems scales from products and services, to the enterprise, and finally global value supply chains.

This is a work-in-progress paper that describes research involving the development and use of technology to create social real-time learning experiences. This technology can provide rapid feedback between students and instructors, enabling the ability to make real-time data-driven decisions to automatically inform and individualize instruction. This paper discusses research being conducted in the following five supporting major areas: 1) Learning Assessment and Tracing, 2) Learning Outcome and Concept Dependencies, 3) Pre-Learning Intervention, 4) In-Process Learning Intervention, and 5) Future Learning Intervention using a learning environment called SlideSpace that has served as a living laboratory for experiments into human interactions.

In this Work in Progress, research [1] indicates that static curricula, with few interactions between instructors and students, reduces the number and quality of formative feedback opportunities for learners, and negatively impacts student learning outcomes. The means by which timely feedback can be captured, stored, analyzed, categorized, and shared with stakeholders may improve performance indicators. Our current work will build on prior work to create an enhanced active, effective learning environment for instructors and students. Major areas of focus include individualized learning assessment, the use of AI to identify pedagogy to active learning indicators, the ability to provide students with scaffolded learning prompts prior to instruction, while students are actively engaged and in improving the curricula and pedagogy for future students. Future work includes the optimization of feedback based on individual students, and addressing intellectual property and privacy concerns for students and instructors.

In this Work in Progress, we believe that our education systems are not capable of evolving at the rate necessary to meet the challenges presented by rapidly changing technology epitomized by Industry 4.0 and the digital transformation. In particular, there are relatively slow and inaccurate feedback mechanisms for the academic program content needs of employers, students and universities. The objective of this research is to create the feedback mechanisms and interactions by which educators, students and employers can communicate their specific educational capabilities, desires and needs, that will provide the dynamic feedback necessary to accelerate the development and evolution of educational programs.