2026 ASEE Annual Conference & Exposition

This methods full paper presents the adaptation of the Modified Delphi Method in the context of curriculum development of a new Master of Engineering degree in Manufacturing, Design, and AI. This project is conducted by the Massachusetts Institute of Technology (MIT) in the USA in collaboration with the New Age Makers' Institute of Technology (NAMTECH) in India. MIT adopted a participatory curriculum design approach for the development of the curriculum framework. One of the core components of the design process consists of the identification of the set of competencies for a master’s-level manufacturing engineering graduate to possess that align with industry needs and future trends in advanced manufacturing. Industry representatives from the USA and India and faculty from MIT and Indian academic partners were recruited to participate in this study.
A Modified Delphi method was adopted and adapted to conduct this study, with adaptations informed by literature and participants’ feedback throughout the process. Our approach consisted of four steps: literature review, survey, separate industry and faculty panels, and a reconciliation “mixed panel”. The novelty of our approach consisted in a final reconciliation panel between the two stakeholders’ groups, industry and faculty, to address and align the differing competency expectations between academia and industry.
An initial review of the literature was conducted to compile a comprehensive list of competencies expected of manufacturing engineering graduates upon completion of the program. A survey was designed and distributed to a group of industry representatives from multiple sectors, selected based on their involvement in the hiring of new graduates, experience supervising recent hires, and managerial-level responsibilities. An identical survey was also sent to faculty. The results from the surveys were the starting point for a series of in-person and online consensus-building panels with industry representatives and faculty to reach consensus on the list of competencies, their definition and the mastery level that new graduates are expected to achieve in the selected competency at degree completion. Analysis of the panel data revealed notable differences between faculty and industry perspectives, which were important to address in the final “mixed panel”, where representatives from both groups were recruited to participate.
The analysis of the panels, performed blending quantitative ratings with qualitative interpretation, highlighted rich conversations enabling participants to collectively refine and prioritize competencies, finalize the specific taxonomy for each of them and reflect on their content and mastery level. This approach afforded the benefit of a structured, iterative consensus-building process designed to facilitate multi-sector participation to minimize bias from dominant voices and promote industry-academia reconciliation/collaboration to reach a shared understanding of the competencies that graduates are expected to possess when completing their degree. Adjustments were made to reduce participants' attrition and fatigue, minimize the risk of superficial consensus and adjust to the online and in-person formats. In this paper, we describe the methodology adopted, the adaptations and adjustments that were made and the approach to data analysis. We also present evaluation data from the analysis of qualitative data and end-of-the-panel surveys to share lessons learned for future implementations.