adaptable-and-agile-programs-to-meet-emerging-workforce-needs

Paper ID #25145 Adaptable and Agile - Programs to Meet Emerging Workforce Needs Mr Eugene Rutz, University of Cincinnati Eugene Rutz is Academic Director in the College of Engineering & Applied Science at the University of Cincinnati Responsibilities include oversight of eLearning initiatives, working with high schools on engineering coursework, and academic oversight of the Master of Engineering program Eugene serves as co-PI on an NSF sponsored Math and Science partnership grant and PI on other grants that examine the intersection of instructional technology and learning c American Society for Engineering Education, 2019 Adaptable and Agile - Programs to Meet Emerging Workforce Needs Background Much has been written regarding the shifting nature of the workforce and the skills needed to contribute to the workforce of the future Common themes include increased technology adoption, data analytics, changing distribution and value chains, and changes in patterns of work [1] and [2] Much has also been written on the need for colleges and universities to adapt to changing demographics and evolving needs of business and industry [3] and [4] The traditional engineering disciplines have served the workforce well and have allowed universities to provide known pathways to students seeking engineering degrees While there continues to be a need and well understood career path for traditional disciplines it is clear that many of the skills needed to participate in the future workforce not fit neatly into a particular discipline An increasing number of jobs and professions require knowledge and skills that are not provided through traditional coursework Big data analysis and artificial intelligence are two such topics that individuals from traditional disciplines including electrical engineers, mechanical engineers, civil engineers and others are requesting that are not part of a traditional curriculum The University Cincinnati Master of Engineering program provides a flexible platform on which to construct new degree programs intended to meet the emerging needs of the workforce New degrees in Artificial Intelligence, Additive Manufacturing, and Robotics and Intelligent Autonomous Systems were conceived and implemented within a month time frame These new degrees cross-disciplinary boundaries and utilize coursework and faculty from multiple traditional disciplines The paper discusses the Master of Engineering program framework, the rationale for the new degree programs, and describes the opportunities and challenges associated with degrees that encompass multiple traditional disciplines The paper is not meant to provide research findings on a topic, rather it provides pragmatic considerations others may find useful in working to accomplish similar goals Master of Engineering Framework At the University Cincinnati the Master of Engineering (MEng) designation is used in the College of Engineering & Applied Science to distinguish a coursework based graduate degree from the traditional research-based Master of Science The MEng was instituted in 2009 to provide an appropriate pathway for individuals who sought a graduate degree that provided skills and knowledge that improved their ability to contribute to the technical workforce Enrollment in the Master of Engineering program has increased steadily from less than 20 in the first cohort to over 250 in the last academic year The MEng program requires the completion of 30 academic credits including the following:  Technical coursework, traditionally courses in a specific discipline  Professional skills courses with one course from project / process management and one course from interpersonal skill development  Elective courses allowing students to pursue broader interests  Capstone project requiring student to demonstrate application of principles learned through the program Several options are available to satisfy the capstone requirement: it can be completed as a project under the guidance of a faculty member or industry partner, a paper developed under the guidance of a faculty, or as an internship in industry Depending on which capstone option is chosen the MEng can be completed in one academic year of full-time study or one year plus an additional semester The College has offered the MEng degree in all the same disciplines as the traditional MS degree and in almost all programs MEng enrollment is greater than MS enrollment Adapting to Meet Needs Many universities have seen rapidly growing interest in areas such as artificial intelligence, additive manufacturing, intelligent systems and other topics A diverse group of disciplines drives the growth An examination of students who enrolled in a graduate machine learning course for instance reveals that in addition to the expected computer science students there are students pursuing mechanical engineering, civil engineering, aerospace engineering, medicine, and other degrees This interest from students coupled with what we know about the changing needs of regional business informed the College that we needed to consider changes to our traditional approach to the degree programs The traditional disciplines and departments add new courses as needs are identified such that a graduate curriculum today will have a number of courses available that were not offered ten or even five years ago Most often the new courses are electives that are seen as complementing the core technical knowledge of a traditional degree path It is becoming increasingly clear though, that a group of students and some business sectors are not being served adequately with this approach of incremental change With input from regional business partners, the College proposed three new degree programs that crossed disciplinary boundaries: Master of Engineering in Artificial Intelligence Master of Engineering in Additive Manufacturing Master of Engineering in Robotics and Intelligent Autonomous Systems Because faculty and programs were attentive to the growing needs in these areas, a number of courses had been developed to provide knowledge and skills in each of these broad categories These courses existed in several different departments and the traditional program structures limited students’ ability to develop a cohesive program of study in these areas The new degree programs were created to remove these barriers and provide an educational program that met the emerging needs New program approval depends on several considerations including academic need, viability (income generated vs costs to offer the program), appropriate fit for the college and university, and capacity of the unit to offer the program If a proposed new program varies significantly from existing programs, state approval is required in addition to university approval The Master of Engineering programs in the various disciplines have a consistent structure and share a certain number of courses (the professional skills courses, the electives and the capstone) This commonality facilitates the creation of new programs, in particular interdisciplinary programs, without requiring state-level approval New Program Curriculum The curriculum for the new program in artificial intelligence was developed as a collaborative effort between faculty in computer science, aerospace engineering and mechanical engineering The AI curriculum is shown in Figure Master of Engineering Artificial Intelligence Project / Process Management – select one course from list of approved courses Interpersonal Skill Development – select one course from list of approved courses Required AI Courses – complete the required courses: CS 6033 Artificial Intelligence EECS 6036 Intelligent Systems or MECH 6035 Intelligent Systems CS 6073 Deep Learning Elective Courses – the following are recommended electives for the program: CS 6037 Machine Learning CS 6054 Information Retrieval AEEM 6096 Fuzzy Control Systems CS 7063 Advanced Machine Learning EECE 7065 Complex Systems and Networks CS 6021 Math logic MEng Capstone in AI focused area Figure Curriculum for MEng in Artificial Intelligence The curriculum for the new program in additive manufacturing was developed as a collaboration between mechanical engineering, materials engineering and aerospace engineering The curriculum is shown in Figure Master of Engineering Additive Manufacturing Project / Process Management – select one course from list of approved courses Interpersonal Skill Development – select one course from list of approved courses Required Courses – select at least of the courses listed: MECH 6097C Intro to Additive Manufacturing MECH 7080 Metal Additive Manufacturing MECH 6023 CAD for Manufacturing Elective Courses – the following are recommended electives for the program: AEEM6001 Advanced Strength of Materials AEEM6099 Systems Engineering Analysis AEEM7052 Finite Element Analysis MECH6020 Intro to Adv Manufacturing MECH6071 Advanced Design for Manufacturing MECH6077 Micro and Nano Manufacturing MTEN 6010 Physical property of solids MTEN 6034 Physics of polymer processing MEng Capstone in Additive Manufacturing focused area Figure Curriculum for MEng in Additive Manufacturing The curriculum for the new program in robotics and intelligent autonomous systems was developed as a collaboration between mechanical engineering, electrical engineering and aerospace engineering The curriculum is shown in Figure Master of Engineering Robotics and Intelligent Autonomous Systems Project / Process Management – select one course from list of approved courses Interpersonal Skill Development – select one course from list of approved courses Required Courses – select at least of the courses listed: MECH 6031 Introduction to Robotics MECH 6032 Robot kinematics and dynamics AEEM 6018 Robot Controls EECE 6015C Instrumentation and Industrial Control Elective Courses – the following are recommended electives for the program: AEEM 6015 Modern Control AEEM 6096 Fuzzy Control Systems AEEM 6098 UAV and UAS AEEM 7063 Space Robotics EECE 6016C Electric Machines and Drives EECE 6017C Embedded Systems EECE 6036 Intelligent Systems EECE 6042 Digital Image Processing EECE 7019 Bio-Inspired Robotics CS 6073 Deep Learning CS 6033 Artificial Intelligence CS 6037 Machine Learning MECH 6036 Robot Vision MECH 7011 Decision Engineering MECH 7015 Humans, Machines, Robots and their Interaction MEng Capstone in Robotics and Autonomous Systems focused area Figure Curriculum for MEng in Robotics and Intelligent Autonomous Systems Challenges in Developing and Offering Interdisciplinary Programs While it is easy to appreciate the need for interdisciplinary collaboration for degree programs, there are certain barriers to implementation, most of which exist for practical reasons At the University Cincinnati, new graduate degree programs are proposed by program faculty then approved by college graduate faculty before being submitted to the University Graduate School for review and approval Because there were no existing program faculty in these areas, the first step was to designate graduate faculty who would be part of these various programs Faculty from various disciplines with the relevant backgrounds and with an interest in pursuing these interdisciplinary areas were eager to participate A graduate program director was also named from among the participating faculty Another practical consideration is who reviews applications and makes admission decisions For graduate programs, admission decisions are based around department structures The interdisciplinary programs have no such structure so new processes had to be established to provide for review and action on applications Student academic progress and rules pertaining to degree requirements, conduct, etc are typically enumerated in a graduate handbook for each program in the College Because the Master of Engineering programs have a consistent structure and academic requirements, the College uses one graduate handbook for all MEng students Any particular requirements deemed appropriate by graduate faculty of a specific program can be called out in an appendix in the common handbook Student advising is another item that must be provided and can present challenges in an interdisciplinary program Since the Master of Engineering program does not include a research thesis, the advising needed is different from a traditional MS program The College has dedicated staff to provide the majority of advising to MEng students regardless of discipline This structure allows for consistent and timely advising on most academic matters affecting students Communicating program opportunities to potential students can be another challenge Students are familiar with and expect to find descriptions of traditional degree pathways The interdisciplinary degrees cause confusion among some potential students Our experience has been that providing multiple means for obtaining information is best This can include links to program details, frequently asked questions and answers, and providing phone and email information to staff who can help students navigate the information and make informed decisions Initial Results and Future Steps The College started the process of developing the degrees early in 2018 and accomplished the goal of having the new programs available beginning in fall 2018 A regional marketing campaign was conducted to raise awareness and drive enrollments This generated moderate interest among potential students but with the limited time from launch to implementation, the number of initial enrollments in the programs were small The Additive Manufacturing and Artificial Intelligence program each had two matriculated students the fall of 2018 while the Robotics and Intelligent Autonomous Systems program had nine matriculated students The College has continued to market these new programs, with recent efforts having a broader geographical reach Interest has grown and includes a large number of interested international applicants Perhaps one of the most encouraging responses has been from the Industrial Advisory Board for the College Feedback from this group has been uniformly positive to these efforts to meet current and emerging needs of business and industry The College has been encouraged to continue to look to future needs and continue to develop programs that meet these needs through creative approaches to offering degree programs References [1] World Economic Forum, “The Future of Jobs Report 2018,” World Economic forum, 2018 Available at http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf [2] J Bughin, E Hazan, S Lund, P Dahlstrom, A Wiesinger, and A Subramainian, “Skill Shift - Automation and The Future of the Workforce,” McKinsey Global Institute, McKinsey and Company, 2018 Available at https://www.mckinsey.com/featured-insights/future-ofwork/skill-shift-automation-and-the-future-of-the-workforce [3] NAP, “The Engineer of 2020: Visions of Engineering in the New Century,” The National Academies Press, 2004 [4] S Glass, “Why Universities Need to Prepare Students for the New AI World,” Forbes, July 24, 2018 Available at https://www.forbes.com/sites/stephanieglass/2018/07/24/whyuniversities-need-to-prepare-students-for-the-new-ai-world/#5fb608b16bc8