Digitally Coupled Learning and Innovation Processes | Industrial

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Digitally Coupled Learning and Innovation Processes Monty Alger, John Jordan, and Darrell Velegol Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.9b03612 • Publication Date (Web): 03 Sep 2019 Downloaded from pubs.acs.org on September 3, 2019

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Industrial & Engineering Chemistry Research

Digitally Coupled Learning and Innovation Processes Monty Alger*1, John Jordan2, Darrell Velegol1 Penn State University, Department of Chemical Engineering, University Park, PA 16802 USA 2 School of Information Studies, Syracuse University, Syracuse, NY 13244 * To whom correspondence should be addressed ([email protected]) Submitted June 29, 2019

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Abstract As engineering education is being forced to evolve, we have been experimenting with four focus areas designed to connect markets and universities, with students transporting the information between them. 1) Shared digital platforms use the same principles of reach and scalability that characterize such businesses as Airbnb and Amazon. 2) Enhanced processes of career discovery draw on a simple 1-page self-diagnostic as well as on a data-centric view of the skills market. 3) Getting market data to inform more classroom (and classroom-related) aspects of pedagogy, including problem-based learning and particular skills, has proven to bring positive outcomes. Finally, 4) focusing and enhancing students’ and interns’ experiences provides a further method of connecting classrooms and labs to market behavior and developing new research to market programs. These four focus areas constitute key aspects of a connected and integrated model in which learning and innovation are seen as complementary efforts.

Keywords: Digital business innovation, feedback loops, engineering education


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Introduction A desk on the second floor of Roger Adams’ lab at the University of Illinois had a PLATO terminal with a familiar orange screen 1. This terminal was part of the work to build computerized engineering modules for students to get instant feedback when working on thermodynamics, heat transfer, or other similar problems. Those who worked with Professor Chuck Eckert as a teacher or colleague know of his passion for innovation in pedagogy, and the early use of the PLATO system in higher education was a great example of his many pioneering contributions to learning and innovation. In the past 150 years, engineering has undergone a series of foundational transitions in response to changing market forces, educational technologies, and professional developments. Whether we look at the MIT chemical engineering Practice School in 1916, 2 the buildout in U.S. university physical plant after World War II, 3 computers in the lab and classroom including PLATO at the University, or recent online innovations such as the Georgia Tech online masters in computer science,4 engineering education has responded to external forces with moments of reinvention. It is fitting, then, that we honor Professor Eckert by asking some pertinent questions about the state of and opportunity for learning and innovation in engineering education. Employers, students, and new players are experimenting with new models of training and certification, often at a drastically lower cost than that charged by traditional providers. Global forces require new dimensions of scalability to reach the many talented and motivated students who cannot matriculate at brick and mortar universities. Innovations in sensors, cloud computing, algorithmic models, and the mobilization of crowds mean that new practices are continually and rapidly reshaping engineering practice: a key requirement is finding people who know both curricular content and its application as well as the many but less obvious paths of lifelong reinvigoration and upskilling. 5 To address these challenges using the new tools at our disposal, we are experimenting with a collaborative model linking markets, employers, universities, faculty and students in new configurations. We have come to know some of the new players, have seen some things that work (and some that don’t), and invite like-minded innovators to join a wider conversation about the next major shift in engineering education.

External forces Higher education is faced with numerous structural challenges. Costs are increasing far faster than inflation, 6 with the resulting heavy debt loads factoring more and more into students’ decisions – regarding major, campus, or even whether to attend college at all. The value of a college degree is no longer assumed, 7 with microcredentials and other nontraditional certifications gaining in credibility and acceptance. 8 MIT’s MicroMasters9 is but one example. Employers are teaming with providers to deliver new kinds of learning: Amazon 10, Wal-Mart 11, and AT&T 12 all are making efforts in this direction. 13


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Part of the reason for the proliferation of alternatives to college derives from the combination of high cost and universities’ disconnection from rapidly changing market needs. 14 Data science is a prime example: Fields from marketing to aerospace all seek recruits with a similar set of skills and aptitudes, but the shortages are acute. Traditional companies cannot pay high enough salaries and lack the ability to use equity (stock grants and options) as a different kind of carrot. Employers are finding that retraining current employees can be a viable alternative 15 to downsizing and attempting to hire from the tight labor pool, but traditional universities rarely support learners with this profile. 16 With global political uncertainty getting higher, international students seek alternatives to the complex world of visas, embargoes, and hiring barriers they face when coming to the United States for school. At the companies that employ engineers, meanwhile, market forces are rewarding winners but challenging laggards. In every market sector, cycle times are shortening and innovations are shifting both the product portfolio and the business model. An HVAC equipment supplier that used to sell assets like chillers and thermostats is now a service provider paid on the basis of uptime, energy consumption, and other customer metrics. Capital markets reward light and agile asset bases; owning plant and equipment can be risky. Companies’ talent pools have to evolve rapidly, but the traditional linear model of relying on universities for curricular updates takes too long. Labor markets and education providers interact only haphazardly; professors’ reward structure can emphasize publication rather than the career readiness17 of their students; the overall process is marked by a lack of feedback and integration. To sum up, today’s models have a legacy linear system design characterized by a heavy overhead layer. There is a need for new, asset-light, short-cycle practices. The old model changes far too slowly given today’s demands. Coupling learning and innovation can help reduce cycle-time, with the additional benefit of accelerating time to market and thus the necessary iterations that mark successful launches. 18

Four postulates We start with four postulates about how the world is being transformed: ● Digital connectivity. Talent identification and recruitment, research, and learning are not orthogonal. Timescales have been significantly compressed, 19 and the current system is not designed for effective feedback control that syncs market and academic time scales. 20 ● New business models. Smartphones, social networks, sensors, and data analytics: The same factors that create the dislocation of traditional practices can also be successfully deployed to help create new business models and solutions. 21 ● Market pull. The workplace will pull the design of the evolving system, rather than universities pushing it. This implies radical shifts in cost and price. ● Learner-centric. The system’s focus will be on the learner, not the teacher, or even the employer of the learner.22


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The dilemma is that there is not an obvious transition path from where we currently stand in learning and innovation, to where we need to be. The purpose of this paper is to share a coupled model of collaboration that connects higher education, workplace, and basic research. Even though the market often sees education and research as orthogonal, we believe that learning and innovation are coupled. This viewpoint aligns with leading pedagogical practices including problem-based learning, blended learning, and the flipped classroom. 23 We believe that experimenting with just a few changes to processes and adding some key connections can make a huge difference. We have piloted elements of the model, taking an approach of leaving existing activities in place while building connecting practices for an integrated model only where required. We’ve been actively pulling in ideas from outside the university – MOOCs, microcredentials, online videos, credits for experiential learning, coding challenge problems, crowd-sourcing – and the list grows continually. Fortunately, the required changes do not require a wholesale discarding of current methods; rather, by adding a few appropriate nudges to the existing system, the required information flows can transform the entire system to dramatically reduce its timescales and raise both responsiveness and effectiveness. The following sections lay out a digitally coupled learning and innovation model that can provide a transition path to the future.

Digitally Coupled Learning and Innovation Processes Digital platforms are being implemented across many market sectors such as Airbnb in lodging, Amazon in retail, Uber in transportation, and Coursera in education. 24 The potential for stepchange reduction in cycle-time for all activities is possible as well as the ability to achieve much more efficient operation. Figure 1 shows the difference between a local, siloed set of activities and an integrated approach using a shared platform. The silo structure creates several difficulties: 1) Similar courses are taught in multiple departments. Fluid mechanics is taught in Civil Engineering, Mechanical Engineering, and Chemical Engineering, and much of the core content is duplicated with application examples reflecting different markets. 2) The functional silo design of most academic departments means that communications are limited, and feedback loops are thus thwarted. Technology enables us to design content and communications differently, to avoid these silos and to avoid duplication. While opportunities exist, change is required to the underlying business and funding models. The National Science Foundation is championing Convergence Research – the need to address a specific challenge or opportunity and deep integration across disciplines25.


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Figure 1. Change from local to integrated model of learning and innovation. Due to the four postulates -especially digital connection -- cycle times have decreased dramatically. This leaves academia with unsustainable costs paying for legacy systems of lower value.

We have taken the concept of digital platforms seen in various market sectors and have been applying it to the University / Workplace interface as shown in Figure 2. Many universities have a dual mission of learning (education) and innovation (research). To achieve greater advantage from technology there needs to be system level, integrated design across universities and multiple workplaces. The challenge is that there are very different cultures, time structures, and underlying business practices that make a system level design a challenge.20 The outcomes of an integrated model for different stakeholder groups are: • Students - increased readiness for the workplace, self-understanding of career and skills options guiding education planning, access to life-long learning content • Companies - access to broader pipeline of diverse talent, improved early retention, reduced time to autonomy, and new innovation opportunities • Universities - access to new content delivery, innovation, and funding opportunities • Society - more life-long learning content and better delivery/access, extensions for broader knowledge retention and transfer Figure 2 shows how we can build connections between university and the workplace; we are not proposing to rebuild either of these. The emphasis is on new value-added “connector” activities that use existing practices. While innovation and learning are often thought of and budgeted as separate activities, technology enables design of practices that integrate learning and innovation in a feedback loop. In the figure, the light boxes with bold letters - core curriculum, research, workplace, and markets exist already.


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Figure 2. General model of integrated learning and innovation connecting University and Workplace. The gray items exist currently; the green items are the connection enhancements. The Classroom+, Experience+, and Innovation+ steps provide the sensors and actuators that enable a feedback loop. The general theme is to “begin with the end in mind,” and to engage continuous feedback among students, universities, and the market. In this figure, the students are the “vital fluid” traversing the process. A critical point is that the students are not only the tuition-paying attendees of the university, but the workers in the workplace, potentially simultaneously.

Near the top of Figure 2, connecting the worlds of the university and the workplace, we have added a student-centered process for career discovery. The purpose of career discovery is to help students develop an understanding of what they might like to do for work and use this to motivate their planning for time at the university and into later life. “Classroom+” is meant to prepare students for a move to the workplace and “Experience+” provides feedback from workplaces to academia. Innovation+ is used to catalyze new concepts that combine workplace and academic perspective. The intent is to build a much more integrated and communicating system, and to have students become the vital “fluid” that provides the connections as they traverse both learning and earning. We summarize the blocks shown in Figure 2 in Table 1. Table 1. Process descriptions of integrated model given in Figure 2. Item

Description

Market Discovery

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Use market skills and jobs data for learning design. Create feedback and connection with employers. Initial market jobs and skills information from Burning Glass

Career Discovery

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Market skills and jobs data to build student career discovery. Students share and translate personal skills and experiences. Mentor sessions to reinforce career choices and options.

Classroom+

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Classroom modules emphasizing skills in application problems. Design as partnership between university and companies. Priority for course module development based on market needs.


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Experience+

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Returning student interns enhance connection of market needs to research. Unique undergraduate and graduate internship programs can be designed. New technology-enabled proprietary knowledge management practices.

Innovation+

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Connect market needs and proposed solutions to build new programs Innovation sessions - “4-Block” summaries discussed with market experts Engage multiple perspectives, people and experience levels

Shared Platform

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Need for a shared global platform -- growing market examples. Professional societies, crowdsourcing, curation, and collaboration. Develop a sharing / financial model for operation.

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The proposed design is a starting point and with continued sharing and improvement new more efficient practices can be designed. In the following sections, we describe details and experiences as well as project on future next steps.

Cloud Platform By working across universities, we can leverage professional societies such as AIChE or ASME, government agencies such as NASA and NIST, and other similar organizations to connect across boundaries. This enables us to pull in and curate resources from a wide range of sources such as Khan Academy, LinkedIn Learning, YouTube, LearnChemE 26 and MOOCs 27 (e.g., Udacity, EdX, Coursera). On these sites there is a variety of educational video covering accounting, finance, supply chain management, presentation skills, lab safety, workplace ethics, statistics, data analysis, technical science subjects, and much more. We see an increased opportunity for professional societies going forward as they can connect evolving market needs to content curation, development, and vetting. In addition, many societies have student chapters at universities that can both expand career awareness among their peers and bring new communications and work practices (such as Slack) into the workplace. Figure 3 shows an example hierarchy developed by curating existing online content for use in a flipped classroom.


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Figure 3. Curation of existing online content for use in classroom+ modules.

Career Discovery A challenge young students face is the declaration of their major. At a time when they have a limited understanding of jobs and the workplace, they are called upon to make this decision. 28 Once committed, they need to complete a prescribed sequence of courses to fulfill degree requirements. Changing majors along the way can be difficult because of prerequisites and other scheduling challenges. This difficulty has led us to develop what we call career discovery so that students have a more informed perspective of their personal attributes, courses, majors and future job possibilities at the beginning of the university experience,29 before choosing their major. In his 2005 Stanford Commencement address, Steve Jobs talked about “connecting the dots” 30. Looking backwards it is a lot easier to see connections than by looking forward. This is true about career planning -- it is hard to look forward when you don’t know what opportunities exist. And, different jobs lead to other jobs that wouldn’t be known looking forward. The career discovery process shown in Figure 2 is designed to be a look back from the future. Most students have limited understanding of the job market and getting them to think and talk about possible future career options is very important. The general career discovery model is shown near the top of Figure 2. The process starts with market discovery -- what jobs and skills exist in the market? We then ask engineering students to hypothesize “what might you like to do?” as opposed to “what’s your major?” This is more openended and gets them thinking more about whether they want to be a project manager, a business unit leader, an entrepreneur, or another path. Students each then build their personal skills and experience grid. This provides a good baseline for what they have done, which leads to discussion


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of their personal learning plan. To supplement the external market view we have licensed two data products from a workforce analytics company.

Market Discovery We start from the market side, with analysis of job and skills demand. We have licensed two products from Burning Glass Technologies, a Boston-based data analytics company that has built a substantial database of job postings, resumes, and government jobs data. Burning Glass also allows for extensive drill-down and filtering of jobs data down to the required skill level. There is skill information that is grouped in three categories: baseline, specialized, and data skills. Matt Sigelman, CEO of Burning Glass, argues that rather than a jobs market, it is more insightful to analyze how companies are looking for skills31. Others have agreed with this perspective in the literature, including project managers in the Scrum methodology. 32 We have most frequently been using two products licensed from among Burning Glass’s many offerings: Labor Insight™ and Program Insight™. Figures 4 through 7 highlight various market views of jobs and skills. A drill-down of 2019 jobs data is shown in Figure 4. There were over 31 million total open job postings in the US at the time of this paper. The data were a surprise to us; for example, the top open job is for registered nurses followed by truck drivers. Of the total, about 20 million of the open positions require a 4-year degree. Additional details are shown in the figure by degree level.

Figure 4. Twelve month Jobs Posting in the US April 2019. Source: Burning Glass Technologies. “Labor Insight™ Real-Time Labor Market Information Tool.” http://www.burning-glass.com. 2019. The data were filtered for Burning Glass Occupation Codes: Science and Research, Engineering, and Manufacturing and Production.


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Figure 5 shows US job postings for several disciplines with specialized and baseline skills listed in priority order from Burning Glass. The market view by academic discipline shows that while there are different specialized skills by discipline, the baseline skills are common across all disciplines. The skills desired by discipline also do not neatly map to courses taught as part of a major. Working with companies, we have been exploring how to connect the market view of disciplines to existing courses and to identify gaps that are opportunities for improving the connection.

Figure 5. Baseline and Specialized Skills for Chemical Engineers - US April 2019. Baseline skills are typically similar across all job postings whereas there are differences in the required specialized skills. However, when looking at specialized skills there are common skills across different discipline groups. From a skills viewpoint a degree is a predefined bundle of skills. Burning Glass has developed hybrid degree model that focuses on skills / jobs and aligns much more with the concept of life-long learning and continual acquisition of new skills. Source: Burning Glass Technologies. “Labor Insight™ Real-Time Labor Market Information Tool.” http://www.burning-glass.com. 2019.


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Figure 6 is a drilldown of job posting for 3 different Burning Glass Occupations: Chemical/Process Engineering, Product Manager and Marketing Manager for the Chemical Manufacturing Industry. Source: Burning Glass Technologies. “Labor Insight™ Real-Time Labor Market Information Tool.” http://www.burning-glass.com. 2019.

Figure 6 is a market-based job view for the occupations in the chemical manufacturing industry. A young chemical engineer might join an R&D product development group. A possible future career move from their first job may be to product management or marketing. But none of her coursework prepared this hypothetical student for market segmentation and sizing, customer feedback, or new product launches. The skills required for a product manager or marketing manager are different from a chemical engineering degree and are typically learned in fragmentary fashion over a period of years working on cross-functional teams. Often a good chemical engineering background is seen as a positive attribute for moving to another function, but it is not sufficient (as the list of specialized skills illustrates). Students need to begin to think about these types of moves early in their education so they can gain broader training and experience in the skills they will need as their career evolves. This also opens the potential for new courses and training for use in the workplace as well as at the university.

Figure 7. Drill down of Jobs Posting for the skill “machine learning” - US April 2019. Source: Burning Glass Technologies. “Labor Insight™ Real-Time Labor Market Information Tool.” http://www.burningglass.com. 2019.

Figure 7 is a skills-based view filtering for “machine learning”. The growth of AI, machine learning, and data analytics has created the need for new “machine skills” to complement existing functional positions. The majority of machine learning job postings are in the market place and


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several “chemical engineering” industries are listed. Having a broad view of where can machine learning be applied as a functional skill in the workplace is part of the broader reskilling effort that is underway. Students who gain experience in these fields have a broad variety of future jobs available from traditional manufacturing into the tech world. Market discovery works in both directions. Existing hiring practices at many companies encourage monocultures: the recruits look and think very much like the interviewer, who is often a recent graduate of the school where recruiting is happening. When change happens, getting fresh perspectives can be challenging given the similarity of the employees to each other. Getting deeper into the skills data allows hiring companies to broaden their recruiting criteria in pursuit of more diversity of background and perspective. 33 Much like in nature, more diverse ecosystems are heartier and respond more readily to external change: a single organism destroyed Ireland’s potatodependent economy while countries with less concentrated food bases survived. In addition to our career discovery work with students, we have been using Burning Glass products to engage local and global companies that hire from our campuses: What skills are in short supply? How might the campuses respond at the undergraduate, graduate, and continuing education levels to help ease the shortage? How can companies more effectively recruit students?

Skills Discovery - “Five Futures” and “Skills Grid” To look forward we have students create their personal one-page “Skills Grid”. In group sessions each student builds their personal grid and then each shares it with others. The ultimate goal is to have them think about what courses and what experiences they would like to have to be able to get their first job. The process encourages students to begin thinking much more about what they need to do prior to graduation and interviewing. And while our attention has been primarily with students, the same approach applies for anyone who is working to manage their career path over decades. As part of career discovery we engage students in discussions of possible future job interests. One tool is for students to consider “Five Futures”. For example, what are 5 job postings a student can find that they would want 5 or 10 years from now? Examples might include startup founder, CEO, professor, design engineer, government employee. Once they hypothesize these 5 futures, they can examine the skills required to get there. Now they have a potential path from present to future, some dots to connect. As they learn over time, a student might find that they no longer find one of the futures to be valuable to them. They can adapt to this future, and pivot to another path. The skills grid one-page template is shown in Figure 8. It is a simple inventory of what they have done segmented by role and category across the columns. We have students share their draft grids with each other to discuss and learn. And we have emphasized that there is no single format or approach. In the discussions we have found that often courses are not explicitly highlighted but embedded in experiences and learning. We have also heard wonderful stories about small


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businesses and leadership on summer jobs. Negotiating skills developed tending bar. The exchanges and sharing among the students also provide new insights. More recently we have complemented these sessions with more senior people in the workplace sharing their life path, lessons learned and what they found through their career. We also ask them to talk about failures they experienced and lessons learned.

Figure 8. Skills Grid Template. Students share their grids with a group and highlight specific experiences and learnings. These are captured with a couple words, but are shared as 30-second stories. This works well for career planning in the workplace as well as university. There is no single format.

The skills grid is a working document for students and serves as a supplement to a resume. A resume is an inventory of what has been done, whereas the purpose of the skills grid is to help assess balance across multiple dimensions similar to a screening Design of Experiments (DOE). The ultimate purpose is to bring together where are the jobs, what are the required skill and what experiences have they had to date. From that begins planning for courses, jobs, internships as they progress through their education and out into the marketplace.

Coupled Learning and Innovation Processes In the sections below, we describe the elements shown in the bottom of Figure 2. The challenge we face is to design and implement new contemporary processes and practices that fit both the rapidly changing workplace and the slowly evolving university. We believe that creating connectors in the existing structure is a needed step to be able to make more significant changes in the future. We have created Classroom+, Experience+, and Innovation+ for this purpose.

Classroom+ Most university degrees have a very long list of required courses. There is little time available to add new classes, and the discussion about what to take out and put in usually takes years. As students enter the workplace there are new skills and experiences they must learn on the job or through non-traditional channels. Additionally, students have very little flexibility in changing


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majors as they approach a dynamic labor economy: some have told us that by the time they finished a degree in their chosen discipline, they were far less enthusiastic once they understood the discipline’s core concepts, but felt they had no option but to continue. The concept of Classroom+ is to develop experience-based training for on-campus workplace preparation as well as for ongoing training at companies. That is, students and young employees learn skills that enable them to gain more from their workplace experiences. Also, by partnering with companies we want to capture the significant application and experiential knowledge that exists in the workplace. At the same time most traditional companies are struggling to reskill their existing workforce, students entering the workforce bring along new skills and experiences that can be part of the reskilling effort, provided the hiring companies fuel new-hire enthusiasm rather than dampen it by saying “here’s how we’ve always done things here.” YouTube has created the “How do I…” format. If you want to fix a leaky faucet, hang a drop ceiling, or perform some other task there is typically a YouTube video available. Students routinely look to YouTube, Khan Academy, and other online sites for skills and application training. Many faculty post content on YouTube and build playlists for student use. As content continues to grow, however, we lack a collaborative process for designing, curating and validating content for broad use. Having a defined team with relevant experience can be part of validation and adding of metadata for access. We have been developing modules for use in a dedicated course or as a supplement for an existing course. Figure 9 is an illustration of how we have been building Classroom+ modules. We design a general problem addressed by a student team typically emphasizing use of multiple skills. An example problem we have used is shown in Figure 10. Working with companies building “How do I…” examples can be created and shared. Companysponsored knowledge capture of long-service employees can use a similar approach. Proprietary information could be restricted access behind a company firewall and logically connected to all shared public application knowledge. A content library could be the basis for supplementing existing or new modules for use in classrooms, internships, continuing education, or in the workplace.


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Figure 9. Classroom+ problem design. The emphasis is on how to solve a problem integrating key skills and practices.

Figure 10. An example Classroom+ Business Problem. Students work in teams on the problem and apply concepts of mass/energy balance, financial analysis and six sigma.

Additionally we have found that group-challenge problems and business simulations help to connect problem solution with engineering skills and analysis. Examples are provided in two separate papers34 35. This is an area we are exploring for future classroom use.

Experience+ Experience+ is to capture what is known (often undocumented) in the workplace and make it more broadly available, being careful to maintain separation of public and proprietary information. We have heard many stories from students returning from internships about the people they met, the advice they received, and practical tips for life. Some have new relationships and a network for


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questions and advice. They also have a new understanding of challenges that exist and the projects underway. Three distinct sets of activities are included under the Experience+ heading: Knowledge creation Many established companies are experiencing severe knowledge drain resulting from workplace retirements. Decades of knowledge are being lost and finding effective means for capturing and sharing is critical. We think that the combination of a student and senior person in the workplace can begin to design what is known, and by applying the YouTube “How do I…” model they can begin to inventory workplace practices in ways they are relevant to entering employees. Confidential information is retained by the owner and is connected to a growing public network of knowledge. There are variations of the MIT Chemical Practice School2 model that could be used to create new public private knowledge partnerships and content with senior professionals at companies acting as the “director”. Knowledge curation Through various student organizations and professional societies and in partnership with companies can we prioritize, design, and develop classroom+ content for training? Can we also access and curate public content at companies and share more broadly? This is where professional societies can play a role hosting content across a range of stakeholders from universities to marketplace. Circular internships In partnership with companies the objective is to prepare students for internships, support them during the internship, and then capture new opportunities for projects when they return to the university. The goal is to build a model for student leadership experience engaging both university and companies. To design and implement new collaboration practices will require funding along with new business and financial models. Workplace engagement can help bridge market needs to university and enable new opportunity identification for basic research 36.

Innovation+ Companies generally know what they want to accomplish but they often do not know how. Faculty sometimes interpret this as withholding information. The challenge is to design effective ways to bridge basic research and market as the cultures, practices, rewards, and time scales of universities and companies are very differen.t20,36 Further, universities and other agencies are sponsoring the rapid growth of entrepreneurship courses, start-up companies, the lean startup methodology, more open intellectual property ownership, innovation centers, and startup launch centers 37. We have explored practices to bridge research with market needs to develop new programs engaging multiple disciplines and perspectives building on capabilities available today.


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To build this connection we have developed a simple innovation practice. First companies share brief descriptions of what they want to achieve. The descriptions are circulated to all interested faculty. Faculty prepare one or more one-page four-block concept pages describing something they could do based their research or capabilities. The four-block is not a proposal, it is a concept they propose based on their understanding of the need and what they think might be relevant. In the oil and gas sector we generated over 100 one-page concepts. (An unanticipated outcome was we could share these multiple times with different companies and provide a much better understanding of the work underway at the university and more immediate connection to faculty.) An innovation session is then held where faculty present their one-page ideas with external company and other representatives. As expected, we often hear “I didn’t know you did that”, “could you do this instead,” or “do you people ever talk to each other?” All of this creates a deeper understanding and engagement from both sides. With the right mix of skills and background at an innovation session many questions can be answered, and follow-up is much easier since market, customer, technical business questions can all be addressed. Figure 11 is an illustration of how the innovation process flows. It is highly iterative and bidirectional. Many new technologies with an intended purpose find a potential home in applications that were never envisioned by the researcher and using research unknown to the company.

Figure 11. Design of Innovation Sessions. Companies provide a list of interests and opportunities which is circulated to faculty. Faculty then develop any number of 1-page “4 Block” sheets that include title, concept, status and proposed steps and are illustrated as the small boxes in the figure. An innovation session is held where options, opportunities and next steps are developed. In many cases what emerges is a new concept which evolved from the interactive discussion. Rules and plans for IP are decided and discussed prior to the session.

The most valuable part of the innovation sessions are the human connections established. There is something powerful about getting people together to share ideas, concepts, and personal experiences. The experience often leads to “ignition moments” 38 of learning, discovery, and transformation. Often it is outside of the formal session when ideas are further developed and explored and relationships established. There is nothing more wonderful than to see the flash of insight cross a student’s face as they realize they know just as much as anyone else in the room about a specific topic and can make a big difference by taking initiative and ownership. In today’s


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digital highly integrated world, finding time to ponder, think and reflect is vital, and bringing radically different views to the discussion from basic science to customer marketing leads to valuable innovation moments. The final catalyst that brings this together is a strategic leadership model that has been very well described. 39

Conclusions and Future Possibilities As we have seen, engineering education is seeing a wide range of experiments to address the many needs and opportunities presented by global digital platforms. Six things should be kept in mind: 1) We are in the early days of a broad and deep transition. It’s too soon to pick winners or dismiss given options as impractical. Small steps amidst a growing community of practitioners who can reflect on the effort appear to be prudent, fast-cycle, and iterative. Maintaining a focus on the learner rather than the institution will be imperative. 2) Data matter and new partnerships will be required to build both the “warehouses” (or whatever metaphor wins out) and the skills base to exploit measurement of essentially every aspect of both learning and engineering practice. The Burning Glass experience has convinced us of the richness of their approach. Learning how to work with new types and scales of data, and with new kinds of data-centric entities, will be essential. 3) Partnerships will beat monoliths, we believe, given the necessity of global scale and reach. Learning to find and build these new cross-organization initiatives will be faster and more nimble than trying to build an Amazon-scale entity inside one company, university, or startup. 4) As uncomfortable as it makes people, deep change is rarely linear: Sports Illustrated did not invent ESPN, nor did Sony launch the iPod. Winners in the previous technology/economic regime can often be caught on the outside of a new wave of change. Learning to spot impending “hockey stick” growth curves (that often come at the cost of less nimble competitors) will be essential in both business and education. 5) Building new practices should be done to relegate transactional activities to online and machine environments so that more human interaction and connection can be established face to face. “Flipping the classroom” (in which students watch lectures at home at their own pace and do what used to be “homework” – problem-solving and application of knowledge -- in the social, collaborate setting of the class period) is a prime example of how digital platforms can humanize learning, and universities are late to this practice.40 6) We have tried to learn and translate the great practices of many others, and recognize that there are many other good approaches and programs underway. While in the near term we believe much can be accomplished with minor tweaks of and connections among existing practices and entities, ultimately the activities described will require new business and funding models across public, private and government organizations. We firmly believe both the engineeringdriven company and the residential university will look very different in 2030 compared to 2010. Whichever practices gain traction, we believe they will share several characteristics. First, they will shorten cycle times and tighten feedback loops, aided in part by better sensors and algorithmic


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sense-making. Second, the effort will be stronger for its degree of inclusiveness and diversity of experiences. Building a global platform takes more than scale; it requires learning from a wide swath of human experience. Third, people of different backgrounds, organizations, and economic motivations will need to listen to and learn from each other -- the challenge is probably more cultural than technological. We end where we started: with appreciation for the pioneering work, but especially the spirit, that Professor Eckert has brought to engineering education. He looked at technology through the lens of the learner, started small but thought big, and invited anyone who was interested to collaborate. The early innovators in our 21st-century wave of change can only hope our combined efforts inspire people to do the same.

Acknowledgments Professor Chuck Eckert was the PhD advisor for MA, and throughout graduate school and after he has been a great mentor and friend. Good times and bad. He has always been there to listen, encourage new ideas, offer a perspective, a motivational comment or simple congratulation. For that MA is forever grateful. We thank many other colleagues who have been part of these ongoing discussions over many years. The authors would like to thank General Electric for financial support of elements of this work.

Conflict of Interest Statement The authors have no declared Conflicts of Interest.

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TOC image: Innovation, education, feedback.


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Digitally Coupled Learning and Innovation Processes | Industrial

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