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In This Issue
Engineering, Technology, and the Future of Work
Autonomous Vehicles Implications for Employment Demand
Creating New Value with Performance-Based Industrial Systems Design and Operations Management An Engineering Opportunity
Education Transformation to Support Lifelong Learning
Beyond Schooling Educating for the Unknowable Future
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Fall Bridge Issue on Engineering, Technology, and the Future of Work
September 15, 2015 Volume 45 Issue 3

Education Transformation to Support Lifelong Learning

Tuesday, September 15, 2015

Author: Katharine G. Frase

The Role of Public-Private Partnerships and Data

When most of today’s 8th graders leave school they will work in jobs that do not yet exist. But current education methods and content cannot effectively prepare them, thus creating an employability divide as degree holders emerge into a workplace without the skills that employers need. The nature of work will continue to rapidly change, so both current and future workers will need to constantly update their skills.

It could be argued that people have always needed to be lifelong learners, but that need is now greater than ever. And the need for lifelong learning has implications for every portion of the education and employment pipeline—in fact, perhaps a linear pipeline is no longer the right image for the US educational process.

In this article I explore two foundational issues for lifelong learning. The first challenge is to prepare students to learn how to learn rather than accumulate facts. What changes are required in the curriculum and pedagogy to enable this? The second challenge is to use data on both employer skill needs and individual capabilities and interests to create personalized guidance for learners, whether it is their first or fifth time through education and training.

Introduction

In an increasingly competitive global economy, persistent technological innovation is radically changing the nature of work and the skills needed to do that work.

Changes that affect the workforce and training needs can be considered as occurring in three waves. In the first, the existing jobs of the older generation are largely unaffected while the incoming generation learns new things and does new jobs. In the second wave, familiar today, new technologies affect existing jobs as well and many workers feel the need to update their skills to continue to advance their careers. Finally, the third wave, which is rapidly approaching, will compel the next generation of workers to continually update their skills throughout their lifetime as marketplace changes are sustained and actually accelerate.

These changes require a reexamination of education, from curriculum to pedagogy, and the use of technology to create personalized guidance for learners.

Nurturing Learners with the Right Skills to Succeed

Besides technical skills or subject-matter expertise, equally important to success in the rapidly evolving workplace are behavioral skills: collaboration, team building, communication, and understanding of the social or cultural context of a type of work.

But according to a recent IBM survey, 51 percent of academic and business leaders believe the current higher education system fails to meet the needs of students, and nearly 60 percent believe it is failing both industry and society (IBM 2015). And a 2012 study by McKinsey reported that 39 percent of employers cite a skill shortage as the primary reason for entry-level vacancies (Mourshed et al. 2012). The employment gap is viewed differently, however, by the three stakeholders—employers, students, and academic institutions: 42 percent of employers and 45 percent of youth surveyed believed that recent graduates were well prepared for the workplace—in contrast to 72 percent of academic institutions that believed their graduates were well prepared (Mourshed et al. 2012; figure 1).

  Figure 1

It is clear that employers and educators need to work together to help students (1) develop deep and broad skills aligned to the new economy and (2) become capable of self-learning to ensure their adaptability to evolving workforce needs.

Fortunately, the dual challenges of teaching students not only to be learners, rather than accumulators of facts, but also to have both broad and deep skills are already transforming education at all levels. In higher education curriculum, a number of efforts are under way to produce T-shaped graduates: the downstroke of the T represents deep expertise and the crossbar represents broad social and language skills. Innovative approaches are also being developed in K–12 education programs and through partnerships between academia and industry, as described in the following sections.

Innovation at the College Level

The challenges to incorporating traditional liberal arts content into technical degree programs are widely discussed (e.g., Bordoloi and Winebrake 2015). Many four-year universities require a structured courseload across both the student’s major and other disciplines, with the idea that exposure to multidisciplinary content (e.g., through required courses in English, social sciences, and languages that are not part of the major curriculum) will foster the broader skills.

Some programs have moved toward a more project-based, rather than lecture-based, curriculum to improve student engagement and encourage teamwork and communication skills. The incorporation of design in engineering (as at Olin College) or the explicit development of self-reflection and portfolios of experience (as at Dublin City University) support the acquisition of synthesis and self-learning skills within a disciplined framework. Still other institutions are adapting and integrating multidisciplinary content into the core engineering curriculum both to enhance relevance to students’ stated interests and to fit more content into the traditional 4-year degree cycle.

There is a growing corpus of evidence that practical experience for students—for example, through internships and similar approaches—enhances both student engagement and the development of professional skills such as collaboration, communication, and adherence to deadlines and workplace requirements (Craig 2010; Miller 2015). This experimentation with methods and curriculum is vital to discover best practices that can be widely leveraged.

Another approach to open up classroom or external time blocks for discussion, synthesis, problem solving, or practical experience involves the flipped classroom, where traditional lecture content is consumed online before class. The transformation of the traditional lecture format has a number of benefits and challenges. Creating compelling online content requires more than simply posting the same lecture that has been used for many years: new modalities (video, simulation, gaming, collaboration) and in-line formative assessments are needed to ensure that students digest, rather than skim, the content. The role of the faculty shifts from “the sage on the stage” to coaching, facilitating, and mentoring, and assumes a level of comfort with using technology in these ways. Significant professional development and willingness to experiment are needed.

The flipped classroom model can deliver benefits beyond time management. Students who explore multimodal curricular materials are more likely to develop self-learning skills. Moreover, the digitization of educational content (including reference, instructional, and student-generated material) inherent in the flipped model enables the collection of near-real-time data to assess the understanding of concepts by an individual student or a class group, providing insights to the instructor on which topics to emphasize in the classroom. The data can also be mined to assess student performance risk and to create personalized recommendations for additional content (whether for remediation or advanced learning). The digital format thus allows the entire class to move forward, but on individualized paths of content and time.

At Marist College the Open Academic Analytics Initiative1 created a risk-alert system using predictive analytics to identify and warn students that their trajectory may not lead to success in a specific course, allowing professors and students to take timely action early in the course. Similar programs at Purdue and other universities have demonstrated the power of data when coupled with analytics in support of decision making (Pistilli et al. 2012).

Innovation at the Precollege Level

Not every worker will, or should, be the product of a 4-year college education, so incorporating “T-shaped-ness” in K–14 and vocational education systems is critical.

In the United States (and elsewhere), however, K–12 education is increasingly defined by standardization of the facts or functions that students are expected to have mastered at each level. Educators need to ensure that students are also gaining the skills they need for lifelong learning, multidisciplinary insight, and employment.

IBM and others are beginning to pilot solutions in these areas, demonstrating the value created for students, their family, their community, and local businesses. For example, in the Gwinnett County (GA) public schools, teachers are being supported with insights about their students and effective intervention methods that go beyond academic methods. Under the leadership of long-standing superintendent J. Alvin Wilbanks, the schools have invested in technology to increase student engagement, develop the professional skills of faculty and staff, and enable teachers to better understand and intervene with individual students within the constraints of curricular standards and time pressures.2 

Innovation Through Public-Private Partnerships

A recent study by the Conference Board (2015) underscores the importance of public-private partnerships and of policy decisions at the employer, government, and education institution levels to improve both the alignment of coursework to workplace needs and the use of these educational pathways. New and innovative educational models are taking shape.

One prominent example is Pathways in Technology Early College High School (P-TECH), which began in Brooklyn in 2011, is spreading to nearly 40 schools around the nation, and is projected to grow by 2016 to an estimated 100 schools both in the United States and in some foreign countries as well (Fritz 2014). P-TECH’s six-year program, with a variety of corporate partners and targeted curricula, combines academic rigor with career focus: students are paired with mentors from the business community and gain practical workplace experience with paid internships. After earning a high school diploma and a no-cost, industry-recognized associate’s degree, graduates are first in line for jobs with an employer partner.

P-TECH’s innovative education model is designed to build 21st century skills, fill in-demand jobs in the United States, and ensure that young people are college and career ready in the skills of science, technology, engineering, and math (STEM)—disciplines that underpin some of the country’s fastest-growing industries. Other similar models are being developed, such as the Georgia Career Pathways Initiative, in which employers “adopt” a career pathway and work with the Georgia State Department of Education to build a K–14 curriculum, including internships and mentoring.3

Partnerships between business and academia can also help craft new curricula and sponsor practical experience for students at the college and university level. A few years ago experts began to predict that data analysis skills would need to be improved to meet marketplace needs as businesses move toward more automation and faster decision-making cycles (Manyika et al. 2011). In response, IBM and several other companies worked with universities to establish the Big Data University (www.bigdatauniversity.com), which creates curricular content, case studies, and new degree programs in the United States and overseas and allows users (now over 250,000 registered) to learn data science technologies. The goal is both to prepare students with the skills they’ll need to work with big data and analytics and to fill the skills gap for companies across industries from health care to finance to manufacturing.

Use of Data to Enhance Student Preparation

All over the world college graduates are un- or underemployed while local employers cannot find job candidates with the skills they need. This mismatch is a financial hardship for all parties—job seekers, employers, and social services—and has causes on both sides. Employers often struggle to articulate their skill needs in enough detail, or enough in advance of the need, for the academic system to adjust curriculum or provide timely advice to students about areas they should pursue. And academic institutions are often unaware of new workforce needs, or are slow or unable to change their curriculum or career counselling.

The use of data and analytics to inform decision making can help, especially in the guidance counsellor’s office. Many high school and college counsellors handle hundreds and in some cases a thousand or more students, with little information besides a transcript and a five-minute interview with the student about her interests. Yet in many cases data exist and can be used to better guide such conversations in the following ways.

  • A student-centric approach to data can create a holistic view of each student, including detailed analysis of academic strengths and weaknesses, extracurricular interests, and other factors.
  • A composite view of the pathway for, and characteristics of, different careers (e.g., number of years in school, kinds of courses, book vs. hands-on learning, earning potential, geographic location) can help students begin to understand which careers might fit them and can enrich and focus the counsellor’s discussion more meaningfully.
  • Inclusion of skill requirements in the strategic planning of local employers can help them predict what skills they really need. What are the characteristics of their most successful employees? (The answer to this is often not as simple as what courses they took or what degree they received.) Will those skills likely be the same or different in 2–3 years? If a company is planning to expand its product line or retrofit its factories, how will that affect the skills needed, not just the number of employees?

These three elements—insights about the individual student, the career pathway, and employer needs—can together support progress toward better employment outcomes for all concerned, and can be similarly used for adults who want, or need, to change careers.

Conclusion

Education has always been vital to economic success at the individual, community, and national levels, but has often struggled to respond in a timely manner to changes in the economy and the workforce. The need for timely adaptation is now acutely important in the rapidly evolving national and global economy. Efforts to improve success across the employability divide call for a combination of enhanced education at all -levels, technology (particularly data-driven insights as education becomes more digital and instrumented), and public-private partnerships between academia and employers.

References

Bordoloi LM, Winebrake JJ. 2015. Bringing the liberal arts to engineering education. Chronicle of Higher Education, April 27. Available at http://chronicle.com/article/Bringing-the-Liberal-Arts- to/229671/.

Conference Board. 2015. The Role of Business in Promoting Educational Attainment: A National Imperative. Report by the Committee for Economic Development. Arlington, VA. Available at https://www.ced.org/pdf/20150408_BBE_Role_of_Business. pdf.

Craig K. 2010. Transformational engineering education. Marquette University. Available at www.ceri.msu.edu/wp-content/uploads/2010/07/ Transformational -Engineering-Education.pdf.

Fritz M. 2014. Six years for high school? Why two extra years is catching on. PBS NewsHour, April 9. Available at www.ptechnyc.org, www.pbs.org/newshour/updates/six-years-high-school-two- extra-years-catching/.

IBM. 2015. Pursuit of relevance: How higher education remains relevant in today’s dynamic world. IBM Institute for Business Value. Somers, NY. Available at http://public.dhe.ibm.com/common/ssi/ecm/gb/en/gbe03676usen/ GBE03676USEN.PDF.

Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers AH. 2011. Big Data: The Next Frontier for Innovation, Competition, and Productivity. Washington: -McKinsey Global Institute.

Miller RK. 2015. Why the hard science of engineering is no longer enough to meet the 21st century challenges. Olin College, May. Available at www.olin.edu/sites/default/files/rebalancing_engineering_ education_may_15.pdf.

Mourshed M, Farrell D, Barton D. 2012. Education to Employment: Designing a System That Works. Washington: McKinsey Center for Government. Available at http://mckinseyonsociety.com/downloads/reports/Education/ -Education-to-Employment_FINAL.pdf.

Pistilli MD, Arnold K, Bethune MD. 2012. Signals: Using academic analytics to promote student success. Educause Review, July 18. Available at www.educause.edu/ero/article/signals-using-academic- analytic s-promote-student-success.

 

 FOOTNOTES

1 Information about the program is available at https://confluence.sakaiproject.org/pages/viewpage.action? pageId=75671025.

2 An interview with Dr. Wilbanks is available at www.ibm.com/smarterplanet/us/en/dispatches/gwinnett-county- schools.html.

3 Information about the initiative is available at https://www.gadoe.org/Curriculum-Instruction-and-Assessment/ CTAE/Pages/Georgia-Career-Pathways-New-Rule.aspx.

About the Author:Katharine G. Frase (NAE) is vice president and chief technology officer, IBM Public Sector.