Of That

Brandt Redd on Education, Technology, Energy, and Trust

21 February 2013

Winds of Change: Higher Productivity in Higher Education

Note: This first appeared last week as a guest post on the Next Generation Learning Challenges Blog. I highly recommend both the blog and the NGLC website.

My first lecture hall experience was American Heritage at Brigham Young University. The course was required for all freshmen and more than 500 of us at a time attended two lectures a week. In a third “lab” period we met with a TA. The professor was charismatic and the instructional design team supplied him with carousels full of colorful slides. Still, a large fraction of the class was asleep at any given time.

Large lecture hall courses are one common method of increasing productivity in higher education. Another is weed-out courses – those designed to convince students that they should choose another, less expensive major. For me the weed-out subject was Discrete Structures. This Computer Science subject is rich with metaphors like trees, maps, chains and links. It can be taught through story, modeling, manipulatives and real-world application. But our version was deliberately dry with an emphasis on precise vocabulary and obscure notational forms. The pass rate hovered near 50% and hundreds of students were convinced that they weren't capable of understanding computer science.

Higher education in the United States is sandwiched between twin pressures, increasing societal needs and expectations on one side with flat or declining funding on the other. To meet this challenge, institutions will have to dramatically increase productivity. But traditional productivity boosts like large lecture halls, weed-out courses or greater admissions selectivity won’t be enough this time around. What’s required is fundamental change to the way we support learning. We need a more personalized approach.

Societal Needs and Expectations

Employment projection is from the Bureau of Labor
Statistics Job Outlook
. Supply is based on National
Center for Education Statistics data on annual
Computer Science BS degrees awarded
. Attrition
is based on a 40-year career span.
While the U.S. unemployment rate hovers around 8%, there is a shortage of engineers and technicians. In 2012, the unemployment rate for software developers was only 2.8%. An Association for Computing Machinery study indicates that the United States will need more than 150,000 new computer scientists each year through 2020 yet our collective colleges and universities only produce 40,000 degree holders to fill those jobs. Healthcare workers are also in short supply. In 2012 the unemployment rate for physicians was 0.8%. For Physical Therapists it was 2.0% and for Registered Nurses, 2.6%.

At a recent Technology Alliance conference it was noted that colleges and universities in Washington State produce less than half as many engineers, technicians and software developers as the state’s employers consume. The rest have to be imported from other states or countries. A speaker from the University of Washington pointed out that they have increased introductory Computer Science enrollment from roughly 1200 to over 2000 per year. But the Microsoft representative responded that they have 3,600 engineering and computer science openings and they’re competing with Amazon, Boeing and many others to fill those spots.

Of 4.3 million freshmen who started college in 2004, only 2.2 million (or 51%) graduated within six years. This isn’t a perfectly accurate figure. Because of the way records are kept, it’s hard to count students who transfer and complete at a different institution. But inadequate record keeping is another symptom that institutions haven’t focused enough on ensuring their students are successful. Higher completion rates will save a lot of wasted student time.

As we move into the 21st century the fraction of unskilled jobs continues to diminish while those requiring advanced skills increase. It’s no longer appropriate to sort students by “aptitude.” We must give students the support and guidance they need to master advanced subjects.

The Funding Landscape

Education is the largest item in most state budgets. In California it accounts to between 52% and 55% of the state general fund. With the recession hitting state revenues and the expiration of stimulus supplements, state fiscal support for higher education dropped by 4.7% between 2011 and 2012, remaining flat in 2013. Overall, annual support has dropped by 10.8% since 2008. On a per-student basis, state and local financing dropped 24% in the 10 years preceding 2011.

At the same time, tuition is rising much faster than inflation. Tuition and fees at U.S. public universities rose 4.8% for the 2012 school year to an average of $8,655. At nonprofit private colleges tuition and fees rose 4.2% to $29,956. In addition to drops in public funding, the cost to provide education is increasing and the recession has diminished private endowments.

Total student debt in the U.S. now exceeds $1 trillion making it higher than the nation’s credit card dept. Student loans aren't a big problem if they are correlated with significantly higher earning potential. But loan approval is not connected with choice of academic major or the graduation rate of the institution.

Personalized Learning

The demands on higher education are greater than ever. We need more graduates – especially in certain fields. We need better completion rates. We need to support students in tackling challenging subjects. Moreover, we have to do this with flat or declining budgets.

The Bill & Melinda Gates Foundation has assembled representatives from a dozen colleges and universities that are trying new approaches with promising results. The Personalized Learning Network, as it's called, includes innovators like Western Governors University and American Public University; pioneering programs at Arizona State University and UC Berkeley; and NGLC grantees like the Kentucky Community & Technical College System, Rio Salado College and Southern New Hampshire University.

Recently I had the privilege of meeting with this group. There’s a lot of variation in their personalized learning programs but they share these common features:

  • Mastery Learning and Independent Pacing: Students have to master the current topic before moving to the next step. Self-pacing grants this freedom and ensures that there aren't gaps in understanding due to bad days or illness. And students don’t waste time on topics that they already understand.
  • High Expectations: The institutions make a commitment to support all students sufficiently so that they can master the material.
  • Feedback: Students and instructors are constantly informed about conceptual understanding and progress through the material.
  • Adaptive Learning: The learning system adapts according to individual student actions and performance.
  • Individual Attention: The programs facilitate abundant 1:1 time between students and faculty.
  • Motivation: Systems and attitudes that foster student motivation include interesting activities, student autonomy, recognizing good performance and avoiding frustration either due to anxiety or boredom.

All of this is enabled through strategic use of technology. Most use some form of blended online and in-person learning. The key point is not to simply add technology but to apply technology in the service of personalized learning.

Personalized learning programs should be able to address higher education pressures for better success and completion rates. But can they also help educate more students at lower cost? I believe so. Technology can automate many tasks that cost a lot of educator time. Video lectures are a personalization technology because they allow students to view on demand and replay as needed. Not only do they save the time in class but they also save the instructor time preparing the lecture. Objective assignments can be graded automatically and feedback given instantly to the student. Feedback to instructors can help them optimize their interactions with students. Subjective grading, while still consuming human time, can also be made more efficient. All of these factors help institutions increase capacity and reduce per-student costs.

Equally important are the savings offered to students. Immediate feedback helps students learn concepts more efficiently and avoids time wasted on misconceptions. Students can advance immediately upon understanding a concept and get credit for things they learned previously. And authentic learning activities support a better and more complete understanding of each topic. In one study by Carnegie Mellon’s Open learning Initiative they were able to teach students the same material in half the time with better retention.

Changing higher education is like turning a glacier. Features like accreditation, tenure, financial aid, credit transfer, and faculty autonomy interlock to form a seemingly insurmountable barrier protecting the status quo. But the twin pressures of increased expectations and diminishing funding result in an unprecedented incentive for change. Like the Maginot Line, traditional barriers won’t be overcome but simply bypassed.

No comments:

Post a Comment