Thursday, January 31, 2013

MIDI turns 30

Musical Instrument Digital Interface

Back in the early 1980s, a technology came along that allowed electronic musical instruments and effects processors to communicate via digital messaging. As a keyboard player in rock bands and computer enthusiast at the time, this was right up my alley! It allowed guys like me with more than one synthesizer and a few effects processors to manage them a little more easily.

Musical Instrument Digital Interface, or "MIDI" was invented by Dave Smith of Sequential Circuits 30 years ago. MIDI is still in use today, and it's use has expanded to many other devices including computers and smartphones.

As a hobbyist item, and one which carried some real complexity, MIDI evolved with the typical support structure of the geek community - the users group. The American MIDI Users Group started up and encouraged local chapters. I founded the Rochester MIDI Users Group in upstate New York soon after. "RMUG" had about 30 members (some musicians, some electronics hobbyists), and held monthly meetings at a local Rochester recording studio. I produced a monthly newsletter that I wrote, photocopied, folded, and mailed to members. Each month at our meetings, a musician or a music store owner would demo a piece of MIDI gear and talk about it's capabilities, both from a musical standpoint and a MIDI capability perspective.

Back in the early 1980s, I was also a computer programmer. I wrote simple software to control MIDI devices from my Apple //e computer. The software could change presets for groups of instruments at the touch of a button, or send "system exclusive" messages to tune the parameters of a single device at a time. I even lectured at a local community college on the subject and taught a few students how to do similar things with their computers and MIDI gear.

Many years later, MIDI is still a part of the underpinnings of much of the equipment that musicians use. But like many good technologies, it is now transparent to most. It simply does its job and fades into the background. Lots of us are grateful that it still works so well.

Happy 30th Birthday MIDI!

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Sunday, January 27, 2013

Does History Matter?

As an exercise for a class, I wrote this "speech" on whether history matters as if I were delivering it to a chapter meeting of the Association for Computing Machinery. Slightly odd premise for a blog post? Yes, indeed. But it was fun to write and I hope it will be fun for some of you to read.

To be clear, I never gave such a speech, and I'm not a member of the ACM. This was simply the set-up for a writing assignment and to demonstrate that I knew some history associated with U.S. higher education.


Good evening fellow ACM members, representatives of the University of Pennsylvania department of computer science, and guests. I’m honored to be here tonight with all of you on this occasion to recognize the 65th anniversary of the Association for Computing Machinery.
Tonight I’d like to consider the question “Does History Matter?” and given the nature of our organization, I’ll approach that question in terms of the 20th century history of science and engineering and the importance of government and academic institutions whose history is intertwined with the ACM.
For many people, history brings to mind lists of key dates, events, and the people whose names are associated with them, but my appreciation for history comes from the opportunity to think about the context for those events, and what motivated the actions of the people involved. It is with that perspective that I reflect on the birth of the ACM 65 years ago, and the times in which the founders lived.
The ACM is known as an educational and scientific society dedicated to the computing profession, but it is also a society rich with history. The ACM has an active and prominent History Committee that organizes workshops on the history of computing and the ACM, and that supports fellowships for the study of our history. The ACM also names its awards after some of the great contributors to computing through history, such as Grace Hopper, Gordon Bell and Alan Turing.
I’d like to take you back to a time just before the birth of the ACM. The defining events of the early 1940s were surely the sprawling world war involving Europe, Southeast Asia, and the United States and affecting people everywhere.  Some of the earliest computers were being put to work to support warfare, helping to calculate ballistic trajectories and to break the encoded messages of enemy forces. Among these was ENIAC, the computer “born” here in Philadelphia at the University of Pennsylvania. With so much at stake, and with the interest and support of the U.S. government, early computer development was advancing at a rapid pace. A British mathematician named Alan Turing, well known to this society and one of the founders of modern computing concepts, helped lead the way. Turing and his team at British military codebreaking center Bletchley Park are credited with cracking German cyphers. Their success in the use of early computer technology was key to the eventual defeat of German forces.
By 1945, the face of the war was changing. Hitler had been defeated, but Japanese Emperor Hirohito was firm in his commitment to war with the U.S. Here again, the science and engineering culture of academia partnered with government would play an enormous role in international events. Vannevar Bush, an engineer and academic from MIT was serving as science advisor to President Franklin Roosevelt during and immediately after World War II, and was also the administrator of the Manhattan Project, leading a team in the successful development of the atomic bomb.
In order to try to bring about the end of World War II, the United States elected to drop atomic bombs on two Japanese cities, Hiroshima and Nagasaki, killing 200,000 people and forcing the surrender of Japan. It was the first and only use of atomic bombs as weapons of war, and I think we’d all agree that their use was clearly a profound moment in history. Whatever your opinion on war and the use of massive force, man has since that day lived with the understanding that we possess the knowledge and the technology to bring about destruction on an incredible scale – perhaps so large a scale that mankind’s very survival is threatened.
Since the end of World War II, nuclear weapon capability has spread to several other countries and delivery systems have evolved from bombs to be dropped from military planes over a city to warheads on intercontinental ballistic missiles, able to be launched from the comfort of home countries. In the decades since, the world has become a much more dangerous place, where a few powerful men can trigger massive destruction and loss of life.
Scientists and engineers, most of whom previously had no involvement with large-scale warfare other than as individual soldiers, were forced to confront the fact that the knowledge and the technology they developed could be turned into weapons of mass destruction. For perhaps the first time, theoretical physicists saw how practical and deadly the application of their work could be, and mathematician’s proofs were now painting bullseyes on military targets. Nevertheless, it was impossible to ignore the value of science and engineering to U.S. military success.
In the years immediately after World War II, Vannevar Bush was still science advisor to the president and still a prominent academic with ties to universities around the United States. There was great interest on the part of the U.S. government in technology, and Bush was able to work with the federal government to establish large-scale funding for academic science and engineering. Ultimately this led to the creation of the National Science Foundation, which today is an enormous source of funding to U.S. universities involved in science and engineering research.
By the late 1940s, with the return of war veterans to the U.S. and a G.I. Bill that helped send large numbers of them to college, the U.S. government took stock of higher education in the country.  In 1947, the President’s Commission on Higher Education produced a report that considered the promise of an educated citizenry and the role of the United States government in making education accessible. The commission spoke strongly in favor of improved access to education for U.S. citizens, regardless of prevailing impediments such as race or ability to pay, and drew a direct correlation among democracy, equal freedom, and education. The report also recognized that in the aftermath of Hiroshima and Nagasaki we stood at a crossroads, at the beginning of an atomic age with potential “as great for human betterment as for human annihilation,” and that “the future of our civilization depends on the direction education takes.” These are quotes from the commission’s report, as is this: “Education is the foundation of democratic liberties. Without an educated citizenry alert to preserve and extend freedom, it would not long endure.” (President’s Commission on Higher Education, 1947).
This was the historical context into which the ACM was born, in 1947, the same year in which the President’s Commission on Higher Education produced their report. With computers serving prominent roles for the military, and increasing research at American universities, computing as a profession was receiving a great deal of attention. It was natural that the foremost researchers and practitioners would want a professional society to support each other and their growing profession.
In the years since, we have seen the development of the minicomputer in the 1960s, and with it a terrific set of partnerships that included government funded research labs at universities, and new players to a computer industry populated with recent graduates from our universities. The PDP and later VAX minicomputers from Digital Equipment Corporation, for example, benefitted greatly by the operating systems developed at UC Berkeley’s federally funded computer science laboratories. As the 1960s ended, a similar set of government, industry, and higher education partnerships led to the development of the Arpanet, which in turn, led directly to the Internet we all use today.

As the 20th century ended and the 21st century began, world-class engineering continued to move from academic research labs directly into American technology companies, resulting in exponentially faster, smaller and more efficient computing. Even desktop microcomputers, once the epitome of personal-sized computing, were giving way to laptop computers and smartphones.

Federal funding of science and engineering research labs in our universities, and the partnerships forged among government, corporations, and universities, have been crucial to the explosive growth in our industry. This growth, in turn, keeps our profession and our professional societies vibrant.

Let me return to the question posed at the start of my remarks. Attention to history allows us to see the real stories behind the evolution of knowledge and technology. The first computers that inspired the founders of the ACM were room-sized, ploddingly slow and power hungry. The computer in my phone, which is a descendent of those first computers, is by comparison lightning-quick, runs for hours on slim batteries, and slips easily into my pocket. Knowing something about the events of the last 65 years allows us to understand the many things that helped to bring that evolution about.

My closing thoughts are these: our history matters a great deal. History puts the facts and the events we think we know into a broader context and helps us to understand not only the “who” and “what” but also the “why” and “how” of important events. The ACM has shown in numerous ways that it cherishes the history of computing. I’m proud to share my appreciation for computing history and the ACM with all of you tonight.

Thank you very much.
President’s Commission on Higher Education. (1947) Higher Education for American Democracy. New York, NY: Harper & Brothers Publishers.

Monday, January 14, 2013

Changing The Way We Fund U.S. Higher Education

Funding public higher education is an ongoing challenge. State budgets feel the strain of limited tax revenues and rising expenses. At the same time, state governments have economic interests and evolving goals in which higher education should play a key role. The time has come for state governments and state higher education systems to build a more efficient partnership through smarter funding approaches, such as performance-based funding.

Funding Today

More than 70% of U.S. students who attend college do so at public higher education institutions, which are funded primarily by a combination of state appropriations and tuition. Historically, appropriations have been based almost entirely on student enrollment levels. The amount per full time student equivalent varies state by state, as well as with changes in state revenues and the educational philosophies of the state leadership in office. Additionally, appropriations for education are made within the context of overall state expenses and the reality of mandatory or high priority spending on infrastructure and medical costs.
State appropriation accounted for $88.5 billion of public college and university funding in 2010 (Zumeta, 2012, p. 16), making it the largest revenue source for public higher education.  Nevertheless, appropriations as a percentage of overall state expenditures peaked thirty years ago and have been declining since (Zumeta, 2012, pg. 72). The recession of the last few years has only accelerated the trend of state appropriations reduction.
Limited state funds for education should be allocated wisely and with key state goals in mind. While historically appropriations provided helpful incentives toward increased college access, today the focus in the U.S. is shifting toward improvements in completion. A changing goal calls for changing incentives.

Performance Funding as an alternative

While today’s state appropriations approach is based on full time equivalent student enrollment numbers, an alternative involves funding based on outcomes. So-called performance-based funding involves associating some portion of state funding for public higher education with desired outcomes such as improvements in degree completion numbers. In this way, the states do more to provide incentives for public colleges and universities to make decisions and operate in ways that lead directly to student success, not just student enrollment.
Performance metrics can be general, such as a count of all graduates, or more specific, such as numbers of graduates with particular degrees that may be important to the state economy. A common example is “STEM” degrees (degrees in Science, Technology, Engineering and Mathematics), which are in demand in many states. The performance metrics can also be more granular, recognizing student progress towards degrees as measured in credits or credits within their major.  As more students reach specified credit milestones, more state funding goes to the institution. In this way, the states can more clearly communicate their goals directly within the funding program, and public colleges and universities can maximize funding by working toward student success and helping to meet the goals of their state.
This is not a new concept. Heller (2011) notes examples around the world such as in Denmark, England, and Israel where funding for higher education is allocated based on the numbers of graduates. In the United States there is a history of performance-based funding, but not all of it has been successful.
Tennessee was among states that tried performance-based funding in the 1980s and 1990s. A small portion of the state funding for public higher education was based on metrics such as graduation rates or controlling the costs per student (Heller, 2011). While today Tennessee has moved the majority of their education funding from base allocation to course completion and other outcomes, they are in the minority. Recent progress has been made in Ohio and also in Indiana, each of which gained attention for comprehensive performance-based funding initiatives in the last few years, but the National Conference of State Legislatures reports that only 10 states currently have performance-based funding programs in place, with 6 other states in a transition stage (NCSL, 2012). That still leaves the majority of states to begin to seriously pursue this approach. Though several states experimented with performance based funding in the past, most backed away from these programs because of “a number of fatal design flaws” (Miao 2012).

Learning form the Past

Lessons have been learned from some of the past efforts at performance-based funding. Jones (2011) discusses a set of design and implementation principles that are informed by failed state programs and that can guide thoughtful current and future efforts.
First, states should begin by designing programs with the input of a broad range of stakeholders. Within each state, the state governments and state higher education systems can start to build a more efficient partnership by carefully designing their program to recognize their unique situation. Input from business leaders in the state may be helpful. Demographics, key industries, and the educational goals of the mix of colleges and universities within the state are among the major considerations.
With key stakeholders at the table early on, the program design can recognize practical state challenges and focus on state goals. Some states will choose to emphasize degree completion within certain fields while others will want to provide more incentives for adult learner re-training efforts. Still others will want to emphasize structures designed to recognize progress in closing persistent racial or ethnic performance gaps.
Another lesson learned from past programs is that if the performance-based funding is not a large enough portion of overall funding, it likely will not motivate changes. While abrupt funding changes could be problematic and needlessly disruptive, the eventual percentage of funding that is performance based needs to be high enough to have impact. States should choose a relatively high target and phase it in over time. For instance, a state that chooses to reach 40% performance-based funding might choose to phase it in 5% per year over 8 years. This avoids disruptively large funding swings and also allows schools to adjust their programs to the new realities. It also allows time for the measurement approaches to become more refined.
To promote early success, programs should measure progress toward goals as well as achievement of the goals themselves.  A performance-based funding approach that sets milestones, as was done in Indiana recently (Kiley, 2011; Miao, 2012), rewards student progress towards goals. This is important since college completion goals may often take years to reach, but progress can be measured and rewarded year to year.
Some failed programs in the past may have been overly simplistic in not fully considering the roles that the various state colleges and universities play when developing goals and metrics for performance-based funding. A state with research universities, comprehensive universities and a system of community colleges is providing educational opportunities to a diverse community of students. Performance-based funding needs to recognize this and be designed such that each segment can “win” by playing their own role well. For example, a four-year university may be rewarded for increases in degree completion while a community college may be recognized for improvements achieved in educating underserved populations or for the numbers of students who progress into state four-year programs.
States that are already studying performance-based funding and taking the first steps with a small percentage of their overall funding should be encouraged to move more aggressively, shifting more of their total higher education funding to performance-based approaches. Those states which haven’t yet moved to performance funding can make a strong start by convening the stakeholders that represent all segments of public higher education and the relevant state government offices to begin to design a program that makes sense for their state.
By getting programs up and running in more states, more data will quickly become available on performance-based programs that work well, so that leading states can show the way to states that lag.
When state governments see higher education as an investment rather than simply an expense, they can communicate what they want as a return on that investment directly through their funding for higher education. The states have an economic interest in an effective system of higher education so that graduates can fuel the economic engine of the state. When graduates reside in the state as taxpayers, and are the employees of local businesses (which also pay taxes), the state benefits.
Performance-based funding is an approach that, when done carefully, can help to build a more efficient partnership between state governments and their state higher education systems.
Lessons from past efforts and the analyses that have been undertaken since position us to make the most of performance-based funding. The time is now to act, with each state moving more strongly to design and implement programs of performance-based funding using very significant portions of their state funding for higher education.

  1. Heller, D. (2011), The States and Public Higher Education Policy: Affordability, Access, and Accountability, Baltimore, MD: Johns Hopkins University Press
  2. Jones, D. (2011) Performance Funding: From Idea to Action, Retrieved from:
  3. Kiley, K. (2011) Performance Anxiety, Inside Higher Ed, Retrieved from:
  4. Miao, K. (2012) Performance-Based Funding of Higher Education: A Detailed Look at Best Practices in 6 States, Center for American Progress, Retrieved from:
  5. NCSL (2012), Performance Funding for Higher Education, Retrieved from:
  6. Zumeta, W., Breneman, D., Callan, P., & Finney, J. (2012), Financing American Higher Education in the Era of Globalization, Cambridge, MA.: Harvard Education Press

Wednesday, January 9, 2013

Participant Pedagogy - A Week of MOOCMOOC

A First Real Swim in the MOOC Pool

These days I'm back in graduate school in a doctoral program in higher education at Penn. I'm fascinated with new thinking and models for higher education, both in terms of how we learn best and also in terms of the role that institutions of higher education could play to help enable more education getting to more people. As a technologist and social network enthusiast, I'm drawn to MOOCs. So much so that I'm hoping MOOCs will be a key element of my research and thesis.

[Note: This short blog post is probably not the place to introduce the casual reader to MOOCs. If that's of interest, please leave a comment. Maybe I can take that on in a future blog post.]

My exposure to MOOCs so far had been reading about them and looking at tools that help faculty to create and organize content. I hadn't actually been an active participant in a MOOC yet, so I signed up for two MOOCs this month and dove in head first. This week, I'm participating in a MOOC on MOOCs. It's called moocmooc. Seriously.

Active participants in moocmooc are reading and collaboratively writing articles, watching and creating youtube videos on learning approaches, and engaging with hundreds of others via twitter on what and how we learn. It's participant pedagogy because we as participants are driving the direction and providing the content, and input on each others work, with the course facilitators gently guiding with daily videos to watch, articles to read, and suggestions of what to create and how to share among participants.

This blog post is an "artifact" of my moocmooc participation – it's something I created in order to engage with other participants, as they create artifacts to help me to engage with them. A great outcome would be lots of comments below helping me to see where my thinking does or doesn't align with others.

The questions I'd like to consider are:  
What is the role of collaboration among peers and between teachers and students? What forms might that collaboration take? What role do institutions play?

These questions can be considered on a continuum, with a giant lecture class on one end (A) and a hyper-collaborative online-only "class" like moocmooc on the other end (B). On the (A) end, there is very little student collaboration and a one-way flow of information, instructor to student. Institutions provide registration and student services and a big classroom to be used on a regular schedule. On the (B) end of the continuum, there is (or can be) constant and free-flowing interaction among peers with collaborative artifact development. Teachers/facilitators provide guidance and coalescing of products, and observations through announcements. Institutions can provide resources (such as servers and online tools to facilitate) or not.

Of course, there is a lot of space between (A) and (B) and all of us involved in higher education have had class experiences that are much more interactive than the large lecture, but less collaborative than a connectivist MOOC (cMOOC).

Is it valuable to have learning experiences at many points along the continuum? I think it is. In no way am I saying that the learning that happens in (A) is not valid or useful. It's just different. The cMOOC experience is invigorating but (and this is well known) it does seem to leave lots of people behind. Many MOOC participants drop out or merely lurk. Perhaps some of them would have been happier with something closer to an (A) experience rather than a (B) experience.

What do you think? Have you participated in a MOOC? If so, did it work out well for you?

Do you learn more easily through interaction with peers? Or does a lecture work better for you? Does it depend on the content?

Please leave a comment below with your thoughts on these questions, or on my comments above.