Learning Publications


Peter J. Denning



Operating Systems Principles and Undergraduate Computer Science Curricula. 1972. This paper received the best paper award at the 1972 SJCC. PJD argued that operating systems had developed a set of first principles of sufficient depth to merit a core course in the undergraduate curriculum. He challenged the orthodoxy of the day, which held that the first principles of computing were in mathematics and programming. The systems argument was successful. Operating Systems Principles courses soon began to show up in every curriculum, and OS has been treated as a core subject ever since.

Ruminations on Education. 1985. The early 1980s seemed unkind to computing education. Beginning with the 1979 Feldman report, a series of groups decried the "brain drain" of systems faculty leaving universities for greener industry pastures. The US NSF began to support experimental computer science with new grant initiatives and with CSNET. Here, PJD argued that with all the external help now coming, it was time for computing educators to stop feeling vicimized and take the initiative to improve their situation. He argued that our public image of "CS=programming" was hurting our standing in the community of sciences. He speculated about a new way to describe the computing field. This essay intrigued the ACM Education Board, which asked PJD to form a committee to present a new framework for the field and its future curricula. That led to the next report.

Computing as a Discipline. 1989. This report from an ACM/IEEE task force, chaired by PJD, introduced the term computing for "computer science and engineering". It offered a way to understand the field in terms of nine major technology areas and the three processes theory, abstraction, and design. These three processes represent the perspectives of math, science, and engineering that are embedded into computing.

Educating a New Engineer. 1992. From ACM Communications, December 1992. The customers of the university have formed new expectations about profession, work, teaching, research, innovation, and the university itself. These expectations portend fundamental changes in our approaches to curriculum, research, and engineers as human beings. Exhibitions are a good way to organize curricula to meet the new expections. Examples of programming exhibitions are given.

Business Designs for the New University. 1996. Every organization with customers has a business design. What happens if the business design of a university becomes obsolete? Published in Educom Review (November-December 1996).

How We Will Learn. 1997. From Beyond Calculation: The Next 50 Years of Computing (Peter Denning and Bob Metcalfe, eds.), Copernicus Books, 1997. A look at how people will view education and learning and the ways in which universities are likely to evolve. A new theory of learning, centered on embodied knowledge, will emerge.

Quantitative Practices. 1997. From Why Numbers Count, Lynn Steen (editor), College Board Press, 1997. Practices are every bit as important as mental knowledge in determining who is literate about computing.

Where Will All The Teachers Go? 1998. A response to the contention that teachers are being pushed out by multimedia systems, testing machines, and databases. The teacher is indispensable. Published as a commentary "Skewering the Stereotype" on David Noble's "Digital Diploma Mills", Educom Review 33, May-June 1998.

The New Engineer, Newly Revisited. 1998. An interview with CareerTech editor Charlotte Thomas explores the implications of The New Engineer for students preparing for engineering careers.

Teaching as a Social Process. 1999. The common stereotypes of teacher as sage or guide don't capture the social value of teaching. They make it appear that teachers can be replaced by machines. Teachers are representatives of professional communities. Students look to them for access to those communities and for assistance in becoming professionals themselves. Published in Educom Review, May-June 1999.

On Active and Passive Writing. 1984. A short essay written in 1984 decrying the overuse of passive voice in much writing and offering active guidance. (With apologies to Raymond Quineau, author of Exercises in Style.)

Designing an IT College. 2000. In 2000, PJD and a team of faculty from different IT specialties designed a model curriculum for an IT school. The curriculum is being implemented at the IT College of the University of the United Arab Emirates. This overview was presented at the World Congress on Computers in Education, August 2001. Also available is the full report on the model curriculum.

Are Students Customers, or not? 2002. In September 2002, the George Mason University Faculty Senate adopted a resolution declaring that students are not customers and that a customer based model is inappropriate for universities. Ten students respond.

The Somatic Engineer. 2003. PJD discusses an usual claim, that engineers need to embody a value dimension, in which they are able to listen to customers, craft offers of value to them, and deliver. The discipline, Value Dynamics, cannot be taught by training the mind. It is taught through immersion, practice, and coaching. Engineers who teach Value Dynamics must already have the value skills. Without this, engineers will be technicians only and not leader-professionals.

Great Principles in Computing Curricula. 2004. In October 2003, the CS Department at NPS initiated a new curriculum organized around a Great Principles framework. Here's an overview of the framework, why it has been difficult to articulate such a framework, experience at NPS, and reflections about computing curricular in general.

Transformational Events (with John Hiles). 2006. As part of a June 2006 special issue of Computer Science Education, the authors disuss a recurrent pattern of innovation and transformation. The pattern includes (1) a "mess" -- a period of discontent with ad hoc solutions to a pervasive problem, followed by (2) a "transformational event", usually a seminal invention or paper, followed by (3) a "settling" period in which the new idea is incorporated into common systems and eliminates the original problem. The authors discuss how this pattern can be used to organize a course on how great discoveries in computing were made. They discuss more generally how to maximize one's chance of being an innovator by identifying and understanding current "messes".

Machines, Languages, and Computation at MIT (with Jack Dennis). 2015. IEEE Annals of the History of Computing (July-September 2015). PJD and JBD discuss the course on computation they created at MIT in 1965 and the subsequent book of the same title they published in 1978. The MIT course was probably the first to examine the power of computing machines using the Chomsky language hierarchy. During the course they found a short undecidability proof of the Correspondence Problem (click here).

The Long Quest for Computational Thinking (with Matti Tedre). 2016. Computational thinking (CT) is a popular phrase that refers to a collection of computational ideas and habits of mind that people in computing disciplines acquire through their work in designing programs, software, simulations, and computations performed by machinery. Modern CT initiatives should be well aware of the broad and deep history of computational thinking, or risk repeating already refuted claims, past mistakes, and already solved problems, or losing some of the richest and most ambitious ideas in CT. This paper presents an overview of three important historical currents from which CT has developed: evolution of computing's disciplinary ways of thinking and practicing, educational research and efforts in computing, and emergence of computational science and digitalization of society. [Won the best paper and best presentation awards of the conference.]

Education Fails to React to Changes in Work (With Matti Tedre). 2016. Helsingin Sanomat, October 26. As technology reduces knowledge work, education should prepare people for a new kind of design work.

Computational Thinking in Science. 2017. American Scientist, January 2017. The computer revolution has profoundly affected how we think about science, experimentation, and research. Computational design, facilitated by computational thinking, is what computatinal scientists use as their scientific method.

Remaining Trouble Spots with Computational Thinking. 2017. Computational thinking has been a hallmark of computer science since the 1950s. Around 2006 the promoters of the CS-for-all K-12 education movement claimed all people could benefit from thinking like computer scientists. Unfortunately, today’s teachers and education researchers struggle with three main questions: What is computational thinking? How can it be assessed? Is it good for everyone? Computational thinking includes designing the model, not just the steps to control it.