To achieve their educational mission, computing departments at research universities increasingly depend on full-time teaching faculty who choose teaching as a long-term career. This memo discusses the need for teaching faculty, explores the impact of teaching faculty, and recommends best practices. The best practices outlined here are designed to benefit everyone: teaching faculty, other faculty, students, and administrators.  These best practices recognize the unique and complementary role that full-time teaching faculty play in the educational mission of the academic computing-research community.

A careful distinction between quality and quantity is key to promoting the future growth of the computing and information field. Toward that end, this document advocates adjustments to hiring, promotion, and tenure practices as well as to the publication culture. Contributions in a small number of high quality publications or artifacts are what should be emphasized; success as a researcher is then not primarily a matter of numbers.

The recommendations that follow were developed over an 18-month period by the CRA Committee on Best Practices for Hiring, Promotion, and Scholarship. As part of this work, the committee conducted interviews in autumn 2013 with more than 75 academic and industry computing and information unit heads to understand the issues and gain insights from practice. Preliminary recommendations were vetted with department chairs and CRA Deans at the CRA Conference at Snowbird in July 2014.

The Computing Research Association’s (CRA) Board of Directors has approved a Best Practices Guide, providing guidance to graduate students, postdocs, advisors and mentors, and departments and institutions on how to have a positive postdoctoral experience within computer science and engineering.  We encourage our colleagues throughout the community to take a look at the document — the latest in a series of white papers about the recent increase in postdocs in the field — and adopt these Best Practices.

The fields of computing and information science and engineering have a strong commitment to interdisciplinary work, with CISE researchers collaborating with electrical engineers in the design of low-power chips; with linguists in the development of natural-language processing systems; with biologists in the exploration of the genetic code; with economists in the formation of theories of on-line commerce; and with statisticians in the discovery of new ways to extract information from rich sets of data—to name just a few examples.

Universities and businesses have considerable incentive to cooperate in the development of intellectual property (IP). Businesses recognize universities for their rich talent pool and enthusiastic graduate students, while universities recognize businesses as a source of real-world problems, technical know-how, and funding. There are numerous examples of successful research collaborations in computer science, computer engineering, and electrical engineering. Mindful that some IP such as gene splicing and human growth hormone have produced “IP goldmines,” many university administrators (and some students and faculty) are eager to establish strong safeguards to protect their rights to intellectual property.

The relentless pressure to innovate in the information technology (IT) industry has drawn university researchers and graduate students into entrepreneurial situations to an increasing degree. The trend affects the academic enterprise in diverse ways, both favorable and unfavorable. The risks and rewards are outlined, and the concept of a Commercialization Oversight Committee is described as a mechanism that can facilitate the best outcomes when interests conflict.

The evaluation of computer science and engineering faculty for promotion and tenure has generally followed the dictate “publish or perish,” where “publish” has had its standard academic meaning of “publish in archival journals” [Academic Careers, 94]. Relying on journal publications as the sole demonstration of scholarly achievement, especially counting such publications to determine whether they exceed a prescribed threshold, ignores significant evidence of accomplishment in computer science and engineering. For example, conference publication is preferred in the field, and computational artifacts – software, chips, etc. – are a tangible means of conveying ideas and insight. Obligating faculty to be evaluated by this traditional standard handicaps their careers, and indirectly harms the field. This document describes appropriate evidence of academic achievement in computer science and engineering.