Henry M. Walker

A revised model curriculum for a liberal arts degree in computer science

high-quality undergraduate computer science major within a liberal arts setting. These recommendations build upon the traditional strengths of a liberal arts education while ensuring reasonable depth in the fundamental areas of computer science. This article updates the 1986 Communications article “Model Curriculum for a Liberal Arts Degree in Computer Science’’ by Gibbs and Tucker [8] (see the sidebar “The Revision Process”). In updating [8], we draw upon important new educational and technological developments in the discipline as well as the recommendations of Computing Curricula 1991 of the ACM/IEEE-CS Joint Curriculum Task Force [2]. A Revised Model Curriculum for a Liberal Arts Degree in Computer Science

Enhancing the social issues components in our computing curriculum: computing for the social good

The acceptance and integration of social issues into computing curricula is still a work in progress twenty years after it was first incorporated into the ACM Computing Curricula. Through an international survey of computing instructors, this paper corroborates prior work showing that most institutions include the societal impact of ICT in their programs. However, topics often concentrate on computer history, codes of ethics and intellectual property, while neglecting broader issues of societal impact. This paper explores how these neglected topics can be better developed through a subtle change of focus to the significant role that ICT plays in addressing the needs of the community. Drawing on the survey and a set of implementation cases, the paper provides guidance by means of examples and resources to empower teaching teams to engage students in the application of ICT to bring about positive social outcomes -- computing for the social good.

Striving for mathematical thinking

Computer science and software engineering are young, maturing disciplines. As with other mathematically based disciplines, such as the natural sciences, economics, and engineering, it takes time for the mathematical roots to grow and flourish. For computer science and software engineering, others have planted these seeds over many years, and it is our duty to nurture them. This working group is dedicated to promoting mathematics as an important tool for problem-solving and conceptual understanding in computing.

Collaborative learning: a case study for CS1 at Grinnell College and Austin

Since Fall, 1992, the author has used techniques of collaborative learning in his sections of CS1 at both Grinnell College and The University of Texas at Austin. These experiments have been successful by various measures: drop rates are very low, students perform well on tests, student motivation and enthusiasm are very high, and the class covers about 20% more material during the semester. This paper describes the approach that has evolved through several iterations of this course.

Do computer games have a role in the computing classroom

Becker’s sample rubrics are divided into two sets. Rubric One, entitled “Style”, included guidelines that would apply to most any program (such as Presentation, which included the Submission attribute discussed above, and Documentation). Rubric Two, entitled “Function & Design”, documented attributes specific to the particular program assignment being assessed (this example was for an English to Latin Translator). In addition to the many English-Latin Translator attributes, Rubric Two contained a Bonus section that allowed for the awarding of extra points for functionality beyond that required of the assignment, which encourages students to go beyond the requirements. In addition to being a great tool for consistent grading, rubrics allow, or rather force, teachers to clarify their definition of excellence and can be useful in planning how to assist students in achieving excellence. [3] If the rubrics are developed in advance of making an assignment, this may allow us to refine and perhaps “perfect” some assignments before they are handed out. Rubrics can also be used to provide detailed feedback to students. Rubrics might be provided to students before assignments are submitted, so that students know what the instructor/grader considers most important. However, some students may use the guidelines to guide their performance and perhaps to do the minimum necessary to achieve a certain grade. In some instances, this is not be desirable. For assignments where creativity is desirable, providing rubrics in advance could actually deter creativity. Also, for many assignments, it may not be possible to determine all levels of performance and how they can be demonstrated in advance. Thus, creation of the scoring rubrics can occur as an assignment is graded. According to Performance Links in Science Assessment, technically sound rubrics are continuous, parallel, coherent, high descriptive, valid and reliable. Each of these terms is defined in [3]. This web resource also provides guidelines for developing rubrics, common errors in developing rubrics, and examples of good and poor rubrics. For more on rubrics, I point you to [1], [2], and [3] for general information; to [4] for a computer science/programming project examples. References [1] Holzberg, C. “Assessment, Assessment Rubrics and Evaluation Guidelines,” http://www.techlearning.com/db_area/archives/WCE/archive s/evalguid.html [2] International Society for Technology in Education, “Educational Computing and Technology Programs Computer Science Rubrics,” http://cnets.iste.org/ncate/n_csrubrics.html [3] Performance Assessment Links in Science, “Rubrics & Scoring” http://pals.sri.com/guide/scoringdetail.html [4] Becker, K. “Grading Programming Assignment using Rubrics,” in Proceedings of the 8 Annual Conference on Innovation and Technology in Computer Science Education, page 253. [5] Becker, K. “General Programming Assignment Rubric,” http://pages.cpsc.ucalgary.ca/~becker/233/Asst/ProgramRubr ic.htm

Computer-mediated communication in collaborative educational settings (report of the ITiCSE '97 working group on CMC in collaborative educational settings)

In educational environments that stress collaboration, the use of computer-mediated communication (CMC) tools can be a source of support as well as a challenge. This paper begins by considering general educational and economic goals and how CMC can be helpful in attaining these goals. A taxonomy of tools for communication and collaboration in education is described. Many sides of the issue are considered, including the roles of teachers and students, problems that can arise and potential solutions, goals and issues of assessment, and software design issues.

Computer Science and the Liberal Arts: A Philosophical Examination

This article explores the philosophy and position of the discipline of computer science within the liberal arts, based upon a discussion of the nature of computer science and a review of the characteristics of the liberal arts. A liberal arts environment provides important opportunities for undergraduate programs, but also presents important constraints. A well designed program can flourish in this environment, and evidence indicates that a liberal arts program in computer science can indeed succeed well.

Games: good/evil

In this special session we present arguments for and against a game-centric computing curriculum. To highlight the issues and ensure equal time for arguments on either side, our session is staged as a debate with three speakers on each side. Our audience is educators and educational researchers interested in the role of game development in the CS curriculum.

The roles of mathematics in computer science

74 acm Inroads 2013 December • Vol. 4 • No. 4 INTRODUCTION Scientific and engineering disciplines generally are closely coupled to mathematics. The natural sciences make mathematical models of the phenomena they study; both the natural and social sciences rely on statistics to tease meaning out of raw data; engineers depend on mathematical models at all stages of system design, construction, and maintenance. The one pair of exceptions to this rule appears to be computer science and software engineering. Practicing software developers make little use of mathematics [20, 31], and conventional wisdom says the same of computer science students. Yet it would be very strange if the relationship between computer science, software engineering, and mathematics were really as loose as it seems. At the very least it would be suspicious for computer science and software engineering to be the only non-mathematical members of the science and engineering family; at the worst it would be downright dangerous for the disciplines to reject methods that characterize the fields whose names they use. This paper argues that, although the day-to-day practice of computing often requires little if any mathematics, there are nonetheless important connections between computer science, software engineering, and mathematics. The next section discusses the roles mathematics plays in computer science, including how specific mathematical topics interact with specific computer science topics, and how mathematical reasoning complements computer science reasoning. The third section explores the role mathematics plays in computer science education and analyzes the disparity between its role in the general discipline and its role in education. A brief conclusion then summarizes the main points and their implications for computer science curricula. Although the rest of the paper focuses on “computer science,” we use the term generically rather than to identify a single precise discipline: our ultimate concern is with the education of computing professionals, most of whom still receive that education through a program that identifies itself as “computer science.” Our argument and conclusions apply to software engineering as well as to computer science. The Roles of Mathematics in Computer Science

A C-based introductory course using robots

Using robots in introductory computer science classes has recently become a popular method of increasing student interest in computer science. This paper describes the development of a new curriculum for a CS 2 course, Imperative Problem Solving and Data Structures, based upon Scribbler 2 robots with standard C. The curriculum contains eight distinct modules with a primary topic theme, readings, labs, and project at the end. Each module resulted from collaboration among former CS 2 students and a faculty member, utilizing an iterative process with revisions. Each lab includes a survey to obtain student feedback that will allow the course to evolve and better fit the needs of future CS 2 students. All materials discussed here are available online for use by others.