A study by a ITiCSE 2001 working group ("the McCracken Group") established that many students do not know how to program at the conclusion of their introductory courses. A popular explanation for this incapacity is that the students lack the ability to problem-solve. That is, they lack the ability to take a problem description, decompose it into sub-problems and implement them, then assemble the pieces into a complete solution. An alternative explanation is that many students have a fragile grasp of both basic programming principles and the ability to systematically carry out routine programming tasks, such as tracing (or "desk checking") through code. This ITiCSE 2004 working group studied the alternative explanation, by testing students from seven countries, in two ways. First, students were tested on their ability to predict the outcome of executing a short piece of code. Second, students were tested on their ability, when given the desired function of short piece of nearcomplete code, to select the correct completion of the code from a small set of possibilities. Many students were weak at these tasks, especially the latter task, suggesting that such students have a fragile grasp of skills that are a prerequisite for problemsolving.

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McCauley, Ren?e, Fitzgerald, Sue, Lewandowski, Gary, Murphy, Laurie, Simon, Beth, Thomas, Lynda and Zander, Carol(2008) 'Debugging: a review of the literature from an educational perspective', Computer Science Education,18:2,67 ? 92This paper reviews the literature related to the learning and teaching of debugging computer programs. Debugging is an important skill that continues to be both difficult for novice programmers to learn and challenging for computer science educators to teach. These challenges persist despite a wealth of important research on the subject dating back as far as the mid 1970s. Although the tools and languages novices use for writing programs today are notably different from those employed decades earlier, the basic problem-solving and pragmatic skills necessary to debug them effectively are largely similar. Hence, an understanding of the previous work on debugging can offer computer science educators insights into how to improve contemporary learning and teaching of debugging and may suggest directions for future research into this important area. This overview of the debugging literature is organized around four questions relevant to computer science educators and education researchers: What causes bugs to occur? What types of bugs occur? What is the debugging process? How can we improve the learning and teaching of debugging? We conclude with suggestions on using the existing literature both to facilitate pedagogical improvements to debugging education and to offer guidance for future research.Peer reviewe

Common exam practice centres around two question types: code tracing (reading) and code writing. It is commonly believed that code tracing is easier than code writing, but it seems obvious that different skills are needed for each. These problems also differ in their value on an exam. Pedagogically, code tracing on paper is an authentic task whereas code writing on paper is less so. Yet, few instructors are willing to forgo the code writing question on an exam. Is there another way, easier to grade, that captures the "problem solving through code creation process" we wish to examine? In this paper we propose Parson's puzzle-style problems for this purpose. We explore their potential both qualitatively, through interviews, and quantitatively through a set of CS1 exams. We find notable correlation between Parsons scores and code writing scores. We find low correlation between code writing and tracing and between Parsons and tracing. We also make the case that marks from a Parsons problem make clear what students don't know (specifically, in both syntax and logic) much less ambiguously than marks from a code writing problem. We make recommendations on the design of Parsons problems for the exam setting, discuss their potential uses and urge further investigations of Parsons problems for assessment of CS1 students.

Fitzgerald, Sue, Lewandowski, Gary, McCauley, Ren?e, Murphy, Laurie, Simon, Beth, Thomas, Lynda and Zander, Carol(2008) 'Debugging: finding, fixing and flailing, a multi-institutional study of novice debuggers? Computer Science Education,18:2, 93-116 Special Issue: Debugging by Novice ProgrammersDebugging is often difficult and frustrating for novices. Yet because students typically debug outside the classroom and often in isolation, instructors rarely have the opportunity to closely observe students while they debug. This paper describes the details of an exploratory study of the debugging skills and behaviors of contemporary novice Java programmers. Based on a modified replication of Katz and Anderson's study of novices, we sought to broadly survey the modern landscape of novice debugging abilities. As such, this study reports general quantitative results and fills in the picture with qualitative detail from a relatively small, but varied sample. Comprehensive interviews involving both a programming and a debugging task, followed by a semi-structured interview and a questionnaire, were conducted with 21 CS2 students at seven colleges and universities. While many subjects successfully debugged a representative set of typical CS1 bugs, there was a great deal of variation in their success at the programming and debugging tasks. Most of the students who were good debuggers were good novice programmers, although not all of the good programmers were successful at debugging. Students employed a variety of strategies to find 70% of all bugs and of the bugs they found they were able to fix 97% of them. They had the most difficulty with malformed statements, such as arithmetic errors and incorrect loop conditions. Our results confirm many findings from previous studies (some quite old) - most notably that once students find bugs, they can fix them. However, the results also suggest that some changes have occurred in the student population, particularly an increased use of debugging tools and online resources, as well as the use of pattern matching, which has not previously been reported.Peer reviewe

Computer science instructors frequently teach using slides displayed with a computer and a data projector. This has many advantages, e.g., ability to present prepared materials and ease of switching the display to a development environment during midpresentation. However, existing computer-based presentation systems severely limit flexibility in delivery, hindering instructors' extemporaneous adaptation of their presentations to match their audiences. One major limitation of computer-based systems is lack of support for high-quality handwriting over slides, as with overhead projectors and other manual presentation systems. We developed and deployed Classroom Presenter, a Tablet PC-based presentation system that (1) combines the advantages of existing computer-based and manual presentation systems and (2) builds on these systems, introducing novel affordances. Classroom Presenter has been used in 25 Computer Science courses at three universities. In this paper we describe the system, summarize results from its deployment, and detail several novel uses of the system by instructors in computer science courses.

Beginning in 2008, we introduced a new CS1 incorporating a trio of best practices intended to improve the quality of the course, appeal to a broader student body, and, hopefully, improve retention in the major. This trio included Media Computation, Pair Programming, and Peer Instruction. After 3 and 1/2 years (8 CS1 classes, 3 different instructors, and 1011 students passing the course) we find that 89% of the majors who pass the course are still studying computing one year later. This is an improvement of 18% over our average retention of 71% for the previous version of the course (measured since Fall 2001). If the focus shifts from retention of passing CS1 majors to retention of CS1 initially enrolled majors, multiple improvements-fewer students drop, more students pass, and more passing students are retainedcompound to increase retention by 31% (from 51% to 82%). In this paper we analyze further aspects of these results, detail the three instructional design choices, and consider how they impact issues known to affect retention.