In research across professions, the development of professional skill traditionally was seen as a process of accumulation of knowledge and skills, promoted by practical experience More recently, this view has been modified to incorporate skillful know-how that is progressively acquired by passing through developmental stages, such as novice, competent, and expert The authors of this article critically review contemporary stage models that are typically applied across professions Their principal critique is that a focus on stages veils or conceals more fundamental aspects of professional skill development On the basis of their critique, the authors propose an alternative model that builds on the strengths of previous models while seeking to overcome their main limitations Finally, the authors outline the implications of their alternative model for professional education, workplace practices, and research on professional development

/pdf/unveiling-professional-development-a-critical-review-of-tbunjrtjt9.pdf

Unveiling Professional Development: A Critical Review of Stage Models

This 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 o...

Debugging: a review of the literature from an educational perspective

2012 [AS13b, Wal12a]. 2013 [Alv13, Bar13, Cam13, Car13, CCS13, Cut13, Edi14, Swe13]. 2014 [CDS13, DN14, ND14, Rod14, Tym14a]. 2015 [DeL14a, DeL14b, She15b]. 2016 [AT16a, CCV16, CCV17, MR15, SDCT16a, SDCT16c, She16a]. 2017 [DG17, EC17, Fit18b, MJ18, TCSM17, TCM17]. 2018 [BG18b, DD17, Dec19b, Gol18, JI18, MKMP18, MMK18, PQH17, She18]. 2019 [Cut19, FI19, HPQ19, MP19a, MPRM19, MP19b, MS19, Rod18, She19a]. 2020 [DH19].

/pdf/a-complete-bibliography-of-publications-in-sigcse-bulletin-1aolnsl5m4.pdf

A Complete Bibliography of Publications in SIGCSE Bulletin: 2000{2009

In this study, we attempted to quantify indicators of novice programmer progress in the task of writing programs, and we evaluated the use of these indicators for identifying academically at-risk students. Over the course of nine weeks, students completed five different graded programming exercises in a computer lab. Using an instrumented version of BlueJ, an integrated development environment for Java, we collected novice compilations and explored the errors novices encountered, the locations of these errors, and the frequency with which novices compiled their programs. We identified which frequently encountered errors and which compilation behaviors were characteristic of at-risk students. Based on these findings, we developed linear regression models that allowed prediction of students' scores on a midterm exam. However, the models derived could not accurately predict the at-risk students. Although our goal of identifying at-risk students was not attained, we have gained insights regarding the compilation behavior of our students, which may help us identify students who are in need of intervention.

/pdf/predicting-at-risk-novice-java-programmers-through-the-3xwk6gg3m7.pdf

Predicting at-risk novice Java programmers through the analysis of online protocols

The area of program comprehension comprises a vast body of literature, with numerous conflicting models having been proposed. Models are typically grounded in experimental studies mostly involving experienced programmers. The question of how to relate this material to the teaching and learning of programming for novices has proven challenging for many researchers. In this critical review from a computer science educational perspective, the authors compare and contrast the way in which different models conceptualize program comprehension. This provides new insights into learning issues such as content, sequence, learning obstacles, effective learning tasks and teaching methods, as well as into the assessment of learning

An introduction to program comprehension for computer science educators

We conducted a study to demonstrate that formal training in debugging helps students develop skills in diagnosing and removing defects from computer programs. To accomplish this goal in an assembly language course, we designed multiple activities to enhance students' debugging skills. These activities included debugging exercises, debugging logs, development logs and reflective memos, and collaborative assignments. In a previous paper, we reported positive qualitative results. Students agreed that formal debugging training enhanced their debugging skills. In this paper, we present positive quantitative results that support our previous qualitative results. Students who completed the optional debugging exercises spent significantly less time on debugging their programs than those who did not. Furthermore, we develop a model of debugging abilities and habits based on students' comments in their debugging logs, development logs, reflective memos, and evaluation surveys. Students and educators could use the model to diagnose students' current debugging skills and take actions to enhance their skills.

Debugging: from novice to expert

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Debugging: from novice to expert