ACM Transactions on Computing Education最新文献

Objectives. Although prior research has uncovered shifts in computer science (CS) students’ implicit beliefs about the nature of their intelligence across time, little research has investigated the factors contributing to these changes. To address this gap, two studies were conducted in which the relationship between ineffective self-regulation of learning experiences and CS students’ implicit intelligence beliefs at different times during the semester was assessed.

Participants. Participants for Studies 1 (n = 536) and 2 (n = 222) were undergraduate students enrolled in introductory- and upper-level CS courses at a large, public, Midwestern university. Race-ethnicity information was not collected due to IRB concerns about possible secondary identification of participants from underrepresented groups.

Study Method. Participants completed a condensed version of the Implicit Theories of Intelligence Scale [16, 54] and the Lack of Regulation Scale from the Student Perceptions of Classroom Knowledge Building scale [51, 53] at the beginning (Studies 1 and 2), middle (Study 2), and end (Studies 1 and 2) of semester-long undergraduate CS courses. Survey responses were analyzed using path analyses to investigate how students’ lack of regulation experiences throughout the semester predicted their implicit intelligence beliefs at the beginning (Study 2) and end (Studies 1 and 2) of the semester.

Findings. Results from Study 1 indicate that undergraduate CS students come to more strongly believe that their intelligence is a fixed, unchanging entity from the beginning until the end of the semester. Moreover, participants’ responses to the lack of regulation scale were predictive of their implicit intelligence beliefs at the end of the semester. Results from Study 2 indicate that ineffective self-regulation experiences early in the semester enhance CS students’ belief in the unchanging nature of intelligence (i.e., during the first half of the semester). Taken altogether, these findings provide evidence that self-regulation experiences influence students’ beliefs about the malleability of intelligence.

Conclusions. Findings align with Bandura's [4] contention that students’ behaviors and experiences influence their values and beliefs. Students who experienced poor self-regulated learning came to view intelligence as more of a fixed, unalterable entity than their more successfully self-regulated peers. Findings suggest that CS instructors can positively affect student motivation and engagement by embedding self-regulated learning strategy instruction into their courses and helping CS students adopt an incremental-oriented (e.g., growth-oriented) belief system about their intellectual abilities.

Project managers tend to confront multiple challenges in Global Software Development (GSD), including misunderstandings about the project requirements, complex estimations of costs, risks, and efforts, along with increases in task allocation and a lack of coordination. “Soft skills” play a fundamental role in solving these challenges, as they are the human or social abilities that facilitate the resolution of conflicts and involve dealing with people and managing projects in their most social and creative dimension. However, developing the soft skills that allow project managers to lead in an effective manner is not an easy task, especially in global or distributed environments, where coordination and control problems are commonplace. One suitable mechanism with which to develop these soft skills is that of serious games, which focus on learning by doing and allow users to simulate real scenarios. The authors of this article are aware of the usefulness of this type of teaching method and have, therefore, developed the serious game described herein. This serious game is denominated as Global Manager and is focused on helping both students and novice project managers to become aware of the factors that may affect GSD projects. Global Manager was evaluated by means of a quasi-experiment based on a pretest-posttest design, which was used to assess whether the game can increase the players’ awareness and knowledge of the factors that a project manager should consider in GSD projects. The results obtained after evaluating the game were quite satisfactory, as the game taught the players to differentiate between global and distributed software projects and to experience situations that may and do occur in these settings. Furthermore, Global Manager helped improve players' perceptions of the importance of different influencing factors in GSD.

This article reports the analysis of data from five different studies to identify predictors of preservice, early childhood teachers’ views of (a) the nature of coding, (b) integration of coding into preschool classrooms, and (c) relation of coding to fields other than computer science (CS). Significant changes in views of coding were predicted by time, prior robot programming experience, and perceptions of the value of coding. Notably, prior programming knowledge and positive perceptions of mathematics predicted decreases in views of coding from pre- to post-survey.

Debugging is a core skill required by programmers, yet we know little about how to effectively teach the process of debugging. The challenges of learning debugging are compounded for novices who lack experience and are still learning the tools they need to program effectively. In this work, we report a case study in which we used a think-aloud protocol to gain insight into the behaviour of three students engaged in debugging tasks. Our qualitative analysis reveals a variety of helpful practices and barriers that limit the effectiveness of debugging. We observe that comprehension, evidence-based activities, and workflow practices all contribute to novice debugging success. Lack of sustained effort, precision, and methodical processes negatively impact debugging effectiveness. We anticipate that understanding how students engage in debugging tasks will aid future work to address ineffective behaviours and promote effective debugging activities.

Competency models are widely adopted frameworks that are used to improve human resource functions and education. However, the characteristics of competency models related to the information security and cybersecurity domains are not well understood. To bridge this gap, this study investigates the current state of competency models related to the security domain through qualitative content analysis. Additionally, based on the competency model analysis, an evidence-based competency model is proposed. Examining the content of 27 models, we found that the models can benefit target groups in many different ways, ranging from policymaking to performance management. Owing to their many uses, competency models can arguably help to narrow the skills gap from which the profession is suffering. Nonetheless, the models have their shortcomings. First, the models do not cover all of the topics specified by the Cybersecurity Body of Knowledge (i.e., no model is complete). Second, by omitting social, personal, and methodological competencies, many models reduce the competency profile of a security expert to professional competencies. Addressing the limitations of previous work, the proposed competency model provides a holistic view of the competencies required by security professionals for job achievement and can potentially benefit both the education system and the labor market. To conclude, the implications of the competency model analysis and use cases of the proposed model are discussed.

As technology and curricula continue to evolve and develop, the prevalence and effectiveness of continuing professional development (CPD) opportunities for computer science teachers is becoming increasingly more important. However, key questions remain about what the characteristics are for effective CPD in this context. Through the presentation of existing literature and the qualitative analysis of interviews with 32 employees from 13 English colleges (n = 14 computer science lecturers, 10 course leaders, and 8 members of senior leadership) this article answers the following question: ‘What are the characteristics of effective continuing professional development for computer science teachers in the 16-18 sector?’ Existing literature indicates how CPD benefits from: (1) knowledge development and application to classroom teaching, (2) self-efficacy development and measurement, (3) observation, feedback and reflection, (4) collaboration and communities of practice, (5) sufficient time, and (6) institution support. Meanwhile, the thematic analysis of interview data led to the creation of five overarching themes: (1) computer science CPD should address various knowledge domains, (2) CPD requires institutional support, (3) CPD should be engaging, (4) computer science CPD should involve a combination of activities, and (5) CPD should be measurable. This qualitative article also presents interview excerpts and contributes to computing education research and practice by presenting a set of thirty guidelines which outlines the characteristics of effective CPD in the context of computer science teachers in the 16-18 sector. These guidelines could be beneficial for both CPD providers and educators in ensuring CPD opportunities are designed more effectively, and with an understanding of both parties’ needs.