Catálogo de publicaciones - revistas

<jats:p>We studied the impact of introducing first-year computer science (CS) students to ethical thinking about the social justice impacts of data collection, tracking, bias, internet privacy, and competitive “real world” system design and critique activities. While basic content was consistent for all, one group was involved throughout the course in peer discussions designed to foster greater engagement, with the anticipation that this would enable students to reach new levels of sensitivity through peer-to-peer interaction. This article reports on our observation of this design, interview, and project data collected throughout the course as well interviews conducted eight months later to learn about how students were retaining and applying what they learned. We found that students are sensitive to the technology-related risks and vulnerabilities encountered by individuals based on race, gender, and, to some extent, age, but they struggle to assess who is responsible for these risks, what to do about bias in technology design, and how to mitigate harms for individuals whom they perceive to be vulnerable, furthering the argument for an integrated ethics curriculum. We explore the value of formal peer-led discussion to evolve social justice thinking with a focus on identity, though note that opportunities for any group discussion are meaningful to students’ thinking about social justice. Over the longer term, students tend to recall and apply ethics that is closely related to their identity, suggesting that empathy has limits.</jats:p>

<jats:p>The aim of this conceptual article is to provide a framework and a lens for educators in diversifying and making CS education more inclusive. In this article, we conceptualize the notion of computer science capital (CSC), which extends Bourdieu’s sociological theory of capital and Archer et al.’s work on “science capital.” The CSC concept was developed by contrasting the concept of science capital with a literature review on key factors affecting students’ aspirations in CS. We argue that there is a need to distinguish between science capital and CSC, because the types of capital that are considered legitimate vary between the field of natural science and computer science. The CSC concept uses a sociocultural perspective on learning and can be understood as a form of symbolic capital that is influential in facilitating students’ possibility to fully participate in, engage with, and form aspirations in CS. The CSC concept consists of three main components, each with associated subcomponents. We believe our CSC framework, along with the self-reflection prompts included in this article, will offer support for reflections for educators in their daily pedagogical work. By taking students’ various levels of social and cultural capital into consideration, educators can plan didactic activities with a focus to strengthen students’ various types of capital. This includes reflection on how implicit and explicit norms, beliefs, thoughts, expectations, values, and ideas can affect the pedagogical practices and ultimately the students. Only when we are reflective about our teaching practices can we be better positioned to construct a more inclusive teaching and learning environment.</jats:p>

<jats:p>Metacognition and self-regulation are important skills for successful learning and have been discussed and researched extensively in the general education literature for several decades. More recently, there has been growing interest in understanding how metacognitive and self-regulatory skills contribute to student success in the context of computing education. This article presents a thorough systematic review of metacognition and self-regulation work in the context of computer programming and an in-depth discussion of the theories that have been leveraged in some way. We also discuss several prominent metacognitive and self-regulation theories from the literature outside of computing education—for example, from psychology and education—that have yet to be applied in the context of programming education.</jats:p> <jats:p>In our investigation, we built a comprehensive corpus of papers on metacognition and self-regulation in programming education, and then employed backward snowballing to provide a deeper examination of foundational theories from outside computing education, some of which have been explored in programming education, and others that have yet to be but hold much promise. In addition, we make new observations about the way these theories are used by the computing education community, and present recommendations on how metacognition and self-regulation can help inform programming education in the future. In particular, we discuss exemplars of studies that have used existing theories to support their design and discussion of results as well as studies that have proposed their own metacognitive theories in the context of programming education. Readers will also find the article a useful resource for helping students in programming courses develop effective strategies for metacognition and self-regulation.</jats:p>

<jats:p>Assessment plays an important role in education and can both guide and motivate learning. Assessment can, however, be carried out with different aims: providing the students with feedback that supports the learning (formative assessment) and judging to which degree the students have fulfilled the intended learning outcomes (summative assessment). In this study, we explore the instructors’ perspective on assessment within the context of introductory programming courses offered to non-computer-science majors at a public tuition-free state-funded university in a Nordic country. These courses are given to a large number of students and also employ several teaching assistants (TAs). We used constructivism as a basis for our study and investigated how instructors implement formative and summative assessments, how they view their role, and what expectations they have of their TAs in these assessments. We interviewed seven course coordinators (main instructors for introductory programming courses with additional administrative duties but without formal responsibility of the grading) and analyzed 205 course artifacts, such as syllabi, lab assignment instructions, and course material from the cross-department TA training course. The results showed that course coordinators use formative and summative assessments both separately and within the same activity. They view themselves as responsible for the assessments, as the planners and material developers, as the organizers and administrators, and as monitors of the assessments. However, the results also showed that these course coordinators delegate much of the responsibility for the assessments to their TAs and expect TAs to both grade the students and provide them with feedback and guidance. In addition, the TAs are also expected to act as informants about their students’ performance. The course coordinators’ role entails many different aspects, where communicating through instructions to both students and TAs is essential. We see that this implementation of assessment, with lots of responsibility distributed to the TAs, could be difficult to manage for a single faculty member who is not necessarily responsible for the grading. Based on the results, we outline some recommendations, such as offering TA training.</jats:p>

<jats:p> <jats:bold>Problem.</jats:bold> K-12 teachers face many challenges when teaching a new subject like computer science (CS). They are often far removed from the research being conducted to identify evidence-driven solutions to these challenges. Likewise, researchers are also often removed from the challenges of classroom practices that teachers face when teaching CS. </jats:p> <jats:p> <jats:bold>Research Questions.</jats:bold> To create a collaborative process for teachers and researchers <jats:italic>outside</jats:italic> of a research practice partnership, we piloted a facilitated process in which CS middle school teachers and CS education researchers collaboratively created CS teacher practice briefs. Our research question for this study was: <jats:italic>In what ways are teachers impacted by the process of creating teacher practice briefs in collaboration with researchers?</jats:italic> </jats:p> <jats:p> <jats:bold>Methodology.</jats:bold> We conducted a qualitative study, using a semi-structured interview protocol to interview five teachers and three researchers to gain an understanding of how this process impacted the participants. We used thematic content analysis to identify several subthemes across our pre-established themes: motivation for teachers to participate, impacts on teachers, perceived impacts on students, and impacts on researchers. </jats:p> <jats:p> <jats:bold>Findings.</jats:bold> We found that the impact on teachers mirrored impacts found on teachers who engage in Research Practice Partnerships, including increased self-efficacy, expanded professional networks, and changed classroom practices. </jats:p> <jats:p> <jats:bold>Implications.</jats:bold> By bringing researchers and educators together with a clear focus on equity-based problems of practice in CS education, the results display a multitude of positive impacts. Teachers indicate that they are are positively impacted, researchers develop a clear understanding of realistic practices, and students are peripherally impacted through changed practices in the classroom. Therefore, the most significant contribution to advance the disciplinary understanding is the potential for this new process to decrease the gap between research and practice. </jats:p>

<jats:p>There has been considerable recent interest in a number of questions related to theory within computing education research. In this editorial, we summarize some of this recent interest, discuss the process in which this special issue came to be, and how papers were selected for inclusion. We end with a brief summary of each of the six papers appearing in this special issue, highlighting the relevance of each to this issue's theme.</jats:p>

<jats:p>Computing is rapidly becoming a critical literacy for succeeding in an increasingly technological world. While the proliferation of programs dedicated to broadening participation in computing increases access, computing education research can benefit from more directly drawing on current interest development theory to improve interventions that increase the desire to participate and persist in computing. In this article, we present an overview of current interest development theory and provide guidance to computing education researchers on ways to ground their conceptualization and measurement of interest in contemporary theory and inform ways of interweaving interest theory throughout intervention or curriculum design. The central contribution of this work is presenting the Integrated Interest Development for Computing Education Framework. This framework is organized around three central dimensions of interest: value, knowledge, and belonging. For each of these dimensions, the framework presents key factors that link the dimension to strategies that can be employed in computing education contexts to help develop interest. The article also describes methods of measuring interest in computing that are consistent with interest development theory, and provides examples and resources for validated measures of interest. We conclude with a discussion of the implications and potential for improving the conceptualization and measurement of interest development in computing education and future work needed to advance an understanding of how interest in computing develops that can lead to improving the design of computing educational programs to support interest development.</jats:p>

<jats:p>The 1980s and 1990s saw a robust connection between computer science education and cognitive psychology as researchers worked to understand how students learn to program. More recently, academic disciplines such as science and engineering have begun drawing on cognitive psychology research and theories of learning to create instructional materials and teacher professional development materials based on theories of learning, to some success. In this paper, we follow a similar approach by highlighting common areas of interest between computer science education and cognitive psychology–specifically theories of analogical transfer–and discuss how cross-pollination of theoretical constructs between disciplines can support research on the teaching and learning of multiple programming languages. We will also discuss areas where computing education research can adapt the existing theories from cognitive psychology to develop domain-specific theories of knowledge transfer in computing and feed back into cognitive psychology research to inform larger debates about the nature of cognition and learning.</jats:p>

<jats:p>Helping students learn to identify and respond to situations involving discrimination is important, especially in fields like Computer Science where there is evidence of an unwelcoming climate that disproportionately drives underrepresented students out of the field. While students should not be considered responsible for fixing issues around discrimination in their institutions, they do have a role to play. In this paper, we present the results of a study in which 318 undergraduate computer science majors were presented with scenarios of discrimination and asked to identify the issues, rate the severity of the issues, and ideate 3–5 responses to address the described situations. They were also asked to identify which of their responses would likely be most effective in addressing discrimination and which of their responses they would be most likely to use if they were in the situation described in real life. Our results show that while students generally are able to identify various forms of discrimination (sexism, racism, religious discrimination, ethnic discrimination, etc.), any ambiguity in a scenario led to students describing the scenario as less severe and/or as an example of oversensitivity. We also show that students come up with many passive responses to scenarios of discrimination (such as ignoring the situation or wishing it had not happened in the first place). Students in our study were more likely to say they would deploy passive responses in real life, shying away from responses that involve direct confrontation. We observed some differences between student demographic subgroups. Women and BIPOC students in CS tend to think these issues are more severe than men and White and Asian students in CS. Women are more likely to ideate direct confrontation responses and report willingness to use direct confrontation responses in real situations. Our work contributes a methodology for examining student awareness and understanding of diversity issues as well as a demonstration that undergraduate computer science students need help in learning how to address common situations that involve either intentional or unintentional discrimination in an academic environment.</jats:p>

<jats:p>There is increasing interest in computer science and computing bachelor programs due to the growing importance of technology in the globalized world. Thus, as higher education institutions strive to serve a diverse student demographic, it is salient to gauge their programming abilities in order to improve guidance on learning processes regarding their initial knowledge state. Despite the availability of certain instruments to measure student programming skills, these are traditionally aimed at younger populations and do not accurately discriminate the different levels of ability among university students. This paper introduces a translation into Spanish and validation of an existing English-language aptitude test for computing jobs that can be used to measure the programming abilities of students with no prior experience in the field. Following a cyclic research methodology, two iterations were carried out in this article. First, the aforementioned test was translated and validated via expert judgment and focus groups, in which certain items were removed subsequent to a quantitative analysis. The resultant instrument underwent a second validation using a larger population of students. Analysis conducted after the second iteration showed this instrument to deliver good internal consistency, good difficulty and discrimination indices, and a moderate correlation with the grades of the midterm exam of a programming course undertaken by first year engineering students. This work contributes to both increasing the number of tests available in the Spanish language with which to assess programming abilities, as well as to the broader literature regarding test adaptation, translation and validation.</jats:p>