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A Future for Computing Education Research

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Seeking to address the most important issues facing the computer education research community.

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... CEdR continues to flourish internationally, despite a paucity of formal pathways or designated degrees in computing education (CEd) for faculty and graduate students [8,18,19,26,32]. Researchers focused in this area may span multiple disciplines (e.g., cognitive sciences and/or CS [11,24,35]) and departments [9], which we define as the academic unit or division overseeing degreegranting programs. ...
... What makes the range of sub-areas and specializations described by the task force and ABET's CAC notable is that although many institutions may consider such programs under a single umbrella, each requires distinct blends of theory and application and can entail different knowledge, competencies, skills, and tools [13]. Accordingly, it is necessary to think about what students are taught and how, resulting in the emergence of CEd as a unique discipline-based education research (DBER) field [8,15]. Understanding computing and maintaining connections to the field can help CEd students contextualize material and appreciate its relevance [14]. ...
... Although CEd contends with more general issues such as retention and how to impart understanding, it also faces dynamic advancements in technology and the need to accommodate the many constituents who want to use and apply technology for their own purposes [31]. Growing numbers of doctoral students focused on CEdR mean a need for more focused pathways, pedagogy, and conceptual understanding [8,19]. There are also distinct publication channels for both computing and education, requiring ways to handle interdisciplinary considerations surrounding departmental milestones for students and faculty. ...
... [20] has found that some academics in the UK felt that their home universities held negative perceptions towards CSEd. At a Stanford University summit in 2014, researchers also agreed that there is a general lack of respect for CSEd and many do not view it as a rigorous discipline [18]. ...
... Community, institutional support [60] Conflicting views in CSEd community on priority research areas [18] Creation and dissemination of high-quality, equity-focused resources, tools, best practices, instruments, assessments [9,39,55,59,85] CSEd not recognized as a sub discipline within CS departments [16] Difficulties conducting qualitative research [37] Difficulty in deciding which department students should be apart of (Computing or Education) [16] Diversity in collaborators, leadership, researchers [8,88] Equal opportunities for networking Flawed peer review bidding processes [68] Funding, incentives, recognition, awards [16,19,42,81,84] Gaps in pay, publication, promotion Importance of conferences vs journals [43] Insufficient publication venues [16,17,43,58] Lack of CSEd faculty mentors for PhD students [17] Lack of infrastructure to support CSEd [19,20] Lack of qualitative research/prioritization of quantitative [18,37] Lack of replication studies (undervalued for publication, promotion, prestige over original work) [1,36] Lack of research questions in regards to research practitioners [25] Lack of respect for CSEd [16,17,20] Lack of validated assessment instruments [82] Limited job prospects [16,17] Limited opportunities to collaborate [16,19,20] Local publications devalued in favor of global research [14] Increased workload and lack of compensation for peer reviewers [68] Methods for linking research to practice and practice to research [41] Outreach viewed as a feminine task with less legitimacy [22] Personal costs (time, training, financial burden of higher education, unpaid labor, etc.) Proliferation of methods (longitudinal research [22], replication studies [1,36]) Removal of physical and other inequitable barriers to publish at and participate in conferences Research that does not match needs of practitioners [24] Strict use of theory requirement in research can stymie the search for better curriculum design [65] Time constraints (teaching vs research) [14,17] Tension between empowering less-established academics while anonymous and open reviews [68] Unclear recruiting practices for academic peer review [68] and workshops and within publications, and access to attend and participate in conferences virtually. It also includes the open access of research artifacts (e.g., publications, data, instrumentation, etc.) [6]. ...
... Community, institutional support [60] Conflicting views in CSEd community on priority research areas [18] Creation and dissemination of high-quality, equity-focused resources, tools, best practices, instruments, assessments [9,39,55,59,85] CSEd not recognized as a sub discipline within CS departments [16] Difficulties conducting qualitative research [37] Difficulty in deciding which department students should be apart of (Computing or Education) [16] Diversity in collaborators, leadership, researchers [8,88] Equal opportunities for networking Flawed peer review bidding processes [68] Funding, incentives, recognition, awards [16,19,42,81,84] Gaps in pay, publication, promotion Importance of conferences vs journals [43] Insufficient publication venues [16,17,43,58] Lack of CSEd faculty mentors for PhD students [17] Lack of infrastructure to support CSEd [19,20] Lack of qualitative research/prioritization of quantitative [18,37] Lack of replication studies (undervalued for publication, promotion, prestige over original work) [1,36] Lack of research questions in regards to research practitioners [25] Lack of respect for CSEd [16,17,20] Lack of validated assessment instruments [82] Limited job prospects [16,17] Limited opportunities to collaborate [16,19,20] Local publications devalued in favor of global research [14] Increased workload and lack of compensation for peer reviewers [68] Methods for linking research to practice and practice to research [41] Outreach viewed as a feminine task with less legitimacy [22] Personal costs (time, training, financial burden of higher education, unpaid labor, etc.) Proliferation of methods (longitudinal research [22], replication studies [1,36]) Removal of physical and other inequitable barriers to publish at and participate in conferences Research that does not match needs of practitioners [24] Strict use of theory requirement in research can stymie the search for better curriculum design [65] Time constraints (teaching vs research) [14,17] Tension between empowering less-established academics while anonymous and open reviews [68] Unclear recruiting practices for academic peer review [68] and workshops and within publications, and access to attend and participate in conferences virtually. It also includes the open access of research artifacts (e.g., publications, data, instrumentation, etc.) [6]. ...
... However, little is known about validated practices, but the importance of CT have been recognized (Parker et al., 2016;Cooper et al., 2014;Grover & Pea, 2018). ...
... Hence, computing education research is positioned to address questions about how to integrate computing into other disciplines. Furthermore, how to broaden and retain students in computing education, deliver computing education, and offer computational literacy equally to all (Cooper et al., 2014;2016). Research related to teachers professional development, evaluation of students' learning using mixed methods, and literature reviews that can identify areas for future research are of particular interest (Fincher et al., 2019). ...
... Study I, III, and IV, included in this dissertation, build on the work of Wilensky and Reisman (2006), Brady et al. (2015), and Sengupta et al. (2013) Findings, presented in section 4.5 from study V, are a continuation of research into the importance of CT in education (Parker et al., 2016;Cooper et al., 2014;Grover & Pea, 2018 can scale and be sustainable for students, educators, and policy makers. ...
Thesis
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Acknowledgements It is a privilege and a great pleasure to have worked with so many people who helped make this dissertation possible. A special thank you to: Ole Sejer Iversen, my supervisor, for being so patient with my background in biology. Also for introducing me to new research areas and to the academic life in an interdisciplinary research center. Michael E. Caspersen, my co-supervisor, for introducing me to computing education research and suggesting I pursued this work. He has tirelessly inspired, believed, and supported me and my work. Deborah Tatar, my co-supervisor, for sparking my interest in computational thinking by inviting me to participate in her own work, and for never failing to point me in the right research direction. Palle Nowack, my close friend and colleague, for inviting me on a winding (road-)trip to the land of computational modeling, and for never taking the easy way back. Keld Nielsen, my much appreciated colleague, for tireless discussions and for insisting on the relevance of our work. Peter Musaeus and the rest of my family, for being so kind as to bear with me throughout this process. Numerous people have contributed to my research.
... There is a need to understand how to measure and support this development of complex CT skills in the context of programming in K-12 learning settings. Assessments and measurements of student learning remain underdeveloped and underresearched in this domain [69] and are often called out among key future CS education research imperatives [8] going forward. However, without sufficient attention to thoughtful measurement of learning, it is believed that CT can have little hope of scaling in K-12 schools [25]. ...
... Researchers have now begun to apply EDM/LA in more exploratory learning to model detailed learner pathways [1]. In the context of programming, EDM methods and related LA have recently been used to study patterns of behaviors in program construction, compilation, and debugging [5,7,8]. For example, Berland et al. [5] used clustering techniques to classify students as following either the "tinkerer" or the "planner" approach. ...
... For example, Berland et al. [5] used clustering techniques to classify students as following either the "tinkerer" or the "planner" approach. Piech et al. [50] and Blikstein et al. [8] used EDM techniques to analyze program snapshots from CS1 students programming "Checkerboard Karel" using Karel the Robot, a programming environment for novices that provides learners with five commands to move Karel in a grid. Using purely data-driven approaches, they derived patterns of program states, examined how students transitioned through these states, developed predictors for good and bad states, and identified "sink" states from which students would only exit with great difficulty. ...
Article
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Systematic endeavors to take computer science (CS) and computational thinking (CT) to scale in middle and high school classrooms are underway with curricula that emphasize the enactment of authentic CT skills, especially in the context of programming in block-based programming environments. There is, therefore, a growing need to measure students’ learning of CT in the context of programming and also support all learners through this process of learning computational problem solving. The goal of this research is to explore hypothesis-driven approaches that can be combined with data-driven ones to better interpret student actions and processes in log data captured from block-based programming environments with the goal of measuring and assessing students’ CT skills. Informed by past literature and based on our empirical work examining a dataset from the use of the Fairy Assessment in the Alice programming environment in middle schools, we present a framework that formalizes a process where a hypothesis-driven approach informed by Evidence-Centered Design effectively complements data-driven learning analytics in interpreting students’ programming process and assessing CT in block-based programming environments. We apply the framework to the design of Alice tasks for high school CS to be used for measuring CT during programming.
... Although we are not the irst scholars to consider how to support and grow the CSEd research community [19], this investigation ofers a new perspective from the vantage point of well-regarded faculty from diferent departments and institutions. Our study advances the ield by identifying the distinctive needs of CSEd advisors and it provides insight into opportunities in the discipline. ...
... Unlike some other DBERs which tend to be centralized within a college (e.g., physics education), CSEd researchers often exist in many departments and schools. They often belong to CS, education, and/or engineering education and computing education topics may be integrated into curricula through the humanities, science, or mathematics [19]. Given the placement of CSEd in higher education, our research explores what unique issues faculty face for their research, teaching, and mentoring of graduate students. ...
Article
Computer science education (CSEd) is a growing interdisciplinary area that continues to gain momentum from students, researchers, and educators. Yet, there are few formal programs or degree options for students interested in pursuing graduate work in CSEd. This paper explores the existing state of CSEd in the United States (U.S.) through semi-structured interviews with ( n = 15) faculty engaged in CSEd research. Thematic coding of the transcripts revealed the complexities involved in the development of formal programs, the distinct considerations for faculty, and the value of having strong ties to both computer science and education. The themes described positive aspects of support and cohesion within the larger community and opportunities to expand knowledge across fields. Applying Cornell and Parker’s principles of interdisciplinary science to the field of CSEd, we provide recommendations for ways forward and describe the potential impact on institutional structures, research capacity, individual and group identities, and teaching and learning. The findings from this investigation not only inform on the present state of CSEd in the U.S., but also offer guidance for CSEd-focused graduate programs.
... In some states, like California, African-American students only comprised 1% of the 10,244 high school students taking the AP CS exam in 2016 [15,32]. Consequently, scholars like Cooper, Grover, Guzdial, and Simon have stressed the need for computing education researchers to not only better understand the lack of diversity in computing but to also look into ways to render computing classes more equitable for a broad spectrum of students [16]. Equity, in that sense, is defined as the democratization of computer science for all students through the recognition of existing advantages and barriers [39]. ...
... Another teacher expressed a similar view: "I think one of the major issues, too, in computer science and it's very hard to manage this as a classroom teacher, boys at this age have a lot of false bravado about everything. They're amazing drivers, they're amazing at sports, you know, anything a boy that's [15][16] year old does, they tend to brag a lot, they're very vocal, they're obnoxious, they're overbearing. And so they will talk about their skills with computers and I think girls really internalize that." ...
Article
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The current efforts to expand computer science (CS) education in K-12 schools, such as the “CS for All” initiative, highlight the need for all students to get an opportunity to study computing. However, as recent research has shown, diversity in computing at the K-12 level remains problematic, and additional research is needed to look at how computer science learning environments can impact minority student interest and retention in CS. In this article, we report results from an in-depth qualitative study of high school computer science teachers’ perspective on barriers to increasing diversity in their classes. Based on teachers’ experiences, we provide practical recommendations on how to encourage equitable learning environments in K-12 computer science courses.
... An important question of computing disciplines is the way people come to understand computing and ways to make it better [15]. Social context is important in exploring how IT curricular frameworks reflect and respond to factors specific to the academic institutions of the IT undergraduate degree programs [62]. ...
... Bowen and Spohrer [5] report that both computer technology and the IT industry have undergone dramatic change and this requires that IT education must also undertake dramatic change. Cooper, Grover, and Guzdial [15] observe that "The economic value of knowing computing is greater than any other STEM field, but computing is the least diverse of all the STEM fields. Thus, too many people are losing out on the advantages of computing. ...
Conference Paper
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As the term 'information technology' has many meanings for various stakeholders and continues to evolve, this work presents a comprehensive approach for developing curriculum guidelines for rigorous, high quality, bachelor's degree programs in information technology (IT) to prepare successful graduates for a future global technological society. The aim is to address three research questions in the context of IT concerning (1) the educational frameworks relevant for academics and students of IT, (2) the pathways into IT programs, and (3) graduates' preparation for meeting future technologies. The analysis of current trends comes from survey data of IT faculty members and professional IT industry leaders. With these analyses, the IT Model Curricula of CC2005, IT2008, IT2017, extensive literature review, and the multinational insights of the authors into the status of IT, this paper presents a comprehensive overview and discussion of future directions of global IT education toward 2025.
... Current society requires individuals to be able to use computers to solve problems and accomplish goals, scholars and the government have asserted the importance of incorporating CT/CS from K-12 education. However, there is currently no clear consensus on how CT/CS education is integrated into the early childhood education setting (Manches & Plowman, 2017) and even what we mean by CT/CS education and appropriate pedagogy concerning young children (Cooper et al., 2014). In early childhood education promoting holistic development and well-being of students, including their social, emotional, and physical needs, is the purpose of early childhood education (NAEYC, 2009). ...
Article
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Many K-12 computer science (CS) education initiatives at the local, state, and federal levels have recently started to focus on engaging the young children. Although most CS education research has focused on the secondary level, only minimal research has explored how computer science (CS) and computational thinking (CT) can be taught in elementary and especially at kindergarten. Understanding how CS and CT are taught at the youngest levels is critical to support the creation of progressive quality curricula and professional development. Therefore, in this study, we delved into the CT/CS curriculum design considerations of five teachers for kindergarteners. Our findings revealed that the primary learning objectives encompassed: 1) Social skill acquisition, 2) Fostering a growth mindset, and 3) Developing basic CT competencies. Moreover, when crafting their CT/CS curriculum, teachers weighed factors such as 1) Their approach to adapting the CT/CS curriculum—whether it be a personalized approach or relying on a pre-packaged curriculum—and 2) Adhering to Developmentally Appropriate Practice (DAP), which took into account individual abilities, interests, and socially relevant contexts. We conclude by discussing the ramifications of these findings in terms of professional development and the shaping of future CT/CS curricula for young learners.
... Qualitative approaches are also uniquely well suited for informal learning spaces without standardised assessments, where participants can instead provide contextualised qualitative data [42]. Nevertheless, there is a shortage of qualitative CER [29,68], especially for specific minoritized groups. One potential reason for a deficit of qualitative studies is the misconception that small participant sample sizes cannot contribute to knowledge, despite the insights that can be gleaned from in-depth studies of small groups [93] and the preponderance of qualitative studies even within the medical research field. ...
... There are also questions about the unique contributions of programming and CT in contrast with other forms of domain thinking (e.g., computational thinking vs. mathematical thinking, historical thinking, scientific thinking, and so on) (Grover and Pea 2013). As a practical caution, this interest in programming across the curriculum is motivated, in no small part, by the bureaucratic challenge of determining where to include computer science in a K-12 curriculum that is already very full (Cooper et al. 2014). In other words, disciplinary integration is sometimes a strategy for addressing administrative concerns rather than benefiting student learning. ...
Chapter
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A guide to computational thinking education, with a focus on artificial intelligence literacy and the integration of computing and physical objects. Computing has become an essential part of today's primary and secondary school curricula. In recent years, K–12 computer education has shifted from computer science itself to the broader perspective of computational thinking (CT), which is less about technology than a way of thinking and solving problems—“a fundamental skill for everyone, not just computer scientists,” in the words of Jeanette Wing, author of a foundational article on CT. This volume introduces a variety of approaches to CT in K–12 education, offering a wide range of international perspectives that focus on artificial intelligence (AI) literacy and the integration of computing and physical objects. The book first offers an overview of CT and its importance in K–12 education, covering such topics as the rationale for teaching CT; programming as a general problem-solving skill; and the “phenomenon-based learning” approach. It then addresses the educational implications of the explosion in AI research, discussing, among other things, the importance of teaching children to be conscientious designers and consumers of AI. Finally, the book examines the increasing influence of physical devices in CT education, considering the learning opportunities offered by robotics. Contributors Harold Abelson, Cynthia Breazeal, Karen Brennan, Michael E. Caspersen, Christian Dindler, Daniella DiPaola, Nardie Fanchamps, Christina Gardner-McCune, Mark Guzdial, Kai Hakkarainen, Fredrik Heintz, Paul Hennissen, H. Ulrich Hoppe, Ole Sejer Iversen, Siu-Cheung Kong, Wai-Ying Kwok, Sven Manske, Jesús Moreno-León, Blakeley H. Payne, Sini Riikonen, Gregorio Robles, Marcos Román-González, Pirita Seitamaa-Hakkarainen, Ju-Ling Shih, Pasi Silander, Lou Slangen, Rachel Charlotte Smith, Marcus Specht, Florence R. Sullivan, David S. Touretzky
... Computing education is one of the key strategic areas in STEM education that is bringing revolution throughout the world [26,27]. The primary goal of CER is to discover and design better computing learning processes. ...
Article
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Computer science graduates face a massive gap between industry-relevant skills and those learned at school. Industry practitioners often counter a huge challenge when moving from academics to industry, requiring a completely different set of skills and knowledge. It is essential to fill the gap between the industry's required skills and those taught at varsities. In this study, we leverage deep learning and big data to propose a framework that maps the required skills with those acquired by computing graduates. Based on the mapping, we recommend enhancing the computing curriculum to match the industry-relevant skills. Our proposed framework consists of four layers: data, embedding, mapping, and a curriculum enhancement layer. Based on the recommendations from the mapping module, we made revisions and modifications to the computing curricula. Finally, we perform a case study of the Norwegian IT jobs market, where we make recommendations for data science and software engineering-related jobs. We argue that by using our proposed methodology and analysis, a significant enhancement in the computing curriculum is possible to help increase employability, student satisfaction, and smart decision-making.
... Learning CT has many benefits beyond programming." In his blog, Guzdial (2019) recently took up the challenge of establishing a definition of CT; he recommends the approach taken by Weintrop et al. (2016), who focus on computational scientists' practices and the subsets of computing skills and thinking they use in their work, and the way in which CT empowers them to apply their thinking and problem-solving skills in their professional life. Also, Angeli and Giannakos (2020) describe how CT education may help engage students in meaningful learning, to develop useful thinking skills for their future education, work and life, and Schaper et al. (2022) discuss emerging technologies related to CT in K-12 education. ...
Article
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There is a global consensus that computational thinking (CT) should be integrated into education, and empowerment is often used as an argument for why future generations need to be able to think computationally. In this paper we report on a systematic literature survey that categorises various strands of empowerment as they unfold in CT education research. We apply an existing categorisation tool that defines the use of empowerment in relation to five interpretations: management, critical, democratic, functional and educational empowerment. Our analysis identifies several important limitations in the current literature. First, ‘empowerment’ is frequently used, but seldom defined, in current CT education literature. Second, the understanding of empowerment varies substantially depending on geographic region, which means that empowerment as an end-goal in CT education may differ significantly from region to region. Our study also found that critical and managemental empowerment are under-represented in the international CT education literature, but are more prevalent in research carried out in the Nordic countries. We conclude this paper by suggesting a research agenda to secure a more palpable research literature related to empowerment and to CT in education, to support future research, and to support ongoing policy-making.
... In the United States, we are currently seeing a broad-based push for increasing access to computer science education in K-12 at the district, state, and national levels (Guzdial, 2016). This effort is particularly focused on engaging younger students, females and underrepresented minorities in computing (Wilson, et al., 2010;Cooper, et al., 2014). In the absence of education policy around computational thinking and computer science education in K-12, it has fallen to academic researchers and professional associations to advance theory and practice in this domain (Gal-Ezer and Stephenson, 2014). ...
... As computer programming is being introduced in K-12 classrooms, either as a discipline or integrated with other subjects, the issue of assessing student learning in this field remains a challenge [12,17,29]. While many efforts are being employed to help teachers in assessing students' programs, there is still a strong need for assessment instruments that can shed light on the students' processes and behaviors while working on a programming task [17,18]. ...
... Although course-taking has improved with time, enrollment in said courses by historically marginalized groups in CSEd has not improved (e.g., African Americans, Native Americans, Latinos, and women; Gretter et al., 2019). Cooper et al. (2014) state that, "studies at the intersection of race, ethnicity, and gender are needed, to better understand why certain groups choose to enter and persist in computing while others do not (p. 35)." ...
Article
Recent research on Computer Science (CS) has largely found that inequities in access persist. In 2016, President Obama announced the Computer Science for All initiative, recognizing that CS is a “new” basic skill in K-12 schools and over US$4 billion was pledged to Computer Science education (CSEd) initiatives. While general support for computer science and the associated funding is currently evident, this has not always been the case. From no mention in 2001’s No Child Left Behind legislation (2002) to making the national educational agenda in 2015’s Every Student Succeeds Act (ESSA), CS has found a place in K-12 education. The current state of the CSEd agenda in the US has been greatly influenced by those who have served in industry. However, ESSA was designed to give states flexibility in creating equitable educational systems, especially for students who have been historically marginalized. Given this contrast of federal legislation and the economic motivations of industry on CSEd, we ask, why did computer science education become part of the US federal agenda, and how have business and industry “pushed” and influenced computer science education? We draw on policies, research, reports, organization websites, and professional networking sites, to better understand the national support for CSEd as well as how state-level flexibility has resulted in specific states engaging within this policy window in varying ways. We then examine one company that has “pushed” a CSEd agenda to highlight the magnitude of the impact of industry on the field of CS. We close with implications for researchers and policymakers.
... Aunque, en promedio, estos usuarios no son nativos digitales, están acostumbrados a realizar varios servicios digitales, lo cual ha contribuido a que muchas IES creen más puntos de contactos digitales con los estudiantes como parte de una estrategia multicanal que abarca los espacios en la web, las aplicaciones móviles, etc. (Uribe, Velásquez & Londoño,2020;Vega & Botero, 2020) Con el mismo propósito están las tecnologías digitales emergentes como la impresión 3D. Con ellas se pueden manipular y estudiar objetos, y fósiles como antigüedades, sin olvidar la posibilidad de generar nuevos prototipos y desarrollos (Peña & Ortiz, 2021;Cabero et al., 2019;Cooper et al., 2014;Johnson, et al.,2014). Por otra parte, los MOOC (Massive Online Open Courses) que traen una versión educativa del Big Data que comúnmente utiliza Learning Analytics. ...
Chapter
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El objetivo general del presente artículo es caracterizar la transformación digital de las universidades a nivel internacional. La metodología es de corte cualitativo y el método es de revisión documental por matrices. La conclusión principal es que los diálogos entre conectividad, multimedia, calidades visuales y computación han cambiado el potencial de la utilización de las nuevas tecnologías en la formación académica. En el presente, la enseñanza en las IES no solo se basa en la transmisión de conocimientos únicos y posiblemente consolidados desde la jerarquía profesor-estudiante, sino que se busca la desconstrucción y construcción del conocimiento colaborativo, donde los estudiantes son actores activos con autonomía y responsabilidad en el proceso de aprendizaje acompañado por la mediación del profesor. De ahí, que este tipo de experiencias tienen como derrotero fortalecer el aprendizaje de los estudiantes y que estos se reconozcan en su entorno como contribuyan creativamente al desarrollo de nuevas soluciones a través de la mediación de las TIC.
... However, this growth is also a unique research challenge, as we know very little about how to best teach our current students. According to Cooper et al. (2014), the expanding field of Computing Education Research (CER) is positioned to address this challenge by answering research questions such as: a) How should we teach computer science, from programming to advanced principles, to a broader and more diverse audience? b) How can we ensure that we retain this more diverse audience through inclusive pedagogy and generally more effective teaching? ...
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Despite being a problem reported in a long time, the high rate of dropout and failure in computing courses remains a problem for the area. In this context, the introductory programming courses are among the worst, generating the highest rates of dropout in the first semesters of the program. Several studies describe pedagogical strategies that try to improve teaching programming and retain more students. Other studies try to identify factors that are related to the success or retention of students. One of the strategies to support the teaching-learning process is to identify students at risk in advance. Although there is a strong relationship between the motivation and the students’ outcome, few works use the motivation as a factor to identify students at risk. This work presents and evaluates a method to identify features that allow predicting at-risk students in introductory computing courses, based on four main components: pre-university factors, initial motivation, motivation through the course, and professor perception. In addition, it is proposed an instrument to assess educational factors that impact on motivation. The method is based on questionnaires, and the results were validated regarding reliability and validity by the Cronbach's alpha coefficient, omega coefficient, and factor analysis, which we proved to be satisfactory. Using the method created, named EMMECS, case studies with 173 students from different courses in computer science in four different universities in southern Brazil were conducted. We carried out several simulations of prediction, using ten different classification algorithms and different datasets. As a result, the best-case scenarios, using support vector machine and AdaBoostM1 algorithms, we identified on average more than 80% of students that would fail, since the first week of the study. The results show that the proposed method is effective compared with related works and it has as advantages its independence of programmatic content, specific assessments, grades, and interaction with learning systems. Furthermore, the method allows the weekly prediction, with good results since the first few weeks
... Adicional a esto, la naturaleza de esta transformación, al igual que los innumerables usos de las herramientas digitales en múltiples sectores, han llamado la atención en el concepto denominador de estas estrategias y es el big data o uso de datos masivos. Este concepto y su posterior uso han ayudado a investigadores a realizar análisis basado en evidencias en las aulas de clase, con el fin de ayudar a los estudiantes en sus procesos formativos (Cooper, Grover, Guzdial, & Simon, 2014). ...
Article
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New technologies are reinventing many sectors of the economy, and the education sector is no stran- ger to these changes. Industry 4.0 permeates these sectors with new innovations that some consider beneficial, others on the contrary, dangerous. However, there are meeting points and changes that will be inevitable in this new era of knowledge. Objective: to present a set of methods, tools and procedures found in the literature review, on how these new technologies are changing and will definitely change all sectors, especially focused on the education sector. Definitions are presented around the elements that are shaping the digital transformation in education, these are artificial intelligence, virtual and augmen- ted reality and big data. Methodology: Technological surveillance is used to search for scientific articles in primary and secondary sources, as well as mainly indexed databases. Results: Examples from 4.0 te- chnologies are presented to support the educational sector. Conclusions: New technologies will be very useful tools to impart knowledge and informative education, thanks to their technical and technologi- cal capabilities. From this, teachers must reinvent and adapt their methods and models of education.
... /10.1145/3328778.3366896 kept pace with the spread of CS programs and curricula [40] and is often called out as one of the key R&D imperatives for computing education [6,12,41]. With growing availability of CS assessments at the high school level, the need for robust measurement-for both formative and summative purposes-is now acutely felt at the middle and primary school levels [7]. ...
Conference Paper
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Teaching of computer science (CS) and programming is rapidly expanding in formal school education. Learning to program is a key ingredient of school CS curricula, and consequently quality measurements of student learning of foundational programming concepts are needed by teachers and researchers. However, high- quality tools for measuring student learning in introductory CS have been under-developed and under-researched. This experience report shares the process of design and refinement of a summative paper- based assessment (that could also be administered online) for introductory programming in middle grades (6-8). We share our experiences with the use of assessment as a pre-post measure in a middle school introductory programming course in diverse, urban school classrooms in the US and use that data to conduct validity, reliability and item discrimination analyses.
... Pedagogy. Teachers can play a critical role in broadening access to computing education in K-12 and beyondcreating classroom cultures that support computational literacy and that offer all students opportunities for computational creation (Brennan, 2013;Cooper, Grover, Guzdial, & Simon, 2014;Cuny, Baxter, Garcia, Gray, & Morelli, 2014;Goode, 2008;Kafai & Burke, 2014;Margolis & Kafai, 2014;Margolis et al., 2012). When considering which programming language to teach with, it may be important to consider not only the students' needs and interests, but also the educator's needs. ...
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Our research is a retrospective study of 10,000+ students enrolled in CS1 (introduction to computer programming) from 118 US college institutions. We employed a survey to collect such data as on the students’ background, academic achievement, programming experience prior to courses enrollment and a second survey to collect teachers final grade reports. After applying multiple matching techniques on a list of key factors, we asked if students who have learned graphical interface programming languages (e.g., Alice, Scratch) as a first programming language prior to college enrollment achieved higher final grade in CS1 than those who had first learned a textual programming language (e.g. C++, Java) as first language or than those who have not learned any programming at all.
... More field-specific aspects should be considered other than intellectual and practical aspects, such as the most important research questions and critical needs of a field. Five areas have been identified as the most important in computing education, including broadening participation, computing in K-12, computing in STEM education, students and learning issues, and tools [5]. As this study found, replication studies in some areas, such as computing in K-12 and computing in STEM education, were very rare in the past decade. ...
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As the societal demands for application and knowledge in computer science (CS) increase, CS student enrollment keeps growing rapidly around the world. By continuously improving the efficacy of computing education and providing guidelines for learning and teaching practice, computing education research plays a vital role in addressing both educational and societal challenges that emerge from the growth of CS students. Given the significant role of computing education research, it is important to ensure the reliability of studies in this field. The extent to which studies can be replicated in a field is one of the most important standards for reliability. Different fields have paid increasing attention to the replication rates of their studies, but the replication rate of computing education was never systematically studied. To fill this gap, this study investigated the replication rate of computing education between 2009 and 2018. We examined 2,269 published studies from three major conferences and two major journals in computing education, and found that the overall replication rate of computing education was 2.38%. This study demonstrated the need for more replication studies in computing education and discussed how to encourage replication studies through research initiatives and policy making.
... Pedagogy. Teachers can play a critical role in broadening access to computing education in K-12 and beyondcreating classroom cultures that support computational literacy and that offer all students opportunities for computational creation (Brennan, 2013;Cooper, Grover, Guzdial, & Simon, 2014;Cuny, Baxter, Garcia, Gray, & Morelli, 2014;Goode, 2008;Kafai & Burke, 2014;Margolis & Kafai, 2014;Margolis et al., 2012). When considering which programming language to teach with, it may be important to consider not only the students' needs and interests, but also the educator's needs. ...
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Background and Context: The relationship between novices’ first programming language and their future achievement has drawn increasing interest owing to recent efforts to expand K–12 computing education. This article contributes to this topic by analyzing data from a retrospective study of more than 10,000 undergraduates enrolled in introductory computer science courses at 118 U.S. institutions of higher education. Objective: We explored the relationship between students’ first programming languages and both their final grades in an introductory computer science course and their attitudes about programming. Method: Multiple matching techniques compared those whose first language was graphical (e.g., Scratch), textual (e.g., Java), or absent prior to college. Findings: Having any prior programming experience had positive effects on both attitudes about programming and grades in introductory computer science courses. Importantly, students whose first language was graphical had higher grades than did students whose first language was textual, when the languages were introduced in or before early adolescent years. Implications: Learning any computer language is better than learning none. If programming is to be taught to students before early adolescence, it is advised to start with a graphical language. Future work should investigate the transition between different types of programming languages.
... PCK has been studied in the context of C&CT both in primary and secondary school settings (Angeli et al., 2016). However, while PCK is recognised as being of crucial importance for effective teaching in C&CT (Saeli, Perrenet, Jochems, & Zwaneveld, 2011), research about ways to understand and promote PCK in C&CT is still in its infancy (Cooper, Grover, Guzdial, & Simon, 2014). There are still many les-sons to learn about providing appropriate and effective PD to pre-service and in-service teachers (Guzdial, 2015;Yadav et al., 2018). ...
Article
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Coding and computational thinking have recently become compulsory skills in many school systems globally. Teaching these new skills presents a challenge for many teachers. A notable example of professional development designed using Constructionist principles to address this challenge is ScratchEd. Upon reflecting on her experiences designing and running ScratchEd, Karen Brennan identified five tensions faced by professional development providers, and proposed that these tensions could be used for scrutinising and critiquing professional development. In this paper we analyse, through the lens of Brennan's tensions, the process we have followed to design, evaluate and improve professional development. We argue that while we have experienced the same tensions, the extent to which we assess learning is a new tension that extends those identified by Brennan. There are strong reasons to assess teachers' knowledge, however, quantitative measures of learning could be at odds with Constructionism: as Papert argued in Mindstorms, constructionist educators should study their learning environments as anthropologists. Consequently, we have called this new tension the tension between anthropology and assessment.
... Burkhardt, 2006;Lesh and Lehrer, 2003;Lesh and Zawojewski, 2007). Growing the knowledge base on how best to effect the integration of CT and STEM has been called out as one of the imperatives for computing education research ( Cooper et al., 2014). The role of CT in non-STEM subjects such as music, social sciences, visual arts, language arts, history, is manifold. ...
... Although computing at the elementary grades is not a new concept [e.g. 19], there is an increased focus on providing early CS experiences to both provide unique instructional opportunities and increase the diversity of the CS field [1,16], students with disabilities, students from lower socioeconomic households, and students from culturally and linguistically diverse backgrounds in CS [17]. Leveraging research in science education that points to the importance of early and sustained exposure [2], the focus of this study is on CS instruction in elementary school. ...
Conference Paper
Despite efforts to integrate computer science (CS) into K-12 education, there are numerous unanswered questions about how students learn CS, how to provide positive computing experiences, and how students interact with each other during CS instruction. To begin to deconstruct these complexities for a diverse range of students, it is important to not only study the outcomes and products of students' computational experiences, but also the processes they take in creating those products. In recognizing the necessity for targeted, narrow research questions, this paper focused on how elementary students interacted with each other during puzzle-based CS instruction. Future work will focus on comparing these findings to students' collaborative interactions in more open-ended computing situations. Data analysis made use of the Collaborative Computing Observation Instrument (C-COI) [M. Israel et al. 2015] to analyze video screen captures of nine students as they engaged in CS activities within Code.org's Code Studio. Findings confirmed three predominant types of collaborative interactions: Collaborative problem solving, excitement and accomplishment related to CS activities, and general socialization.
... These have focused on providing kids with an engaging exposure to the creation of computational artifacts and largely ignored issues of assessment. Consequently, assessments of CT remain underdeveloped and under-researched (Yadav et al., 2015) and this issue has been called out as a key future CS education research imperative (Cooper.. Grover, Guzdial, & Simon, 2014). They are conspicuously missing from tbr early introductory programming curricular offerings rolled out online by entities such as Code.org and Khan Academy. ...
Chapter
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As educators move to introduce computing in K-12 classrooms, the issue of assessing student learning of computational concepts, especially in the context of introductory programming, remains a challenge. Assessments are central if the goal is to help students develop deeper, transferable computational thinking (CT) skills that prepare them for success in future computing experiences. This chapter argues for the need for multiple measures or “systems of assessments” that are complementary, attend to cognitive and noncognitive aspects of learning CT, and contribute to a comprehensive picture of student learning. It describes the multiple forms of assessments designed and empirically studied in Foundations for Advancing Computational Thinking, a middle school introductory computing curriculum. These include directed and open-ended programming assignments in Scratch, multiple-choice formative assessments, artifact-based interviews, and summative assessments to measure student learning of algorithmic constructs. The design of unique “preparation for future learning” assessments to measure transfer of CT from block-based to text-based code snippets is also described.
... Secondly, more than ever, this points to a need for formative and summative assessments designed to measure student understanding, including misconceptions, and also to refine pedagogy and curricula. This has been pointed out as an imperative to scaling up CS in K-12 [2,8,22]. Our current research involves developing pedagogical strategies that address these issues and recommendations, as well as formative and summative assessments. ...
Conference Paper
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Programming in block-based environments is a key element of introductory computer science (CS) curricula in K-12 settings. Past research conducted in the context of text-based programming points to several challenges related to novice learners' understanding of foundational programming constructs such as variables, loops, and expressions. This research aims to develop assessment items for measuring student understanding in introductory CS classrooms in middle school using a principled approach for assessment design. This paper describes the design of assessments items that were piloted with 100 6th, 7th, 8th graders who had completed an introductory programming course using Scratch. The results and follow-up cognitive thinkalouds indicate that students are generally unfamiliar with the use of variables, and harbor misconceptions about them. They also have trouble with other aspects of introductory programming such as how loops work, and how the Boolean operators work. These findings point to the need for pedagogy that combines popular constructionist activities with those that target conceptual learning, along with better professional development to support teachers' conceptual learning of these foundational constructs.
... Using data from the U.S. Bureau of Labor Statistics, Miller (2014) argues that computer science skills are increasingly necessary for careers in all industries and that, by 2020, we will have a million more computer science positions than computer scientists. Cooper, Grover, Guzdial, and Simon (2014) argue that to address the deficit of general computing literacy and qualified computer scientists, interventions to improve computing instruction are needed. ...
Article
In highly procedural problem solving, procedures are typically taught with context-independent expository text that conceptually describes a procedure and context-dependent worked examples that concretely demonstrate a procedure. Subgoal labels have been used in worked examples to improve problem solving performance. The effect of subgoal labels in expository text, however, has not been explored. The present study examined the efficacy of subgoal labeled expository text and worked examples for programming education. The results show that learners who received subgoal labels in both the text and example are able to solve novel problems better than those who did not. In addition, subgoal labels in the text appear to have a different, rather than an additive, effect on learners compared to subgoal labels in the example. Specifically, subgoal labels in the text appear to help the learner articulate the procedure, and subgoal labels in the example appear to help the learner apply the procedure.
Conference Paper
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In this paper, we present a preliminary description of the field of inquiry encompassed by the philosophy of computing education. We first attempt to identify a general framework for investigating characteristic questions of a philosophical nature that arise within the STEM application domains. We describe the categories such questions fall under and use the philosophy of computing to illustrate this process. We also consider an alternative approach to identifying philosophical issues within a practical field, using the philosophy of education as an example. We consider the related subject of the philosophy of engineering education and see how this has recently emerged as an object of study in its own right. We investigate the similarities and differences between this field and the philosophy of computing education, and provide an initial description of the latter subject area. We also discuss how it relates to the subject referred to as Computing Education Research. Finally, we draw some conclusions about why there is this puzzling, apparent lack of interest in current work in this area, and suggest reasons why the pursuit of philosophical inquiry into computing education should be an important aspect of scholarly study in the subject. Keywords-philosophy, philosophy of computing education, philosophy of engineering education, philosophy of computing, philosophy of education.
Article
Computational Thinking (CT) through programming in higher education is considered an important skill for students to become problem solvers and thrive in the new digital workplace. Despite the wide interest, a systematic map of CT through programming in higher education is still missing. The aim of this study is twofold. First, we aim to provide a systematic map of the relevant research by identifying the areas and sub-areas of CT through programming teaching and learning in higher education. Second, we aim to investigate these areas based on two dimensions: their evolution over the years and the branches to which CT is applied. For this purpose, we apply a systematic mapping methodology. Main results include the identification of the CT areas of Knowledge Base, Assessment, Learning Strategies, Tools, Factors and Capacity Building. Of these, Knowledge Base, Assessment and Tools have significantly evolved throughout the years, while Capacity Building has only recently emerged. In addition, the introduction of CT to undergraduate students and preservice teachers differs mainly in the tools used and the CT elements that are assessed. The study contributes to the field by providing a structured type of research conducted and identifying gaps and opportunities for future research.
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Resumo Este artigo apresenta um estudo de caso sobre o desenvolvimento do Pensamento Computacional em crianças do Ensino Fundamental I, através do aprendizado de programação por meio da Robótica Educacional, fazendo-se uso exclusivamente de tecnologia livre e materiais recicláveis e de baixo custo. Busca-se também levantar hipóteses acerca da existência de uma relação direta entre certas características cognitivas de crianças com idade entre 8 e 10 anos (tais como a habilidade de sequenciar eventos ou ideias, a habilidade de realizar operações mentais a partir de experiências concretas, dentre outras) e a habilidade para realizar determinadas atividades relacionadas ao aprendizado de programação de computadores. Os resultados observados indicam (a partir do uso de um kit didático desenvolvido para a realização deste estudo) a possibilidade de desenvolvimento das seguintes habilidades do Pensamento Computacional: capacidade de abstração, compreensão de fluxos de controle, depuração e detecção sistemática de erros, pensamento iterativo, uso da lógica condicional e decomposição de problemas. No tocante às investigações relacionadas à maturidade cognitiva, foram encontrados indícios da existência de uma relação direta entre as características cognitivas analisadas e a realização de determinadas tarefas ligadas à programação de computadores, como o desenvolvimento de programas puramente sequenciais e a compreensão da ideia de processamento. Abstract This paper presents a case study about the development of Computational Thinking in primary school children (3st to 4th grade) via the teaching of programming abilities with the use of educational robotics, free technology and recyclable, low cost materials. We aimed at raising some hypotheses on whether there is a straight relationship between some cognitive aspects of children aged 8-10 (such as the ability to put events and ideas in sequence, the ability to execute mental operations on the basis of concrete experience, among others) and the ability to execute activities that may be linked to the learning of computer programming. The observed results indicated (from the use of a didactic kit developed for the accomplishment of this study) the possibility to develop the following computational thinking skills: abstract thinking ability, understanding of flows of control, Debugging and systematic error detection, iterative thinking, use of conditional logic and problem decomposition. Regarding the investigations related to cognitive maturity, we found evidence of a correlation between the cognitive characteristics analyzed and the performance of certain tasks related to computer programming, such as the development of purely sequential programs and understanding of processing idea.
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Design is a distinct discipline with its own practices, tools, professions, and areas of scholarship. However, practitioners from other fields often leverage aspects of design in their own work, leading to subfields like engineering design and architecture design that are neither wholly design nor wholly the intersecting discipline. Similarly, design and computing are known to intersect in educational contexts. Unfortunately, we do not yet have a clear understanding of how to characterize the kinds of design that may accompany computing topics, resulting in challenges to teaching and learning. This gap is particularly prevalent in K-12 computing education, where design is often used to promote student engagement but rarely studied as its own disciplinary phenomenon. Toward the goal of better understanding the nature and role of design in computing education, this article motivates and describes two qualitative, exploratory analyses of how design skills manifest in popular K-12 computing education curricula and activities. We find evidence to suggest two types of design within existing computing education curricula and standards: nondisciplinary problem-space design , which deals with defining software requirements, and disciplinary program-space design , which deals with choosing how best to meet those requirements. We find that these two types of computing design may exist independently, but they often overlap, creating an intriguing intersection of discipline-specific computing design educational activity. Finally, we discuss the practical implications of proceeding with research and educational practice in light of these results, highlighting the need for further exploration into the unique overlap of design and computing education.
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Computational Thinking (CT) through programming attracts increased attention as it is considered an ideal medium for the development of 21st century skills. This intense attention leads to K-12 initiatives around the world and a rapid increase in relevant research studies. However, studies show challenges in CT research and educational practice. In addition, the domain has not been mapped to facilitate comprehensive understanding of the domain challenges and development of CT curricula. The purpose of this study is to develop a conceptual model based on a systematic literature review that maps the CT through programming in K-12 education domain. The proposed Computational Thinking through Programming in K-12 education (CTPK-12) conceptual model emerges from the synthesis of 101 studies and the identification of CT Areas. The proposed model consists of six CT Areas (namely Knowledge Base, Learning Strategies, Assessment, Tools, Factors and Capacity Building) and their relationships. The model could aid domain understanding and serve as a basis for future research studies. In addition, it could support the integration of CT into K-12 educational practices, providing evidence to educational stakeholders and researchers as well as bringing closer research, practice and policy.
Chapter
It has been more than a decade since Jeanette Wing's (2006) influential article about computational thinking (CT) proposed CT to be a “fundamental skill for everyone” (p. 33) and that needs to be added to every child's knowledge and skill set like reading, writing and arithmetic. Wing suggested that CT is a universal skill, and not only for computer scientists. This call resonated with many educators leading to various initiatives by the International Society for Teacher in Education (ISTE) and Computer Science Teachers Association (CSTA) provided the groundwork to integrate CT into the K-12 curriculum. While CT is not a new concept and has been taught in computer science departments for decades, Wing's call created a shift towards educational computing and the need for integrating it into curriculum for all. Since 2006, many scholars have conducted empirical or qualitative research to study the what, how and why of CT. This chapter reviews the most current literature and identifies general research patterns, themes and directions for the future. The purpose of the chapter is to emphasize future research needs by cumulatively looking at what has been done to date in computational thinking research. Consequently, the conclusion and discussion section of the paper presents a research agenda for future.
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The correct sequence of courses in a curriculum can ensure that students develop their knowledge and skills holistically. The challenge level can also be more evenly distributed. Creating these sequences is difficult because curriculum designers must consider multiple potentially conflicting criteria simultaneously. There currently exists a dearth of tools for analyzing the curriculum that incorporates course dependencies as defined by curriculum designers while also considering students' pathways through the curriculum. In this paper, we present Curri, a data-driven curriculum visualization system that scrapes dependencies from our university's published curriculum and leverages student academic data to determine when, on average, students take each course. We evaluate our approach with a case study and two focus groups. This work provides initial evidence that considering both dependencies and students' temporal performance leads to new analyses and insights.
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The number of computer science (CS) courses has been dramatically expanding in U.S. high schools (HS). In comparison with well-established courses in mathematics and science, little is known about how the decisions made by HS CS teachers regarding how and what to teach impact student performance later in introductory college CS courses. Drawing on a large sample of 2,871 introductory college CS students at 115 U.S. institutions who had taken a CS course in HS, we examined the topic coverage and prevailing instructional methods in the HS course and investigated how these experiences influenced student performance in college CS. Controlling for differences in student background, we find two predictors of higher grades in college CS: greater frequency of coding-related activities in HS (programming, debugging, studying algorithms) and lower frequency of “non-coding” computer use (e.g., data analysis, computer security). Interaction models revealed a more complex story. Coding-related activity more heavily benefited students who did not have coding help available at home. In the 28% of college CS courses in which instructors employed innovative pedagogies, students with higher ACT or SAT mathematics scores had a greater advantage than in traditionally taught courses. Finally, in the innovative college courses, students whose HS CS exams had typically included testing on vocabulary did worse than students whose exams had not included such tests.
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This paper presents a case study about the development of Computational Thinking in primary school children (3st to 4th grade) via the teaching of programming abilities with the use of educational robotics, free technology and recyclable, low cost materials. We aimed at raising some hypotheses on whether there is a straight relationship between some cognitive aspects of children aged 8-10 (such as the ability to put events and ideas in sequence, the ability to execute mental operations on the basis of concrete experience, among others) and the ability to execute activities that may be linked to the learning of computer programming. The observed results indicated (from the use of a didactic kit developed for the accomplishment of this study) the possibility to develop the following computational thinking skills: abstract thinking ability, understanding of flows of control, Debugging and systematic error detection, iterative thinking, use of conditional logic and problem decomposition. Regarding the investigations related to cognitive maturity, we found evidence of a correlation between the cognitive characteristics analyzed and the performance of certain tasks related to computer programming, such as the development of purely sequential programs and understanding of processing idea.
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A teacher and students coding together make explicit the unwritten rules of programming.
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Between 2011 and 2013, an updated set of national standards for secondary school computer science education was introduced in New Zealand. This change caused great difficulties for many existing "computing" teachers. After many years of teaching primarily word processing, they were suddenly tasked with teaching programming, even though they were themselves unable to program. In this paper we describe the structure and results of two in-service professional development workshops for these teachers. The workshop structure places emphasis not only on improving a teacher's programming skill, but on exposing him or her to validated pedagogical techniques in programming education. Preliminary results are positive, with most teachers being able to transfer the training into their own classrooms. After the workshops, teachers continue to request support, especially additional classroom-ready materials. We maintain that effective in-service training must include this ongoing support.
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This paper describes the application of the research framework educational reconstruction for investigating the field data management under a CS education perspective. Like the many other innovations in CS, Big Data and the field data management have strong influences on students' daily lives. In contrast, school does not yet sufficiently prepare students to handle the arising challenges. In this paper we will describe how we apply an educational reconstruction approach to prepare the teaching of essential data management competencies. We will summarize the main goals and principles of educational reconstruction and discuss the application of the framework to the topic data management, as well as first outcomes. Just as educational reconstruction is suitable for finding the essential aspects for teaching data management and for designing classes/courses on this topic, it also seems promising for the curricular development of other CS innovations as well.
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Various aspects of computational thinking, which builds on the power and limits of computing processes, whether they are executed by a human or by a machine, are discussed. Computational methods and models are helping to solve problems, design systems, and understand human behavior, by drawing on concepts fundamental to computer science (CS). Computational thinking (CT) is using abstraction and decomposition when attacking a large complex task or designing a large complex systems. CT is the way of thinking in terms of prevention, protection, and recovery from worst-case scenarios through redundancy, damage containment, and error correction. CT is using heuristic reasoning to discover a solution and using massive amount of data to speed up computation. CT is a futuristic vision to guide computer science educators, researchers, and practitioners to change society's image of the computer science field.
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Jeannette Wing’s influential article on computational thinking 6 years ago argued for adding this new competency to every child’s analytical ability as a vital ingredient of science, technology, engineering, and mathematics (STEM) learning. What is computational thinking? Why did this article resonate with so many and serve as a rallying cry for educators, education researchers, and policy makers? How have they interpreted Wing’s definition, and what advances have been made since Wing’s article was published? This article frames the current state of discourse on computational thinking in K–12 education by examining mostly recently published academic literature that uses Wing’s article as a springboard, identifies gaps in research, and articulates priorities for future inquiries.
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The National Science Foundation funded a synthesis study on the status, contributions, and future direction of discipline - based education research (DBER) in physics, biological sciences , geosciences, and chemistry. DBER combines knowledge of teaching and ...
Finding 10,000 teachers
  • J Cuny