Exploring Computer Science

Goode, Joanna; Margolis, Jane

doi:10.1145/1993069.1993076

Cited by 133 publications

(33 citation statements)

References 12 publications

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“…Curriculum design: content, pedagogy and assessments 4.1.1. FACT content The seven-week FACT curriculum (Table 1) was inspired by the 36-week long ECS high school curriculum (Goode et al, 2013) and included topics that were considered by the authors as foundational and engaging for a shorter course for middle school. While CT encompasses several elements (Grover & Pea, 2013), FACT focused largely on algorithmic problem solving in addition to broader notions of computing as a discipline.…”

Section: Methodsmentioning

confidence: 99%

Designing for deeper learning in a blended computer science course for middle school students

Grover

Pea

Cooper

2015

Computer Science Education

326

148

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The focus of this research was to create and test an introductory computer science course for middle school. Titled "Foundations for Advancing Computational Thinking" (FACT), the course aims to prepare and motivate middle school learners for future engagement with algorithmic problem solving. FACT was also piloted as a seven-week course on Stanford's OpenEdX MOOC platform for blended in-class learning. Unique aspects of FACT include balanced pedagogical designs that address the cognitive, interpersonal, and intrapersonal aspects of "deeper learning"; a focus on pedagogical strategies for mediating and assessing for transfer from block-based to text-based programming; curricular materials for remedying misperceptions of computing; and "systems of assessments" (including formative and summative quizzes and tests, directed as well as open-ended programming assignments, and a transfer test) to get a comprehensive picture of students' deeper computational learning. Empirical investigations, accomplished over two iterations of a design-based research effort with students (aged 11-14 years) in a public school, sought to examine student understanding of algorithmic constructs, and how well students transferred this learning from Scratch to text-based languages. Changes in student perceptions of computing as a discipline were measured. Results and mixed-method analyses revealed that students in both studies (1) achieved substantial learning gains in algorithmic thinking skills, (2) were able to transfer their learning from Scratch to a text-based programming context, and (3) achieved significant growth toward a more mature understanding of computing as a discipline. Factor analyses of prior computing experience, multivariate regression analyses, and qualitative analyses of student projects and artifact-based interviews were conducted to better understand the factors affecting learning outcomes. Prior computing experiences (as measured by a pretest) and math ability were found to be strong predictors of learning outcomes.

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Section: Methodsmentioning

confidence: 99%

Designing for deeper learning in a blended computer science course for middle school students

Grover

Pea

Cooper

2015

Computer Science Education

326

148

View full text Add to dashboard Cite

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“…Therefore, if a goal of robotics competitions is to increase girls' participation in computer science as well as other STEM fields, passively providing girls with computing opportunities may not be sufficient. Instead, pedagogy and role distribution on robotics teams must be organized to draw explicit connections between the social practices of girls and the disciplinary practices of computer science; there is some evidence that a focus on inquiry-based instruction may provide these opportunities (Goode & Margolis 2011). Additionally, active recruitment of girls into these activities and of female mentors to serve as role models could be necessary to retain their interest and involvement (Barton et al 2008;Margolis & Fisher 2002).…”

Section: Practical Considerationsmentioning

confidence: 99%

Gender, interest, and prior experience shape opportunities to learn programming in robotics competitions

et al. 2016

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Background: Robotics competitions are increasingly popular and potentially provide an on-ramp to computer science, which is currently highly gender imbalanced. However, within competitive robotics teams, student participation in programming is not universal. This study gathered surveys from over 500 elementary, middle, and high school robotics competition participants to examine (1) whether programming involvement in these competitions is associated with motivation to pursue additional programming experiences and (2) whether opportunities to learn programming varied by gender, age, and competition type. Results: Results showed a significant association of students' programming involvement with their motivation to learn more programming. Interestingly, in the youngest groups/entry-level competitions, girls were heavily involved in programming. Unfortunately, in older/more advanced competitions, girls were generally less involved in programming, even after controlling for prior programming experience. These gendered effects were substantially explained by programming interest. Conclusions: While robotics competition experiences may motivate students to learn more programming, gender gaps in programming involvement persist in these learning environments and appear to widen as students grow older and enter more advanced competitions. Therefore, addressing gender imbalances in programming will likely require greater attention to particular curricular and pedagogical characteristics of robotics competitions that support girls' interest and involvement in programming.

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“…These standards contain five strands: Computational thinking, Collaboration, Computing Practice and Programming, Computers and Communication Devices, and Community, Global and Ethical Impacts. The Exploring CS model curriculum [43] covers six areas: HumanComputer Interaction, Problem Solving, Web Design, Introduction to Programming, Computing and Data Analysis, and Robotics. As K-9 is part of K-12, these guidelines can also be considered part of the discussion on what to teach at K-9 level.…”

Section: Curricula For K-9 Cs Educationmentioning

confidence: 99%

Concepts in K-9 Computer Science Education

Barendsen

Mannila

Demo

et al. 2015

Proceedings of the 2015 ITiCSE on Working Group Reports

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This exploratory study focuses on concepts and their assessment in K-9 computer science (CS) education. We analyzed concepts in local curriculum documents and guidelines, as well as interviewed K-9 teachers in two countries about their teaching and assessment practices. Moreover, we investigated the 'task based assessment' approach of the international Bebras contest by classifying the conceptual content and question structure of Bebras tasks spanning five years. Our results show a variety in breadth and focus in curriculum documents, with the notion of algorithm as a significant common concept. Teachers' practice appears to vary, depending on their respective backgrounds. Informal assessment practices are predominant, especially in the case of younger students. In the Bebras tasks, algorithms and data representation were found to be the main concept categories. The question structure follows specific patterns, but the relative frequencies of the patterns employed in the tasks vary over the years. Our analysis methods appear to be interesting in themselves, and the results of our study give rise to suggestions for follow-up research.

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Exploring Computer Science

Cited by 133 publications

References 12 publications

Designing for deeper learning in a blended computer science course for middle school students

Designing for deeper learning in a blended computer science course for middle school students

Gender, interest, and prior experience shape opportunities to learn programming in robotics competitions

Concepts in K-9 Computer Science Education

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