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State-Based Progress Towards Computer Science for All
ACM Inroads, 2016R ecognizing the importance of providing every student with an opportunity to learn computer science, President Obama announced his Computer Science for All initiative in January of 2016 [17].
Renee Fall +3 more
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Preparing STEM Teachers to offer New Mexico Computer Science for All [PDF]
Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, 2017 In this paper, we describe a new teacher professional development program, New Mexico Computer Science for All (NM-CSforAll), that prepares high school science, technology, engineering and math (STEM) teachers to serve as learning coaches / teaching assistants for a dual credit Computer Science (CS) course. The dual credit course for students follows a
Maureen Psaila Dombrowski +2 more
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Good (and Bad) Reasons to Teach All Students Computer Science
, 2017 Recently everyone seems to be arguing that all students should learn computer science and/or learn to program. I agree. I see teaching all students computer science to be essential to counteracting our history and present state of differential access by race, class, and gender to computer science learning and computing-related jobs.
Colleen M. Lewis
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Automated Assessment in Computer Science Education: A State-of-the-Art Review
ACM Transactions on Computing Education, 2022Practical programming competencies are critical to the success in computer science (CS) education and go-to-market of fresh graduates. Acquiring the required level of skills is a long journey of discovery, trial and error, and optimization seeking ...
José Carlos Paiva +2 more
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Exploration of Intersectionality and Computer Science Demographics
ACM Transactions on Computing Education, 2021Although computing occupations have some of the greatest projected growth rates, there remains a deficit of graduates in these fields. The struggle to engage enough students to meet demands is particularly pronounced for groups already underrepresented ...
S. Lunn +3 more
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The race to implement computer science for all
School Science and Mathematics, 2019 Margaret J. Mohr‐Schroeder
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Computer Science Education, 2020
Background and Context Computational thinking (CT) is considered as a valuable literacy for all students, and its inclusion in compulsory schooling could increase the numbers of underrepresented students who pursue computing-related careers.
Wendy Huang, C. Looi
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Background and Context Computational thinking (CT) is considered as a valuable literacy for all students, and its inclusion in compulsory schooling could increase the numbers of underrepresented students who pursue computing-related careers.
Wendy Huang, C. Looi
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Computer Science Education, 2020
Background and Context Overlaying Computer Science (CS) courses on top of inequitable schooling systems will not move us toward “CS for All.” This paper prioritizes the perspectives of minoritized students enrolled in high school CS classrooms across a ...
Jean J. Ryoo +3 more
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Background and Context Overlaying Computer Science (CS) courses on top of inequitable schooling systems will not move us toward “CS for All.” This paper prioritizes the perspectives of minoritized students enrolled in high school CS classrooms across a ...
Jean J. Ryoo +3 more
semanticscholar +1 more source
Computer Science Education, 2020
Background and Context: Though computer science education is marked by a pronounced racial participation gap, there is little research about effective ways that teachers can be supported in creating racially-just and equitable computer science learning ...
J. Goode +4 more
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Background and Context: Though computer science education is marked by a pronounced racial participation gap, there is little research about effective ways that teachers can be supported in creating racially-just and equitable computer science learning ...
J. Goode +4 more
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Equalizing Data Science Curriculum for Computer Science Pupils
European Conference on Modelling and Simulation, 2020Data science is a new interdisciplinary field of research that focuses on extracting value from data. As an interdisciplinary science it integrates knowledge and methods from computer science, mathematics and statistics, and the domain knowledge of the ...
Koby Mike, Tamir Hazan, O. Hazzan
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