Cs 173 Homework For Kids

Homework is a cornerstone of students' academic lives. Using a social cognitive view of achievement beliefs as a theoretical framework, we conducted a qualitative study to examine perceptions of homework among a diverse group of low socioeconomic status (SES) ninth graders who attended low-quality schools. Students participated in individual interviews and their average 9th- and 10th-grade GPAs were collected from school records. Their comments reflected complexity and nuance with respect to their achievement goals. Although higher and lower achievers shared some common views about what constituted enjoyable and disagreeable homework, differences emerged in how they expressed their commitment to their work and their engagement in their learning. Students overall did not have much assigned homework, and reported little or no consequences if they did not complete their assigned tasks. In the face of these low teacher expectations, higher achievers maintained a commitment to learning, and lower achievers were indifferent. Higher achievers were engaged in their assigned tasks and expressed a desire to learn, whereas their lower achieving peers were detached and avoidant. Despite very different beliefs about and approaches to homework, both higher and lower achievers signaled their need for support in their learning. Students need to believe that homework is meaningful and that teachers value it enough to design high-quality assignments and monitor their completion. Lower achieving students need ongoing attention and guidance from their teachers in order to find relevance in and see the value of homework tasks. Teachers can meet this challenge in part by enlisting and supporting family members and peers in the homework process.

Introducing Data Science to School Kids

Authors: Shashank SrikantAspiring Minds, Redwood city, CA, USA
Varun AggarwalAspiring Minds, Redwood city, CA, USA
Published in:

· Proceeding
SIGCSE '17 Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education
Pages 561-566

Seattle, Washington, USA — March 08 - 11, 2017
ACMNew York, NY, USA ©2017
table of contents ISBN: 978-1-4503-4698-6 doi>10.1145/3017680.3017717
2017 Article
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computational thinkingcomputational thinkingdata scienceinteractive learning environmentsk-12 educationk-12 educationpersonalizationsupervised learningsupervised learningvisualization

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