Culturally Relevant CS Pedagogy - Theory &amp; Practice

Mejias, Marlon; Jean-Pierre, Ketly; Burge, Legand; Washington, Gloria

doi:10.1109/respect.2018.8491699

Cited by 18 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This workshop sought to identify additional ways with with we can present a more realistic view of a career in data science whether in a research or industrial setting. Mentoring plays an important role in helping students from underrepresented groups [18] reach their career potential. These students often are first generation undergraduate and graduate students who are facing new academic and career challenges while putting a brave face on these seemingly insurmountable issues in order to reduce concern from their families [19].…”

Section: Discussionmentioning

confidence: 99%

The Data Science Fire Next Time: Innovative strategies for mentoring in data science

Jackson¹,

Maestre²

2020

Preprint

View full text Add to dashboard Cite

As data mining research and applications continue to expand in to a variety of fields such as medicine, finance, security, etc., the need for talented and diverse individuals is clearly felt. This is particularly the case as Big Data initiatives have taken off in the federal, private and academic sectors, providing a wealth of opportunities, nationally and internationally. The Broadening Participation in Data Mining (BPDM) workshop was created more than 7 years ago with the goal of fostering mentorship, guidance, and connections for minority and underrepresented groups in the data science and machine learning community, while also enriching technical aptitude and exposure for a group of talented students. To date it has impacted the lives of more than 330 underrepresented trainees in data science. We provide a venue to connect talented students with innovative researchers in industry, academia, professional societies, and government. Our mission is to facilitate meaningful, lasting relationships between BPDM participants to ultimately increase diversity in data mining. This most recent workshop took place at Howard University in Washington, DC in February 2019.Here we report on the mentoring strategies that we undertook at the 2019 BPDM and how those were received.

show abstract

Section: Discussionmentioning

confidence: 99%

The Data Science Fire Next Time: Innovative strategies for mentoring in data science

Jackson¹,

Maestre²

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…That is, to be truly accessible, learning opportunities must also honor and support young people's intellectual, linguistic, and social repertoires of practice (Gutiérrez & Rogoff, 2003;Paris & Alim, 2014). For example, a group of researchers in CS education at Howard University found success in teaching an introduction to programming and graph theory course using the Washington DC Metro System map as a way to build on learners' existing funds of knowledge (Mejias et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

Near Peer Pedagogies for Culturally Sustaining Computer Science and Mathematics

Freeman,

Tucker-Raymond,

Gutierrez

2023

JCSI

View full text Add to dashboard Cite

In this study, College STEM Literacy Workers act as co-teachers in 9th and 10th grade classrooms alongside mathematics teachers as they both learn to integrate a 30-hour integrated computer science/mathematics curriculum. As part of the curriculum for educator learning, we adapted the Algebra Project’s “Model of Excellence” for culturally relevant-sustaining pedagogies. We used the framework to explore how teachers understand College STEM Literacy Workers’ contributions in the model as well as College STEM Literacy Workers’ own experiences in the classroom. We found that while teachers and College STEM Literacy Workers did not individually instantiate the model of excellence, they were able to achieve its constituent components between them. We explore differences between teachers and College STEM Literacy Workers and the ways in which they worked together. We end with implications for a new model of excellence.

show abstract

Empowering Diverse Learners: Embracing Culturally Relevant Pedagogy (CRP) in Engineering, Higher Education, and K-12 Settings

Wahed,

Pitterson

2024

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Culturally Relevant CS Pedagogy - Theory & Practice

Cited by 18 publications

References 19 publications

The Data Science Fire Next Time: Innovative strategies for mentoring in data science

The Data Science Fire Next Time: Innovative strategies for mentoring in data science

Near Peer Pedagogies for Culturally Sustaining Computer Science and Mathematics

Empowering Diverse Learners: Embracing Culturally Relevant Pedagogy (CRP) in Engineering, Higher Education, and K-12 Settings

Contact Info

Product

Resources

About