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ENACTing change: Partnering with Milwaukee Public Schools to encourage computational thinking

Midwest | May 05, 2022

Student writing on whiteboard with marker

Equipping students with strong computational thinking or problem-solving techniques is not only essential for preparing them to address challenges in today’s high-tech world, but opens doors to numerous high-paying, in-demand careers. In Milwaukee Public Schools (MPS), which educates the largest number of Black students in Wisconsin, district leaders are working to build teachers’ capacity to provide quality computational thinking instruction to all students across grades K–12.1 At the middle school level, math teachers are eager to integrate the core practices of computational thinking into their instruction in ways that allow the time needed to promote deep math learning in students.

To support middle school teachers in these efforts, MPS and REL Midwest have established the ENgagement and Achievement through Computational Thinking (ENACT) partnership. This partnership will develop, test, and refine an approach for integrating computational thinking into the MPS grade 6 mathematics curriculum using culturally responsive teaching practices. Through these activities, the ENACT partnership seeks to provide grade 6 students in the district with opportunities to improve their achievement in math.2

The core practices of computational thinking

Computational thinking’s five core practices (Table 1) provide approaches for developing computational solutions to problems. By integrating these practices into instruction, teachers can help shift learning in math from memorizing procedures to understanding concepts. Research shows that student proficiency in computational thinking is associated with improvements in spatial ability, reasoning, and problem solving—all skills that underlie general academic achievement3 and performance on assessments in mathematics.4 Further, research indicates that computational thinking practices are positively related to student performance on math assessments5 when teachers also integrate culturally responsive instructional practices, such as those that support students’ interests,6 sense of identity,7 belonging,8 and beliefs about their abilities.9

Table 1. Core Practices of Computational Thinking

Core Practice Descriptions

Pattern Recognition

Looking for ways that problems or situations are similar or different so as to help develop strategies and solutions

Abstraction

Identifying and representing the important information in a problem or situation

Decomposition

Breaking a complex problem into smaller parts that are easier to address

Debugging

Finding and fixing mistakes to improve one’s work

Algorithms

Developing and using systematic, step-by-step approaches to problems

Sources: Barr & Stephenson, 2011; Rich & Yadav, 2020; Dong et al., 2019; Weintrop et al., 2015.

ENACTing culturally responsive computational thinking 

REL Midwest will work with MPS partners to develop training and coaching materials for the ENACT approach, including a video series that models how teachers can implement computational thinking concepts in a culturally responsive way. The ENACT resources will guide teachers in implementing the five core computational thinking practices alongside six culturally responsive teaching practices associated with improvements in student outcomes: including affirming cultural identity, creating a sense of belonging, providing feedback for growth, assigning meaningful work, listening to students’ voices, and demonstrating a sense of caring.10

Teachers participating in the ENACT professional development series will work shoulder-to-shoulder with ENACT coaches to implement lessons like the ones presented in the video series and adjust their practices to better fit their individual classroom and student contexts. Through this process, MPS grade 6 teachers will help test the ENACT video series and related materials and provide feedback that REL Midwest researchers can use to refine the approach for broader use in districts beyond Milwaukee.

I hope that I will be able to learn new and engaging ways to support inquiry within my 6th grade math classroom. My goal
is to gain new skills in planning, reflecting, and revising lessons that I will be able to use and take with me throughout
my teaching career.

—Elizabeth Killian, Roosevelt Middle School

Looking ahead

The ENACT partnership’s work will proceed in phases over the next 5 years. As findings become available, REL Midwest will collaborate with ENACT partners to share lessons learned and key takeaways with stakeholders and the public, including the final set of resources. By supporting grade 6 MPS teachers’ use of computational thinking concepts and culturally responsive practices, ENACT seeks to strengthen the ability of middle school math teachers to increase student math achievement, engagement, and self-efficacy. This work complements other REL Midwest projects that aim to inform policy and practice to improve student outcomes.

References

1 The number of Wisconsin students taking Advanced Placement (AP) Computer Science A or Computer Science Principles has increased in recent years(College Board, n.d.). However, opportunity gaps in AP Computer Science experiences persist across students with different racial/ethnic characteristics. Less than 2 percent of Wisconsin students who took the AP Computer Science exam during the 2017/18 school year identified as Black. College Board. (n.d.). Understand the class of 2018 results. https://reports.collegeboard.org/archive/2018/ap-program-results

2 Century, J., Ferris, K. A., & Zuo, H. (2020). Finding time for computer science in the elementary school day: A quasi-experimental study of a transdisciplinary problem-based learning approach. International Journal of STEM Education, 7(1), Article 20. https://eric.ed.gov/?id=EJ1255304; Serrano Corkin, D. M., Ekmekci, A., & Fisher, A. (2020). Integrating culture, art, geometry, and coding to enhance computer science motivation among underrepresented minoritized high school students. Urban Review, 52(5), 950–969.; Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M. (2020). Computational thinking and mathematics using Scratch: An experiment with sixth-grade students. Interactive Learning Environments, 28(3), 316–327.

3 Lei, H., Ming Chiu, M., Li, F., Wang, X., & Geng, Y. (2020). Computational thinking and academic achievement: A meta-analysis among students. Children and Youth Services Review, 118. https://doi.org/10.1016/j.childyouth.2020.105439

4 Rich, K. M., & Yadav, A. (2020). Applying levels of abstraction to mathematics word problems. TechTrends, 64(3), 395–403.; Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M. (2020). Computational thinking and mathematics using Scratch: An experiment with sixth-grade students. Interactive Learning Environments, 28(3), 316–327.

5 Rodríguez-Martínez et al., 2020.

6 Cheryan, S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in Psychology, 6(49). https://doi.org/10.3389/fpsyg.2015.00049

7 Kong, S. C., & Wang, Y. Q. (2020). Formation of computational identity through computational thinking perspectives development in programming learning: A mediation analysis among primary school students. Computers in Human Behavior, 106(106230). https://doi.org/10.1016/j.chb.2019.106230

8 Master, A., Cheryan, A., & Meltzoff, A. N. (2016). Computing whether she belongs: Stereotypes undermine girls’ interest and sense of belonging in computer science. Journal of Educational Psychology, 108(3), 424–437. https://psycnet.apa.org/doi/10.1037/edu0000061

9 Cheryan et al.. 2015; Whitley, B. E., Jr. (1997). Gender differences in computer-related attitudes and behavior: A meta-analysis. Computers in Human Behavior, 13(1), 1–22.

10 Gripshover, S., & Paunesku, D. (2019). How can schools support academic success while fostering healthy social and emotional development? PERTS, Stanford University. https://perts.net/static/documents/Conditions_for_Learning-January_2020.pdf

Author(s)

Laura Checovich

Laura Checovich

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