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1. Micro:bit vs. Python: Students’ perceptions and attitudes toward computing

   Veng, S; Mouza, C; Pollock, L (March 2024, Proceedings of Society for Information Technology & Teacher Education International Conference)

   Cohen, J; Solano, G (Ed.)

   There has been a growing interest in teaching computer science (CS) concepts to students at a younger age. Increasingly, block-based programming has been used in place of traditional text-based programming languages, like Python, in K-12 education. However, little empirical research has been conducted to compare the combination of the former and physical computing with the latter. This study aimed to address this gap by comparing the attitudes and perceptions of elementary school students in the two approaches in a six-week afterschool program. The findings from the experiment indicated that students’ attitudes and perceptions toward computing were more positive when using physical computing. These findings suggest potential pedagogical implications and future research directions. 

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2. Teaching A Computer To Sing (TACTS): Integrating Computing and Music in a Middle School, After‐School Program

   Heines, Jesse M.; Walzer, Daniel A. (June 2018, Journal of computing sciences in colleges)

   This paper reports on an after‐school program that introduced middle school students to computing through music. The program ran for two years, from October 2015 through April 2017. It involved singing, encoding music with ABC notation, and programming music with Pencil Code. We describe the program’s goals and the activities students pursued, as well as suggestions for improvement. While rigorous evaluation of such a program is difficult, we present survey and focus group results that show that students’ attitudes toward the program were positive and that they did learn some programming. 

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3. Promoting and Supporting Computer Science Among Middle School Girls of Color: Initial Findings from BRIGHT-CS

   https://doi.org/10.1145/3328778.3366855  

   Madrigal, Veronica; Yamaguchi, Ryoko; Hall, Adam C.; Burge, Jamika D. (February 2020, SIGCSE '20: Proceedings of the 51st ACM Technical Symposium on Computer Science Education)

   BRIGHT-CS (Building Student Retention through Individuated Guided coHort Training in Computer Science) is a research and development project that 1) creates a computer science learning ecosystem for middle school Black girls and other girls of color and 2) researches the merits of the ecosystem in supporting persistence in CS to determine best practices for broadening participation to other marginalized student groups in computing. First, this paper describes the BRIGHT-CS program, from the structural, instructional, and curricular designs of the program to partnerships with local and community organizations that make up the ecosystem. Second, it presents the initial findings of research on the program and its impacts on student outcomes such as social-emotional attributes associated with persistence. The study employs a multi-method descriptive design. Data includes student surveys, interviews (from students, parents, instructors, teachers, and mentors), artifact reviews, and student observations. The study includes 46 students across four middle schools in two states. At the start of the program, 37% of the students reported being very interested in CS, and 72% reported being very confident in learning CS. This is much higher than a national benchmark of students. After four months of program implementation, the qualitative results show a more nuanced picture of the value of a learning ecosystem. First, the ecosystem offers implicit messaging about equity and success. Second, the ecosystem offers explicit messaging about personal challenges and improvement. Third, following the implicit and explicit messaging to students, students went from naïve confidence to authentic self-efficacy in CS. 

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4. A Multiyear Investigation of Student Computational Thinking Concepts, Practices, and Perspectives in an After-School Computing Program

   https://doi.org/10.1177/0735633120905605  

   Mouza, Chrystalla; Pan, Yi-Cheng; Yang, Hui; Pollock, Lori (February 2020, Journal of Educational Computing Research)

   In this work, we examine whether repeated participation in an after-school computing program influenced student learning of computational thinking concepts, practices, and perspectives. We also examine gender differences in learning outcomes. The program was developed through a school–university partnership. Data were collected from 138 students over a 2.5-year period. Data sources included pre–post content assessments of computational concepts related to programming in addition to computational artifacts and interviews with a purposeful sample of 12 participants. Quantitative data were analyzed using statistical methods to identify gains in pre- and post-learning of computational thinking concepts and examine potential gender differences. Interview data were analyzed qualitatively. Results indicated that students made significant gains in their learning of computational thinking concepts and that gains persisted over time. Results also revealed differences in learning of computational thinking concepts among boys and girls both at the beginning and end of the program. Finally, results from student interviews provided insights into the development of computational thinking practices and perspectives over time. Results have implications for the design of after-school computing programs that help broaden participation in computing. 

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5. Uncovering Middle School CS Students’ Understanding of Variables and Control Structures: A Cognitive Think-Aloud Approach

   https://doi.org/10.22318/icls2023.110257  

   Yang, Hui; Basu, Satabdi; Rutstein, Daisy; Rachmatullah, Arif; Tate, Carol; Ortiz, Christopher; Rulifson, Eliese (October 2023, International Society of the Learning Sciences)

   This poster presents findings on middle school students’ understanding of core Computer Science (CS) concepts, such as variables and control structures, using cognitive think-aloud interviews with eight students. Each student worked on 16-22 formative assessment tasks designed to assess understanding on the ‘Algorithms and Programming’ middle school CS standards. Our study describes students’ interpretations of the CS concepts and discusses potential factors influencing student interpretations. Significance and next steps are described. 

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