Category Archives: Computer Science

Engaging Educators in Emerging Technology Research

December 4, 2024AI in Education, Computer Science, Educator professional learning, EducatorCIRCLS, Teachers & ResearchersJudi Fusco

Image by Tung Lam from Pixabay

by Cassandra Kelley, Sarina Saran, Deniz Sonmez Unal, and Erin Walker

This blog post discusses the outcomes of an Educator CIRCLS workshop that disseminated computer science education research findings to practitioners while prompting broader discussions of AI in classrooms

This past summer and fall of 2024, Educator CIRCLS hosted a series of webinars, workshops, and convenings between researchers and practitioners focused on artificial intelligence (AI) literacy. Specifically, they were designed to engage participants in reflective conversations about ethics, equity, and other problems or possibilities of practice concerning the integration of AI (especially genAI) in PreK-12 education.

As part of this series, our team from the University of Pittsburgh piloted a novel strategy for research dissemination, in which we developed supplemental curricular resources or guided activities and shared them with educators in a workshop format. The goals behind these activities were twofold:

To facilitate discussion among educators about current research on the integration of emerging technologies that incorporate AI (e.g., robots and intelligent tutoring systems) and how they might impact the future of learning in education settings, and

To provide a mechanism for educators to think critically about ways to introduce elements of AI literacy to students via real world exercises that can simulate the work that researchers are doing (see Translating Research on Emerging Technologies for Educators for further background context about the design of this workshop).

During the planning stage of the workshop, we felt it was pertinent to get a better understanding of PreK-12 teachers’ experiences with professional learning for computer science (CS) education. We wanted to speak directly with them about the impact of these experiences on their practice and seek their recommendations for how these professional development programs are designed.

We interviewed 20 educators from 16 states, who taught across different grade levels and/or content areas. Most interviewees felt a disconnect with research dissemination as a form of professional learning and expressed their desire to better understand how emerging technologies connect with research-based practices and learning theories. They discussed how previous workshops they have attended either focus directly on the technology tools or on a mandated “turnkey curriculum” based on rote memorization and knowledge transfer (e.g., Advanced Placement CS course materials). Teachers expressed how they appreciated receiving curricular resources because such resources help them to stay current in this ever-evolving field. They would like to see less “direct instruction” lessons and more real-world approaches with project-based or problem-based learning (PBL) that promote inquiry—similar to what is expected in the industry. They also emphasized the need for further collaborative opportunities to ideate on promoting digital/AI literacy through their instruction.

Following our conversations with teachers, we intentionally designed a workshop with guided activities, based on research projects on emerging technologies, that could expose practitioners to existing literature and findings while potentially seeding new ideas for curricula. Our workshop design incorporated the following structure: (1) outline the theoretical framework and CS concepts, (2) have participants experience different roles (e.g., student, educator, and researcher) within inquiry-based activities, (3) share project research findings, (4) discuss implications for practice and ways to address AI literacy, and (5) reflect on the overall format of the workshop and considering how to improve the design of future workshops.

We featured two research projects:

Project 1: The design of intelligent robots with social behaviors and their potential roles in learning settings

Project 2: Utilizing neuroadaptive learning technologies to assess a learners’ cognitive state with brain imaging

Our first session on teachable robots presented a research project that examined middle school students’ interactions with Nao robots in mathematics instruction. Participants were asked to think about the design and implementation challenges in building a robotic dialogue system for learning from the perspective of a student, educator, and a researcher. They explored CS concepts related to Natural Language Processing (NLP) by: (1) determining keywords used in solving a math problem, (2) reviewing sample dialogue scripts and Artificial Intelligence Mark-up Language (AIML) that researchers used to program the Nao robot, and (3) interacting with prototype simulations created in Pandorabots that represented social and nonsocial versions of a chatbot. We also shared further extensions that could potentially be remixed or adapted for use with students, such as revising the dialogue by adding more social elements, writing a new script for solving a different math problem in AIML, developing a chatbot to test the code, or experimenting with a program such as Scratch to create a dialogue between two sprites.

Our second session on neuroimaging and educational data-mining presented a research project that examined how students process information while interacting with intelligent tutoring systems. A major component of this study focused on the analysis of data collected by these systems to uncover patterns or trends that can inform and potentially improve teaching and learning practices. Additionally, neuroimaging brain data was collected as a proof of concept to explore how it might be analyzed to better understand how cognition, attention, and emotion affect learning (for further background on how this equipment works, see Neuroscience in Education). Similar to the first workshop, we presented guided activities to help participants think about the design of intelligent tutoring systems and the types of data collected ; participants created their own data visualizations from sample datasets for analysis using the free educational software, Common Online Data Analysis Platform (CODAP) and categorized example brain activation images based on the corresponding levels of task difficulty. Further extension activities were shared, such as outlining specific actions that an intelligent tutoring system might take to provide feedback (e.g., hints, prompting questions, or praise) in response to student behavior and debunking “neuro-myths” in education.

At the conclusion of each workshop, we asked educators their thoughts about the potential benefits and challenges of integrating these emerging technologies in PreK-12 classrooms and what they would like future research to explore. Our goal was to hear practitioner voices and gather input for researchers and developers to consider. This led to a focused discussion on the need to promote AI literacy in education, especially to address ethics and transparency.

Key takeaways from the experience are:

Teachers appreciate the opportunity to learn more about innovative research projects, but they especially like the idea of being in dialogue with researchers and potentially playing a role in the work that’s being done. Many volunteered to pilot future projects exploring the implementation of curricula and/or emerging technologies with their students if invited.

Teachers expressed that the content in our guided activities, while rigorous, enabled them to be more reflective. They were engaged with the hands-on simulations of the research and discussed how “active learning helped to promote deeper thinking.” As one participant mentioned, the activities allowed her to “think outside of the normal pedagogy box.”

Teachers had mixed feelings on the relevance of the workshop content and how to bring it into their schools or classrooms. Some thought it would be challenging to implement the activities with students due to external factors and other curricular mandates. As one participant stated, “one tension with cutting-edge research is that it’s difficult to be practical in the moment. I think you’re on the right track with scaling down the technology or bringing the insights to the classroom level…this [workshop] is way more effective than most formats, but I think you would have a difficult time getting educators to opt in.” Meanwhile another participant said, “in both workshops, the concepts and practice of the teachable bot and neuroimaging was beyond the ‘here and now’ of teaching and learning, but the examination of how our current concepts of pedagogy may change as we catch up to the technology.” Additionally, several teachers discussed how the workshop offered new ways for them to think about bringing in real-world data and student-led projects to promote further inquiry and AI literacy.

Teachers valued the opportunity to collaborate with other educators and researchers. They liked exploring different lenses (e.g., student, teacher, and researcher) while engaging in reflective discussions about the impact of research on their practice. One teacher highlighted how it felt like a “safe space to troubleshoot uses of AI and educational data mining” and another expressed appreciation for “garnering others’ experiences to get further ideas for their own classroom.”

Based on overall positive feedback from our teacher participants, we believe this research dissemination workshop model is worth exploring with other projects, especially since educators felt they were able to take something meaningful away from the experience. As one participant stated, “I feel very fortunate to be involved in this work. I’m very happy that your team is working to push the boundaries of how we learn and teach.” This gives us hope that researchers will consider the importance of collaborating and co-designing with educators. Additionally, this work validates the need for further mediation between research and practice, which potentially can include creating new roles for “knowledge brokers” (Levin, 2013) to promote further dialogue across these boundaries in order to truly make a broader impact.

Thank you to Sarah Hampton and Dr. Judi Fusco for their thinking and feedback on this post.

References:

Levin, B. (2013, February). To know is not enough: Research knowledge and its use. Review of education, 1(1), 2-31. DOI: 10.1002/rev3.3001

About the Authors

Cassandra Kelley, Ed.D. has over fifteen years of experience in K-12 and teacher education. She earned her doctorate degree in Learning Technologies from Pepperdine University and is passionate about exploring new tools that can improve teaching and learning. She currently serves as a Broader Impacts Project Coordinator at the University of Pittsburgh and supports CIRCLS with Expertise Exchanges in the AI CIRCLS and Educator CIRCLS sub communities. Cassandra also teaches graduate courses for National University in the Master of Science in Designing Instructional and Educational Technology (MSDIET) Program.

Sarina Saran is a third-year undergraduate student at the University of Pittsburgh pursuing a B.S. in Computer Science and a B.A. in Media and Professional Communications. She is curious about the intersection of technology and communication, and she has been able to develop a greater understanding of the challenges in this area as an Undergraduate Research Assistant in the Office of Broader Impacts.

Deniz Sonmez Unal is a Ph.D. candidate in Intelligent Systems at the University of Pittsburgh. Her research focuses on modeling student cognitive states using multimodal data, including interaction logs, verbal protocol data, and neural signals to enhance the diagnostic capabilities of intelligent tutoring systems.

Erin Walker, Ph.D. is a co-PI of CIRCLS and a tenured Associate Professor at the University of Pittsburgh, with joint appointments in Computer Science and the Learning Research and Development Center. She uses interdisciplinary methods to improve the design and implementation of educational technology, and then to understand when and why it is effective. Her current focus is to examine how artificial intelligence techniques can be applied to support social human- human and human agent learning interactions.

Translating Research on Emerging Technologies for Educators

November 24, 2024AI in Education, Computer Science, Educator professional learning, EducatorCIRCLS, Teachers & ResearchersJudi Fusco

Return to Educator CIRCLS.

Image by mcmurryjulie from Pixabay

by Cassandra Kelley

This blog post discusses the development of an Educator CIRCLS workshop aimed to “translate” or disseminate computer science education research findings to practitioners while promoting AI literacy.

Have you ever played the telephone game, where a sentence is whispered into someone’s ear and passed from person to person, until the final person reveals the message aloud to see how closely it aligns with what was originally said? I am frequently reminded of this childhood game in my role as the Broader Impacts Project Coordinator at the University of Pittsburgh and CIRCLS, where I think about how we can “translate” research into practice for practitioners; however, the game has become much more challenging due to the technical terminology, academic jargon (e.g., research methodologies), and other contextual phrases that are often included within the message being communicated. Moreover, all of the players have individual “language barriers” (e.g., prior knowledge, experience, expertise, etc.) that add another layer of difficulty to ensure the mediated message is comprehensive for all.

My broader impacts position, inspired by the National Science Foundation (NSF) merit review criteria, was created as an avenue for broadly disseminating research on emerging technologies for teaching and learning—similar to programs such as Research Practice Partnerships (RPP) or Research Experiences for Teachers (RET). I was drawn to this opportunity because I feel it is critical not only for educators to learn about and understand education research, but also for researchers to consider the direct impact of their work on practice. I firmly believe in the importance of bridging the gap that currently exists between research and practice by promoting partnerships among all stakeholders, which can include further engagement in participatory research and involvement in co-design models.

As a former PreK-12 educator and higher education faculty member supporting pre-service teachers, my initial concern about this translation process was thinking about how students and teachers will benefit. From my own experience working in school systems, I have observed an institutional culture where research and policy are “thrown” at teachers through mandates and other recommendations. Educators’ voices are often missing from the conversation and there is not an immediate focus on how to best support their practices, which truly should center on the needs of students. I have also witnessed researchers temporarily engaging with educators for the purpose of conducting a study and then disappearing, which I personally know can feel like a one-sided transaction.

These factors led me to consider novel strategies for research dissemination that could potentially build stronger connections between researchers and practitioners. Specifically, I wanted to explore the development of supplemental curricular resources to be shared with teachers during a workshop so they could have opportunities to: (1) interact with computer science (CS) education concepts and understand their relationship within research findings, (2) experience the role of a learner and researcher, (3) engage in discussion with other educators and researchers about the impact of specific research projects on practice—especially with regard to the integration of emerging technologies, and ultimately to (4) bring elements of their professional learning back into the classroom via guided activities that could be adapted for implementation with students.

It is important to note that these goals were shaped through many discussions with practitioners, especially after having the opportunity to speak directly with 20 educators about their experiences as participants in professional development programs for CS education. I sought their recommendations for how we might design and structure a workshop to disseminate research findings via our supplemental curricular resources (see Engaging Educators in Emerging Technology Research for further details about the facilitation of this workshop). Throughout these reflective conversations, it was frequently mentioned how most programs tend to be “technocentric” and focus more on “new shiny technology tools” rather than pedagogy for classroom integration or research-based practices and learning theories. Educators advocated for further rigor and inquiry-based activities that immerse them into the research literature, paired with opportunities for collaboration and the exchange of ideas or curricular resources; each of these elements would be intentionally incorporated into our workshop design.

Additionally, I connected with members of interdisciplinary research teams to better understand their different areas of expertise and the methodologies used across projects. I had to consider the application of CS terminology and concepts within each project (many of which were new to me) and pinpoint the key areas to focus on in the translation. Fortunately, I was introduced to a new undergraduate student in the lab who was double majoring in both CS and communication. She was eager to help and became a translator for me when I wore my “learner hat,” similar to how a teacher’s assistant or tutor might provide direct instruction to dive deeper into the content. Likewise, I would then put on my “teacher hat” and explain pedagogical concepts (e.g., scaffolding, asking different levels of questions, Universal Design for Learning- UDL strategies, etc.) or learning theories (e.g., constructivism, sociocultural learning, project-based learning, etc.) while we discussed how we could take research findings and use them to develop supplemental curricula or guided activities for dissemination to educators.

A final consideration in the development of these guided activities was how to simulate the research procedures in an immersive way without the technology equipment. This was necessary because we wanted to acknowledge potential constraints of implementation in schools, such as access issues and the need for further technical support or training—not to mention how expensive these emerging technologies are. Therefore, we engaged in further conversations with the research teams about how we might develop user-friendly prototypes of simulations that educators could interact with on their own devices. Our discussions reminded us that there may be further barriers to research dissemination in the traditional schooling environment including challenges with existing curricula requirements and/or scheduling constraints. For this reason, we decided it might make more sense to frame our activities as supplemental or enrichment materials that can be adapted/remixed across a variety of settings (e.g., after school programs or summer camps).

In summary, these convenings with researchers and practitioners across what Wenger-Trayner and colleagues (2014) refer to as the “boundaries in landscapes of practice” helped us consider the institutional culture bounding each landscape. We found it extremely valuable learning from multiple perspectives and using these insights to help us identify existing boundaries and ways to collectively navigate them.

Key takeaways from the experience are:

Acknowledge the systemic barriers with regard to education policy and practices in different community settings.

Engage in learning partnerships by collaboratively negotiating and exploring the existing boundaries. This includes actively listening to all voices (e.g., researchers and practitioners) from different landscapes (e.g., PreK-12 education, higher education, and industry) to create a two-way dialogue of mutual reflection.

Focus less on the technology and more on the diffusion of innovative ideas as well as the AI literacy needed by ALL stakeholders for advancement of these ideas.

Develop immersive guided activities that promote further conversations about AI literacy while being grounded in research and learning theories. Be sure to clearly communicate these connections when translating back-and-forth and offer opportunities for reflective discussion.

Seek feedback at every stage of the iterative process and prioritize the community partnerships across the landscapes of practice above all.

Remember that the ultimate shared goal or vision is to positively impact the future of learning for students.

Since I personally identify as both a researcher and practitioner, I have learned firsthand the importance of negotiating my own experiences to build a bridge between my understanding of the teaching practice and students’ needs, while also thinking critically about advancing the field of education research. In order to bring these landscapes together, researchers must consider ways to make their work more accessible so they can get the necessary buy-in from teachers that will propel institutional change and innovation in the future of schooling and education. Likewise, educators need to keep seeking opportunities to stay abreast of current research findings, especially to help lead this exploration of new pedagogical practices or emerging technologies that can support teaching and learning. One avenue to achieve this is establishing sustained partnerships between researchers and practitioners through co-design or participatory research. Moreover, the incorporation of “intermediaries” or “knowledge brokers,” which Levin (2013) defines as “people or organizations that translate or transmit research,” similar to my position as a Broader Impacts Project Coordinator, can “play a critical role in the process of diffusing ideas and practices in education” (p. 21). It is my hope that researchers will take into account how emerging scholars, such as school administrators, academic coaches, a subgroup of PreK-12 teachers, post-doctoral students, or graduate students, might be leveraged to help spearhead this essential translation of research into practice.

Thank you to Sarina Saran, Deniz Sonmez Unal, Sarah Hampton, Dr. Erin Walker, and Dr. Judi Fusco for their thinking and feedback on this post.

References:

Levin, B. (2013, February). To know is not enough: Research knowledge and its use. Review of education, 1(1), 2-31. DOI: 10.1002/rev3.3001

Wenger-Trayner, E., Fenton-O’Creevy, M., Hutchinson, S., Kubiak, C., & Wenger-Trayner, B. (Eds.). (2014). Learning in landscapes of practice: Boundaries, identity, and knowledgeability in practice-based learning. Routledge.

About the Author

Cassandra Kelley, Ed.D. has over fifteen years of experience in PreK-12 and teacher education. She earned her doctorate degree in Learning Technologies from Pepperdine University and is passionate about exploring new tools that can improve teaching and learning. She currently serves as a Broader Impacts Project Coordinator at the University of Pittsburgh and supports CIRCLS with Expertise Exchanges in the AI CIRCLS and Educator CIRCLS sub communities. Cassandra also teaches graduate courses for National University in the Master of Science in Designing Instructional and Educational Technology (MSDIET) Program.

Supporting Computationally Rich Communication During Remote Learning: Lessons Learned

January 14, 2022Computer Science, EducatorCIRCLS, Engineering, Guest Author, STEMPati Ruiz

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By Colin Hennessy Elliott & the SchoolWide Labs Team

This post was written by a member of the SchoolWide Labs research team, about their experience during the pandemic and what they learned from middle school science and STEM teachers as part of a larger Research-Practice Partnership between a university and a large school district in the United States. The post was reviewed by practicing Educator CIRCLS members. The purpose of the blog is to help open the door between the worlds of research and practice a bit wider so that we can see the differing perspectives and start a dialogue. We are always looking for more practitioners and researchers who want to join us in this work.

The COVID-19 pandemic pushed many school communities online last school year in the US. Teachers were charged with accommodating so many needs while holding levels of care and compassion for students and their families. As a multi-year research project aimed at supporting teachers in integrating computational thinking in science and STEM learning, we worked with renewed senses of compassion, creativity, and struggle. We witnessed how students and teachers innovatively developed computationally rich communication using the technologies from our project while teaching and learning remotely. Below we share a few moments from the 2020-21 school year that have helped us learn what it takes to engage middle school students in computational practices (i.e. collaborating on programming a physical system, interpreting data from a sensor) that are personally relevant and community-based. These moments offer lessons on how collaboration and communication are key to learning, regardless of whether the learning takes place in person or remotely.

Who we are

The SchoolWide Labs research team, housed at the University of Colorado Boulder with collaborators at Utah State University, has partnered with Denver Public Schools (DPS) for over five years. We work with middle school science and STEM teachers to co-develop models for teacher learning that support the integration of computational thinking into science and STEM classrooms. The team selected, assembled, and refined a programmable sensor technology with input from teachers on what would be feasible in their classrooms and in collaboration with a local electronics retailer (SparkFun Electronics). This collaboration focused particularly on programmable sensors because they offer opportunities for students to develop deeper relationships with scientific data, as producers rather than just data collectors.¹ This aligns with modern scientific practice where scientists often tinker with computational tools to produce the data they need to answer specific questions.

The Data Sensor Hub (DaSH) is a low cost physical computing system used in the curriculum and professional learning workshops developed by the SchoolWide Labs team. Ensuring the DaSH would be low cost was a priority of the team as an issue of access and equity. The DaSH consists of the BBC Micro:bit, a connection expander called the gator:bit, and an array of sensors that can be attached to the micro:bit and gator:bit with alligator clips (see Figure 1). Students can easily assemble the DaSH themselves to experience the physical connections and hard wiring. Students and teachers can write programs for the DaSH using MakeCode, a block-based programming environment that can be accessed via a web browser, making it easy to use with various computer setups. For students with more programming experience, MakeCode has the option to use python or javascript to program the micro:bits.

Figure 1.The Data Sensor Hub (DaSH). The picture on the left depicts the components of the DaSH used with the Sensor Immersion Unit including the micro:bit, Gator:bit and three sensors (top to bottom: soil moisture sensor, microphone sensor, environmental sensor). The picture on the right shows a teacher and student interacting with the DaSH set up just for the microphone sensor.

Before the COVID-19 pandemic, our research team co-designed curricular units with teachers interested in using the DaSH to engage middle school students in scientific inquiry. Currently there are four units available on our website, three that use the DaSH and one that uses a 3-D printer. The Sensor Immersion Unit – the only unit teachers implemented remotely in the 2020-21 school year – has students explore the DaSH in use via a classroom data display, learn basic programming, and create their own displays that collect environmental data (sound, temperature, carbon dioxide levels, or soil moisture) to address a question of their choice. For example, one group of students decided to investigate climate change by measuring atmospheric carbon dioxide levels in their neighborhoods and exploring the impact of plants and trees. The goal is for students to develop ownership of the DaSH as a data collection tool by wiring the hardware and programming the software. In the process, they engage in computational thinking and computationally rich communication when they discuss their use of the DaSH with peers and the teacher.

In the 2020-21 school year most middle schools in Denver Public Schools were remote. Several STEM teachers, with more curricular flexibility, decided to provide DaSHs to students who wanted the responsibility of having them for a period of time. Having the DaSHs in students’ homes offered opportunities to make the barriers between home and school less visible, as students conducted place-based investigations and emergently took on the role of data producers. For example, some students shared temperature data and carbon dioxide levels in and around their homes with the class. In these moments, students emergently took on the role of data producers. Below, we share two examples from observing student and teacher interactions in virtual mediums which helped our research team learn about what is possible using the DaSH. We also developed new supports to help teachers facilitate extended student collaboration and communication when using the DaSH.

Lesson Learned 1: Increasing student collaboration in virtual settings

One middle school STEM teacher, Lauren (a pseudonym), had the opportunity to teach different cohorts of eighth graders in the first two quarters of the 2020-21 school year. A new SchoolWide Labs participant, she was enthusiastic about implementing the Sensor Immersion Unit with her first cohort in the first quarter. She navigated the logistical challenges of getting DaSHs to over half her students along with the pedagogical challenges of adapting the curriculum to a remote setting. After her first implementation, she shared that she was disappointed that her students rarely collaborated or shared their thinking with each other when they were online. We heard from other teachers that they had similar struggles. Before Lauren’s second implementation, we facilitated several professional learning sessions with the aim of supporting teachers to elicit more student collaboration in remote settings. Through our work together, we identified the importance of establishing collaboration norms for students, offering continued opportunities to meet in small groups virtually, and modeling how to make their work visible to each other. In Lauren’s second implementation with new students during next quarter, she intentionally discussed norms and roles for group work in “breakout rooms,” or separate video calls for each group (her school was not using a software that had the breakout room functionality). One of the resulting virtual rooms with three eighth graders during the Sensor Immersion Unit was especially encouraging for both Lauren and our research team. Without their cameras on at any point, the three boys shared their screens (swapping depending on who needed help or wanted to show the others) and coordinated their developing programs (on different screens) in relation to the DaSHs that two students had at home. Their collaboration included checking in to make sure everyone was ready to move on (“Everyone ok?”) and the opportunity to ask for further explanation from others at any point (“hold on, why does my [DaSH]…”). With their visual joint attention on the shared screen, the three successfully navigated an early program challenge using their understanding of the programming environment (MakeCode) and hints embedded in it (developed by the research team).

Lesson Learned 2: Adapting debugging practices to a virtual environment

Many science and STEM teachers new to our projects have struggled with finding confidence in supporting students as they learn to program the DaSH. They specifically worry about knowing how to support students as they debug the systems, which includes finding and resolving potential and existing issues in computer code, hardware (including wiring), or their communication. This worry was further magnified when learning had to happen remotely, even with some students having the physical DaSH systems at home. Common issues teachers encountered in student’s setup were consistent with the bugs that we have identified over the course of the project including: 1) code and wiring do not correspond, 2) problems in the students’ code, 3) the program is not properly downloaded onto the micro:bit, and more.²

Being unable to easily see students’ physical equipment and provide hands-on support made some teachers wary of even attempting to use the SchoolWide Labs curriculum in a remote environment. However, those teachers who were willing to do so made intriguing adaptations to how they supported students in identifying and addressing bugs. These adaptations included: 1) meeting one on one briefly to ask students questions about their progress and asking them to hold up their systems to the camera for a hardware check, 2) holding debugging-specific office hour times during and outside of class time, and 3) having students send their code to teachers to review as formative assessments and debugging checks. Although debugging required more time, patience, and creativity from teachers and students, these activities were generally successful in making the DaSHs work and helping students become more adept users.

Future Directions

As teachers and students have gone back to attending school face-to-face, the lessons learned during remote instruction continue to inform our work and inspire us as a SchoolWide Labs community. As these two examples show, the ingenuity of teachers and students during a tough shift to virtual learning led to new forms of computational thinking, communication, and collaboration. It became more clear that there was a critical need for at least some students to have the physical systems at home to deeply engage in the process of being data producers, which is indicative of the curriculum being so material rich. Yet, simply having the the DaSH in hand did not ensure that students would participate in the kinds of communication important for their engagement in and learning of the targeted science and computational thinking practices. While we continue to explore the complexity of teacher and student interactions with the DaSH, this past summer and fall we have been working with participating teachers (new and returning from last year) to develop a more specific set of norms, which include small group communication norms and roles. Additionally, we have begun to consider other strategies that may support students to learn programming and debugging skills, such as the use of student-created flowcharts to represent their view of the computational decisions of the DaSH. The shift to virtual learning, and now back to face-to-face instruction, has required us to more deeply reflect on the professional learning that best supports teachers in using the DaSH and accompanying curriculum in a variety of instructional settings, with both anticipated and unanticipated constraints. We welcome the opportunity to continue learning with and from our colleagues who are similarly engaged in this type of highly challenging but extremely rewarding endeavor to promote computationally rich and discourse-centered classrooms.

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More Information

More on SchoolWide Labs work:

Visit our website.
Gendreau Chakarov, A., Biddy, Q., Hennessy Elliott, C., & Recker, M. (2021). The Data Sensor Hub (DaSH): A Physical Computing System to Support Middle School Inquiry Science Instruction. Sensors, 21(18), 6243. https://doi.org/10.3390/s21186243
Biddy, Q., Chakarov, A. G., Bush, J., Hennessy Elliott, C., Jacobs, J., Recker, M., Sumner, T., & Penuel, W. (2021). A Professional Development Model to Integrate Computational Thinking Into Middle School Science Through Codesigned Storylines. Contemporary Issues in Technology and Teacher Education, 21(1), 53–96.
Gendreau Chakarov, A., Recker, M., Jacobs, J., Van Horne, K., & Sumner, T. (2019). Designing a Middle School Science Curriculum that Integrates Computational Thinking and Sensor Technology. Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 818–824. https://doi.org/10.1145/3287324.3287476

Important references for our work

Hardy, L., Dixon, C., & Hsi, S. (2020). From Data Collectors to Data Producers: Shifting Students’ Relationship to Data. Journal of the Learning Sciences, 29(1), 104–126. https://doi.org/10.1080/10508406.2019.1678164

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining Computational Thinking for Mathematics and Science Classrooms. Journal of Science Education and Technology, 25(1), 127–147. https://doi.org/10.1007/s10956-015-9581-5
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¹ See Hardy, Dixon, and Hsi(2020) for more information about data producers and collectors.
² Table 2 in Gendreau Chakarov et al. (2021) has a full list of common DaSH bugs students have encountered across the project.

Exploring the 2021 STEM For All Video Showcase

June 14, 2021Computer Science, Culturally Responsive Teaching, EducatorCIRCLS, STEM, Teachers & ResearchersPati Ruiz

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Featuring 287 short videos of federally funded projects aimed at improving STEM and Computer Science education, the 2021 STEM For All Video Showcase highlighted strategies to engage students and address educational inequities. The array of 3-minute videos showed the depth of work going on in the field to think about equity and social justice in the wake of COVID-19. Below are some favorites of our CIRCLS team that we hope you enjoy as well!

Co-Creating Equitable STEM Research Led by Communities
Contributed by Leah Friedman
This video features a project partnership between the Cornell Lab of Ornithology and community organizations around the country that are historically excluded from science research. Centering community wisdom and leadership, the group investigates the impact of noise pollution on public health in order to co-create appropriate solutions. This project is an amazing model of upending typical hierarchies of knowledge creation or control in STEM research, provides a really concrete framework for conducting research with community members, and exemplifies ‘broadening’ in every sense of the word.

Interest Stereotypes Cause Gender Gaps in STEM Motivation
Contributed by Judi Fusco
Thinking about stereotypical gendered messages that young children, older children, teens, and even adults receive about whether they belong somewhere is so important. These messages may be subtle, nuanced, and not intended, but they happen; we need to make sure we aren’t excluding anyone, especially without realizing it.

Activity for Stories of Algebra for the Workplace
Contributed by Jeremy Roschelle
What if every student could tell a story of how they’ll use math in the future career? Although this is just a beginning, it seems to me the technology for personalized AI-driven STEM storytelling will arise soon enough — and could help students create their own STEM identity.

You Deserve A Seat at The Table: The Data Economy Workforce
Contributed by Jonathan Pittman
This video features a project at Bethune Cookman University that uses an immersive game learning experience to help students gain 21st century digital workforce skills. Using gamified immersion is an excellent approach to build workforce skills and learn about the future of work.

Big Data from Small Groups: Learning Analytics and Adaptive Support in Game-based Collaborative Learning
Contributed by Dalila Dragnić-Cindrić
In this project, groups of up to four students work together in a 3D game-based environment called Crystal Island to solve complex eco-problems. A research team from Indiana University and North Carolina State University is investigating how students in small groups communicate and coordinate with each other when problem solving. Researchers used learning analytics to drive adaptive support.
The lead presenter is one of our Emerging Scholars, Asmalina Saleh. PIs are James Lester and Cindy Hmelo-Silver. CoPI is Krista Glasewski.

Activity for “WHIMC: Using Minecraft to Trigger Interest in STEM”
Contributed by Wendy Martin
If you are a fan of Minecraft or alternative histories you should check out H. Chad Lane’s video about his project: What-If Hypothetical Implementation in Minecraft (WHIMC). I enjoyed learning about how those researchers were encouraging students to create alternate worlds to help them better understand the phenomena that shape our own world.

To explore videos from past video showcases, visit the STEM For All Multiplex.

Breaking Barriers in Computer Science via Culturally Relevant Educational Tools (Part 3)

September 17, 2020Computational Thinking, Computer Science, Culturally Relevant Education, Culturally Responsive Teaching, Guest AuthorPati Ruiz

By Joseph Chipps, Ed.D.

In the last post, I gave background on ethnocomputing and culturally situated design tools, two constructs I used to develop culturally relevant education in newer, equity-designed computer science classes (e.g., Exploring Computer Science (ECS)¹ and AP Computer Science Principles (AP CSP)²). It is much more challenging to build those theories and tools into AP Computer Science A due to the use of shared tools and languages. So what can be done in AP Computer Science A?

First, we can increase sociopolitical awareness. In computing, we invite students to identify and address social inequities as developers of technology. For example, in the e-textiles unit of ECS, students construct a textile computing artifact with touch sensors, and collect the ranges read by the sensor when their peers use the artifact. As each student will produce a different range, the developer must synthesize the data while coding to make distinct cases for their product to follow. Inevitably, some students will be unable to use the product due to gender or race because of the way the technology was developed. This then leads to discussions of technology as biased (i.e., airport scanners discriminate against people of color (POC) and facial recognition not recognizing POC). An opportunity I took in the AP Computer Science A curriculum was to introduce the concept of variable declarations using a Student object that contains data (name, age, gpa, and gender). I invited groups of students to discuss what type of data they would make each variable, and to explain their reasoning. Some of the groups assigned gender to a boolean variable (one of two possible states, i.e. true/false) while others assigned gender to a String variable (any array of characters, i.e. “Female”). As students shared stories and engaged in dialogue, the class quickly realized that assigning gender to a boolean value transfers human bias to technology, and rejects the existence of non-binary genders.

Second, we can implement practices from culturally relevant education by using the experiences of students as an asset in the classroom. One of the ways to attach learning to the experiences of students is to connect curriculum to the real world. For example, DiSalvo, Guzdial, Bruckman, and McKlin³ studied how high school Black and Latino male students negotiate between geeking out and being cool when testing games. When students learned it was a real job in the world, students were more likely to maintain their interest and identity in computer science. A second way to attach learning to the lived experiences of students is to connect to students’ perceptions of self (or self-identity). Frederick, Donnor, and Hatley⁴ conducted a meta analysis of culturally responsive education (CRE) programs in technology education, and determined that courses that utilize CRE should acknowledge students’ representations of self. To achieve this, curriculum should present diverse and realistic perspectives as well as provide spaces for students’ voices and self-expression. I cannot think of examples in computer science; however, Nichole Pinkard’s⁵ (2001) Rappin’ Reader and Say, Say, Oh Playmate expertly used oral traditions and play rituals, prior knowledge of African-American children, as a method of early literacy instruction. Furthermore, the authors advise that those who acknowledge lived experiences of students also need to find ways to counter harmful narratives and deficit identity formation.

Third, we can build connections with local community members. For example, Lachney⁶ leveraged the expertise of programmers, students, and schools in the development of the cornrow curves CSDT. The programmers worked with community hair braiders to help develop the computational patterns in the software. But how do we build culturally situated design tools that can be part of the shared tools and languages of industry? Ogbonnaya-Ogburu, Smith, To, and Toyama⁷ adapted critical race theory to human-computer interaction (HCI) and concluded that the technology sector is prone to interest convergence; that is, the inclusion of POC in technology requires benefits to those in power. For example, changes in designs may not occur unless they help all people, not just POC. Talking with students about this helps create awareness. This overlaps with good techquity practices.

Finally, we can invite students to personalize computing artifacts. Kafai, Fields, and Searle⁸ studied the experiences of students personalizing electronic textile projects. The final project of the e-textiles unit invites students to develop any textile artifact of their choice as long as it has touch sensors and LEDs, and exhibits four different behaviors based on the user input. Projects have included play mats that force arguing siblings to hold hands for a certain amount of time, t-shirts and hats that display teams and schools in bright lights, and plush dolls that play music when squeezed. The authors found that allowing for personalization showcased aesthetic designs while revealing the diversity embedded in technology development.

When I design CRE curriculum for computer science, I frame the class as project-based, where students collaboratively construct videos, images, applications, presentations, pdfs, and other artifacts to demonstrate their understanding of material. Rather than present information for them to consume, I provide methods of inquiry, where students must reflect, research, discuss, and build their own understanding of content from their unique sociocultural context. Inquiry is situated on real-world contexts. When I can, I invite students to develop their artifacts using culturally situated design tools. To go beyond the curriculum, I challenge students to question the impacts of computing on the economy, society, and culture while providing space for ideas and dialogue, independent of a patriarchal, capitalist, and white framework. Which algorithms are biased, and how can we deconstruct bias within the logic? What does an anti-racist programming language look like? How do we counter deficit narratives in classes like AP Computer Science A, where the shared tools and languages could negatively impact purposefully excluded communities (PEC)s. And to reiterate, what does anti-racist eduction look like when students are forced to use the shared tools and languages of a profession that purposely excludes them?

Read Part 1 of the series.

Read Part 2 of the series.

Goode, J., Chapman, G., & Margolis, J. (2012). Beyond curriculum: The Exploring Computer Science Program. ACM Inroads, 3(2), 47–53. https://doi.org/10.1145/2189835.2189851
Astrachan, O., Cuny, J., Stephenson, C., & Wilson, C. (2011, March). The CS10K project: mobilizing the community to transform high school computing. In Proceedings of the 42nd ACM technical symposium on Computer science education (pp. 85-86).
DiSalvo, B., Guzdial, M., Bruckman, A., & McKlin, T. (2014). Saving face while geeking out: Video game testing as a justification for learning computer science. Journal of the Learning Sciences, 23(3), 272-315.
Frederick, R., Donnor, J., & Hatley, L. (2009). Culturally responsive applications of computer technologies in education: Examples of best practice. Educational Technology, 49(6), 9-13.
Pinkard, N. (2001). Rappin’ Reader and Say Say OH Playmate: Using Children’s Childhood Songs as Literacy Scaffolds in Computer-Based Learning Environments. Journal of Educational Computing Research, 25(1), 17–34. https://doi.org/10.2190/B3MA-X626-4XHK-ULDR
Lachney, M. (2017) Culturally responsive computing as brokerage: Toward asset building with education-based social movements. Learning, Media and Technology, 42(4), 420-439. doi:10.1080/17439884.2016.1211679
Ogbonnaya-Ogburu, I. F., Smith, A. D., To, A., & Toyama, K. (2020, April). Critical Race Theory for HCI. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-16).
Kafai, Y. B., Fields, D. A., & Searle, K. A. (2014). Electronic textiles as disruptive designs: Supporting and challenging maker activities in schools. Harvard Educational Review, 84(4), 532-556. doi:10.17763/haer.84.4.46m7372370214783

Breaking Barriers in Computer Science via Culturally Relevant Educational Tools (Part 2)

September 15, 2020Computational Thinking, Computer Science, Culturally Relevant Education, Culturally Responsive Teaching, Guest AuthorPati Ruiz

by Joseph Chipps Ed.D.

In the last post, I gave background on my school, situation, and the problems I was trying to address to bring in more people of color (POC) and females into the white and Asian male dominated Computer Science (CS) courses in my school. I also gave background on Culturally Relevant Education (CRE)¹ the term I will use that encompasses culturally relevant pedagogy and culturally relevant teaching.

In order to develop Exploring Computer Science (ECS)² and AP Computer Science Principles (AP CSP)³ using a culturally relevant educational framework, curriculum developers of those courses relied on theories and tools positioned within culturally relevant education: ethnocomputing and culturally situated design tools.

Ethnocomputing attempts to bridge the gap between culture and computing in that it assumes that computing is not a neutral activity; rather, computing is informed by capitalist, patriarchal, and western logic, beliefs, and tools⁴. Ethnocomputing originated from the idea that computing should be taught using relevant cultural artifacts and references of the local learners; that is, the cultural contexts of the learner⁵. In the ECS curriculum, through collaborative practices and methods of inquiry, students develop their own understanding of computing using journal writing, dialogue, construction of culturally meaningful artifacts, and presentations. In the code.org AP CSP curriculum, students develop a protocol for sending a color image through a network by creating their own personal favicon, the little icon at the top of a browser tab. This activity allows students to develop icons from their sociocultural backgrounds; students create their own symbols for computing, and through those symbols construct meaning as well as perception of self. Furthermore, the biases of the instructor are acknowledged as students work together to construct their own ideas and interpretations of computing.

AP Computer Science A externally tests students’ understanding of Java, an object-oriented programming language. Object-oriented refers to a style of programming in which we use data structures called objects to hold data that belongs to the object (i.e. a Student’s name, age, and gpa). I give a detailed example at the end of the post, that shows how I attempt to use items from students’ lived experiences to construct the rationale and embedded logic of encapsulating data within a single entity while using a design artifact from industry to help students code-switch.

As I teach about Class and Object in Java, I know they are symbolic tools, shaped by generations of programmers over time. Even the diagram in the example below is a constructed symbol, formed by decisions and negotiations over time within the programming community. So I have to ask: am I acclimating my students to cultural norms embedded within a larger system that purposely excludes them or am I supporting their futures by teaching them tools and languages required for code-switching?

ECS and AP CSP have the privilege of using tools and languages not shared by the programming community because they were designed to exist outside of professional communities for the specific purpose of increasing participation, but activity within a course that has historically used industry standard languages will always be mediated by the shared tools and languages of the professional community. Yes, I can create student-centered activities that allow students to construct their own ideas of concepts and logics, and invite students to raise sociopolitical consciousness in their and other communities. But am I doing a disservice to those students by forcing them to construct the logic, symbols, and beliefs of a culture that purposely excludes them? Or am I helping them enter this community?

Culturally Situated Design Tools (CSDT) support ethnocomputing in that they are collaboratively developed tools that exist outside of the shared tools of computing, and are inspired by purposefully excluded communities (PEC) culture. For example, a collaborative project in ECS requires students to present the cultural background of Native American bead looms, connections between bead looms and mathematics, and their own authentic bead loom designs that they construct using a CSDT. Embedded in this lesson is the realization that computing and mathematical concepts are not singularly defined and owned by white, patriarchal, western history; rather, embedded within Native American cultures. Alternatively, in ECS, after learning the history of cornrows, students use a CSDT to design and reflect on the mathematics of cornrow curves. Students investigate recursion through a CSDT that simulates cornrow curves. When I was taught recursion in a Java class, I heard names like Fibonacci and solved problems that required some understanding of basic number theory. Students constructing recursive artifacts using a non-western tool like a cornrow design simulator is anti-racist computing education. We are putting the stories that were removed from education back into the curriculum.

But what does a CSDT look like when the purpose of a course is to introduce students to the shared tools and languages of the professional community? How can we leverage the experiences and voices of those who have not been included in the development of tools we use to design and execute computing? How do we promote anti-racist education when the tools and languages we use are embedded in exclusionary culture⁶? These were the barriers I faced when trying to implement ethnocomputing via culturally situated design tools in my AP Computer Science A curriculum. I still do not have answers. Perhaps a next step in computing is to design anti-racist computing tools and languages for industry. How can we use heritage cultural artifacts and vernacular culture to support the development of anti-racist computing tools and languages that can be used in industry as well as education? In my next post, I will explore what can be done in courses like AP Computer Science A such as increasing sociopolitical awareness, using the experiences of students, building connections within the community, and personalizing student-constructed artifacts.

Java Example Details:

For example, a class called Student would be an archetypical framework for how to define a student in a computer, and would include three parts: what data a student has (name, age, gpa, etc); how to create a student (which data can we set initially vs which data can be set later) and; actions we can do with the student data (update data, access data, add new scores to the gpa). While a class is a template for an object, an object is an instance that we can create. For example, once I have defined the template for what a Student is in a file called Student.java, then in a runner file, I can create a Student named Alice and input all of Alice’s data. I can then store all of Alice’s data within the object called Alice. Over time, I can access and manipulate Alice’s data, and even have Alice’s data interact with other Students’ data if, for example, I want to know the average GPA of the school or any selection of Students. The concept of objects is essential to AP Computer Science A. Consequently, I developed a lesson inspired by ethnocomputing for the first week of the course that would invite students to interpret experiences from their life into an object (discussed above). Figure 1 shows an example of what students must create.

MatzohBallSoup

– chefName : String

– ingredientNum : int

– temperature : double

+ getChefName(): String

+ getIngredientNum(): int

+ getTemperature(): double

+ setChefName(String): void

+ setIngredientNum(int): void

+ setTemperature(double): void

+ toString(): String

Figure 1. Example of object design from my Java curriculum

Read Part 1 of the series.

Read Part 3 of the series.

Aronson, B., & Laughter, J. (2016). The theory and practice of culturally relevant education: A synthesis of research across content areas. Review of Educational Research, 86(1), 163-206. doi: 10.3102/0034654315582066
Goode, J., Chapman, G., & Margolis, J. (2012). Beyond curriculum: The Exploring Computer Science Program. ACM Inroads, 3(2), 47–53. https://doi.org/10.1145/2189835.2189851
Astrachan, O., Cuny, J., Stephenson, C., & Wilson, C. (2011, March). The CS10K project: mobilizing the community to transform high school computing. In Proceedings of the 42nd ACM technical symposium on Computer science education (pp. 85-86).
Tedre, M., Sutinen, E., Kahkonen, E., & Kommers, P. (2006). Ethnocomputing: ICT in cultural and social context. Communications of the ACM. 49(1), 126-130. doi: 10.1145/1107458.1107466
Babbitt, B., Lyles, D., & Eglash, R. (2012). From ethnomathematics to ethnocomputing. In Swapna Mukhopadhyay & Wolff-Michael Roth (Eds.). Alternative forms of knowing mathematics (pp. 205–219). doi: 10.1007/978-94-6091-921-3_10
Margolis, J., Estrella, R., Goode, J., Holmes, J.J. and Nao, K. Stuck in the Shallow End: Education, Race, and Computing. MIT Press, Cambridge, MA, 2010.

Breaking Barriers in Computer Science via Culturally Relevant Educational Tools (Part 1 of 3)

September 8, 2020Computer Science, Guest AuthorPati Ruiz

By Joseph Chipps, Ed.D.

Dr. Chipps is a computer science teacher at Granada Hills Charter High School as well as an adjunct faculty member of the secondary education department at California State University, Northridge. He has an Ed.D. in Learning Technologies, and wrote this to share his thoughts and expertise on developing culturally relevant educational tools in computer science.

Part 1

Science, technology, engineering, and math are all segregated fields, but computer science is particularly segregated¹. Although new K-12 courses are being developed using culturally relevant education tools in order to increase participation among women, BIPOC, English language learners, and those with disabilities (and intersections thereof), the number of students taking a first year college equivalent computing class is still very low. Building culturally relevant educational tools in a first year college-level course is difficult due to the inherent goal of introducing students to the tools and languages of an exclusionary professional community. This issue is not just an issue in computer science. I raise the following question to all teachers: how do we authentically provide culturally relevant education to those who use the shared tools and languages of a professional community that has a history of purposely excluding others? My hope is that students can become part of industry and help change this, but not lose their own culture.

This 3-part blog series is about my attempt to develop culturally relevant educational tools for AP Computer Science A. Additionally, I offer an analysis of how programmer culture is generationally embedded within shared tools and languages, and what needs to change in computer science education to remove barriers for purposefully excluded communities (PEC)s. I should note that I am a white male, and I believe that education is an inherently political act due to white supremacy as an embedded culture within all institutions. I do what I can to change it and work to not perpetuate the problem.

I began teaching at Granada Hills Charter High School (GHCHS) in 2008, and each year between 2008 and 2012, we offered one to two sections of AP Computer Science A with twenty to thirty students per section (4500 students in the school). I took over the class in 2010 when the previous computer science teacher retired, and I was shocked by the lack of female students as well as non-white and non-Asian students. This was not a local phenomenon; rather, enrollment in AP Computer Science A is historically low. According to AP, only 0.05% of the approximately 1.9 million California public high school students took the AP CS A exam in 2017.

In addition, students of color comprise over 60% of California’s high school-aged population, and yet the number of students of color who take the AP Computer Science A exam in California is incredibly low.

	California Population (≅1.9 million)	AP CS A Test-takers (10,286)
Latinx	53% ≅ 1 million	15% ≅ 1543
African American	6% ≅ 114,000	1% ≅ 103
Native American / Alaska Natives	~1% ≅ 19,000	* = 5

*Only 5 Native American/Alaska Natives passed the test out of the 10,268 test-takers from California in 2018.

Low participation rates among students of color have resulted in computer science not being offered at 75% of schools nationwide with the highest percentage of PECs and only 2% of schools with large ratios of PECs offering AP Computer Science A².

The CS10K Initiative³ provided a space and opportunity for new courses such as Exploring Computer Science⁴ and AP Computer Science Principles⁵ to transform computer science education for the purpose of increasing participation among PECs, and these courses have demonstrably been successful. In 2013, I began offering Exploring Computer Science at GHCHS, and in 2016, I introduced AP Computer Science Principles. In the 2019-2020 school year, over 800 students took computer science at GHCHS; the ethnicity of students parallels that of the overall school demographics, and we have a 3:2 ratio of men to women (we are still working on that). Between 2010 and 2019, GHCHS saw a 1700% increase in students taking computer science.

The College Board also notes that since the introduction of AP Computer Science Principles in 2016, AP computer science classes (cumulative) have observed a 343% increase in Black students, a 315% increase in Latinx students, and a 257% increase among female students. Courses like Exploring Computer Science and AP Computer Science Principles were developed based on current research in equity-oriented computer science education, and were purposefully designed to increase participation.

So what is the big deal about developing a culturally responsive curriculum for AP Computer Science A? If it was done for other courses, why is AP Computer Science A still a problem? For that, we need to understand what culturally responsive education means in computer science.

The development and consequential nuances of culturally relevant education is important in realizing the inherent differences between building curriculum for Exploring Computer Science and AP Computer Science A. When I received my credential, multicultural education was still being taught as a framework for cultural diversity; however, little attention was paid to the inherent biases and belief systems of those who developed curriculum and facilitated learning experiences, and multicultural education was criticized for its reliance on cultural symbols such as food and holidays⁶. Additionally, despite good intentions, those cultural symbols tended to be byproducts of bias, and further flattened groups to stereotypes and single stories⁷.

In response to the criticisms of multiculturalism, two frameworks emerged: culturally responsive teaching and culturally relevant pedagogy. Culturally responsive teaching empowers students by increasing awareness of their lived experiences and acknowledging their sociocultural frames of reference in order to situate experiential learning within the needs of students^8,9. Alternatively, culturally relevant pedagogy^10,11 refers to the beliefs and approaches that guide curriculum development¹². Culturally relevant pedagogy aims to use students’ cultural references and positioning within systems of power to guide curriculum and transform learning experiences by challenging social inequities¹¹.

Both of these frameworks use a social justice approach to education in its view of student identity and experience as an asset. It should be noted that culturally responsive teaching and culturally relevant pedagogy are used somewhat interchangeably in literature, so, going forward, I will use the term culturally relevant education (CRE)¹² as an umbrella term that covers both approaches. In my next post, I’ll discuss using Exploring Computer Science (ECS) and AP Computer Science Principles (AP CSP) that were developed to be culturally relevant using ethnocomputing and culturally situated design tools.

Read Part 2 of the series.

Read Part 3 of the series.

Margolis, J., Estrella, R., Goode, J., Holmes, J.J. and Nao, K. Stuck in the Shallow End: Education, Race, and Computing. MIT Press, Cambridge, MA, 2010.
Margolis, J., & Goode, J. (2016). Ten lessons for computer science for all. ACM Inroads, 7(4), 52–56. https://doi.org/10.1145/2988236
Astrachan, O., Cuny, J., Stephenson, C., & Wilson, C. (2011, March). The CS10K project: mobilizing the community to transform high school computing. In Proceedings of the 42nd ACM technical symposium on Computer science education (pp. 85-86).
Goode, J., Chapman, G., & Margolis, J. (2012). Beyond curriculum: The exploring computer science program. ACM Inroads, 3(2), 47–53. https://doi.org/10.1145/2189835.2189851
Cuny, J. (2015). Transforming K-12 computing education: AP® computer science principles. ACM Inroads, 6(4), 58-49. https://doi.org/10.1145/2832916
Banks, J. A. (2013). The construction and historical development of multicultural education, 1962–2012. Theory into Practice, 52(sup1), 73-82. doi: 10.1080/00405841.2013.795444
Kim, S., & Slapac, A. (2015). Culturally responsive, transformative pedagogy in the transnational era: Critical perspectives. Educational Studies, 51(1), 17-27. doi:10.1080/00131946.2014.983639
Gay, G. (2010). Culturally responsive teaching: Theory, research, and practice (2nd ed).Multicultural Education Series. New York, NY: Teachers College Press.
Gay, G. (2013) Teaching to and through cultural diversity. Curriculum Inquiry, 43(1), 48-doi: 10.1111/curi.12002
Ladson-Billings, G. (1994). What we can learn from multicultural education research. Educational Leadership, 51(8), 22-26. Retrieved from https://eric.ed.gov/?id=EJ508261
Ladson-Billings, G. (2014). Culturally relevant pedagogy 2.0: Aka the remix. Harvard Educational Review, 84(1), 74-84. doi:10.17763/haer.84.1.p2rj131485484751
Aronson, B., & Laughter, J. (2016). The theory and practice of culturally relevant education: A synthesis of research across content areas. Review of Educational Research, 86(1), 163-206. doi: 10.3102/0034654315582066

Interview with Creative Coding in Python Author Sheena Vaidyanathan

August 20, 2019Book Club, Computer Science, STEM, Written by: Pati RuizPati Ruiz

We were lucky enough to get to interview Creative Coding in Python author Sheena Vaidyanathan at CSTA 2019 in Phoenix, AZ! We asked her some of the questions that the CIRCLEducators compiled, check out her responses:

Can you tell us a little bit about how you got started in both art and computer science?

I am a computer scientist and have been involved in technology for many years. When I decided to take a break from tech, it was the perfect opportunity for me to pursue something I had always wanted to do – art. I decided to enroll in the local college to take art classes and also volunteer in the local schools to teach art. I found that I looked forward to days in the classroom and I really loved teaching. So when a position for an art teacher opened up in one of the local schools, I applied and got it. When the art position went away, I was able to transition to teaching computer science since that is my background. I throw in art when possible into my computer science classes!

Can you tell us about your book?

I wrote Creative Coding in Python: 30+ Programming Projects in Art, Games, and More. It is unique in that it uses colorful illustrations and creative projects to explain programming concepts. It is definitely the most beautiful coding book I have ever seen and will be a fun way for anyone (at any age – not just kids) to discover the joy of coding. I explain concepts using simple everyday metaphors and short snippets of code, and give step by step instruction for fun projects like chatbots, and games along with flowcharts and pseudocode. There are also challenging extension activities. It is not dumbed down, I share challenging and complex topics in an accessible way. In my book, you will learn about everything from data types, graphical user interface (GUI), function callbacks and more.

What are your tips for people new to CS to get started?

Start small, try one lesson and modify that small project that’s already working. Can you run it? Can you change a couple of lines of code? Then, once you’ve seen what code can do, you should take a class to learn more about programming.

What are some challenges that you face when training teachers about integrating computer science in their classrooms?

One challenge in elementary and middle school is that even if the teacher knows the content (coding) and wants to integrate it, they still need to justify whether or not it works with the rest of the content standards that they are teaching.

Teachers tend to go to the more tried and tested methods of teaching content (which doesn’t include coding) because introducing coding activities can take up valuable time resulting in them not having the time needed to do other topics/work. That balance can be very challenging. Even math teachers who know some coding and understand the advantages of using it to teach math, often do not use it in their classes. This is because they are short on time, and are under pressure of teaching a lot of content and making sure that students do well on the tests.

What are some of favorite projects in your book?

I am greatly inspired by the LOGO programming language and Seymour Papert’s original turtle, so I love using the turtle to teach coding. It is a classic way, and I still think the best way to teach kids to code. The turtle puts the child in the code. They have to think like the turtle in order to move, this is called body syntonic. If they need to make the turtle on their computer “go left” they have to think about moving their entire body as if they were the turtle. This helps them think about instructions in a different way; the instructions are something that they can see themselves doing. It’s tangible and visual and it’s a connection that they will always remember because they were the turtle. By programming an object on the screen, kids learn to be specific in their directions. The computer will only understand what they write in their program.

My other favorite project (shared in my book – image below) goes back to my artistic background, and uses geometric shapes. In the project, you’re creating geometric shapes to create a bigger picture. You can use functions to define a house, for example, which is a rectangle followed by a triangle with other shapes. Once you’ve defined a shape, you can write code to repeat it. So using geometric shapes, really appeals to me, because it’s relatable to how you would draw in real life. It’s so visual and then there’s a connection to code that I really like and I think it works very well to help people learn more about coding.

** In our book club, you will be challenged to create art work and follow along in Sheena’s book in Chapter 2.

What are you working on now?

I launched a new elective and I’m exploring more tools to make sure I’m bringing in the right tools to teach the content. I’m exploring Artificial Intelligence (AI) in K-12 and am part of the AI4K12 initiative.

Sheena shared her work at CSTA 2012 in a session titled Strategies for Teaching Coding to All Students which focused on her new class Coding Apps Games & more and the other was about work being done to advance computer science education in the area of AI.

There are so many resources that Sheena has put together on her website, so check them out! Connect with Sheena on Twitter https://twitter.com/Sheena1010 and CIRCL Educators https://twitter.com/CIRCLEducators .

Book: Creative Coding in Python by Sheena Vaidyanathan

Book Club, Computational Thinking, Computer Science, Learning, STEM

Please join us for a discussion of Creative Coding in Python by Sheena Vaidyanathan. We will be using Wakelet, Twitter, and GitHub for this book club.

About this Book

Creative Coding in Python by Sheena Vaidyanathan contains activities that can be used in a classroom or on your own. You are encouraged to code along as you read the book, by typing in your own code. In Creative Coding, there are a few projects for you to explore. In our book club we will dig into the first two projects:

CREATE YOUR OWN CHATBOTS

Taken from the website “Using the Big Ideas from this chapter, we will get user input and then respond to the user by putting information on the screen. This will be a simple chatbot. There will be ideas in subsequent chapters that you can use to make this chatbot better. You can change the actual text of the chatbot responses or questions to customize it.”

CREATE YOUR OWN ART MASTERPIECES

Taken from the website “Using turtle graphics is a fun way to learn Python and create artwork using code. We’ll give the virtual turtle instructions, known as functions and combine these functions to create complex art pieces.”

About the Author:

Sheena currently teaches computer science in grades 6–8 in the Los Altos School District, in Los Altos, California. In her role as the district’s Computer Science Integration Specialist, she is involved with the STEM program in the district to develop the computer science program for K–8 in all the elementary and junior high schools in the Los Altos School district. She has developed the curriculum and conducted professional development to bring computer science to all 4500+ students in the district. Read more about Sheena on her website and in the CIRCL Perspective.

How to Participate:

We will use Wakelet, Twitter, and GitHub in this book club. Sign up today to receive email updates.

Wakelet

Wakelet is described as “an easy and enjoyable way to save, organize and share content from across the web. Never lose a link again. With Wakelet, you can bookmark the content that matters to you, organize it how you like, and add your own images and notes to give context. People everywhere are using Wakelet to save, organize and share content in stunning, visual collections.So, whether you’re a student, traveller, blogger, brand or business, it’s easy to start bookmarking.“

We will use Wakelet to easily share resources we can use in classrooms and projects we create while participating in this book club Creative Coding in Python.

Resource 1- Popular Programming Languages
Resource 2- Flowchart

Project 1 – Share your chatbot
Project 2 – Share your art work

Twitter
We love to see you share your thoughts and work on Twitter using #CIRCLedu on Twitter and mentioning @CIRCLeducators ! Also, please share any book recommendations for future book clubs!

How to Encourage Young Women and Marginalized People to Participate in CS and Engineering (part two)

February 15, 2019Book Club, Computer Science, Engineering, Learning, STEM, Teachers & Researchers, Uncategorized, Written by: Pati RuizPati Ruiz

by Pati Ruiz

This is the second post in a two part series based on my dissertation which focused on encouraging the participation of women and African Americans/Blacks, Hispanic/Latinx, and Native Americans/Alaskan Natives in computing. The first post focused on modeling an interest and passion for CS and creating safe spaces for students. This post focuses on building community, introducing students to careers, and making interdisciplinary connections.

Build Community and Connect Students with Mentors

Family support is important! Young adults encouraged and exposed to CS by their parent(s) are more likely to persist in related careers (Wang et al., 2015). And did you know that women are more likely than men to mention a parent as an influencer in their developing a positive perception of a CS-related field, more often citing fathers than mothers as the influencers (Sonnert, 2009)? Unfortunately, parents’ evaluation of their children’s abilities to pursue CS-related fields differs by gender; parents of boys believe that their children like science more than parents of girls (Bhanot & Jovanovic, 2009). Nevertheless, family support is crucial for young women and supportive family members — whether or not they are connected to the tech world — play a critical role in the encouragement and exposure that young women get to the field.

Helping parents understand the role that they can play is important. As educators, we can model for them how to encourage their children as well as how to dispel misconceptions and harmful stereotypes that their children might have heard. Sometimes parents and family members themselves might unknowingly be perpetuating harmful computer science world misconceptions with the comments they make to their children. As teachers, we can provide parents with training that might help them understand how to encourage and expose their children to the field in positive ways. After all, the research shows that this support can be provided by anyone – not just educators.

All of the young women in my study described the value of mentors. Even seeing representations of female role models in the media can encourage a young woman to pursue a CS-related degree. It’s important for young women to see representations of people who look like them in the field and to have real-life female mentors and peers who can support them in their pursuit of CS-related degrees and careers. As a result of the low number of women in the field, mentors and role models for women are primarily men. While this can be problematic, it does not have to be. Cheryan et al. (2011) found that female and male mentors or role models in computing can help boost women’s perceived ability to be successful if those role models are not perceived to conform to male-centered CS stereotypes. The gender of the role model, then, is less important than the extent to which that role model embodies current STEM stereotypes.

The actionability of some of the factors described above, then, allows educators and others to positively influence and encourage young women in high school to pursue CS degrees in college (Wang et al., 2015).

Introduce Careers

In their recent report titled Altering the Vision of Who Can Succeed in Computing, Couragion and Oracle Academy described the importance of introducing youth to careers in technology. They find that:

“It is critical to improve the awareness and perception of a breadth of careers in computing to meet the demands of our workforce and the desires of our students. We need to elevate high demand and high growth computing fields such as user experience (UX) and data science – that when understood, appeal to and attract underrepresented populations.“

What this report found is what I found in my research; many African Americans/Blacks, Hispanic/Latinx, and Native Americans/Alaskan Natives students don’t know people working in the computing field and don’t know what career options can look like. Couragion is working to change this by providing inclusive, work-based learning experiences that prepare students for jobs of the future. What I like about Couragion’s approach is that students are able to use an app to explore careers and engage with role models through text, activities, and videos. As they work their way through different career options, students take notes and reflect using a digital portfolio. I think this is a great way for students to develop career consciousness, something I wish I had when I was in school (as a student and teacher)!

As a teacher, the way I would connect my students with industry careers was to connect with local groups like GirlDevelopIt and invite speakers to my classroom. I also had college students visit my classroom – it usually works well to have recent graduates come back to talk to students because students relate well to recent high school graduates. I also introduced computer scientists in the news. If I were teaching right now, I would highlight 2018 MacArthur Fellow Deborah Estrin. In her Small Data Lab at Cornell, Dr. Estrin and her team are designing open-source applications and platforms that leverage mobile devices to address socio-technological challenges in the healthcare field. Or, I might direct them to this recent article written by Clive Thompson titled The Secret History of Women in Coding.

Some participants in my study mentioned that they ended up majoring in CS because of a mentor. One participant talked about how one of her high school teachers “dragged her to” a Technovation event. There, she ended up seeing a young woman who she “saw herself” in so she decided to apply to the same college that the mentor attended, got in, and went. This participant envisioned herself there because of this near-peer. She said that she didn’t connect with her mentor once she got to the university that they both attended for a year together, but just seeing her ahead of her in the program was motivating.

Again, the idea here is to create opportunities for students to connect with people in the field – to see themselves and to see the possibilities. Some groups that my students have worked with include Girls Who Code, Black Girls Code and Technolochicas – there are many others. Which ones do your students work with?

Make Interdisciplinary Connections

Finally, we have the idea of making interdisciplinary connections. CIRCL Educator Angie Kalthoff wrote a post for EdSurge discussing this very topic. Angie encourages teachers to ask their students: What are you doing outside of school that you want to tell other students about? She and a group of Minnesota educators organize student-powered conferences where middle schoolers showcase what they’re really interested in learning about. Check out her post because getting together with other educators to organize your own student-powered conference might be an excellent way you support and recruit young women and African Americans/Blacks, Hispanic/Latinx, and Native Americans/Alaskan Natives!

Interdisciplinary connections can be facilitated by teachers and it’s important to note that all of my study participants were very thankful to their K-12 teachers for having encouraged their pursuit of a technical field – even if they didn’t know they had. As one participant described, “a teacher who’s clearly passionate” is particularly encouraging.

One resource that can help you make interdisciplinary connections with students iss Connected Code: Why Children Need to Learn Programming by Yasmin B. Kafai and Quinn Burke. Join the CIRCL Educators book club to discuss this book starting in April!

Please note that the featured image for this post was created by #WOCinTech Chat, check them out! We’d love to hear from you — Tweet to @CIRCLEducators or use #CIRCLEdu.