Category Archives: Guest Author

Developing Sample Computational Thinking Lessons with ChatGPT

AI in Education, Computational Thinking, EducatorCIRCLS, Guest Author, Learning Technologies, Written by: Merijke Coenraad, Written by: Pati Ruiz

by Pati Ruiz, Merijke Coenraad, and Judi Fusco with contributions from Julio Vazquez

What is ChatGPT?

Let’s start with some definitions, ChatGPT is commonly classified as a natural language processing model, meaning it deals with language and human speech patterns, and “generative artificial intelligence”, meaning that it is AI that creates new content — in this case, new text.

More specifically, ChatGPT is a chat-based generative pre-trained transformer. Meaning that the model: (1) can generate responses to questions (Generative); (2) was trained in advance on a large amount of the written material available on the web (Pre-trained); (3) and can process sentences differently than other types of models (Transformer). Basically, it’s a chatbot that allows a user to ask a question in plain language and get a response in a way similar to how a human would reply.

What does this mean for education?

“ChatGPT is a good prompt for conversation.
I see this tool as a starting point for teachers and students.”
-Julio Vazquez, North Salem Central School District

Despite the precedent of banning access to ChatGPT set by New York City Public Schools in January 2023, not all school districts are following suit. Some educators believe that these AI systems and tools are out in the world and the best thing educators can do is to teach students to partner with AI tools so they can be better prepared for a technological world. For example, English teacher Cherie Shields was recently interviewed by the New York Times where she shared that she assigned students in one of her classes to use Chat GPT to create outlines for a recent essay assignment. She shared that the process helped deepen students’ understanding of the stories while also teaching them to interact with an AI system by manipulating their inputs to get the responses they were looking for. In this case, ChatGPT became a tool that can support learning when we thoughtfully include it in our lessons and also guide students in using it well.

Dr. Julio Vazquez, Director of Instruction and Human Resources, and his team are encouraging experimentation and access to ChatGPT for all faculty and staff and are thinking about how to provide students with access in a manner that will not conflict with student privacy laws. Staff members are rolling their sleeves up and starting to explore and learn about how they can use it with their students productively. In fact, they are exploring the use of ChatGPT to develop sample Computational Thinking (CT) lesson plans that the team uses as a jumping off point in their CT Pathways development process.

ChatGPT for Developing Sample Computational Thinking Lesson Plans

compass pointing north
North Salem Central School District
In a recent conversation with Dr. Vazquez, we asked him more about how he and his teachers are incorporating ChatGPT in their computational thinking lesson planning process.

Dr. Vazquez and his colleague Cynthia Sandler, Library Media Specialist, started by entering prompts into ChatGPT and seeing what came out. The searches started with prompt terms that went something like “generate a 5th grade lesson for computational thinking focusing on science.”

As the team began to analyze the lesson plans that came out, they realized they needed to make adjustments. Julio shared that he and his team have become better at giving ChatGPT enough context so that the lessons that are developed are closer to what the team expects of a lesson plan and the content better aligns to both CT and content area standards. For example, a more recent lesson prompt terms included:

“write a science lesson that integrates
9-12.CT.1
Create a simple digital model that
makes predictions of outcomes. and HS-PS1-5. Apply scientific principles and evidence to explain how the rate of a physical or chemical change is
affected when conditions are varied.”

The prompt terms and outputs were documented and provided a good starting point for sparking conversation. On first pass, the team collectively agreed that they liked the structure of the generated lesson plans. Beyond format and in terms of the content of computational thinking and subject area standards, the prompt terms entered into ChatGPT also included Habits of Mind, thinking dispositions which are implemented in North Salem, as well as the use of Visible Thinking Routines.

Dr. Vazquez and his team have worked with ChatGPT to develop sample computational thinking lessons across all subject areas K-12. These lessons are not meant to be implemented in the classroom “as is,” but rather, these sample lessons are to be used as a first draft, a starting point for consideration and conversation in North Salem. Teachers will vet the lessons for accuracy and then iterate and improve them in order to meet the learning needs of their students. Given the need for high-quality, integrated computational thinking lessons we will continue to work with Dr. Vazquez and his team at North Salem to learn more about how they are integrating ChatGPT in their work and their vetting process. We look forward to sharing more! Until then, do you have questions for us? Are you integrating ChatGPT in your classroom, school, or district? Let us know @EducatorCIRCLS.

Educator CIRCLS posts are licensed under a Creative Commons Attribution 4.0 International License. If you use content from this site, please cite the post and consider adding: “Used under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).”
Suggested citation format: [Authors] ([Year]). [Title]. Educator CIRCLS Blog. Retrieved from [URL]

Enhancing Learning Performance With Microlearning

EducatorCIRCLS, Guest Author, Teachers & Researchers

iPads used by students in school classrooms
image by Arthur Lambillotte via Unsplash
by Courtney Teague, Rita Fennelly-Atkinson, and Jillian Doggett

Courtney Teague, EdD, Deputy Director of Internal Professional Learning and Coaching with Verizon Innovative Learning Schools program based in Atlanta, GA.
Rita Fennelly-Atkinson,EdD, Director Micro-credentials with the Pathways and Credentials team based in Austin, TX
Jillian Doggett M.Ed, Project Director of Community Networks with Verizon Innovative Learning Schools program based in Columbus, OH


What is microlearning?
Microlearning is a teaching and learning approach that delivers educational content in short, focused bursts of information. Microlearning tends to focus on one objective, and the learning doesn’t require more than 1-20 minutes of the learner’s time. Schools and teachers can use microlearning to supplement traditional instruction or as a standalone learning tool. microlearning has been around for a long time–remember those flashcards at kindergarten that helped us learn numbers, the alphabet, and colors? However, schools were largely unaware of how powerful this learning strategy can be for a teacher.

Microlearning has several potential benefits for both learners and teachers. For learners, microlearning can provide a more engaging and interactive learning experience. This type of instruction can also help to reduce distractions for students who become disengaged with unnecessary learning information. For teachers, microlearning can be used to differentiate instruction and address the needs of all learners. Additionally, microlearning can save instructional time by allowing teachers to deliver targeted information in a concise format. Teachers can tailor microlearning content to focus on specific skills or knowledge gaps (Teague, 2021).

Microlearning is flexible and can be accessed anytime, anywhere. Learners can complete microlearning activities on their own time, at their own pace. Microlearning is like a seasoning for learning; it seasons and heats up information to make the process of comprehending new knowledge easier. It has been part-and-parcel in many schools’ instructional strategies since time immemorial, but only recently have we begun paying attention to how powerful this strategy really can be when used correctly.

microchip being held
image by Brian Kostiuk via Unsplash
What does microlearning look like?
Microlearning can come in many forms. Below is a list of 10 microlearning examples:

  1. Short, Focused Videos
  2. Infographics
  3. Podcasts or Audio Recordings
  4. Social Media Posts and Feeds
  5. Interactive Multimedia
  6. Animations
  7. Flashcards
  8. Virtual Simulations
  9. Assessment Activities: Polls, Multiple-Choice Questions, Open Response Questions
  10. Games

How can teachers use microlearning effectively to maximize content retention, personalize learning experiences, and bolster student engagement?

Use microlearning to Active Student Prior Knowledge and Generate Excitement for New Learning

Assign microlearning, such as a self-paced learning game, to assess and activate prior knowledge around a topic. Or place a few bite-sized learning opportunities about an upcoming lesson in your Learning Management System (LMS) for learners to preview beforehand to generate interest and excitement for new learning.

Use microlearning to Personalize Learning Experiences

Creating microlearning in various formats covering multiple topics gives learners the agency to make meaningful choices about their learning paths. For example, to learn a new concept or build new skills, learners can choose to engage with an interactive image, listen to a short audio guide, participate in a learning game, or watch an explainer video or animation. Additionally, learners who need remediation or want to extend their learning can quickly access content to review a topic again or complete additional microlearning lessons.

Use microlearning to Encourage Communication and Collaboration

Create different microlearning bites, each covering a specific objective or portion of a learning goal. Assign each student to engage with one microlearning bite and then use the Jigsaw method to have learners learn about a new topic in a cooperative style. Similarly, you can assign microlearning that includes thought-provoking, probing questions and have learners discuss on a discussion forum or by recording and responding to each other’s short video or audio responses.

Use microlearning to Engage Families and Caretakers

Distribute microlearning to learners’ families and caretakers to help them quickly learn content learners are learning in class to support them in taking an active role in their child’s learning at home.

Use microlearning to Reduce Time Spent Grading

Create microgames and assessments using tools that automatically grade and provide learner analytics to reduce the time spent grading. For example, create an interactive video with embedded questions, a short quiz on your LMS, or a learning game that automatically grades learners’ responses and provides you with learner analytics you can use right away to inform just-in-time teaching.

Use microlearning to Build Classroom Community

Have learners create microlearning lessons to teach each other about themselves, topics that interest them, or around specific learning objectives that they have mastered. Use these bite-sized pieces of learning to expand your microlearning repository, give learners ownership of their learning, and foster a sense of classroom community.

Use microlearning to Promote Learning Outside of School

Over time, create and curate a repository of microlearning assets, such as explainer videos, audio recordings, infographics, learning games, trivia quizzes, flashcards, etc., on your Learning Management System (LMS). Then, learners can easily access and continue their learning outside of school, cultivating a life-long learning mindset.

How to assess microlearning?
The flexibility of microlearning allows for an abundance of possibilities in how it is assessed. For example, if your goal is simply to educate people about a new process using a video, then you don’t have to assess, you can simply measure the reach by the number of views and effectiveness by the level of adherence to the new process by a specific date. If your goal is to educate people about the available services, then your performance indicator might be the use of those services. In other words, you have a license to be creative and to assess learning effectiveness in many different ways.

More formally, the evaluation of learning can be categorized into two types: assessments and indicators (Fennelly-Atkinson & Dyer, 2021). Assessments include most formal and informal methods of evaluating learning, which include surveys, check-ins (i.e. verbal, data, progress, etc), completion rates, knowledge checks, skill demonstration observations, self-evaluations, and performance evaluations. Meanwhile, indicators include indirect measures such as performance, productivity, and success benchmarks. Which type you use is largely dependent on the learning context and need. The key questions to consider are the following:

  • What measurable change is the microlearning impacting?
  • Do you need individual, organizational, or both types of data?
  • What is the ease of collecting and analyzing the data?
  • Can existing evaluations or indicators be used to measure the impact of learning?

What are the drawbacks of microlearning & how to mitigate them?
Microlearning does have some potential drawbacks. For one thing, it can be easy for learners to become overwhelmed by the sheer volume of micro-lessons that they are expected to complete. Additionally, microlearning can sometimes result in a fragmented understanding of a topic, as learners are only exposed to small pieces of information at a time. Microlearning often does not provide an opportunity for learners to practice and apply what they have learned. However, these potential drawbacks can be avoided or mitigated when microlearning is designed into learning activities. Another potential drawback of microlearning is that it can be difficult to maintain a consistent level of quality control. With so much content being produced by so many different people, it can be hard to ensure that all of the material is accurate and up to date. This problem can be mitigated by careful selection of materials and regular quality checks. Because of this, microlearning can create a significant amount of work for teachers. In order to properly incorporate microlearning into their classrooms, teachers need to have a good understanding of the material and be able to effectively facilitate discussion and debate. While it may require some additional effort on the part of teachers to do microlearning, it feels worth it as it has the potential to significantly improve student engagement and learning outcomes.

Which tools can you use to create microlearning?
While microlearning does not necessarily require the use of digital tools, the reach and potential of these types of learning experiences is magnified by technology. Because microlearning is so short and usually discrete, there are many types of tools and methods of delivery that can be used. Formal authoring tools such as LMSs and Articulate can be used, but are not required. Any type of tool that can create a static or dynamic piece of content can be used. Further, any type of delivery system can be used to disseminate the learning. Making microlearning relevant and specific to the learning context, environment, and audience are key to selecting a content creation tool and delivery systems (Fennelly-Atkinson & Dyer, 2021).

Summary
To wrap it up, microlearning is breaking down and chunking learning into bite-sized pieces. Microlearning might be small but can have a big impact on powerful teaching and learning. It can take many different forms, which means that there are just as many content-creation tools and delivery platforms. Likewise, there are a variety of ways to assess microlearning depending on the goal and purpose for its use. There is no one correct way of creating microlearning. Microlearning can be as simple as listening to the pronunciation of words on an audible dictionary online application. Teachers can use this flexible method of microlearning to support research-based instructional practices and personalize learning experiences.

So how might you use this approach to meet the modern learner’s needs? Tweet @EducatorCIRCLS and be part of the conversation.

References

Fennelly-Atkinson, R., & Dyer, R. (2021). Assessing the Learning in microlearning. In Microlearning in the Digital Age (pp. 95-107). Routledge.

Teague, C. (2021, January 11). It’s All About microlearning. https://community.simplek12.com/webinar/5673

Educator CIRCLS posts are licensed under a Creative Commons Attribution 4.0 International License. If you use content from this site, please cite the post and consider adding: “Used under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).”
Suggested citation format: [Authors] ([Year]). [Title]. Educator CIRCLS Blog. Retrieved from [URL]

Supporting Computationally Rich Communication During Remote Learning: Lessons Learned

Computer Science, EducatorCIRCLS, Engineering, Guest Author, STEM

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.

Image is a diagram that shows the micro:bit, (smaller looking electronics component with a 6 by 6 array of small LEDs in the middle) inserted into the Gator:bit (larger electronics board with five LED lights in the middle) with three sensors to the left and three wires between the gator:bit and sensors.Image shows a hand holding the micro:bit inserted into the Gator:bit with alligator-clip wires connecting the gator:bit to the microphone sensor.

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.

Educator CIRCLS posts are licensed under a Creative Commons Attribution 4.0 International License. If you use content from this site, please cite the post and consider adding: “Used under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).”
Suggested citation format: [Authors] ([Year]). [Title]. Educator CIRCLS Blog. Retrieved from [URL]

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
______________________
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.

Humanizing AI Research in Education by Broadening Community Engagement

EducatorCIRCLS, Event, Guest Author

Headshot of woman with black hair, a white wall in the background.Author: Aditi Mallavarapu

Learning Sciences and Technology Postdoctoral Researcher at CIRCLS. Her research projects all have the shared goal of collaborating with practitioners to design and build computational and analytical methods and tools to support and improve exploration-based learning. She has worked professionally as a technical consultant where she developed software solutions for healthcare and financial organizations. As an instructor she is involved with underserved communities to pique their interests in Computer Science.

This blog is the second of the three-part shared series, between NEXUS and the Center for Integrative Research in Computing and Learning Sciences or CIRCLS. The first post described the synergy between the two communities, and introduced the CIRCLS priority around broadening/inclusion in Learning Analytics/AI in education. In this post, we highlight the concerns and the importance of “broadening” participation in research of AI in education, equally raised by both the communities.

Seven people sit around a table looking and holding up colorful post-it notes. Several women wear a headscarf, two blue and two black.
Photo by Zainul Yasni (@zainulyasni6118)

The “Fate” of AI education research

Education, like many other fields, has been revolutionized in this era of datafication. The omni-present machines, with the so-called “intelligence,” are being used to improve the way we learn and teach through devices and technologies, and connect learners, teachers, and even families across ecologies (classrooms, museums, homes) to manage learning. Some innovations have started to dominate the way we learn and remember, sometimes even remembering for us. The imaginative artificial technologies enacted in Star Trek with communicators, talking virtual assistants, and video chats have become our reality. But this reality has not been equitably rolled out across individuals, schools, or communities.

As AI technologies become intertwined with our daily lives, there are justifiable concerns in society around algorithmic fairness, accountability, trustworthiness and ethics (“FATE”). Research is developing rapidly to ask how can we, as a community, rethink AI-based technological progress to address this inequity? How can we address the concerns around privacy, trust, and bias, that have become prevalent due to the prolific use of data and recording devices in these AI technologies? Progress in defining the nature of the challenges, and ways forward, is being made in both the Learning Analytics and AIED communities, but there remains much to do.

Researchers have suggested addressing these issues, in part, by broadening community engagement. With the recent transition to online learning due to the COVID-19 pandemic, the need to address these issues has become more urgent.

Addressing the issues by broadening engagement

For over a decade, researchers have been working synergistically across disciplines to address issues around equity, privacy, trust and bias. Some researchers have highlighted, humanizing the issues by engaging all stakeholders, learners, educators, caregivers and domain experts, in contributing to the design of the AI systems. One goal of broadening engagement is to consider the complex dynamics that result from multiple perspectives of the different stakeholders involved in a learning process, while designing the AI system. To fully achieve this, the design process should provide the stakeholders an active and respected role, which is non-trivial. The black box-like opaqueness that many of these AI technologies possess makes it difficult for practitioners to contribute. This should not be an excuse.

One way of providing everyone a platform to voice their opinions is to reduce the opaqueness through enacting and visualizing scenarios, making the design process about the humans involved in conceiving and using the system. Taking such a human-centered approach engages practitioners in conversations around what should be measured, and how that measurement could be used in decisions, with a hopeful view of mitigating at least some unwarranted applications and effects that a researcher alone might not be able to anticipate from where they sit.

Come be a part of the conversation!

We at CIRCLS, have planned the CIRCLS’21 convening for the community with the theme of “Remake Broadening.” Broadening participation for emergent technologies, like AI design, is an important aspect of this initiative. The keynote speakers have vested interests in broadening participation in Computer Science and AI education across different age groups and communities using emergent AI technologies. They have planned to engage the attendees in thinking about “designing for broadening” through “broadening participation in design.”

The community will also be hearing from the researchers at the AI institutes, iSat, AI-ALOE and AIEngage.org (part of the 11 institutes that won the recent NSF “AI institute” competition). This session will highlight how the community of both researchers and practitioners can contribute to and participate in AI research.

We invite SoLAR members to the conversation. Our Expertise Connections sessions (September 13, 4pm Eastern: Equity and Ethics Considerations for AI) and our Strategy sessions (September 14, 3pm Eastern: Remake Broadening) will allow researchers and practitioners alike to survey the emerging landscape and think strategically about how we could remake the envisioned broadening. We’ve designed these sessions to engage participants with the most pressing topics in small group activities — a “low floor and high ceiling” setting for both practitioners and researchers, that encourages the understanding of each others’ perspectives.

We hope this plan will give all attendees the chance to shape the broadening process. Our vision for this convening is a first step to “remake broadening”. With more engagements to follow, we hope to keep the conversation going even after the convening. We hope you’ll join us. You can see details about all the sessions when you register and explore Swapcard for CIRCLS’21.

Educator CIRCLS posts are licensed under a Creative Commons Attribution 4.0 International License. If you use content from this site, please cite the post and consider adding: “Used under a Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).”
Suggested citation format: [Authors] ([Year]). [Title]. Educator CIRCLS Blog. Retrieved from [URL]

Models for Science Learning: Answering the NGSS Call

EducatorCIRCLS, Guest Author, Science, STEM

By Korah Wiley
Korah Wiley is a learning sciences researcher at Digital Promise with over ten years of classroom teaching experience. Her prior work as a STEM researcher instilled a passion for making the STEM fields more accessible to students and educators.

As a student, I loved all the animal-related topics—topics about plants…not so much. When I became a biology teacher and got to the section on plant biology and photosynthesis in the curriculum I was using, I knew that I, like my students, would need to “hit the books”. However, I quickly found myself deep in the world wide web of teaching and learning resources available online, because I knew that reading a textbook was only going to take my understanding so far. To really understand the material deeply enough to teach it, I needed a multimedia resource. I searched high and low and finally found an animation of the process at a level of detail that would give me the confidence that I understood the process well enough to answer my students questions and support them in their learning process.

The learning process that I sought to engage my students in wasn’t the standard, memorize this information and take a test in a couple of weeks. Rather, it was the kind of learning called for by the Next Generation Science Standards (NGSS)—the three-dimensional integration type. At that time, the North Carolina School of Science and Mathematics was one of the lead state partner organizations for the development, adoption, and implementation of the NGSS. In preparation for the 2010-2011 school year, the science department dean shared the draft NGSS documents and essentially said, “This is the future of science learning and we will help lead the way.” So, as a department, we revised our current curriculum and instruction to align with the call of the NGSS to engage students in the practices of science and engineering with the goal of developing an integrated understanding of disciplinary core ideas and crosscutting concepts.

Finding this photosynthesis animation was great, because 1.) it helped me to understand photosynthesis better and 2.) I could use it to engage my students in the science practice of using a model to understand natural phenomena, particularly ones that are invisible to the naked eye. My students and I went on a journey inspired by the NGSS to learn more than just the what and why of photosynthesis, we were also learning the how. Learning how photosynthesis took place led us to an even more interesting question, what if? What if human cells could harness light and make energy? (It’s actually not as far-fetched as it sounds; Goodman & Bercovich, 2008.)

The question of “what if” led me down new paths when I joined a team to develop a middle school, STEM enrichment program for minoritized and first-generation, college-bound students, called Labs for Learning. What if we developed the program curriculum to engage the participants, rising 7th graders, in a rigorous learning experience, similar to the curriculum we developed to align with the NGSS? Would it be too much for students who were barely in middle school and in woefully under-resourced middle schools at that? Encouraged by the learning experiences we were supporting for our high school students, we took a chance!

I was responsible for teaching biology topics to the 7th graders, which, to my chagrin, included even more about plants! I relied on what I knew worked, the photosynthesis animation that was so helpful for me and my high school students. The animation, for all its awesomeness, was just out of reach for the middle school students, who were really intimidated by the names of the molecules and complexes. Wanting to figure out a way to still use the animation, (knowing that it could help them develop a deeper understanding of key concepts like energy and matter transformation), I told them to just focus on the process and ignore the names. (I figured if they understood the process then they could learn the names later.) This scaffolding ultimately led to physical reenactments of the process, where we turned the abbreviations of the molecule and complex names into initials of the characters. We all had a fantastic time, they all learned the process, and many were inspired to learn the full names of their characters. (It was so exciting to watch!)

These experiences stuck with me when I was deciding on my dissertation focus. In particular, there were three things that followed me into graduate school:

  1. the limited number of resources available to support secondary students in understanding the mechanism of biological phenomena,
  2. the deep capacity of middle school students for mechanistic reasoning, and
  3. the power of a well-designed animation to support robust learning for me and my students.

To help with these problems, I decided to create a photosynthesis animation that focused on the mechanism of photosynthesis such that middle school students (and their teachers) could develop the type of scientific and integrated understanding called for by the NGSS.

After making the animation, I embedded it into an online photosynthesis unit in the Web-based Inquiry Science Environment (WISE) to evaluate whether and to what extent it supported students to meet the NGSS performance expectation for photosynthesis (MS-LS1-6). I found that, similar to my Labs for Learning experience, middle school students are capable of understanding far more complex ideas than we give them credit for (publication under review). Even with as little starting knowledge as knowing the inputs and outputs of photosynthesis, namely that carbon dioxide and water go into the plant and sugar (glucose) and oxygen come out, they were able to learn the biochemical mechanism of the process. While the assessment boundary for the photosynthesis performance expectation states that assessment for the standard does not include the biochemical mechanism of photosynthesis, my findings along with those of numerous other studies say that the middle school students can handle it and can benefit from it in their future STEM learning (Ryoo & Linn, 2012; Russ et al., 2008; Krist et al., 2018). The framework documents for the NGSS, too, recognize the need for understanding mechanisms when developing and constructing scientific explanations (National Research Council, 2012). Answering the call of the NGSS and other ambitious science reform efforts to support students in developing integrated and multi-dimensional science knowledge requires an exploration of mechanisms.

Admittedly, deep exploration into unfamiliar topics is scary, especially as a teacher who is expected to know the answers. But what better way can a teacher support students in the learning process than if they join the process themselves? As the world changes, and learners can look in many places for answers, what they need is not the answer, they need a model of how to learn in a world where information abounds. Such a model will position students to know more than just the answers. They will know how to discover, how to use the wealth of resources available to them to find out. That’s what we can model for our students by learning with them.

At the rate that new information is being generated there is no way any one person can know everything. I suggest, find resources that push you to your edge and invite your students to also explore the edge of their knowledge and ability. You might not know the biochemical mechanism of photosynthesis, for example, but that’s okay, you can learn with them. Find a resource that helps you and scaffold it to help them. Doing so will model for your students how to move from not knowing to knowing a little more, and a little more.

When you do this, you can also help them understand why it matters, and more importantly, why it matters to you. Share with them what’s interesting about the topic to you. Invite them to explore their ideas and share their experience to find out why it matters to them. Position them as pioneers in a space that could make that knowledge worth knowing for someone else. Invite them into the world of imagination and what if; prompting them with, this is the current state but what could be?

These are just some of the learning adventures that you can take with your students. The NGSS is an invitation to deeper more meaningful discovery and learning, for the students as well as the teachers. Your students need a brave guide into the world of the unknown. If you can find resources that allow you to share that space with them, they will appreciate your guidance and example of how to learn throughout their life.

Now that I’ve done this work, I understand how exploring the mechanisms of different phenomena creates rich and transformative learning experiences for ourselves and our students. With the world moving and changing as fast as it is, we need to support students in learning as much as they can, which oftentimes is more than we think!

Acknowledgments. I need to note that the animation discussed here was created in collaboration with a multistakeholder design team, that included disciplinary experts, learning scientists, software developers, teachers and students. My dissertation work was funded by the National Science Foundation (DRL: 1418423; 1813713).

References:
Krist, C., Schwarz, C. V., & Reiser, B. J. (2018). Identifying essential epistemic heuristics for guiding mechanistic reasoning in science learning. Journal of the Learning Sciences, 28(2),
160–205. doi: 10.1080/10508406.2018.1510404

National Research Council. (2012). A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington, D.C.: National Academies Press. doi: 10.17226/13165

Russ, R. S., Scherr, R. E., Hammer, D., & Mikeska, J. (2008). Recognizing mechanistic reasoning in student scientific inquiry: A framework for discourse analysis developed from philosophy of science. Science Education, 92(3), 499–525. doi: 10.1002/sce.20264

Ryoo, K., & Linn, M. C. (2012). Can dynamic visualizations improve middle school students’ understanding of energy in photosynthesis? Journal of Research in Science Teaching, 49(2), 218–243. doi: 10.1002/tea.21003

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two VR goggles hang from hooks

Virtual Reality in K12 Education: A Reality Check

Guest Author, Virtual Reality

by Aditya Vishwanath

Aditya Vishwanath is a PhD candidate and Knight-Hennessy scholar in the Learning Sciences program at the Stanford Graduate School of Education. With his advisors Roy Pea and Jeremy Bailenson, Aditya researches the merits of immersive virtual reality for learning. He is also the co-founder of Inspirit, a 3D and VR lab platform that offers immersive simulations for STEM education.

It is Spring 2015, and schools around the country are being visited by colorful Subarus packed with new ‘Google Cardboard’ headsets: a virtual reality platform that promised to be affordable for classrooms around the world. We imagined the VR platform might be a killer app, which in the tech world means it would make a major impact and everyone would want it. It was called Expeditions and it offered a suite of 360-degree virtual ‘field-trips’ to almost anywhere on the planet, the moon, and inside the human body. I was lucky to be part of a project team from Georgia Tech in 2015 that brought Google Expeditions to a low-income after-school center in Mumbai. Our students and teachers were thrilled to visit the seven wonders of the world or explore a 3D rendering of the human heart with existing basic $30 Android phones and a standard 3G internet connection. Following this project, our team introduced Google Cardboard to a charter school in Atlanta, a Title I school near the Georgia-Tennessee border, and many suburban public schools. Again, more excitement from all involved!

Unfortunately, today, none of the schools we visited in India or the US use Google Expeditions, and our cardboard headsets mostly collect dust on the library shelf. It turns out that the field trips were too disconnected from the syllabi and lesson plans of the teachers. It is 2020, and in a pandemic-hit world where the stage was set for VR and apps like Expeditions to shine, why don’t we see use of this technology in classrooms or the home? What went wrong?

A few numbers: 81% of the USA owns a smartphone and recent statistics show that over 90% Americans live in an area that has access to 4G internet. Shouldn’t we, at the very least, expect to see some use of basic $10 Google Cardboard VR content in classrooms, given the amount of 360-degree field trip content available out there? Clearly, the challenge at hand is not limited to hardware and infrastructural costs of VR. Prices are rapidly falling and access to high-quality VR hardware is steadily improving. So what are some other bottlenecks beyond the technical and cost barriers that we would need to overcome to make VR mainstream in K12? And what can we learn from the Expeditions pilots?

Curriculum and standards alignment
Despite the proliferation of VR education content, there is still a gap between the everyday activities of the classroom and the suite of VR offerings out there. On the cusp of 2020, VR is still a very new medium. And there is still not enough K12 content available to incentivize a school, district, or classroom to invest in this technology. For most teachers, VR is that one-off underwater coral reef educational experience you used with your students in 2016, and now  the headsets collect dust on a shelf. To overcome this gap between content libraries and everyday classroom use, content creators will need to work with curriculum experts to better align content with standards, curriculum, and possibly even develop robust and flexible lesson plans that can support frequent (and meaningful) use.

Integrating pedagogy
VR is new, and with this, it carries a certain charm or ‘charisma’. Most people are overwhelmed by the very first time they experience VR, not because the underlying content experience was good, but because the experience was new. Novelty wears off. Will VR still stimulate the same curiosity and excitement it created the very first time? Scholars like Roy Pea and Chris Dede have demonstrated, through years of research on virtual environments, that designing experiences with sound pedagogical methods allow you to move past novelty. Implementing teaching and learning methods with VR will maintain engagement beyond the initial novelty-phase. Most teachers already know this from their experiences with other digital aids. Most experimental research with VR till date has occurred in expensive labs, often many degrees removed from the complexities of an everyday classroom. In the coming years, we need to witness more real-world VR deployments and studies alongside the rapid growth of VR-education companies.

Tapping into the unique capabilities of VR
Most content creators come to VR with the question,  “How can VR outperform video” but that is the wrong question to ask. Instead, we should ask, “What can VR offer that is impossible to offer with video, or any other medium before VR?” Researchers such as Jeremy Bailenson have consistently advocated that tasks that are physically expensive, dangerous, or impossible to simulate or experience are ideal candidates for VR. It is critical that educators ask fundamental questions: how is VR uniquely adding value to the learning experience? What is it doing that cannot be accomplished by video or any other digital or non-digital learning aid? If we can develop these simple filters and then apply them, we’ll see that most of the unnecessary use-cases that are enamored by the glamor of VR will fall away and we’ll be left with a narrow but very powerful set of application areas that deeply promote learning.

Additionally, collaboration between practitioners, researchers, and developers is key. The VR technology expert needs to build bridges with the district administrator, school teacher, and student. Each group here has a unique area of expertise that will contribute to furthering the collective vision of making VR real for the classroom. We must also support more systematic experimentation grounded in theory with VR learning content in real-classrooms (or homes during remote learning periods) and not protected laboratory spaces to learn what really is needed and what will work.1
As costs keep falling, and as access to quality hardware rapidly improves, we are seeing VR increasingly enter K12 learning environments again. Oculus, which released the popular Quest headset last year, just announced a cheaper and more powerful Quest 2 headset a few weeks ago. Quests are among the first high-end non-tethered consumer headsets that are cheaper than the standard laptop or tablet in your average public school classroom (though there are concerning trends around forcing users to log in with a Facebook account, which will certainly slow down adoption). Is this the beginning of rapid adoption of VR in the classroom? Is VR now here to stay? Or is this another wave of optimism like Google Cardboard and Expeditions? The last thing we want is to build a virtual hammer and search for virtual nails.

Note: This article mostly centers the discussion around the use of mobile-VR and basic headsets, which offer no more than 3 degrees of freedom (or movement) in space (we call these 3dof headsets). Recent research has shown that these 3dof headsets do not necessarily offer any learning benefits besides improving engagement in the short term, and studies show conflicting findings2. Future work may need to focus on immersive, high-fidelity, headsets that offer more degrees of movement — 6dof and above. (Examples include the Quest, HTC Vive, and others.) Findings on training, learning, and learning transfer with these high-end devices are more promising, though there are practical considerations to keep in mind with these devices, since they can be bulky, non-portable, and expensive. This is also something to consider as we go forward.

Thanks, Aditya Vishwanath for sharing this post on VR in K12 classrooms. From CIRCL Educators we want to ask teachers and other practitioners, what are your thoughts on VR in the classroom? How does it work for your students? Do you use it? Why or why not? How does it work for students who have IEPs or physical disabilities? What do developers need to know? Tweet @CIRCLEducators and @Adi_Vish and let us know.

1One project that demonstrates collaboration was led by Laura Shackleford and colleagues: “Teaching social science through virtual reality and game-based learning”

2Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225-236.

abstract wall

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

Computational Thinking, Computer Science, Culturally Relevant Education, Culturally Responsive Teaching, Guest Author

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.

  1. 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
  2. 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).
  3. 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.
  4. 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.
  5. 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
  6. 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
  7. 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).
  8. 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
Close-up of hands on a laptop computer

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

Computational Thinking, Computer Science, Culturally Relevant Education, Culturally Responsive Teaching, Guest Author

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.

  1. 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
  2. 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
  3. 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).
  4. 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
  5. 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
  6. 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.
Dr. Chips in front of water

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

Computer Science, Guest Author

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 students8,9. Alternatively, culturally relevant pedagogy10,11 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.

  1. 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.
  2. Margolis, J., & Goode, J. (2016). Ten lessons for computer science for all. ACM Inroads, 7(4), 52–56. https://doi.org/10.1145/2988236
  3. 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).
  4. 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
  5. Cuny, J. (2015). Transforming K-12 computing education: AP® computer science principles. ACM Inroads, 6(4), 58-49. https://doi.org/10.1145/2832916
  6. 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
  7. 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
  8. Gay, G. (2010). Culturally responsive teaching: Theory, research, and practice (2nd ed).Multicultural Education Series. New York, NY: Teachers College Press.
  9. Gay, G. (2013) Teaching to and through cultural diversity. Curriculum Inquiry, 43(1), 48-doi: 10.1111/curi.12002
  10. 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
  11. 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
  12. 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
Book Cover for Biology Everywhere

Reaching Outside the Classroom: Connecting Science to Daily Life and Other Disciplines

Guest Author, Science

by Melanie E. Peffer, PhD

Dr. Melanie Peffer has a BS and PhD in molecular biology from the University of Pittsburgh and completed a postdoctoral appointment in learning sciences from Georgia State University. She combines her expertise in molecular biology and the learning sciences to study how people learn, understand, and engage with biology content.

When am I EVER going to need to know this?

We’ve all heard students say that before. It’s even more pertinent now in the digital age when so many of the concepts we teach in classrooms are a simple Google search away.

It’s not a matter of if a student needs to know something – but when and how they’ll need the information they learn in our classrooms.

When the time comes in which a student needs to engage with a scientific issue in the course of their daily lives, how can we ensure that students leave the classroom feeling empowered to engage?

Book Cover for Biology Everywhere

Biology Everywhere bridges the gap between the classroom and practical biology knowledge needed in the real world. Copies are available at www.biologyeverywhere.com

I wrote Biology Everywhere: How the science of life matters to everyday life with this question in mind. The bedrock of my book, and the associated online course, seeks to empower individuals to engage with science issues by presenting them through the lens of our daily experiences and in connection with other disciplines. This is especially important to consider in light of the COVID19 pandemic – which is forcing society to engage with science issues on a daily basis.

Teaching science in connection with our daily experiences.

Science content can feel abstract to students. That fuels the idea that science is inaccessible, and drives students away from engaging in the classroom. They feel like they can’t do it, or aren’t smart enough and so they shut down. They disengage with scientific issues, not just in the classroom but in society as well, and may even choose to align what they consider to be good science with their political party affiliation.

When we think about the applicability of science to our daily experiences, the content becomes relatable and therefore more accessible. This approach is also more student driven, too.  One easy lesson that can be done in person or remotely is to task students with finding something interesting or mysterious to them and ask a question about it. Then, build a science lesson around the child’s question. Allowing students to ask their own questions is also a powerful way to deepen student learning and engagement.

child mixes contents in bowl

Cooking and baking is rife with opportunities to talk about practical applications of chemistry.

Kitchen chemistry is very accessible. I cook with my son – and he gets very excited to see the bubbles that appear when we add baking powder to the mix when making pancakes. It becomes a very easy science lesson to talk about the bubbles that form make the pancake fluffy. You can adapt this for an older student by talking about the exact chemical reaction that is occurring. If you aren’t sure, this is an opportunity to look it up and learn together.

In the context of biology, I look towards big issues in today’s society to highlight and discuss with students. When I cover ecology, I demonstrate how ecological principles apply to our daily lives – such as issues around conservation. For example, what makes reusable eco-friendly or not and some of the trade-offs around reusable products. You can watch this video on plastic versus reusable bags that is based on my book here.

Teaching Science in Connection with Other Disciplines

If you think about a traditional school, there are science teachers in a science classroom … the music teacher in the band room … the history teacher in the history classroom. And the history teacher is going to teach … well, history!

In the real world though, the lines between disciplines are much more blurry. Helping teachers connect lessons in their disciplines to science content is a major thrust of Chris Woods’ work with dailySTEM and his podcast series, STEM Everyday.

How about in the context of biology? What if I said art was foundational to biology?

We hear about the STEAM movement – adding an A for arts to STEM. But what does that really mean?

When thinking about how science really works in the real world, it’s fundamentally a creative process. Coming up with new questions to ask, methods for studying the world, and making sense of the data we get – it all requires creativity and thinking outside the box.

The fine arts have had a measurable impact on biological science as well. Take for example Santiago Ramon y Cajal’s drawings of neurons. His ability to accurately draw neurons with his artist’s eye towards form and function led to one of the most important discoveries in the history of neuroscience: that the neuron is the functional unit of the brain, a discovery that continues to inform modern neuroscience.

Or John Audobon’s paintings of birds. Some of the birds he painted, like the Carolina parakeet, have gone extinct – so his paintings are important parts of natural history.

Conversely, biology also tells us about our experience with the arts, too. Why do we feel chills when listening to music? Dopamine release. Dopamine is a neurotransmitter, or chemical that is released by neurons to communicate with one another. Dopamine regulates motivation and pleasure – including the pleasurable responses we have to music. Scientists found that if you inhibit dopamine release, people enjoy music less. If you do the opposite and increase dopamine release, music is even more enjoyable.

Making Science Accessible in Light of the COVID19 Pandemic

The COVID19 pandemic is forcing people to engage with the realities of how science works – and for some, it’s their first experience with the messy, iterative, constantly evolving nature of authentic science inquiry.

The pandemic brought the question “when am I EVER going to need to know this” into a new light. It can’t be avoided or subverted – as a society, we’re grappling with real scientific (and mathematical) issues.

Whether it’s mask wearing, applying the basic principles of life to define what a virus is – and why we can’t treat it with antibiotics, or understanding the process of developing and testing a COVID19 vaccine or treatments, it is necessary for us all to engage with these issues and make informed decisions.

Where to start? We can teach the student in front of us – but also recognize that the general public is struggling too. I suggest we start with building the confidence in science first – present it through the lens of our daily experiences and in connection with other disciplines. Then, when the time comes to engage with scientific issues, people feel empowered to engage and make an informed decision.