In 7th grade, I got my first exposure to programming. At the time, I did not know it, but this one moment would shape a significant amount of my future. This exposure was my father (a software engineer) bringing me into his home office and showing me the block-based visual programming language and website.

Scratch had its public launch 17 years ago. At that time, the iPhone was a month away from being launched, and Netflix sent you DVDs in the mail. Given the times, block-based programming was revolutionary. Fast forward to 2024 – ChatGPT has 100 million weekly users, and autonomous vehicles roam the streets of San Francisco. As technology changes, the way we teach about it must change, too.

The time has come for programming to become a core class for students in grades 6th and up. This would be a radical change to the framework of modern education, and as such, the expectations and pedagogical approach to this class should be radical as well. Before I dive into what I believe a core computer science course would look like, I want to touch on my teaching background and influences.

I teach at a small independent school that practices project-based learning and takes a STEAM approach to education. In my eyes, the most important part of this pedagogy is that we focus more on the “process” rather than the “product”. With this approach, the true purpose of middle school education is fully realized.

Most people do not remember all the books they read in middle school, or every ancient civilization they learned about, or even most of the math equations they were taught… and that’s ok. Middle school, first and foremost, should teach students to be independent thinkers and people. That is to say, it should teach students the importance of taking the “process” of learning seriously. When you have the “process” of learning down, any new “product” you need to produce or problem you need to solve is attainable. The “process” of learning is what allows you to face these new challenges. 

So why computer science? Well, there is the easy argument that computer science and related technology are taking over our world, and to prepare students for the world, we should teach them computer science. While I wholeheartedly agree with this point, I think the real reason why computer science should be taught as a core class in all middle schools is even more compelling. I believe no other subject emphasizes and reinforces the “process over product” model more than computer science, especially if it is taught with this in mind.

Every day, my class starts with the same three words: “ABC: Always Be Coding!” And I mean this. As long as you are coding, you are actively practicing the “process” of learning. There are no compulsory assignments, no tests, and no specific homework. You are just asked to show up and program. Students work independently and at their own pace and follow lessons, projects, and challenges I have pre-created, but if they ever have an idea they would for something they would rather program, they are encouraged to stop those lessons and give it a shot. When they are in my classroom, they are in charge of their learning. This is tasking students with a great deal of responsibility, and there is a world where a student chooses to just write 100 print statements in a row, but that is not how it has ever gone in my classroom. Even with a student who has this mindset, their class typically goes something more like this:

A student comes to class and hears that they are in charge of what they learn and do, with no assignments and no tests. You can see the sparkle in their eyes, and I know they will not get anything done in class for the first week or so. I don’t do much to preempt this outcome, but I do make sure to ensure they have an IDE up and are at least putting a few print statements down. As much as I love programming, even I cannot say that simply writing print statements is enjoyable, and every student who has tried to pull this or something similar comes to the same conclusion. As this is going on, they can hear their fellow classmates having a blast, working on personality quizzes, text adventure games, battle simulators, etc. It is now time to plant the first seed. I don’t give this student an assignment or tell them what to do, but I do go over to their program and type something interesting in, something they can emulate. Maybe it’s changing the text color, or maybe it’s an if statement that prints a funny message with the right input; it depends on the student. After they mess around with this new method of control for a while, they typically ask their first question. “How do I do…” and from there, the process has begun. Going forward, they still may need more redirection and motivation than their peers, but they are actively practicing the “process”.

Even a student like this will at least master if statements and start using basic loops in a trimester. For the rest of the class, the ones who really take control of their learning might get loops mastered or even start using functions. The independence they learn and practice in this class also actively helps me, the teacher, to pay more attention to students who need more help getting motivated.

This model can work for most teachers and students, even with bigger class sizes. And that is not due to anything other than the joy students get from programming. Statistically, computer science/Engineering is second only to Drama/Art as students’ favorite class (Code.org). So not only do students buy in due to the responsibility they are given, but they buy in because they enjoy it.

This pedagogical approach does set teachers up for one very specific yet important challenge: grading. When you don’t give assignments of any sort, and you have some students writing object-oriented programs while other students are barely getting to loops, surely it must be impossible to grade?

If you are focused on “products”, then yes, it is nearly impossible to grade. I tried this once, and it required me to constantly make new assignment rubrics and assign them to students individually on our LMS. It was extremely inefficient and I could never imagine doing it with a class of more than 15 students. But then it hit me. If the focus of the class is on “process”, then shouldn’t the focus of assessment be on “process” as well?

This epiphany has made assessing less stressful and has allowed my feedback to more accurately assess my students’ approach to the learning process. The key that makes this all work is coming up with the right standards to assess on (my school also practices Standards Based Assessment). The following, are the 3 standards I assess students on:

Code Readability: 

This standard promotes best practices in coding, but more importantly, it allows students to more efficiently ask each other for help. Asking each other for help is another way to promote students’ taking control of the learning process in class.

Efficiency:

In addition to promoting best practices in coding, this standard ensures that students think about how they use the control statements they learn about.

Iterative Design:

This standard promotes student investment in the learning process and is by far the most important standard to assess. This assesses students on their willingness to reflect on their work and make it more efficient and readable. If standards are to be a reflection of what you expect from your students, then this one is essential.

With these standards, I am able to assess any student working on any project, regardless of level. When students read their comments, they immediately apply feedback so that with each project, their creative process becomes more efficient. A process-based assessment empowers each student to think critically about how they learn and create.

While there is no doubt that widespread computer science education is increasingly necessary in a technology-centered world, the real reason we need to teach computer science is that it provides a creative environment for students to experiment with the process of learning. If taught in an engaging and student-led manner, we will be able to educate a generation of learners who are prepared for the modern world and all of its challenges.

About the Author

Andrew Verrilli is a passionate computer science educator who currently teaches at Alta Vista School in San Francisco. His classes have included Everyday Programming, Board Game Makers, and Natural Design. One of his favorite projects to work on with students is P Tunes, a web-scraping Python program that saves links to students’ favorite songs on YouTube. Andrew is also an avid egg tosser.

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At the July 2020 meeting, the CSTA Board elected me to serve as Chair-Elect. Serving alongside CSTA Board Chair Jen Rosato, I learned to collaborate with board members, CSTA staff, chapter leaders, members, and other stakeholders to better lead the work of the board. Taking on the responsibility to lead means working closely with Jake Baskin, our executive director. Our leadership was challenged with shepherding the organization through the COVID-19 pandemic. For two years, our events, meetings, etc., were presented and attended virtually.   

At the July 2021 meeting, I started my two-year journey of leading our CSTA Board. I became CSTA Board’s first gay chair. During my time as Board Chair, I learned the amazing opportunity and responsibility it is to lead such a large association. In this role as the chief elected officer, I have learned so much about CSTA, its members, and computer science education overall. Additionally, the Chair leads the Executive Committee, meets every other week with the executive director and chair-elect or past chair, and serves on the following committees: audit, nominations and elections, and governance. I collaborated with the international committee to better identify how CSTA can be a value in other countries. I have been able to represent CSTA’s Board at IDEA Con, CSEd Con, ECEP, CSTA Annual Conferences, CSTA Volunteer Summit, various CSTA virtual summits, ASAE CEO training, CSTA New England Conference, Texas CSTA Chapters Conference, and many impromptu conversations with others. I was able to kick off CSTA Chapter Leadership Summits, learning and collaborating with my fellow chapter leaders. I served as CSTA Dallas-Fort Worth President from March 2018 – October 2024. I have made a number of new friends, colleagues, and collaboration partners through my travels around the country. Through these experiences, I have learned so much from others. This is such a valuable opportunity to learn from people from diverse backgrounds who bring many perspectives I may not have considered.  

Today, I serve out my last year of board service as the CSTA Board Past-Chair and interim Treasurer with Charity Freeman, CSTA Board Chair.  I passed the gavel to Charity during our July 2023 meeting. Serving in my current capacity allows me to serve as an advisor to Charity and Jake Baskin. This year, I will continue my leadership journey by traveling to Washington D.C., for our Computer Science Education Week event at the White House. In February 2024 and again in July 2024, I will visit Las Vegas for our board meetings and our upcoming annual conference. Through virtual meetings, I will continue to serve on the executive board, finance committee, nominations and elections committee, and the CSTA Standards for CS Teachers reflective teachers working group.

My role with Plano ISD changed in July 2023. I am now the Career and Technical Education Coordinator responsible for PK-12 computer science, engineering, and our FIRST robotics program. I now serve as the past-president of CSTA Dallas-Fort Worth. I continue my work in Texas by serving as a member of the Texas Exploring Computing Education Pathways team.  

I will admit these past five years have been a lot of work and opportunities to celebrate our work. I have developed some great friendships with people around the country. Working closely with others focused on developing opportunities for students of all backgrounds and taking away barriers to entries has been an important part of my journey. If you are interested in serving CSTA through board service, please apply to the Nominations and Elections Committee to be considered for this year’s ballot. I am excited to continue supporting CSTA in any way I can going forward. I don’t take lightly the honor of earning a CSTA lifetime membership. If I can support your journey at the school, district, state, or national level, please feel free to reach out. 

CSTA Board Applications for 2024 are now open. Learn more.

About the Author

A public education teacher for twenty years, Dan Blier spent the last seven years as the computer science curriculum specialist for Plano Independent School District. As of July 2023, he was promoted to the position of career and technical education coordinator in the STEM career cluster, which includes computer science, engineering, and robotics.

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Introduction

Since the wide release of Generative Artificial Intelligence (Gen AI) in November 2023, there has been a plethora of discussions on the future of computer science (CS) education. Some have wondered whether CS education is even necessary any longer in light of the speed which GenAI can generate codes. If an article such as “So Much for ‘Learn to Code” is any indication, we might assume CS education is no longer needed in college. After all, using automated tools such as GitHub CoPilot can certainly save so much time that several tech companies have announced layoffs of a large number of employees. According to the media, all coding can now be done by chatbots! 

However, as Equity Fellows of the Computer Science Teachers Association (CSTA), we believe that the expansion of effective CS education for all is needed now more than ever before. In this time of excitement and uncertainty, CSTA is both leading the charge to incorporate AI tools into CS education while debunking a fatalistic view of the future of the CS field. We firmly believe that a stronger educator voice in the age of AI is critical as the pressure to quickly implement AI into the education system intensifies. 

History of Education Technology Implementation

The conversation around rapid AI implementation in education feels rather familiar to many educators. Some argue that this is no different than several previous education technology (a.k.a. edtech) fads that never fulfill their promise. 

In his 2018 article “Twenty Year of Edtech,” Martin Waller enumerated four distinctive reasons why many edtech innovations over time have failed. First, edtech tends to focus more on the tech part rather than the education part. Second, many underestimate historical learning from both the success and the failure of a particular tool that functioned similarly. Third, rather than designing specifically for education, many edtech tools are re-purposed, often incorrectly and hastily, for education. Finally, many edtech developers ignore the complexity of the educational field in other fields, such as banking or media industries that use technologies. 

Regardless of their background in CS and AI, school leaders and educators are (and should be) concerned about this occurring once again as more and more AI tools are being introduced to the marketplace and the education field. Various so-called AI companies are promising the silver bullet to fix education once again, which is why we believe that educators’ and school leaders’ voices are needed to ensure that we do not repeat our past mistakes in edtech implementation. 

Definition and history of AI

Before we transition to what we mean by centering the educators’ voices, it is important that we define what we consider to be AI. According to the recent White House Executive Order, (EO) AI is defined as “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments,” and Gen AI is defined as, “the class of AI models that emulate the structure and characteristics of input data in order to generate derived synthetic content. This can include images, videos, audio, [code], text, and other digital content.”

As school leaders and CSTA Equity Fellows, we want to be clear that AI is not new. AI has been used in niche applications such as intelligent tutoring systems, automated grading, or even early warning systems. For example, we have had voice recognition that generated synthetic contents (i.e. Siri or Alexa giving answers that they found online) for years now. As such, the belief that the use of AI is going to replace CS education or teachers in the classroom is not only absurd but unrealistic. In fact, we believe that an increased investment in CS education is crucial, given the growing need for AI literacy throughout the education system.

Increased importance of CS Education in the age of AI

As educators and school leaders, we want to acknowledge that chatbots can code much quicker than a person, which is one of the benefits of automation. Just as producing words quicker doesn’t necessarily improve the quality of one’s writing, being able to code faster doesn’t mean that the outcome will be better. In fact, we have seen erroneous products being mass-produced by AI generators. 

We must remember that CS education goes beyond teaching students to code. In fact, coding skills often are secondary to CS education. Research has shown that engaging students in creative programming activities is the best way to help them develop computational thinking (CT) skills. In the age of AI, integrating CT skills and CS education into their curriculum has become more important for our students than ever before. Because it allows us to equip students with the ability to understand and critically evaluate AI-generated content, address bias issues, ensure transparency and accountability in AI systems, protect student data and privacy, and ultimately, shift the focus towards human-centered computing and learning.

What can CS teachers do? 

As Equity Fellows and practitioners, we believe that the conversation around AI in education and CS education must center educator voices. Two ways that we can achieve the goal are: 

(1) Advocate for a clear and comprehensive policy on AI in education for the protection of all participants in the education field.

(2) Focus on developing and implementing a human-centered CS curriculum.

1. Advocate for a statewide AI policy grounded in research

In a recent Scientific American article, Lauren Leffer referred to a study that showed that “the participants who received the fake AI suggestions went on to incorporate the same bias into their future decisions, even after the guidance was no longer offered” (Leffer, 2023). Of course, one can argue that being exposed to incorrect information can have a lasting impact on the learner. However, a number of research on misinformation in media indicates that AI-generated content holds additional weight and influence on the learners. 

Therefore, we as educators must demand that all States create strong policies and regulations to address issues related to AI, including bias, transparency, and accountability. Although the White House has created the Blueprint for an AI Bill of Rights, we argue that each state should create a robust policy on the proper use of AI for its own education system that includes guidelines for ethical and responsible use of AI technology. 

We recommend that each state ground its policies on AI in the EO that focuses on five key principles: (1) safe and effective systems, (2) algorithmic discrimination protections, (3) data privacy, (4) notice and explanation, and (5) human alternatives, consideration, and fallback. These principles underscore the importance of developing and using AI in a manner that respects individual rights and societal values, which should allow for extensive discussion in CS  classrooms.

2. Focus on developing and implementing a human-centered CS curriculum

In the realm of human-centered computing and learning environments, CS educators play a pivotal role in shaping the narrative around AI integration. Emphasizing a focus on human-centric approaches, as stated by the California Department of Education’s Learning with AI, Learning about AI, all educators should be involved in guiding students to explore the ethical dimensions of AI and its impact on society. For CS educators, this mandate leads to additional obligations of developing and implementing a technical curriculum of coding to create just and ethical algorithms based on ethically collected data sets.  

While all educators should use existing curriculums, such as Common Sense Media’s AI Literacy Curriculum that encourages discussions on responsible AI usage, CS educators must teach their students to learn to align technological advancements with human values. This emphasis not only equips students with the necessary technical skills but also instills in them a sense of responsibility and awareness regarding the societal implications of AI, moving beyond simply coding. 

To achieve that goal, we recommend that CS educators consider doing the following:

1. Become familiar with common terms and definitions and explicitly teach them to the students.
2. Review reputable publications, such as the Artificial Intelligence and the Future of Teaching and Learning and its Core Messages, and share the learning whenever possible.
3. Implement curriculums created by and for teachers, such as Code.Org. 
4. Create professional learning opportunities for fellow CS educators and share resources via organizations such as CSTA.

Conclusion

In light of the rapid advancements in AI and its widespread integration across various sectors, including education, we believe in the growing importance of CS education. With the evolution of technology, there is a parallel need for educational methods to evolve, such as incorporating CT and human-centered computing into all school curricula. Educators, particularly CS teachers, are key in helping students navigate the complexities of AI and its effects on society. Adopting a human-centered curriculum that is anchored in ethical standards and policies is crucial for all students, and CS teachers must spearhead this vital educational shift. Our future depends on it!

Disclaimer: This post was written 100% by human authors, not generated by an AI.

References

1 Korducki, K. M. (2023, September 26). So much for “learn to code.” The Atlantic. https://www.theatlantic.com/technology/archive/2023/09/computer-science-degree-value-generative-ai-age/675452/

2 Gleeson, C. (2024, January 10). Amazon Is Laying Off Hundreds Of Twitch, Prime Video And MGM Studios Employees. Forbes. https://www.forbes.com/sites/caileygleeson/2024/01/10/amazon-is-laying-off-hundreds-of-twitch-prime-video-and-mgm-studios-employees/?sh=58f42/45a1d

3 Weller, M. (2018, July). Twenty Years of Edtech. EDUCAUSE Review. https://er.educause.edu/articles/2018/7/twenty-years-of-edtech

4 Executive Office of the President. (2023, October 30). Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. The White House. https://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/

5 J. R. Carbonell, “AI in CAI: An Artificial-Intelligence Approach to Computer-Assisted Instruction,” in IEEE Transactions on Man-Machine Systems, vol. 11, no. 4, pp. 190-202, Dec. 1970, doi: 10.1109/TMMS.1970.299942.

7 Leffer, L. (2023, October 24). Humans Absorb Bias from Al-And Keep It after They Stop Using the Algorithm. Scientific American. https://www.scientificamerican.com/article/humans-absorb-bias-from-ai-and-keep-it-after-they-stop-using-the-algorithm/

8 The White House. (2023, November 22). Blueprint for an Al Bill of Rights / OSTP | The White House. https://www.whitehouse.gov/ostp/ai-bill-of-rights/

9 California Department of Education. (n.d.). Learning With AI, Learning About AI – Computer Science. https://www.cde.ca.gov/pd/ca/cs/aiincalifornia.asp

10 Common Sense Education. (2024). AI Literacy Lessons for Grades 6–12. from https://www.commonsense.org/education/collections/ai-literacy-lessons-for-grades-6-12

11 Ruiz, P., & Fusco, J. (2024). Glossary of Artificial Intelligence Terms for Educators. https://circls.org/educatorcircls/ai-glossary

12 U.S. Department of Education, Office of Educational Technology. (2023). Artificial Intelligence and Future of Teaching and Learning: Insights and Recommendations. https://tech.ed.gov/ai-future-of-teaching-and-learning/

13 U.S. Department of Education, Office of Educational Technology. (2023). AI and the Future of Teaching and Learning: Core Messaging Handout. https://tech.ed.gov/files/2023/05/ai-report-core-messaging-handout.pdf

14 Code.org. (2024). Artificial Intelligence. https://code.org/ai

About the Authors

Dr. Kip Glazer

Dr. Kip Glazer is a proud Principal of Mountain View High School in Mountain View California, home of Google and in the heart of Silicon Valley. She is a 2023 CSTA Equity Fellow and a member of the Engage AI Practitioner Advisory Board. Prior to becoming a principal, she was a classroom teacher, technology coach, and administrator. As an immigrant and English-language learner, she is passionate about leveraging learning technologies to augment learning opportunities for historically underserved populations of students. For nearly a decade, Kip has worked with a number of learning science researchers in connecting research to practice in the K-16 education space. In recent years, she participated in several AI-related webinars hosted by Educator CIRCLS, a project funded by the National Science Foundation. She also participated in the webinar hosted by the US Department of Education’s Office of Education Technology at the launch of the official report, “Artificial Intelligence and the Future of Teaching and Learning.” She has written several book chapters and blog posts on AI, game-based learning, and the proper use of education technology. She is an experienced writer, speaker, and presenter. You can find her on LinkedIn.

Dr. Sonal Patel

Dr. Sonal Patel is a CSTA Equity Fellows and a Program Manager for Computer Science and Digital Learning at the San Bernardino County Superintendent of Schools. She works with her team to build, plan, and facilitate the design, development, and implementation of equitable educational technology and Computer Science programs. Sonal continues to work closely with educational partners to help lead county and state-wide efforts in broadening K-12 access and participation in Computer Science. In addition to this, she is working alongside the California Department of Education to expand awareness and understanding of how artificial intelligence can transform K-12 education. Dr. Patel’s dedication to the advancement of educational technology and her deep commitment to fostering inclusivity have resulted in a remarkable impact on the educational landscape in San Bernardino County and beyond.

The post The Evolving Landscape of Computer Science Education in the Age of AI — Recommendations for Computer Science Educators appeared first on Computer Science Teachers Association.

All that Dan does is informed by his desire to help his students find joy in learning. When his school rolled out a computer science initiative three years ago, Dan jumped at the opportunity to be a part of it. “I have never had more fun teaching,” he says. In a school where all the students have an IEP, he’s found that computer science is a great way to learn joyfully and collaboratively. His teaching practice incorporates “We Do” coding, where he lets his students follow along as he codes. To encourage participation, he’ll make deliberate mistakes, giving students the opportunity to jump in and tell him where he went wrong. Dan says, “I can’t stop smiling when this happens. They are learning!”

His computer science discoveries class is a space of exploration and creativity. It helps demystify the practice of computer science, and students can have fun creating their own apps and web pages. To accommodate the many learning needs of his students, Dan incorporates text readers, extended time, and teamwork into his practice, with great results. “Success is also measured by student engagement,” he says. “Is there laughter in the room? The only time the room should be quiet is when we’re taking a test.” The rest of the time, he wants to see active participation and collaboration. Dan is proud to report that out of his 96 computer science students, 92 of them have passed his class with a grade of C or higher.

In the same vein, his esports team lets students see the many skills that can be learned from playing video games, especially teamwork and strong communication. He encourages his students to think actively and critically about the games they’re playing, with group discussions on what the students would change and improve about each game.

Dan is constantly seeking out new learning opportunities to improve his teaching practice. He’s a NASA Connects member who volunteered to beta-test the new SPARX curriculum, which takes a collaborative, hands-on approach. He is taking part in a year-long fellowship with Urban Arts to teach AP computer science through video game development, and he also participated in a PD opportunity, CS Inclusion for All, that highlighted strategies for teaching computer science to special-needs students. He was a member of the first cohort of a QEM Network program designed to connect quality CS teachers of underserved students, and he will speak at an upcoming training for the next cohort.

As Dan heads into his time as a CSTA Equity Fellow, his greatest desire is to form strong connections with his cohort and find learning opportunities to improve his personal practice as a CS teacher for special-needs students. “I am open to taking as many training sessions as humanly possible,” he says. Knowing how much he has benefited from the professional development he’s experienced, Dan is eager to create PD opportunities to encourage other teachers to incorporate computer science into their teaching. “Computer science is so much more than coding!” Dan says. He’d love to create mini–computer science lessons that could be included in many different subject areas. Drawing on his background of working with special education students, he would also love to build on his CS Inclusion training to find new ways to teach computer science to all students.

Dan says, “I hope to build new friendships, so that together we can raise awareness about the inequities in computer science and help change this field for the better.”

The post Joyful and Collaborative Computer Science with CSTA Equity Fellow Dan Jones  appeared first on Computer Science Teachers Association.

Introduction

As an ESE computer science teacher, I have made it my mission to ensure that all students have the chance to explore the amazing world of computer science. A disability shouldn’t limit your educational opportunities. You cannot spell disability without ability. Everyone deserves equal access to education, and accommodations should be provided to ensure that individuals with disabilities can thrive in this field of study. I feel extremely privileged to have been selected to participate in a yearlong UDL4CS (Universal Design for Learning Computer Science) educational cohort training program. Through this program, I met Dr. Maya Israel and Dr. Joanne Barrett from the University of Florida and have learned how to implement and continually apply the UDL4CS guidelines in my classroom.

In the rapidly evolving landscape of technology, computer science education has become a crucial component of a well-rounded curriculum. However, ensuring equitable access and participation in computer science for special needs students remains a challenge (Stark, Reich, 2023). This article explores the equity gap in computer science education and highlights the importance of Universal Design for Learning (UDL) and other strategies in creating an inclusive learning environment. 

The Equity Gap

Special needs students often face barriers in traditional computer science classrooms, hindering their ability to fully engage with the material. From physical challenges to diverse learning styles, these barriers contribute to an equity gap in computer science education. Special education is often left out of the decision-making process when it comes to technology and other academic pathways (Stark, Reich, 2023).  To address this, educators must adopt inclusive approaches that cater to the unique needs of every learner. 

Universal Design for Learning

UDL is a framework that aims to create flexible learning environments that accommodate diverse learners. In the context of computer science, UDL involves providing multiple means of representation, engagement, and expression. For instance, incorporating visual aids, auditory resources, and hands-on activities can enhance comprehension and participation for special needs students (CAST, 2018). Incorporating a UDL approach to computer science education at my special needs school has helped me to open the doors of computer science for my K-12 students. 

Breaking Down Lessons

1. Visual and Auditory Representation: Utilize visual aids such as infographics, diagrams, and videos to supplement textual information. Provide audio descriptions for visual content to support students with visual impairments (CAST, 2018). 

2. Hands-On Activities: Incorporate interactive and tactile elements into lessons to engage students with different learning preferences. Use physical computing tools or adaptive technologies to enhance hands-on experiences (CAST, 2018).  

3. Adaptive Resources: Offer personalized learning materials based on individual needs. Provide access to assistive technologies, such as screen readers or speech-to-text tools, to accommodate diverse learning abilities (CAST, 2018).  I like to use text-to-speech whenever possible. The learning platform my district uses has the ability to enable this function, I enable it for every assignment.

4. Flexible Assessments: Implement varied assessment methods, allowing students to demonstrate understanding through different modalities. Consider project-based assessments that showcase practical application of computer science concepts (CAST, 2018). 

5. Collaborative Learning: Foster a supportive and collaborative learning environment where students can learn from each other.  Encourage peer mentoring and group activities to enhance social interaction and cooperation (CAST, 2018).  

Bridging the equity gap in computer science education for special needs students requires a holistic approach. Universal Design for Learning, along with other inclusive strategies, plays a pivotal role in creating a supportive and accessible learning environment. By embracing diverse learning styles and addressing individual needs, educators can pave the way for a more equitable and inclusive future in computer science education for all students. As I enter my third year of teaching computer science, I am extremely excited to write that this year my high school special needs students are taking AP computer science for the first time ever at my school.

References

CAST (2018). Universal Design for Learning Guidelines version 2.2. Retrieved December 30, 2023 from http://udlguidelines.cast.org

Stark, A. Reich, S. (2023) “What about special ed?” Barriers and enablers for teaching with technology in special education [electronic version]. Science Direct, 193, 1-17. Retrieved January 6, 2023, from https://www.sciencedirect.com/science/article/pii/S0360131522002366#abs0010

About the Author

Dan Jones is in his third year of teaching computer science and sixth year of teaching special needs students at Whispering Pines Educational Center in Miramar, Florida. He takes great pride in connecting the world of computer science to his student’s everyday lives. He is a graduate from Florida International University with a master’s degree in higher education administration. He is also a doctoral candidate in K-12 organizational leadership. Dan’s true passion is his love of education and his desire to elevate his students to the next level of their educational journeys. He is committed to creating a career pathway program for his students and helping them find out what their passion for the future is. He brings a diverse technical background to classroom having spent 22 years as a Cadillac and ASE certified master technician. He is relentless in his pursuit of learning and teaching computer science and is currently working on completing the requirements for a STEM teaching fellowship at Florida Atlantic University. He is a 2023 CSTA Teaching Excellence regional award winner. He is the robotics and Esports coach at his school and hosts gaming tournaments for his students when they are not competing against other schools. He recently won a gaming lab, seven Alienware Gaming Computers through High School Esports League (HSEL) and is having a blast teaching AP computer science this year. He believes that everyone can learn computer science.

The post Bridging the Equity Gap in Computer Science Education for Special Needs Students: A Focus on Removing the Dis-Ability Label and Letting Students’ Abilities Shine. appeared first on Computer Science Teachers Association.

By: Kate O’Brian

As fears about widespread cheating with AI have been assuaged in recent headlines, I have a confession to make: I’ve been using technology to “cheat” on everyday tasks since working towards my undergraduate degree. On top of that, I believe it’s about time teachers start “cheating” more often with automation and AI. 

Of course, I don’t mean “cheating” as in plagiarism or dishonesty. I started my career in the studio art world, so I’m usually the first person to insist we give credit where credit is due and strive for authentic, original, and meaningful work. But what about professional tasks that require none of those qualities—authenticity, originality, or meaning? What about the rote administrative work that makes up a large portion of the increasingly-demanding workloads that still threaten teacher retention and wellbeing post-pandemic?

To illustrate what kind of “cheating” could help teachers stay teaching for longer, I’ll share a snapshot from my undergraduate years: when I was studying Studio Art, I couldn’t get into Design 101 until my very last semester in college. By then, I was a full-blown graphic design geek with all but one course’s worth of traditional art training far behind me. But during the height of the pandemic, with all on-campus studios shut down, I was asked to find time—and, more importantly, space undisturbed by my five chaotic roommates—to go back to all the messy basics. 

Rather than convert my bedroom in our packed DC townhouse into an oil painting studio, I did what graphic designers do best: I learned to thrive within my constraints. Using as much of the traditional methods as I could, I’d leverage my tech skills when space or materials ran out. The nearly-finished still life painting became a mini multimedia masterpiece with a few Photoshop touch-ups. The tarot-inspired paper cutting took off with some help from the laser cutter reserved at the library’s Maker Hub. And, most importantly, making do with my strengths and resources allowed me to spend my time and energy on personal priorities rather than the world’s limitations that semester. 

I see a clear parallel between those pandemic-era digital workarounds and the tech landscape that teachers are facing today. The web is buzzing with hype around emergent technologies like automation and artificial intelligence, but spectators seem decidedly split on whether or not it’s acceptable to leverage them in all aspects of daily life. The pandemic had a devastating impact on the teaching workforce, and teachers who remain in the field are in desperate need of effective strategies to manage multiple responsibilities while also preventing burnout. Artificial intelligence and automation, at their best, can be a part of one such strategy. After all, teachers aren’t often hired for their meticulous formatting abilities or email-drafting prowess. We’re in this field because of our creativity, passion, and empathy, so actually applying those skills should be our top priority. 

I’m a firm believer that using automation and AI at work is far from unethical. These innovations can actually allow educators to spend more time and resources on aspects of teaching that make good teachers truly irreplaceable. Here’s why:

• Building Relationships & Rapport: The power of student-teacher relationships to support academic achievement is old news for many educators. Nonetheless, it can be hard to find the time for interpersonal priorities when an overflowing inbox and last month’s ungraded assignments are calling your name. When digital tools cut down on time spent record-keeping, planning, and assessing, teachers have more bandwidth to make relationship-building with students a priority. And while AI can easily help out with rote administrative tasks, it will never be as personable as a real person. 
• Applying Creativity vs. Generating Content:  News stories like The New York Times’ recent lawsuit against OpenAI may sound discouraging and even dystopian, but they also point out an intriguing imbalance in AI’s abilities. AI is extremely skilled at copying what’s already out there, but not so great when it comes to imagination and personalization. That means AI might be better than you at coming up with a general standards-based lesson plan in 60 seconds flat, but it’s still no match for the creative ways you integrate in-depth knowledge of your student population into your teaching. You can leverage technology guilt-free for basic formatting and idea-generating tasks knowing full well that your creative personal touch is what makes your teaching truly meaningful.
• Modeling a Growth Mindset: I know firsthand how tempting simple shortcuts can be in a field where “busy” sometimes means you’re only five minutes ahead of your students. But it’s important for students to see our humanity through imperfection. While I always automate my lesson plan format these days, I take the extra time to create lesson content from scratch and later share successes and failures honestly with students. That way, I model the power of yet for my students and then iterate on those lessons with confidence knowing that my efforts will support student success in the future. While AI-generated one-off activities can fill time in a pinch, your evaluation, reflection, and iteration are what make custom lessons worth refining and repeating.

Make It Matter – Applying Automation & AI to Teacher Prep & Planning

If you’re new to AI and automation or eager for more ways to take advantage of technology in the new year, these starting points can help you make the most of your time in 2024:

1. Test out automation with templates: I’m quite particular when it comes to formatting: I used to spend hours poring over my lesson plans to perfect every element. While there’s nothing wrong with being detail-oriented, automating my lesson plan format with Google Apps Script has freed up countless hours to spend on collaboration and innovation instead without sacrificing creativity or quality. I highly recommend creating templates you can auto-fill with Google Form responses for standardized documents like lesson plans, grading, and more. Though it does require a bit of time upfront, this detailed tutorial walks you through setting up custom automations with templates in Google Workspace. Thank me later!
2. Use AI’s strengths to your advantage: Though “generative AI” and “prompt engineering” have quickly become a part of our modern lexicon, you might still be wondering how they relate to teaching. AI’s greatest strength is generating content based on user input—the more specific and detailed the prompt you input is, the better the generated output will be. There are plenty of AI-powered tools for teachers customized for specific tasks—my team leader recommends Magic School, QuestionWell, Diffit, and Beautiful.ai. But beyond specific platforms, brushing up on prompt engineering for educators can empower you to use AI to its greatest potential in all aspects of your teaching practice.
3. Be a role model for responsible tech use: Though we can’t control students’ exposure to emergent technologies, we can help them engage responsibly and critically with our rapidly-changing tech landscape. OpenAI, the creators of ChatGPT, published some suggestions for using AI effectively and ethically in the classroom, but it’s important to note that exploration is only recommended—with parental consent—for students ages 13 through 18. Nonetheless, discussing AI with younger students in developmentally-appropriate ways can spark conversations around the ethics of remixing, critically analyzing information using primary sources, bias in AI, and so much more. CSEd organizations like Day of AI offer great Intro to AI lessons by age and grade, so you can find an entrypoint that best suits your specific student population. 

Fearlessly engaging with AI tools as educators and openly discussing their superpowers and limitations with our students is a great way to empower them to be 21^st-century thinkers and creators. Cheers to a productive and AI-powered new year!

Citations & Further Reading

Cheating Fears Over Chatbots Were Overblown, New Research Suggests

How School Leaders Can Rebalance Teachers’ Job Demands and Resources – Edutopia

Design Constraints Are Not Restraints – They Stoke Creativity – Designers

Maker Hub – Georgetown University Library

Teachers Partnering with Artificial Intelligence: Augmentation and Automation – Digital Promise

Two Years Later: How COVID-19 Has Shaped the Teacher Workforce – NIH National Library of Medicine

Improving Students’ Relationships with Teachers to Provide Essential Supports for Learning – American Psychological Association

The Times Sues OpenAI and Microsoft Over A.I. Use of Copyrighted Work – New York Times

The power of yet | Carol S Dweck | TEDxNorrköping

Iterating – Chicago Public Schools

Google Apps Script for Education: Enhancing Classroom Efficiency

The Magic Automatic Lesson Planner with Google Forms

7 AI Tools That Help Teachers Work More Efficiently – Edutopia

Prompt engineering for educators – making generative AI work for you

Magic School – Join over 900,000 teachers saving time using MagicSchool to help lesson plan, differentiate, write assessments, communicate clearly, and more

QuestionWell – A.I. to help teachers do their homework

Diffit – Teachers use Diffit to get “just right” instructional materials, saving tons of time and helping all students to access grade level content

Beautiful.ai – Introducing generative AI presentation software for the workplace

Teaching with AI – Open AI: “We’re releasing a guide for teachers using ChatGPT in their classroom—including suggested prompts, an explanation of how ChatGPT works and its limitations, the efficacy of AI detectors, and bias”

Day of AI – Curriculum: All Grades | Ages 5-18

About the author

Kate O’Brian is a Makerspace, Art, and STEAM Educator for grades 1-6 at AIM Academy in Conshohocken, PA. Inspired by her CSEd research with Dr. Yasmin Kafai and her experience as an LD teacher, Kate began her Make It Matter series to connect academic findings to her teaching practice and share these connections with fellow educators around the globe. 

Linkedin | YouTube 

The post Automation & Artificial Intelligence for Educators: Making Time for What Matters in 2024 appeared first on Computer Science Teachers Association.

“Coming from the Diasporan (Black) and LGBT communities,” says Victor, “my lived experiences inform my commitment to breaking down barriers and building bridges.” He maintains a particular focus on supporting Black women and girls to overcome the barriers that have led to their systemic underrepresentation in computer science. Through Coding with Culture, he partnered with several Atlanta metropolitan area schools and youth programs,  which serve a  majority-Black population of K–8 students, to craft a dynamic computer science curriculum that encouraged students to envision themselves as leaders and innovators in the technology fields. Victor notes that many of the students went on to choose HBCUs and MSIs for their college education.

Victor makes a point of creating a safe, open culture in which students feel comfortable sharing their experiences. As a member of the LGBT community, he was able to be an ally to other LGBT+ students, and he works hard to “foster an environment where they feel heard, valued, and empowered in their learning.” This environment, in turn, leads to better classroom discussions, more robust student participation, and positive feedback on the experience from his students.

Victor extends his personal impact by offering training to educators serving marginalized student populations, especially in Black communities. Coding with Culture makes use of the principles of the Abolitionist Teaching Network, as well as the Kapor Center’s Culturally Responsive-Sustaining Computer Science Education framework, to ensure that Black history, culture, and excellence are foregrounded and honored throughout his educational practice. As part of his commitment to creating “equitable, joy-filled learning environments” for Black students, Victor created a unit called “Design a Minecraft HBCU” that weaves HBCU institutional history together with technical learning. Such efforts are designed, he says, to “nurture a profound sense of belonging and identity, anchoring students’ engagement in a broader social context.”

The work doesn’t stop at the classroom. Victor maintains a longtime partnership with InspiredU, an organization attempting to combat Atlanta’s digital divide through workshops and distribution of tech hardware. He partnered with the Pinky Cole Foundation to sponsor Black female students to participate in CodeHouse’s Tech Exposure Day. He’s also partnered with Mr. Odie Gray, and with the Diversity Cyber Council  which provides free computer science workshops and trainings to teens and young adults  from the Atlanta area who might not otherwise have access to such opportunities. Victor’s organization, Coding with Culture is also partnering with Decatur Makers to provide over 500 scholarships for Google Career Certificates in 7 areas through Grow with Google’s partnership program. 

Victor wants to use his time as a CSTA Equity Fellow to acquire new skills and tools to support computer science education for marginalized groups. He says, “I am committed to using this fellowship to amplify my advocacy voice and drive change for historically excluded communities.” The importance of collaboration with like-minded peers has always been key to his practice, and he can’t wait to learn from and with his cohort. He hopes to build new connections among the many organizations working to bridge gaps in equity.

Continuing his work with HBCUs, Victor hopes to develop a professional development series tailored to pre-service teachers studying at HBCUs, to ensure that new teachers will understand how to incorporate computer science and computational thinking into their classrooms. He would also like to curate a database of women working in CS and STEM fields as a means to connect Black and Brown students with professionals who share their identities. Finally, he’s eager to raise awareness of CS and tech news from HBCUs through an increased social media presence or even a podcast. He says, “Raising awareness about HBCUs as viable pathways to tech careers will help students from underrepresented backgrounds see these institutions as supportive environments offering excellent opportunities in the tech field.”

Victor’s excited to keep pushing for systemic change in CS education, with the collaboration of his cohort. He recognizes that “achieving equity requires collaboration and partnerships—a systems-level approach that acknowledges the interconnectedness of all communities,” and he hopes to forge those connections during his fellowship.

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Cynthia states that her mission as an educator is to “empower as many students as possible through academic exposure to help students have a voice and reach their full potential.” When she first learned about the inequities that exist for Black students in computer science, she was disappointed and angry. “I wanted to blame others,” she says. “Instead, I decided to be that change agent.” She took it upon herself to start learning about computer science and incorporating it into her curriculum and afterschool programs.

When Cynthia questioned the lack of Black and Latinx students in invention conventions (a computer science–heavy event) and in computer science demonstration videos, she heard that Black students’ reading skills weren’t good enough to start learning computer science at younger ages. She was told that “maybe in middle school, the teacher would introduce the computer.” This experience inspired her disrupt inequities for her young Black student, and she advocated tirelessly for more computers in elementary classrooms. With a bank of five computers for her class of 25, she shared Code.org with her students, and they began to learn coding together.

From there, it was off to the races! Cynthia continued to seek out development opportunities that would enable her to teach tech skills to her students. She launched afterschool coding classes, to which she continues to add new components like podcasting, videography, and writing, using Soundtrap, Adobe Express, and the Google and Microsoft suites of office software. In the current school year, she is adding sessions on computational thinking and careers in computer science, and her students will get to make use of tools from micro:bits to Raspberry Pi to Hummingbird Bit Robotics Kits. She also partnered with Girls Who Code to create a coding club for girls and nonbinary students, and with Amazon Future Engineers to create one for boys and nonbinary students, allowing students to choose the club that feels most comfortable for their gender alignment.

Throughout her career as a computer science educator, Cynthia has proactively sought out partnerships and platforms to improve her students’ experience and access to new opportunities. As the lead teacher for her school’s partnership with the Museum of Science and Industry, she receives monthly trainings and leads in the creation of action plans for equitable, schoolwide access to STEM and computer science education. She has taken advantage of development opportunities wherever she can find them, including robotics training through Infosys, training on paper circuits through Chibitronics, and training on Scratch via Girls Who Code. Each of these educational opportunities has provided Cynthia with new sets of tools and skills, and her goal throughout is to find new ways to, in her words, “close learning gaps and give students a voice that empowers them.”

As a CSTA Equity Fellow, Cynthia hopes to learn more about the inequalities that exist in computer science and the strategies her cohort of fellows have used to disrupt them. The diversity of perspectives this fellowship offers is a true draw for Cynthia, who says, “I want to collaborate with others with similar thoughts and those who differ.” Using an inquiry-based approach, she hopes to develop her skills as a computer scientist and an educator, digesting as many new concepts, tools, and ideas as she can over the course of her fellowship.

“Basically,” Cynthia says, “I want to be proactive.” She hopes to create written action plans that identify strategies and training opportunities to create more equitable computer science classrooms. She believes in the value of trainings offered “for teachers by teachers and for students by students.” Through collaboration, hard work, and perpetual learning, Cynthia believes she will emerge from the fellowship “as a more robust and wiser change agent for CS education.”

Cynthia can’t wait to work with her cohort to “change mindsets in the CS world, one classroom at a time!”

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Introduction

Imagine a symphony of marching bands, their rhythmic pulse mirroring the beating heart of the community. This is Umoja, unity in action, a principle that echoes through the code of computer science, guiding us to break down complex challenges into harmonious steps. Kwanzaa, celebrated from Dec.26 to Jan. 1, illuminates the vast heritages of the African diaspora. Its regal name, derived from the Swahili phrase “matunda ya kwanza” (first fruits), is rooted in seven core principles, the Nguzo Saba, which serve as a foundation for community development and personal growth. These principles aren’t confined to a holiday; they pulse through the lives of those in the Diaspora, a code in our DNA, driving us forward like a tide against the shore, eroding walls of injustice, and carving a path towards liberation. We didn’t create these principles; we’ve lived them:

• Umoja (Unity): Fostering unity in the family, community, nation, and race.
• Kujichagulia (Self-Determination): Defining and shaping one’s own identity and destiny.
• Ujima (Collective Work and Responsibility): Building and maintaining community together, and solving problems as a collective.
• Ujamaa (Cooperative Economics): Supporting and growing businesses and movements that benefit the entire community.
• Nia(Purpose): Developing a collective vision for community building and development.
• Kuumba (Creativity) Using creativity and innovation to improve the community.
• Imani (Faith): Believing in the community, its leaders, and the righteousness of their struggle.

In parallel, computational thinking is a problem-solving process essential in the field of computer science, but its application extends far beyond. It involves several key skills:

• Decomposition: Breaking down complex problems into smaller, more manageable parts.
• Pattern Recognition: Identifying similarities and differences to help solve problems.
• Abstraction: Focusing on important information only and ignoring irrelevant details.
• Algorithmic Design: Developing step-by-step solutions for problems.
• Efficiency: Solving problems in the most effective and resourceful way, optimizing processes to achieve goals with minimal waste of time and resources.
• Innovation: Devising novel solutions and approaches to complex problems, often by combining existing concepts in creative ways
• Critical Thinking: Systematically evaluating and synthesizing information to make logical decisions and solve problems effectively. 

This article explores how the principles of Kwanzaa resonate with and reflect the components of computational thinking. It delves into the ways these cultural values can enhance and inform the skills necessary for effective problem-solving in the modern technological landscape.

1. Umoja and Decomposition

Umoja, the principle of unity, emphasizes fostering togetherness within families and communities, highlighting that collective efforts surpass individual actions. In computational thinking, this aligns with decomposition, the process of breaking down complex problems into smaller, more manageable parts. Applying decomposition to community challenges allows for addressing large issues by dividing them into specific, smaller challenges. This method enables individuals or groups within the community to tackle these challenges effectively based on their unique capabilities and resources.

2. Kujichagulia and Algorithmic Thinking:

For instance, in addressing a community-wide issue like educational disparities, decomposition involves pinpointing specific elements such as resource accessibility, teacher-student ratios, or the availability of after-school programs. By focusing on these distinct aspects, various community members can contribute to solving each part, thereby collectively addressing the larger problem. This approach not only simplifies problem-solving but also fosters community participation and unity, as everyone works together towards a common goal, embodying the essence of Umoja through collaborative effort and shared responsibility.

Think of the countless black coders who, despite systemic barriers, carved their own paths in the tech world. Like Katherine Johnson, whose meticulous calculations fueled NASA missions, they embodied Kujichagulia, self-determination. Their journeys reflect the methodical planning of algorithmic thinking, each step carefully chosen to navigate the labyrinth of challenges toward their ultimate goal.

This methodical planning, reflective of Kujichagulia, empowers the student to break down their larger goal of a successful Computer Science career into manageable steps. It involves a series of conscious decisions and actions, each step carefully aligned with their ultimate objective of excelling in the field of technology. This approach not only ensures a focused educational journey but also embodies the essence of self-determination in shaping their future in the tech industry.

3. Ujima (Collective Responsibility)  & Pattern Recognition:

Historically Black Colleges and Universities (HBCUs) and the Black community stand as testaments to the transformative power of collective action, where shared responsibility paves the way for innovative solutions. This principle aligns with pattern recognition in computational thinking, where identifying trends and behaviors informs effective decision-making. In the context of HBCUs, this could involve analyzing data on student performance and outcomes to tailor educational programs and resources, ensuring they meet the specific needs of the student body. By recognizing and responding to these patterns, HBCUs can enhance their support systems, leading to improved student success and well-being.

4. Ujamaa (Cooperative Economics) & Abstraction:

Ujima, the Swahili principle of collective responsibility, beats at the heart of the Black community’s approach to tackling systemic issues. By weaving together insights from lived experiences with data-driven analysis, communities can recognize patterns of inequity in health, employment, and housing. This shared knowledge becomes the foundation for targeted solutions, like improving healthcare access or advocating for fair housing policies. This collaborative approach, where analysis and community spirit merge, ensures solutions are not imposed from above, but built together, brick by brick, to address the unique challenges and dreams of the Black community.

Historically, Black communities have thrived by pooling resources, sharing knowledge, and supporting each other’s endeavors. This collaborative spirit, an embodiment of Ujamaa in action, can be seen as a form of collective abstraction. Like in computational thinking, where complex problems are distilled to their core elements, Ujamaa encourages communities to step back from individual challenges and focus on the bigger picture of shared prosperity. By abstracting away from individual successes and failures, and instead prioritizing the advancement of the community as a whole, Ujamaa fosters a powerful drive for collective progress.

5. Nia(Purpose)& Efficiency

In a city like Atlanta, a burgeoning hub of Black excellence in computer science and innovation, the principles of Ujamaa offer a blueprint for even greater achievements. By intentionally applying cooperative economics within the tech sector, there is an extraordinary opportunity to amplify success and foster an environment where collective progress is the measure of achievement. In this model, success is not just individual but communal, where each advancement contributes to the upliftment of the entire community. Atlanta, with its rich history and vibrant culture, is uniquely positioned to lead this movement, demonstrating how cooperative intentions and actions can propel the entire race towards unprecedented heights in technology and beyond. This approach not only honors the legacy of Ujamaa but also paves the way for a future where the success of one is the success of all, embodying the true spirit of collective prosperity and Black excellence.

For HBCU students and alumni, their journey to success is intricately linked to their heritage, guided by principles like Nia (purpose), which fosters a unique blend of purpose-driven focus and computational efficiency. In computational thinking, efficiency is a crucial skill, involving the ability to solve problems in the most effective and resourceful manner. This skill is pivotal for HBCU students and alumni who, understanding their purpose, navigate their educational and professional paths with this computational efficiency. It’s not merely about speed but about optimizing every step for maximum impact, a direct reflection of their deep sense of purpose.

6. Kuumba (Creativity) & Innovation

This strategic approach, deeply ingrained in Nia, mirrors the resilience and perseverance celebrated in Dr. Maya Angelou’s “I Still Rise.” By applying computational efficiency, HBCU students and alumni meticulously chart their course, making calculated moves and overcoming obstacles with unwavering determination. Their journey, marked by purposeful and efficient problem-solving, turns challenges into opportunities, exemplifying how the integration of computational thinking and cultural principles like Nia can transform limitations into triumphs.

Kuumba, the Nguzo Saba principle of creativity, isn’t just about artistic expression; it’s a fuel for innovation, especially in a landscape marked by limitations. Take HBCU marching bands, vibrant testaments to this spirit. Despite facing resource disparities, these bands innovate like mad scientists, transforming constraints into canvases for excellence. They hack limitations, turning shoestring budgets into sophisticated sonic landscapes. Instruments become extensions of their creative spirit, weaving complex harmonies and rhythms that defy expectations. This isn’t just about marching and music; it’s pushing boundaries, redefining what a marching band can be, and igniting a wave of innovation that ripples through the broader HBCU community.

The spirit of Kuumba isn’t confined to the pulsating rhythms of marching bands; it also ignites flames of innovation in social spheres. Take the founding of Black Greek organizations like Alpha Phi Alpha, Sigma Gamma Rho, and Kappa Alpha Psi. These pioneers, facing the harsh realities of white college campuses in the early 1900s, didn’t settle for existing structures. Instead, they embodied Kuumba by creating something new, transformative – brother and sisterhoods rooted in service and excellence. This wasn’t just about social gatherings; it was about redefining what community could be in the face of adversity, forging lifelong bonds that transcended institutions and generations.

7. Imani (Faith) & Critical Thinking

But their innovation didn’t stop there. These organizations, along with the Divine 9 founded at HBCUs, became incubators of leadership and activism, empowering members to tackle social injustices and uplift their communities. By breaking the mold and building their own legacies, these founders demonstrated the true power of Kuumba – not just to create, but to create with a purpose, to leave a lasting impact on the world around them.

Imani, the Swahili word for faith, is not merely a passive belief in the Nguzo Saba; it’s a dynamic force woven into the very fabric of the Black American experience. It’s the unwavering conviction in unseen horizons, the ancestral flame illuminating the path towards liberation despite systemic shadows. This principle resonates deeply with the computational thinking skill of critical thinking, especially when viewed through the lens of Black America’s historical struggle for equality and justice.

Framed through this lens, critical thinking transcends mere analysis; it becomes a beacon of hope, illuminating a path towards a more just and equitable world. It’s the strategic calculus that fueled the Civil Rights Movement, guiding the boycotts, marches, and prophetic pronouncements of Malcolm X, Fanny Lou Hamer and countless others. Their unwavering Imani fueled their critical dissection of the socio-political landscape, allowing them to anticipate challenges and craft effective responses. This potent synergy of faith and critical thinking laid the groundwork for dismantling oppressive systems and reshaping societal norms..

Similarly, Historically Black Colleges and Universities (HBCUs) stand as physical manifestations of Imani. Founded on the bedrock belief in education’s transformative power for Black Americans, these institutions have not only provided access to knowledge but have also nurtured generations of critical thinkers. HBCUs have empowered their students to challenge societal norms, question the status quo, and become architects of innovation in diverse fields. They’ve birthed leaders who think critically, envision equitable futures, and refuse to settle for a world where justice remains an elusive mirage.

Conclusion

The Nguzo Saba, Kwanzaa’s seven principles, weave a vibrant tapestry when paired with computational thinking. This union unveils a legacy rich in Black history, resilience, and innovation. These principles aren’t mere concepts; they’re lived experiences, ancestral wisdom, and guiding stars. When reflected in computer science, their power shines through, mirroring the same ingenuity and critical acumen that Black communities embody.

Educators, mentors, and leaders shaping young minds remember: you’re not just imparting skills; you’re awakening a generational DNA of greatness. Every lesson, challenge, and triumph becomes a flame igniting Umoja, Kujichagulia, Ujima, and the rest. Your role transcends classrooms; you’re architects of a future where Black excellence in computer science isn’t an exception but the norm.

By integrating the Nguzo Saba with computational thinking, we unlock a powerful framework for problem-solving, innovation, and building a more equitable future. Black contributions to computer science haven’t simply been successes; they’ve redefined the field itself. Our experiences – of struggle, resilience, and ingenuity – mirror the core principles of computational thinking. This fusion can not only empower future generations of Black computer scientists but also inform diverse approaches to problem-solving in fields beyond technology. Let us embrace these principles, not just as words, but as guiding lights to shape a future where Black excellence flourishes not just in code, but in every aspect of society.

About the Author

Victor “Coach” Hicks, a luminary based in Atlanta, Georgia, is the distinguished founder of Coding with Culture. Committed to establishing a “Kindergarten through HBCU” pathway in computational and design thinking, Coach Hicks is a fervent advocate for Historically Black Colleges and Universities.

Through innovative programs in Computer Science/STEM, tailored Professional Development for Teachers, and impactful partnerships, he empowers the next generation. Coach Hicks’ mission is underscored by a dedication to culturally responsive and sustainable pedagogy, revolutionizing STEM education. His accomplishments include recognition in Forbes Magazine and presentations at prominent international and national level ed tech conferences, solidifying his influence in the field.

The post Computational Thinking & Culture: The Nguzo Saba appeared first on Computer Science Teachers Association.

What if school districts across the globe did something radical in 2024? “What’s more radical than school districts’ attempt to close the now too wide learning gap?” you ask. Well, how about intentionality? Yes, being intentional in integrating CS in all classrooms, especially preschool and elementary levels. Not the intentional where we sometimes say when actually meaning, “I’ll try to remember the purpose for …”  I mean ‘intentional’ at another level that’s not happening in all U.S. districts. I’m talking about computer science in every, EVERY classroom. No matter the subject, computer science has to have an intentional permanent spot. Not just a section where one says, “Oh darn! We didn’t have enough time for this lesson for computer science. Maybe the next lesson.” Intentional with computer science — treating it as the heartbeat of the work.

In an article by Edweek, “Only slightly more than half of U.S. schools offer computer science, and even fewer elementary and middle school do.” The latest data from the Nations Reportcard regarding the United States is: “The 2023 reading scores for age 13 students at all five selected percentile levels declined compared to 2020. The declines ranged from 3 to 4 points for middle- and higher-performing students to 6 to 7 points for lower-performing students, though the score declines of lower performers were not significantly different from those of their middle- and higher-performing peers.” Wow!

Let’s imagine students from preschool to high school having computer science as a significant asset to the pulse of their classroom: their ELA, math, science, social science, etc., classroom.  Here’s another thought. What if all districts decided to implement CS into their non-computer science classrooms, the ones that mean well but actually dabble with CS by assuring students use the computer every now and then.  Check it out…

There is research that many U.S. students performed lower in reading and math in the SY22-23 than in SY19-20 compared to same-aged students in other parts of the world.   The New York Times  article Math Scores Dropped Globally, but the U.S. Still Trails Other Countries, reported: “Just 7 percent of U.S. students scored at the highest levels in math, compared with 23 percent in Japan and South Korea, and 41 percent in Singapore, the top-performing country.”  

Now districts, it appears, are scrambling to “restore the learning” or “lost learning,” as some refer to it. Let’s think about this for a moment. If something is being restored, it usually means bringing back to its previous version. If something is lost, that denotes trying to find it in its same condition and returning it to the owner. In a Harvard Magazine article, Post-COVID Learning Lossess,  Congress passed an American Rescue Plan for pandemic relief funding that “amounted to $190-billion allocation for school districts to help students catch up.”  The same article cites Tom Kane, director of the Center for Education Policy Research at the Graduate School of Education, stated that “there was little federal guidance” and “everyone was ‘left on their own’.” He is also quoted as stating in an interview that “‘…nobody knows how to help students catch up.’”

Well, prior to the early part of the COVID-19 era, according to a Washington Post article, U.S. students performed much lower in reading and math than children their age globally.  So, why are we trying to “restore” or “find” the past learning? Let’s start something new this new year! Let’s intentionally incorporate CS into every subject area.

Computer science integration lends itself to many benefits. According to Microsoft’s education team, “An important part of building up students’ CS capabilities is to engage learners as early as possible, which encourages and supports creative expression and the development of computational thinking skills.”  Let’s consider the “What if, then possibly” factor. The “What if, then possibly” factor is an imaginary platform allowing educators to take facts and envision realistic outcomes, leading to the possibility of making them happen.

What if districts put a heavy emphasis on computational thinking in the preschool grades? Then there is a strong possibility that as the students mature, they are successful in all subject areas.

What if apprehensive educators took the plunge to learn a bit more about CS and use strategies that required students to do more with age/grade-appropriate CS tasks. There is a possibility that students develop a hidden career talent.

What if projects like the science fair are captured digitally on slides and submitted for a grade?

What if the textbooks all had key parts in digital 3D formats? Then, many of the students may focus more on knowing more.

What if all teaching schedules had scheduled block times for CS in all classrooms?

It’s time for action in 2024. Do we really want to restore or find past learning habits? Let’s do something different. Let’s provide a platform that goes beyond helping students be successful but provides society with thinkers who can organize and problem-solve. Here’s a thought: do we really wait until a child is near adulthood to implement any skills with fidelity? Then why not incorporate computational thinking skills via computer science each day in elementary school, beginning with preschool?

I leave you with this quote from the Journal of Computer Science Integration:

“To be successful in a changing economy, students must learn to think algorithmically and computationally, to solve problems with varying levels of abstraction. These computational thinking skills have become so integrated into social function as to represent fundamental literacies. However, computer science is not widely taught in [PreK] K-12 US schools. Efforts to create computer science standards and frameworks have yet to make their way into mandated course requirements.”   

Resources

Nations Reportcard

Journal of Computer Science Integration

Micro Soft article

Washington Post articleNew York Times  article Math Scores Dropped Globally, but the U.S. Still Trails Other Countries

About the Author

Cynthia Brawner is a National Board veteran teacher with over 25 years of experience. She teaches all subjects: English Language Arts, Math, Science, Social Studies, Writing, and coding to her third-graders at Wadsworth STEM Elementary in Chicago, Illinois. She runs the after-school Computer Science, Podcasting, Inventors, and Videography clubs for grades 3rd to 8th.

Cynthia’s educational mission: empower as many students as possible through academic exposure to help students have a voice and reach their full potential. She’s a PilotLight Food Education Fellow, a Field Museum Ambassador, a DonorsChoose Ambassador, A Scholastic SuperSTEM Advisor, a Museum of Science and Industry Teacher Initiative Partner, and a Global Schools Mentor. She holds several postgraduate degrees: an MA in Early Childhood Advocacy and an MS in School Administration. She also holds several certificates from Adobe Exchange Education, ISTE, and CSTA. She is active in the faith-based community and continues to enjoy teaching.

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