Category Archives: Written by: Pati Ruiz

From Research to Practice: Introduction & Computational Thinking

Computational Thinking, Computer Science, Teachers & Researchers, Written by: Angie Kalthoff, Written by: Pati Ruiz

by Angie Kalthoff and Pati Ruiz

Cyberlearning researchers including Shuchi Grover, Satabdi Basu, Eni Mustafaraj, Jodi Asbell-Clarke, and Katie Rich have been writing about and discussing computational thinking. Their research has been instrumental in helping us think about what these concepts and skills look like in the classroom. One thought from the CT primer that really resonated with us is:

“Increasing access to CT instruction is now widely discussed as a social justice issue.”

As educators with the goal of making Computer Science (CS) accessible for all, we often find ourselves wondering “how can I, share CS with other educators who might feel intimidated by this topic?” In this post we, Angie and Pati will, share how we are connecting what researchers are working on in many different domains and thinking about with what K-12 educators and parents can do to bring CS to their students and children. After all, as the authors of the CT primer point out: “several CT skills are not exclusive to the field of computer science.” For both of us, taking a broader lens gives us more tools to help.

I (Angie) don’t have a formal education in CS. I started my teaching career in an English Language(EL) classroom. It was during my time in my classroom, I discovered I really enjoy helping others create through the use of technology. This led me into my current role as a Technology Integrationist in a K-12 public school district.

My first tools for electronic creation included the iPod (yes, iPods the iPad wasn’t released yet) and interactive whiteboards. While my journey with these devices started as tools of consumption, they led towards tools of creation. However, it wasn’t until I discovered CS that I really felt like I was empowering my students to create anything they could think of. I saw coding as a way of self expression. This mindset grew in me as I explored research in the early childhood CS field.

The image below shows that, while CT can be a new concept for some of us, there are already many situations in which it can easily be brought into existing lessons. Learn more about Advancing Computational Thinking Across K-12 Education (the image below is from this document).

I (Pati) studied computer science in business (Operation and Management Information Systems) in college, but I didn’t get to begin teaching stand-alone CS classes until 10 years after I started teaching because they weren’t offered in my schools. I did teach digital literacy and computational thinking (CT) classes early on, as part of a Middle School skills curriculum. However, my understanding of CT has changed a lot since I worked with my first group of Middle School students. Thanks to the work of researchers that is summarized in this Computational Thinking Primer, I was able to learn more about the skills and dispositions important in CS education and continue iterating on the very first lessons I designed. One of the things that helps me in my teaching is to read about the research being done, think about what was learned, and bring back what I can to my classroom to make improvements. The research I read gives me different ways to think about what I’m seeing in my students and also what I’d like to see.

As researchers like Shuchi Grover and Jodi Asbell-Clarke have pointed out, experts still do not agree on what CT is and there is a CT communication problem. Angie, Sarah, Judi, and I did a lot of thinking on this topic when we worked on the Computational Thinking for Teachers & Parents Webinar Series to help teachers and parents bring CT into the classroom and into their homes. It took time for us to work through relevant research articles and examples. One thing that I really enjoyed about this process was getting to discuss these topics with other very thoughtful people and hearing about new lessons and games. Although I did not play it until much later, one CT game that I now enjoy playing is Human Resource Machine. In this game, you program office workers to solve puzzles using coding commands. According to the game developers, “you start the game with just 2 commands, and gradually earn more as you’re promoted. The entire language contains only 11 total commands – but they’re enough to simulate almost any computer algorithm in the world!” As long as you can do this well, you are considered a “good employee” and can work for another year. You should check it out and see if it could fit into your classroom or just help you think about CT on your own!

Finally, as we discussed how to share what we had learned about CT with other educators, we wondered where CT fits in other terms we had been using for years like digital literacy, programming, and CS. To help us think about these terms we remixed an image by Colin Angevine that we found in a report titled Computational Thinking for a Computational World.

In summary, computer science can be seen as the academic discipline that includes programming. Computational thinking includes the problem-solving processes that involve thinking, as Grover and Pea (2013) describe, “like a computer scientist when confronted with a problem.” Computational thinking is useful in many STEM domains and can be brought into other subject areas.

If you are interested in learning more about CT, visit Digital Promise microcredentials Computational Thinking: Key Elements and Practices. At the site, you will find competency-based recognition for professional learning on a variety of additional topics. In future blog posts, we’ll consider how CT differs from Computer Science education and teaching technology skills. Finally, please leave us a comment – we’d love to hear from you about how you use research to guide your work!

References

Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38-43.

NRC. (2010). Report of a workshop on the scope and nature of computational thinking. Washington, DC: National Academies Press.

NRC. (2011). Report of a workshop on the pedagogical aspects of computational thinking. Washington, DC: National Academies Press.

What is Pseudocode?

Computational Thinking, Computer Science, STEM, Written by: Angie Kalthoff, Written by: Pati Ruiz

by Angie Kalthoff and Pati Ruiz

Welcome back! As many of us head back to school, we wanted to share our thoughts on Pseudocode and making coffee is one example we thought would be appropriate. Think of pseudocode as a way to help you organize your thoughts in a sequential manner as you design your project, before you translate it to code. Pseudocode is written in a form that is similar to the language you speak, and allows you think through how to solve a problem without having to worry about the rigorous syntax of a programming language.

In fact, pseudocode is simple enough that you don’t need a background in computer science (CS) to write or read it. Pseudocode is can be translated into a programming language and is a great way to help you organize your thoughts. Students might write pseudocode for non-programming or “unplugged” activities, or as they prepare to write programs in block languages or more advanced programming languages.

You may be wondering: Why not just use code to write the program? Syntax. When writing in pseudocode, you are taking your thoughts and transcribing them into a language you understand and can communicate to others. You are in control of the structure and don’t have to worry about choosing a specific programming language or worry about syntax errors (which mean that your code does not work!). The goal of pseudocode is to describe the code of your program in a relaxed way – without worrying too much about the details. And, while pseudocode is written in “english-like” language, more experienced programmers (also known as developers) tend to write pseudocode that is more similar to the syntax of the target programming language.

Sometimes, using images or flowcharts also help as you design your project. A flowchart often starts with a question that has two possible answers:

  • yes/no
  • true/false

Flowcharts use special shapes to represent steps, decisions, or actions, and lines between shapes  to show the flow or sequence between the steps. Shapes used include ovals (for start and end), diamonds (for questions/decisions), rectangles (for processes), and other actions. Additional shapes could also be used – it’s up to you! To learn more about flowcharts, visit Pseudocode and Flowcharts.

Classroom use of Pseudocode

Many lessons have been developed to help you and your students think sequentially about everyday tasks. By starting in early grades, students will have practice developing their “computational discourse skills”. Computational discourse skills are described by Grover and Pea (2013) as ones that help children develop a vocabulary that is faithful to the computer science discipline while also allowing for the development of an understanding of programming and computational thinking concepts and skills.

Classroom connections to pseudocode include tasks your students have to complete and the directions they need to follow to accomplish these tasks. When students wash their hands, there are a series of steps that are taken. You can think of these as the directions for handwashing or as an algorithm (a list of steps that you can follow to finish a task). To write these steps, we break them down into understandable chunks, and write them in a sequential order.

If someone has never washed their hands before, you could not simply say “wash your hands.” Instead you could write it out in pseudocode.

Wash your hands.
    Walk to a sink.
    Turn on the water.
    Pump the soap dispenser as many times as necessary with one 
    hand while holding your second hand below it in order for the 
    soap to fall into that hand. 
    Stop pumping when a quarter sized amount of soap is in the  
    second hand.
    Once soap is in hand, rub hands together to distribute soap     
    between hands.
    Place hands under running water while rubbing them together.
    Rub hands until so is no longer present.
    Turn off water.
    Pick up towel and rub on hands until hands are dry.

Here are a few example lessons that you could start using in your K-5 classrooms to build students’ computational discourse skills::

In addition to the unplugged activities shared above, students in grades 6-12 can begin developing a pseudocode practice as a precursor to writing code. This Bubble Sort Unplugged Activity is an excellent example of what older students should be able to do with pseudocode. Another example is this Python ‘elif’ exercise found on usingpython.com. Professional programmers all have their own pseudocode styles – some like less detail and some prefer more detail. Some developers use a different method altogether during their software development process.

Want to know what pseudocode could look like? Visit Gabriel Comeau’s post to see how he describes how to make coffee using pseudocode.

Resources

Works Cited:

Grover, S., & Pea, R. (2013). Using a discourse-intensive pedagogy and android’s app inventor for introducing computational concepts to middle school students. In Proceeding of the 44th ACM technical symposium on Computer science education (pp. 723-728). ACM.

CS Recommendations

Computational Thinking, Computer Science, Written by: Pati Ruiz
By Pati Ruiz

This post is not sponsored by anyone and I receive nothing for these recommendations.  I make them because I like the tools. My recommendations have been tried with high school aged students and older.

What tools do you recommend for learning to program?

As a high school computer science teacher, I often get this question from other teachers as well as friends and family members: What tools do you recommend for learning to program? I have learned that the people asking either have absolutely no experience programming or they have the basics down and want to learn more or teach others. As a result, the recommendations that I give most often are:

  1. For those with no experience: Codecademy
  2. For teachers and those with some experience: Trinket

Codecademy is great for most people who just want to get a taste for programming. It is designed as a tutorial platform for beginners, and provides lessons as well as an introduction to several different programming languages.

For fellow teachers who want to bring programming into their classrooms and those who have some of the basics down and want to dig deeper into projects, I recommend Trinket because it is:

  • Easy: Trinket is an “all-in-one coding environment”
  • Free: Trinket is free to use and gives you access to open (also free) educational resources
  • Inclusive: Trinket allows users to program on whatever device they have access to whether it’s at school, a public library, or home.

To begin with, Trinket is easy to use, with a clean and simple user interface. Trinket works very well for people who might not want to download a text editor like atom, worry about having the correct system setup, or work in terminal. I have been using Trinket in CS1 for HTML5 and CSS, and in CS2 for Python, for over three years now. One of the reasons I keep coming back to it is because some of my students work on iPads, some work on laptops, and some borrow school laptops. Trinket makes it easy for people to learn from any device as long as they have access to their account via the Internet. This is a great tool, especially for learners without consistent access to the same device.

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The second reason I recommend Trinket is because it is an open-ended coding tool that also provides free content and lessons. In my CS1 class, for example, students explore HTML5 and CSS. After a few lessons on HTML5 and CSS, students use Trinket to practice what they have learned. They see how they need to link HTML files to CSS files, and they discover how these interact with one another. When my CS1 students begin to learn HTML, they “remix” a trinket that I created to guide the lesson. My students are able to use the trinket that I created as a guide, and they begin to use what they learned to change the trinket and make it their own. Ownership and giving students something do are essential parts of learning. With Trinket, students are the owners of their own code and they can see immediately how editing code changes their webpages. As Dewey described in Democracy and Education (1916), “doing is of such a nature as to demand thinking, or the intentional noting of connections; learning naturally results (Ch. 12).” Trinket allows the student to be actively involved and engaged in the learning process.

In my CS2 class, I use the textbook Python for Everybody by Dr. Charles Severance. This textbook can be found on the Trinket website along with interactive trinkets to guide learners along the way. I agree with the Trinket team that Python is a great first language . Having said that, Trinket also has Think Java: How to Think Like a Computer Scientist by Allen B. Downey & Chris Mayfield  on their site for people to work through. These high-quality open educational resources are important for those of us who are educators because they can save us a great deal of time. As a result, instead of developing content, teachers can focus on supporting student learning in their classrooms.

Finally, I appreciate the Trinket team’s commitment to creating inclusive learning environments and opportunities for all learners. Through the development and support of open education resources like the ones I mentioned above, the company provides a variety of learning experiences for a wide range of learners. As an added bonus, the team at Trinket has translated some of their offerings to several languages! The Spanish version is especially useful to me since many of my family members prefer to learn in Spanish. Switching back to English, here is an example of one of Trinket’s interactive challenges – try it to learn a little bit about programming in Python. ​

Check out these trinket lessons and how teachers Meg Ray and Paul Kostak  are using Trinket.

On a related note, If you’re interested in learning more about computational thinking,  sign up for this upcoming CIRCL webinar series: Computational Thinking for Teachers & Parents. The webinars will take place Jan. 30, Feb. 6, and 13.  See the above link for more information and to register. 

Computational Thinking Webinar

Computational Thinking, Webinar, Written by: Judi Fusco, Written by: Pati Ruiz, Written by: Sarah Hampton

By Pati Ruiz, Sarah Hampton, Riley Leary, Judi Fusco, and Patti Schank

For the last few months, we’ve been  reading, thinking, and talking about computational thinking (CT) in preparation for three Webinars for Teachers and Parents on the topic. The webinars are on January 30, February 6, and February 13. Go to the link above to sign up for the webinar and get all the details.

ct

A lot of the websites and articles we reviewed about computational thinking for teachers gave us only a brief introduction to it.  We’ve read about what researchers have been doing and how they have been thinking about CT, and using their research, we’ve been trying to think about what CT means for and looks like in the classroom. We also know that it’s a new topic for parents, and that parents may want to think about what it means and what it can look like at home.

The term computational thinking was made popular in a paper in 2006 by Jeannette Wing, and since then, researchers have expressed different understandings and definitions of the term. There wasn’t a common understanding of what it was then, and exactly “What is it?” is still a fair question today. Some people equate computational thinking with coding, but others do not. We agree that computational thinking is a much broader set of skills than just coding or programming, and that it’s not the same thing as computer science. Computational thinking skills include abilities that help people use computers to solve problems. Being able to program is one way of interacting with a computer, but there are other ways that one can work with a computer, and computational thinking is needed in more than just programming classes. For example, when researching for a history project, students may need to use data to strengthen their arguments. Students are using CT when they locate, evaluate, analyze, and display data. Learning to program is an advantage, in terms of learning to think in a new way, but we believe that programming is not the only way to incorporate CT into classes. We’ll explore these things in our webinars.

The first session will be an overview of CT. The second session will be geared toward what CT can look like in K12 classrooms. At our third session––a special webinar for parents or other caregivers––we will think about projects and practices that can be done at home with kids to help them learn and think in this new way. Come to the webinars to learn and think with us about computational thinking and what it looks like in K12 classrooms and at home! Please share this information with interested colleagues and parents as well. We hope to see you there!

Programming + Music with EarSketch

Computer Science, Video Showcase, Written by: Pati Ruiz
By Pati Ruiz

The timing of this year’s  STEM For All Video Showcase worked well for me as a teacher. It allowed me to see something right when I was starting to evaluate my curriculum and prepare for next year. During the 2017-18 school year, I will be teaching two high school computer science courses: one is an introductory course for Sophomores and the other is a new (for me) intermediate course for Juniors. Due to time constraints, our school schedule will not allow me to offer the AP Computer Science Principles course. Instead, I am designing a curriculum that’s appropriate for my students. I am excited about the content and hope it will be engaging for them.

As I watched the videos in the showcase, the EarSketch: teaching coding through music video presented by Lea Ikkache and Jason Freeman really captured my attention, or, dare I say it – caught my ear. As I read through the discussion thread, I learned quite a bit from the comments. I learned that there is a community of CS educators who are now using EarSketch, and even a Facebook group where the community can discuss the curriculum and share their materials and tips. The curriculum is aligned with the AP CSP standards currently, and the team is looking to align to CSTA standards in the future! Among other topics, students will learn to use variables, loops, conditionals, and lists appropriately. They will also learn to use functions and write appropriate comments for their code.

Now that it’s August, I find myself planning for next year and really digging deeper into this curriculum. As I work through the modules, I find that the instructions are very clear and well-structured, and the tasks are engaging. Best of all, EarSketch is super easy to use because it’s completely free and works right in your web browser – there’s nothing to download or install. So my students can easily access this programming environment from home or the library. While you can use EarSketch in either Python or JavaScript, I have opted to use the Python version. I am learning a lot, and am even planning to invite our music teacher to our class so she can help us make sense of the music theory elements that we might encounter. I am lucky to teach in a school where the performing and visual arts are emphasized. I will also be encouraging music teachers to check this tool out.

I am still learning about EarSketch, but what I can tell so far is that it will engage some of my students (all young women) who are very involved with music-based extracurricular activities. It is also an application for programming that my students might not be anticipating. Through my dissertation study, I am learning about the importance of designing relevant and interesting examples and assignments for our students. EarSketch is definitely going to provide my students an opportunity to apply and practice programming concepts in a creative context with very appropriate supports in the form of instructions, resources, and examples. There are many links to audio and video files throughout!

I know that the research group is conducting further research to better understand EarSketch and its implementation in schools, specifically as AP CSP classes integrate the curriculum. I will be on the lookout for more publications about EarSketch – here is one about engagement across gender and underrepresented populations. Also, check out this EarSketch video that includes a variety of perspectives of people who have engaged with music and computer science through EarSketch.

​Image from Website:

For more information about EarSketch:

Video:  EarSketch: teaching coding through music
Website: EarSketch
Journal Article: EarSketch: A STEAM-Based Approach for Underrepresented Populations in High School Computer Science Education

Encouraging Young Women in CS: Shifting Perceptions and Attention

Computer Science, Written by: Pati Ruiz
By Pati Ruiz

Let me start this post with some facts about women in computer science (CS):

  1. Women account for 18% of computer science graduates in the United States. (NCES, 2012)
  2. Women make up 26% of the Computer Science and Mathematical Science workforce. (NSF, 2012)

As a high school CS teacher at an all-girls school, I always want to learn more about what I can do to encourage my students’ continued participation in CS. While I know that not all of the young women I teach will want to pursue CS, some will and some who might not have considered it might decide to with the right information and support.

I have always suspected that teachers play a critical role in supporting a student’s’ persistence in CS. In compiling articles for my dissertation, I found studies that document the factors that play a role in CS participation. In this post, I share some of what what I have learned and what it means for me as an educator.

Wang, Hong, Ravitz, and Ivory (2015) found that young women tend to decide to pursue a STEM-related field, including CS, long before they begin college. Some studies document CS gender differences as early as grade 5. Indeed, once a girl enters college, CS degree and class requirements can be overwhelming to female undergraduates because they more often start college having taken fewer classes than the male students. In addition, girls are often interested in more than “just programming computers;” young women tend to be interested in creating computing tools to help society. It is important to show girls that CS is a field with diverse applications and a broad potential for positive societal impacts because of the value that women place on making positive contributions to society.

There are four factors that influence a young woman to pursue computer science: social encouragement, career perceptions, academic exposure, and self-perception. The good news is that Wang et al. (2015) conclude that the factors playing a role in a young woman’s decision to pursue a CS-related degree in college are largely controllable. This means that K-12 educators, family members, and friends can play a significant positive role in encouraging and exposing young women to pursue CS.

Exposure is important.  Students who took one CS class were more likely to want to pursue CS. When it comes to gender, Wang and Moghadam (2017) found that while there is no difference in access to computers or CS learning opportunities for young women and men, there is less awareness of opportunities. Girls are less likely to know about clubs, online sites, or other opportunities outside of school to learn CS. Boys are more likely than girls to learn CS on their own, in a group or club, and online. More boys than girls are encouraged by being told they are “good at” CS (44% of boys versus 12% of girls were encouraged by a teacher and 43% of boys versus 17% of girls were encouraged by a parent).

This means that educators and people in the lives of young women play a large role in providing opportunities for them to learn about the CS field and then encourage these young women to pursue it. So, what can we do? As an Intro to CS teacher, I will continue to work to make (extra) sure I create supportive learning environments as I share the field of CS and tell them that they can be “good at CS.”  I will also encourage them if they don’t feel that they “are good at it;” there is no reason they can’t be good if they work hard (ala Dweck’s growth mindset and Duckworth’s grit).

Since a young woman’s family plays a large role in whether they will pursue CS or not, I know I need to create opportunities to reach out to my student’s parents to help them understand why and how they might encourage their daughter to enter and persist in computer science and related fields. I will also continue to encourage their participation in CS. It is also important for students to have peer support – I can encourage students to support one another through on and off-campus clubs and activities.

In many ways, what I already do is similar to what I learned I should do. I learned that I should go out of my way to bring in guest speakers (young women in particular) to talk with my students about the opportunities available to them if they decide to pursue CS. It is important to me that my students understand that solving problems with people who have different information, opinions, and perspectives is beneficial for all. It’s also great when they get to hear about the impact and the fun the young women have in the field. By encouraging my students to explore the various areas within CS and exposing them to practitioners in the field, I hope that more of the young women I teach will consider pursuing a career in computer science.

I also learned about curriculum and pedagogical approaches, too, but I’ll discuss those in a another blog post. I am just starting my dissertation study that will examine factors that might encourage or discourage the participation of more women in undergraduate CS programs. I am interested in what types of learning experiences encourage or discourage participation by a diverse group of students in undergraduate computer science departments. The work by Wang, Hong, Ravitz, and Ivory (2015), Wang, Hong, Ravitz, and Modhadam (2016), and Wang and Modhadam (2017) has been helpful in guiding my research. More importantly it has helped me better understand my role as a CS educator.

References:

National Science Foundation. (2012). Science and Engineering Indicators 2012. Washington, DC. Retrieved from http://www.nsf.gov/statistics/seind12/c0/c0i.htm

National Center for Education Statistics (2012). Degrees conferred by degree-granting institutions. Washington, DC. Retrieved from http://nces.ed.gov/programs/digest/d12/tables/dt12_318.asp

Wang, J., & Moghadam, S. H. (2017). Diversity Barriers in K–12 Computer Science Education: Structural and Social. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 3–8). http://doi.org/10.1145/3017680.3017734

Wang, J., Hong, H., Ravitz, J., & Moghadam, S. H. (2016). Landscape of K-12 Computer science education in the U.S.: Perceptions, access, and barriers. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education, (pp. 645–650). http://doi.org/10.1145/2839509.2844628

Wang, J., Hong, H., Ravitz, J., & Ivory, M. (2015). Gender differences in factors influencing pursuit of computer science and related fields. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education – ITiCSE ’15, (pp. 117–122). http://doi.org/10.1145/2729094.2742611

2016 NSF Video Showcase: Broadening Participation

Diverse Learners, Video Showcase, Written by: Pati Ruiz

 

By Pati Ruiz

The NSF 2016 Video Showcase: Advancing STEM Learning For All featured 65 videos under the “Broadening Participation” keyword. This topic is an important one for those of us who work in the classroom. I learned through the Cyberlearning 2016 conference that the NSF established the Broadening Participation in Computing Alliance Program between 2006 and 2009 to address issues of engagement and education in computing and computationally-intensive disciplines across the K-20 education landscape.

One underrepresented group discussed in the NSF video showcase was students with diagnosed learning differences. Two of the videos on this topic were very interesting to me – these were Diverse Learning Technologies: Helping students with LD, ADHD, and ASD reach their full potential in STEM and Accessible PhET Simulations for Diverse Learners. In order to learn more about working with diverse learners, I spoke with Amar Abbott, a High Tech Center Access Specialist and faculty member at Taft College. Here is our conversation:

Question: You watched the Diverse Learning Technologies: Helping students with LD, ADHD, and ASD reach their full potential in STEM and Accessible PhET Simulations for Diverse Learners videos from the 2016 NSF Video Showcase. What did you find interesting about them?

Amar Abbott: I thought that they were very informative and I especially liked that all of the videos had closed captioning embedded. This makes them accessible to a wider audience. Also, I learned a lot about the technologies that are being developed for helping students with learning differences.

Question: How might these videos inform your practice?

Amar Abbott: These videos have helped me think more deeply about cognitive load and helping students and teachers monitor learning. One question that came up for me is: If a tool provides some support for the cognition of the student, what can the community [around the student(s)] also do to help support cognitive learning? In addition, I would also like to learn more about the situative and social supports that might help students.

Question: What will you do with what you learned from these videos?

Amar Abbott: I appreciated the introduction to Landmark College, their resources, and research group there; it’s a great model. Their focus on UDL is especially excellent because their work stems from direct experience. I am going to try to visit Landmark and hopefully develop long-term relationships with the researchers and students there.

As for the accessible PhET Simulations for Diverse Learners project video, I learned a great deal about what affordances learners need for activities like simulations. The video was to the point, and I like that it highlighted a blind student working with the PhET Simulations. Projects like these puts accessibility in the forefront and that helps all learners.

It was great to hear Amar’s thoughts, and as a teacher, I will be interested in following both of these projects. I am especially interested in what the University of Colorado team discovers about how simulations “are shaped by sociocultural norms of science, [and] can also be used to change the traditional norms of how students engage in the classroom.” This work will be helpful for everyone interested in broadening participation and engaging all learners in STEM topics.

2016 NSF Video Showcase: A Teacher’s Perspective on Embodied Design

Embodied Learning, Learning, Video Showcase, Written by: Pati Ruiz

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By Pati Ruiz

NSF recently hosted the Advancing STEM Learning for All 2016 Video Showcase. The showcase included 156 videos of innovative work being done in the STEM fields across the country. I served as one of 35 facilitators for the 2016 showcase, which means that I reviewed and commented on the videos, and used a rubric to vote for best videos. The videos from the 2016 showcase (as well as the 2015 showcase) are all publicly available for anyone to view. They can be filtered by several categories, such as keyword, age/grade level, and state. As a K12 educator, I found the age/grade level filter especially helpful as I tried to find projects related to the work that I do in 9-12 education.

One topic that blew my mind was the work being done around embodied design. Embodied learning designs set up the conditions for learners to engage their body in learning activities through interactive learning environments and whole-body interactive simulations (Lindgren, Tscholl, Wang, & Johnson, 2016). In a recent study of middle school students, Lindgren, and colleagues (2016) found that enacting physics concepts and experiencing these critical ideas in an immersive, whole-body interactive simulation led to significant learning gains, higher levels of engagement, and more positive attitudes towards science when compared to viewing a desktop version of the same simulation. One of the researchers behind this study, Robb Lindgren, submitted this video to the showcase: Gesture Augmented Simulations for Supporting Explanations. Other examples of embodied learning include a video about Advancing New Science Learning and Inquiry Experiences via Custom-Designed Wearable On-Body Sensing and Visualization and this one about VEnvI: Learning Computational Thinking Through Creative Movement.

Wanting to learn more, I went to circlcenter.org where I found the DIP: Developing Crosscutting Concepts in STEM with Simulation and Embodied Learning project and the Promoting Learning through Annotation of Embodiment (PLAE) project. I also found more information on  VEnvI: Exploring Grounded Embodied Pedagogy in Support of Computational Thinking.  As a teacher, I appreciate projects with content and ideas that are immediately applicable in the classroom. For example, VEnvI software is available for download and use in classrooms; the team is currently seeking funding for wider dissemination to teachers and students. Their software allows students to program a virtual character to move in realistic ways. In the showcase video, the VEnvI team shows clips of the dance routines that they have developed to help students learn programming concepts. Students first learn a dance routine and then move to computers where they program their avatar to do the same routine they just learned. You can see students repeating the routines as they write their program, engaging their bodies in the learning activity. I haven’t found the dance routines available to teachers online, but I can clearly see the value of movement to teach basic computer science concepts.

​As a teacher who might benefit from this team’s work, I hope the team gets more funding for the implementation stage of this project. Thinking about other practitioners who might also benefit from the work by this team makes me wonder how the team might disseminate this project to a broader audience. Modifying the VEnvI website to provide a space for teachers to develop and share content for the tool might be one way to do this. Like other projects that are still in the development or concept stages, this project will be very interesting to follow.

I encourage other teachers and practitioners to take a look at the Advancing STEM Learning for All 2016 Video Showcase. Comments and videos are accessible on the Video Showcase site, so go check them out. While you can no longer comment there, you can leave comments here about the videos and we’ll get them to the researchers. Please look for next year’s showcase where you, too, can provide feedback to researchers!

Lindgren, R., Tscholl, M., Wang, S., & Johnson, E. (2016). Enhancing learning and engagement through embodied interaction within a mixed reality simulation.Computers & Education, 95, 174-187.

Practitioner POV of Constructivist Approaches

Constructivism, Mathematics, Written by: Pati Ruiz

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By Pati Ruiz

Pati Ruiz is a doctoral student in Learning Technologies at Pepperdine University. She has worked as a teacher (Spanish and Computer Science), Director of Learning Technology, and is the incoming Dean of Studies at Convent of the Sacred Heart in New York City.

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As a teacher studying the learning sciences in graduate school, I understood  constructivist practices in theory, but I often wondered what constructivism looked like in action. Taking a constructivist perspective, Windschitl (2002) describes learning as an act of both individual interpretation and negotiation with others, where knowledge is the collection of what is constructed individually and collectively. In classrooms, a constructivist or open approach should support learners in actively constructing their own knowledge, but what does that really look like? How much time does it take? What are the challenges?

I spoke with some teachers to learn more about how they support an open approach to learning in their classrooms. This post will focus on the strategies of a middle and high school math teacher I interviewed. Future posts will focus on the work of high school Spanish and English teachers.

Math Classroom Example: Christine Trying a New Curriculum
Christine DeHaven is in her fifth year teaching middle and high school math. In her Honors Algebra 1 class at Pacific Ridge School, she always taught in a very guided or instructivist approach. For example, if the topic was lines, she would first lecture about lines, then work out one example in front of the class, and then students would do some problems on their own in class. For homework, students would complete more problems that progressed in difficulty. The class would then move on to the next topic. Christine noticed that students were just memorizing steps instead of problem solving, so she decided she needed to change her teaching approach.

Christine had learned about a new curriculum that allowed the students to learn through conferences and visits to other schools, including The Bishop’s School, Deerfield Academy, and Phillips Exeter Academy (where the curriculum was developed). Christine and a colleague decided to swap their traditional direct-instruction approach for a problem-based approach. Christine had seen the new curriculum in action, and felt that it could work at her school, too. Still, she modified the curriculum slightly for her students. Sometimes the transition to a new approach needs to be done gently. Here is what Christine’s curriculum looks like now.

First, students are assigned 8-10 homework problems per night. The goal for students is that they attempt all of the problems before class. When they arrive to class the next day, students pick a problem to solve on the board. Multiple students may put up the same problem, and everyone contributes at least one problem. After all of the problems are on the board, groups of students go to the board to present one problem at a time. If there are multiple solutions to the same problem, Christine leads a discussion about which solution is more efficient. With this new method, Christine finds that her students have more ownership of what they are learning. They apply problem solving skills to the homework and construct their own understandings through their solutions and conversations about their solutions. When they present their work and discuss the various solutions, students gain a better understanding of the concepts because they have to make a case for or against a certain way of solving a problem. Christine also encourages students’ use of graphing as a method to solve the homework problems. Students use tools like the Desmos Graphing Calculator to see a visual representation of the problem. In this way, Christine guides students to look at problems in three different ways: numerically, algebraically, and visually.

Parent education and administrator support has played an important role in the ease of adopting her new curriculum. While Christine initially received some negative feedback about her approach from parents, she felt well supported by her school administrators who are able to point concerned parents towards research and articles about the success of this approach. Open house became an opportunity for Christine to educate concerned parents–she even encouraged them to work with their children to solve the daily homework problems. Christine still attempts to engage parents by encouraging them to follow along on the course website. Many do, and often share stories of working on problems with their children. While parents were initially skeptical, many now tell Christine how much they appreciate the new approach and they have fun helping their children with their math homework. In the beginning, Christine also got negative feedback from students. But – for the most part – they have come around now that they have more practice with the approach. Something else that has helped students adjust is that the homework problems they are solving are very realistic; students can relate to them. For example, one problem, which aims to help students understand how dangerous glancing at a phone is when driving, asks students to compute how far they would drive down the highway in the time it took them to read or respond to a text message. Many of Christine’s students are learning to drive or have friends who are, so problems like these are relevant and engaging to them. (Please don’t text and drive!)

Though challenging, Christine persisted in adopting the open curriculum because she felt that it was the best approach for her students. She thinks that students have a better understanding of the concepts they have covered. For example, they understand how to factor a polynomial and aren’t just guessing and checking. She reports they are able to prove why the square root of 2 is irrational. They also have a better sense of how a graph relates to algebra, and they persist in solving problems. When solving homework problems, students don’t always know the math theories or strategies they are using, but they are developing algorithms and figuring out problems as they go. These are essential skills for mathematics. Additionally, when students don’t solve a problem the first time, they are willing to try again and again. In this way, they are developing a growth mindset and starting to see the payoffs.

This approach has been more time consuming for Christine. It’s the first time she’s seen many of these problems on the homework, so she needs to solve them all in multiple ways before going to class. She needs to think like her students and try to anticipate the problems they’ll have and the misconceptions they might bring to a problem. This means she really needs to know the content she’s teaching. It’s more prep time before class, especially in the first year, but this way she knows how to guide discussions and ask the right questions. Christine uses her expertise to help students gain a deeper understanding and make connections to content they have seen before. She’s not lecturing as much anymore, but she remains the content area expert.

This idea leads to something that might be a struggle for some. It is described by Harland (2003) like this:
“When students arrived at a position where they could function well together and drive the enquiry forward, they seldom asked for help, and the teaching team no longer had their old roles and familiar student contact. Paradoxically, we felt some sense of loss at this stage and concluded that a lot of pleasure in teaching had gone…”

For Christine, though, she simply sees her role as a teacher changing. She is now more of a facilitator who ensures that students hit certain key points. She guides students in thinking more deeply by helping them ask questions instead of giving them answers. Her connection with students is now stronger, in her opinion. Preparing for class is more involved and time-consuming and her role in the classroom is smaller. But for Christine, that’s okay. What excites her about teaching is helping students discover the math that she loves, and she’s doing that.

If you’re interested in learning more about open approaches to Mathematics education, Christine recommended the Exeter Mathematics Institute and the Mathematics Visionary Project. We would love to hear what you think and the questions you might have for Christine or other teachers.

Harland, T. (2003). Vygotsky’s zone of proximal development and problem-based learning: Linking a theoretical concept with practice through action research. Teaching in higher education, 8(2), 263-272.

Windschitl, M. (2002). Framing constructivism in practice as the negotiation of dilemmas: An analysis of the conceptual, pedagogical, cultural, and political challenges facing teachers. Review of educational research, 72(2), 131-175.