Category Archives: STEM

Ambitious Mashups and CIRCLS

AI in Education, Cyberlearning, STEM, Teachers & Researchers, Webinar

By CIRCL Educators

CIRCL, the Center for Innovative Research in Cyberlearning, has come to an end, but don’t worry, we’re getting ready to roll over to a new project called CIRCLS, the Center for Integrative Research in Computing and Learning Sciences. Stay tuned here and we’ll keep you apprised of any changes. Of course we’ll still be working to bridge practice and research and share what CIRCLS is doing and what we, as educators, are thinking about and facing in our work. If you’d like to get more involved with our work, please contact us! We’re looking for more educators to think and write with.

In the meantime, before we transition to CIRCLS, we want to dive into the final report from CIRCL. In it, we reflect on what we’ve learned since 2013 when CIRCL started. The world and technology have both changed quite a bit. Over the years, CIRCL worked with the approximately 450 projects funded by the National Science Foundation through their Cyberlearning program. The term Cyberlearning is a hard word to grasp, but the program and the projects in it were about using what we know about how people learn and creating new design possibilities for learning with emerging technology. In addition, in a 2017 report, we noted a strong commitment to equity in the CIRCL community. That commitment continues and is discussed in our final report with recommendations for future work to strengthen this important theme.

One thing we were struck by, in the review of the projects, was that there were many innovative designs to enhance learning with technology. As we tried to categorize the projects, we noticed that most contained combinations of multiple technologies, learning theories, and methods. While this may sound confusing, these combinations were purposefully designed to help augment learning and deepen our understanding of the technologies and how people learn. We looked for a term to use to explain this phenomenon and couldn’t find one, so we came up with a new one: Ambitious Mashups. In addition to the importance of mashing things up, the report also discusses:

Next week, we’ll be part of a webinar and talk through the different sections of the report. The webinar welcomes practitioners who want to learn more about research on emerging technologies from NSF-funded projects. While the projects aren’t always ready for use in a school today they offer ideas for new projects and new ways to think about how to use technology to support learning. The ambitious mashup projects think about learning in different ways and show how grounding activities in what we know about how people learn can help meet learning goals and outcomes. Ambitious mashups are usually exciting and give new ideas. CIRCL Educator Sarah Hampton says CIRCL reports can “help you get excited about the future landscape of education.”

We invite you to join us to learn more about Ambitious Mashups and Reflections on a Decade of Cyberlearning Research Webinar
Date: 10/28/2020
Time: 4 pm Eastern / 3 pm Central / 1 pm Pacific

Register

 

 

Book Review: You Look Like a Thing and I Love You

AI in Education, Engineering, Learning, STEM, Teachers & Researchers, Written by: Judi Fusco

By Judi Fusco

During CIRCL Educators’ Summer of Artificial Intelligence (AI), I read the book You Look Like a Thing and I Love You: How AI Works and Why It’s Making the World a Weirder Place1, by Dr. Janelle Shane. I got the recommendation for it from fellow CIRCL Educator, Angie Kalthoff.

I found the book helpful even though it is not about AI in education. I read and enjoyed the e-book and the audio version. As I started writing this review, I was driving somewhere with one of my teenagers and I asked if we could listen to the book. She rolled her eyes but was soon laughing out loud as we listened. I think that’s a great testament to how accessible the book is.

Teaching an AI

Many of us use AI products like Siri or Alexa, on a regular basis. But how did they get “smart?” In the book, Dr. Shane writes about the process of training machine learning2, systems to be “intelligent”. She tells us how they certainly don’t start smart. Reading about the foibles, flailings, and failings that she has witnessed in her work helped me understand why it is so important to get the training part right and helped me understand some of what needs to be considered as new products are developed.

Dr. Shane starts out comparing machine learning and rule-based AI systems, which are two very different types of AI systems. Briefly, a rule-based system uses rules written by human programmers as it works with data to make decisions. By contrast, a machine learning algorithm3 is not given rules. Instead, humans pick an algorithm, give a goal (maybe to make a prediction or decision), give example data that helps the algorithm learn4, and then the algorithm has to figure out how to achieve that goal. Depending on the algorithm, they will discover their own rules (for some this means adjusting weights on connections between what is input and what they output). From the example data given to the algorithm, it “learns” or rather the algorithm improves what it produces through its experience with that data. It’s important to note that the algorithm is doing the work to improve and not a human programmer. In the book, Dr. Shane explains that after she sets up the algorithm with a goal and gives it training data she goes to get coffee and lets it work.

Strengths and Weaknesses

There are strengths and weaknesses in the machine learning approach. A strength is that as the algorithm tries to reach its goal, it can detect relationships and features of details that the programmer may not have thought would be important, or that the programmer may not even have been aware of. This can either be good or bad.

One way it can be good or positive is that sometimes an AI tries a novel solution because it isn’t bogged down with knowledge constraints of rules in the world. However, not knowing about constraints in the world can simultaneously be bad and lead to impossible ideas. For example, in the book, Dr. Shane discusses how in simulated worlds, an AI will try things that won’t work in our world because it doesn’t understand the laws of physics. To help the AI, a human programmer needs to specify what is impossible or not. Also, an AI will take shortcuts that may lead to the goal, but may not be fair. One time, an AI created a solution that took advantage of a situation. While it was playing a game, an AI system discovered there wasn’t enough RAM in the computer of its opponent for a specific move. The AI would make that move and cause the other computer to run out of RAM and then crash. The AI would then win every time. Dr. Shane discusses many other instances where an AI exploits a weakness to look like it’s smart.

In addition, one other problem we have learned from machine learning work, is that it highlights and exacerbates problems that it learns from training data. For example, much training data comes from the internet. Much of the data on the internet is full of bias. When biased data are used to train an AI, the biases and problems in the data become what guide the AI toward its goal. Because of this, our biases, found on the internet, become perpetuated in the decisions the machine learning algorithms make. (Read about some of the unfair and biased decisions that have occurred when AI was used to make decisions about defendants in the justice system.)

Bias

People often think that machines are “fair and unbiased” but this can be a dangerous perspective. Machines are only as unbiased as the human who creates them and the data that trains them. (Note: we all have biases! Also, our data reflect the biases in the world.)

In the book, Dr. Shane says, machine learning occurs in the AI algorithms by “copying humans” — the algorithms don’t find the “best solution” or an unbiased one, they are seeking a way to do “what the humans would have done” (p 24) in the past because of the data they use for training. What do you think would happen if an AI were screening job candidates based on how companies typically hired in the past? (Spoiler alert: hiring practices do not become less discriminatory and the algorithms perpetuate and extend biased hiring.)

A related problem comes about because machine learning AIs make their own rules. These rules are not explicitly stated in some machine learning algorithms so we (humans aka the creators and the users) don’t always know what an AI is doing. There are calls for machine learning to write out the rules it creates so that humans can understand them, but this is a very hard problem and it won’t be easy to fix. (In addition, some algorithms are proprietary and companies won’t let us know what is happening.)

Integrating AIs into our lives

It feels necessary to know how a machine is making decisions when it is tasked with making decisions about people’s lives (e.g., prison release, hiring, and job performance). We should not blindly trust how AIs make decisions. AIs have no idea of the consequences of its decisions. We can still use them to help us with our work, but we should be very cautious about the types of problems we automate. We also need to ensure that the AI makes it clear what they are doing so that humans can review the automation, how humans can override decisions, and the consequences of an incorrect decision by an AI. Dr. Shane reminds us that an “AI can’t be bribed but it also can’t raise moral objections to anything it’s asked to do” (p. 4).

In addition, we need to ensure the data we use for training are as representative as possible to avoid bias, make sure that the system can’t take shortcuts to meet its goal, and we need to make sure the systems work with a lot of different types of populations (e.g., gender, racial, people with learning differences). AIso, an AI is not as smart as a human, in fact, Dr. Shane shares that most AI systems using machine learning (in 2019) have the approximate brainpower of a worm. Machine learning can help us automate tasks, but we still have a lot of work to do to ensure that AIs don’t harm or damage people. 

What are your thoughts or questions on machine learning or other types of AI in education? Tweet to @CIRCLEducators and be part of the conversation.

Thank you to James Lester for reviewing this post. We appreciate your work in AI and your work to bring educators and researchers together on this topic.

See a recent TED Talk by author Janelle Shane.

Notes:

  1. Read the book to find out what the title means!
  2. Machine learning is one of several AI approaches.
  3. Machine Learning is a general term that also includes neural networks and the more specialized neural network class of Deep Learning. Note also, a famous class of ML algorithms that use rules are decision-tree algorithms.
  4. Some algorithms “learn” with labeled examples and some without, but that’s a discussion beyond the scope of this post.
STEM for ALL video hall logo and text: Eager Maker: Studying the role of failure in design making

EAGER: MAKER: Studying the Role of Failure in Design and Making

STEM, Video Showcase, Written by: Angie Kalthoff

by Angie Kalthoff

One of the videos in the STEM for All Video Showcase covered learning what failure means. In the video, Alice Anderson says, “we really heard from educators that they wanted their learners to struggle and persist through struggle and problem solve.” I connected with what Alice described in the video, it made me think “This is it! This is what I want too!” This blog post shows my reflections on this video.  I recommend watching the video to better think with me about the role of failure in learning.

As an educator, I value growth mindset–being able to say to myself, I don’t know it yet but I can work towards it and try my best. I work to instill this mindset in my students at the early childhood, elementary, and university levels. When reviewing this STEM for All project, I connected with a comment made by Adam Maltese “My sense is that the best way to achieve this is to create a culture where iteration toward improvement is a core ideal.”

There’s often not time nor the correct culture for iteration in schools. With my students, I use the word FAIL as an acronym: First Attempt In Learning; I tell my students that I expect them to fail, I fail too. I know it can be frustrating to fail and I try to support them with read-alouds of books to show how the characters have dealt with failure.  (Side note, for inspiration and to show grit, Rosie Revere, Engineer books are great to share with students.) I will share more from the video about projects and findings around failure and some ideas for the classroom.

Overview of the program featured in the video

Over the last few years, the research team that created the video explored how kids (9-15 years of age) engage in making in both formal and informal contexts to see how they respond when things do not go as planned. They looked at how youth reacted to moments of failure and what role adults play in these experiences in hopes of finding a way to help kids persist when they experience frustration. Their goal was to help kids keep coming back and understand how they define failure.

Kids in this study were from three locations: a museum-based maker program, middle school classrooms, and an after-school making and tinkering program.

Around persistence, the team considered was if the attitude displayed by students was related to how familiar a learner was with the tools and materials. Could their familiarity have influenced their persistence?  For example, if a student was engaging with new material and they gave up after only a few attempts but persisted much longer on another project, was there any correlation between having experience with a tool and the amount of time spent problem solving.

How to use in practice

If you’re interested in thinking more about failure, this project gave some practical tips teachers can implement in their classrooms. To illustrate, I make connections from their suggestions to similar things I’ve done in classrooms.

They suggest: Save failures to learn from.

After attending DevTech professional development and working with students in the Early Childhood Technology (ECT) Graduate Certificate Program at Tufts University (where I currently work), I was inspired to keep a Kibo (a robot created for young children available through Kinderlab Robotics) hospital of broken parts. Instead of throwing away parts that no longer work, we keep them for kids to see and explore. They now get to explore broken motors to understand why it’s important for them to use them appropriately. By keeping things that don’t go right, or are a fail, they get to learn from the experience. In this STEM for ALL research project, researchers explain how at one summer camp, they created a Museum of Bent Nails. They took the experience of being frustrated when learning how to use nails and the failure one might feel when one becomes bent and turned it into a learning experience. Fellow CIRCL Educator, Sarah Hampton also loves how it turns all the hard work and learning into a badge of honor — it’s such a tangible way to value failure as a necessary part of the process!

They suggest: Facilitate learning, don’t fix things that aren’t working.

When I was first attempting to facilitate learning with kids and programming, I attended a Code.org workshop. In the workshop, I heard a suggestion about pretending to hold a teacup or actually holding something in my hands like a cup or a book to stop me from taking control of a device to fix broken programs. By doing this, as I walk around as an educator, I am not tempted to touch student projects and fix things for students. Instead, I ask questions to help when students are stuck.  (It’s really easy to not realize you do things FOR students!)

Some tips from educators in the video:

  • Keeping your hands behind your back while talking with learners (so you don’t handle their project)
  • Ask for permission to touch student projects
  • Suggest that learners ask two other people before a teacher

They suggest: Take time to reflect on your own behaviors

Related to facilitating learning and not doing it for the students, Co-Presenter Amber Simpson shared what she did: “I decided to wear a GoPro camera to capture my interactions with upper elementary students engaging in making activities. It is alarming what you learn in watching yourself on video as I was not necessarily modeling appropriate behavior for the undergraduate students I was working with in the space. I found myself not allowing the elementary students to experience failure as much as I thought (or hoped for). However, being on this project has made me aware of such instances and trying to be mindful of my response (or not) to failures not only in making contexts but other contexts such as an academic setting.”

If you have the resources, it is great to watch yourself on video. Okay, it might be a little painful, but the insights are so important.

They suggest: Think about how the word FAILURE is used.

The researchers discussed the reticence they saw in educators to use the term failure. For K12 classroom educators, it can be hard for us to embrace because of the need to assign grades. For informal educators, who are often bound by the need to make the experience fun, they may find the word failure antithetical to their purposes. Also, a teacher’s background relates to how they use the word failure.  For example, educators with an engineering background are very familiar with iteration in a design cycle and bring that in. Educators with an artistic background also talk about the process of creating and not ever reaching “the end.” That notion can either be daunting — to think one is never done, or it can be comforting to know that you can always continue to improve.

As an educator, I am still curious about a few other things related to practice:

  • Mindset around failure. What were people already thinking about and how did past experiences influence their experience?

I know some of my students are more ready to think about and handle failure.  How can I help all of them?

  • Working through struggles. How can adults help kids redefine failure as a chance to try something new?

I have some new ideas, but I’m going to keep thinking about this.

  • Developing practical experiences around struggle. Can a particular experience be designed to help all kids and adults become comfortable with struggle?

Again, no easy answer, I’ll keep thinking here.

Practical note: I discussed this project and the idea of failure with Sarah Hampton. She and I agree that it is important to instill the iteration/design process into lessons and yet we find it hard to take the time with current academic expectations and demands in the school day. If you have suggestions for us, please share via Twitter at @circleducators and #CIRCLedu

Presenters’ Choice Award Winning Project:Hero Elementary

Science, STEM, Student-driven Learning, Video Showcase

By Angie Kalthoff

When I saw that Joan Freese was the lead presenter for Hero Elementary, I knew I had to check it out! I have long followed her work at TPT Twin Cities with SciGirls, a separate project. The project I’ve been most interested in is SciGirls Code: A National Connected Learning Model to Integrate Computing in STEM Learning with Middle School Girls, supported by the National Science Foundation’s STEM + Computing Partnerships Program. You may have read my post from last year on the STEM For ALL Video Showcase Featuring SciGirls Code. I knew I wanted to review this Presenters’ Choice award winning project called Hero Elementary.

Overview of the program
The video gives an introduction to Hero Elementary. Go watch it if you haven’t. Hero Elementary is described as an equity driven educational media initiative focused on improving school readiness on science and literacy in grades K-2. The design of the program includes aspects on Universal Design for Learning (UDL) and equity strategies. Kids engage in activities to promote a growth mindset and Social Emotional Learning (SEL) in a blended approach. They have real world hands-on learning plus digital and multimedia learning. It has 25 science-themed educational media collections, called “playlists,” which are ”aligned to NGSS. Resources provided to educators include:

  • Animated stories
  • Digital and analog games
  • Non-fiction ebooks
  • Hands-on science activities
  • Digital Science Power Notebook

Hero Elementary has a target audience of kids in Latinx communities, English Language Learners, children with disabilities, and children from low-income households.The program “ignites children’s natural curiosity, broadens their understanding of how the world works, and empowers them to make a positive difference in their communities.” Their approach is child centered, equity focused, and asset based. As a constructivist inspired program, kids build their knowledge through active learning and reflection, which helps them make sense of their new learning experiences.

The goal of the program
Using formative research to aid in development, the project is working to transform learning and track progress with embedded learning analytics. Hero Elementary’s resources integrate science and literacy. The team identified similarities in the following English and science standards strands:

  • Science and Engineering Practices: Utilize the skills, thinking, and language of Scientific Inquiry and Engineering Design.
  • Literacy & English Language arts: Produce and receive communication in a variety of forms.

Through playful characters, kids learn about the “Superpowers of Science” by engaging in activities that encourage them to investigate, collect information, look for patterns, name the problem, make sense, explain, ask questions, compare, show what they know, and figure out a solution. Science educators will recognize these superpowers as the Science and Engineering practices, part of the NGSS. The program has a focus on literacy as well that appeals to many of the educators who have been involved in the development of this program. The program will debut for all this coming summer.

Educators involved with this program receive professional development training and free resources. Hero Elementary uses a train-the-trainer model with support from child-serving partners across the country, all of whom have a strong commitment to equity, interest in science education, and experience working with targeted student groups.

Using in practice
If you work in elementary education, you have probably experienced that the school day is full and planned out to the minute. I think the approach Hero School has taken – alignment to standards that schools are already implementing – is great.
Hero Elementary is broken into playlists. A playlist is a collection of content about a topic to inspire, empower, and deepen children’s science learning. Each playlist consists of the following resources: ebooks, hands on-activities, notebooks, videos, and digital games. While there are 25 playlists, educators can pick what works best in their classroom.

Through the research done on this project, the Hero Elementary team has found that kids are paying attention to the extent to which a character is relatable. CIRCL Educators feel that this topic deserves its own blog post. Watch for an upcoming post to read more about how kids are paying attention to character relatableness and why this matters for learning. In the meantime, check out how Hero Elementary can help bring fun science content and NGSS into your classroom.

Creative Coding in Python book

Interview with Creative Coding in Python Author Sheena Vaidyanathan

Book Club, Computer Science, STEM, Written by: Pati Ruiz

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

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

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

Can you tell us about your book?

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

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

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

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

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

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

What are some of favorite projects in your book?

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

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

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

What are you working on now?

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

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

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

Creative Coding in Python book

Book: Creative Coding in Python by Sheena Vaidyanathan

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

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

Sign up to stay informed about the book club!

About this Book

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

CREATE YOUR OWN CHATBOTS

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

CREATE YOUR OWN ART MASTERPIECES

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

About the Author:

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

How to Participate:

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

Wakelet

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

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

Resource 1- Popular Programming Languages
Resource 2- Flowchart

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

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

Woman types on laptop code books surround her photo by #WOCinTech Chat

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

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

by Pati Ruiz

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

Build Community and Connect Students with Mentors

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

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

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

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

Introduce Careers

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

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

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

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

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

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

Make Interdisciplinary Connections

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

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

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

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

4 students in The International Community for Collaborative Content Creation

The International Community for Collaborative Content Creation (IC4)

Collaboration, Cyberlearning, STEM, Video Showcase, Written by: Sarah Hampton

by Sarah Hampton

In my last post, we talked about how much there is to effective collaboration and discussed some of the things we should promote during collaborative activities. In this post, I will share how one cyberlearning project is capitalizing on all my favorite aspects of collaboration.

A few months ago, I had a chance to facilitate for the 2018 STEM For All Video Showcase, an online collection of very short videos from federally funded projects that aim to improve STEM education. I really enjoyed thinking deeply about my assigned videos and having conversations with the researchers involved, and, since then, I’ve enjoyed watching several more of the videos outside my group. One of these projects has continued to hold my thoughts. It’s called the International Community for Collaborative Content Creation (IC4). In this project, students from different countries collaborate online to create a media presentation, most often a video, that explains a STEM topic to their peers. The groups work across national, cultural, and ethnic boundaries to create these artifacts using tools such as Google Hangouts, Skype, Slack, and iMessage to communicate. Several things about this project are appealing to me:

  1. Students are reflecting deeply on STEM topics, deeply enough to be able to explain them to others. The project team calls this “participatory teaching”. As Einstein said, “If you can’t explain it simply, you don’t understand it well enough.” So, the expectation for meaningful content comprehension is embedded in the project. Furthermore, Project Lead, Eric Hamilton observed that, “If you combine helping people with learning, then instead of being in class to do well on a test, you instead are learning to help yourself and others succeed. The result can be transformational.”
  2. The researchers place an emphasis on the process of finding and negotiating shared meaning. Coming to a shared understanding through interaction and reciprocal sense-making is called co-construction. Co-construction can result in a visible outcome like a jointly created physical product and/or an invisible outcome like a more sophisticated way of thinking about something. The students involved in IC4 are not passively receiving knowledge. They are actively co-constructing their understanding of STEM topics as they grapple with them in conversations with others and as they co-construct digital media artifacts. I highly recommend Learning by Collaborating: Convergent Conceptual Change, Co-constructivism in Educational Theory and Practice, and From Intersubjectivity to Group Cognition to learn more about how this plays out during collaboration and what it brings to the learning process.
  3. The participants represent fundamentally distinct cultures, countries, economic, and social backgrounds. People tend to consciously and/or subconsciously choose to socialize with others who are similar to themselves. (That tendency is called homophily if you’re interested in googling a term to learn more.) At the same time, research tells us that diverse groups routinely outperform their homogeneous counterparts. And it doesn’t only benefit the group, it benefits the individuals, too.
  4. Students are working on STEM problems that matter. One teacher said that initially students selected their own STEM topic, but in a more recent iteration, they were asked to choose topics from the UN Sustainable Development Goals. Too often, we ask our students to complete tasks that carry no real-world meaning, and I know that our world has untapped intellectual capital in our students – I see it every day! Why not allow our students to apply what they’re learning in their subjects to work toward solutions for ambitious real world challenges? After all, they are the ones who will inherit them.

Because I’ve been so encouraged by the nature of this project, I keep thinking about how it could be implemented on a larger scale, and like many projects that have piqued my interest, I am frustrated by the very real obstacles that would make that challenging. Right now students are participating in this project in club settings. I’m sure part of that is because of the difficulty coordinating online meetings in different time zones; parts of the project occur synchronously and other parts asynchronously. But I would love to see this become accessible for all students as part of their everyday classroom experiences. However, teachers are so constrained by their national and state mandated learning objectives that there isn’t much time for long-term projects like these. In my opinion, this is an absolute shame! I feel like we are sacrificing more important goals (international cooperation, shared meaning making and problem solving with diverse peers, and the UN sustainable development goals) for more immediate and measurable ones (subject/verb agreement and fraction operations). I’m not saying the latter goals are unimportant, but rather I am saying that there has to be a way to teach and assess the latter in the context of the former. We as teachers need to feel like we have the time, permission, funding, and support to pursue both goals during the school day. Otherwise, meaningful and ambitious projects like this will not be able transform education at the scale I think it has the potential to do.

Stepping beyond my teacher role for a moment, as a parent, I want this kind of learning experience for my sons. I want them to engage in real and significant problems with people they otherwise wouldn’t have access to without social media and a digital makerspace. As a parent, I would be willing to sacrifice three to six weeks of standard educational fare for that kind of experience. I remain encouraged by the fact this project is active and federally funded. Despite the lag between current educational research and widespread current education practices, I hope this suggests we’re headed in the right direction. I tend to be a wee bit impatient sometimes, so my husband has to frequently remind me that you only make slight adjustments to the course when you’re steering a big ship. I just hope that by the time my boys are in middle school this is the course we’ll be on.

Since some of my favorite aspects of this project are co-construction, diverse participants, and working on challenges that matter. I would love to hear your take on the project and your reactions to my concerns about the obstacles to running this through the classroom. Let’s see if we can negotiate some shared meaning online just like these students are doing. What aspects of the project appeal to you? What obstacles would prevent you from doing something similar during your school day?

Learn More

2018 Stem for All Video Showcase

IC4 2018 Showcase Video

IC4 Website

CIRCL Perspective on Project Lead, Eric Hamilton

Co-constructing Shared Meaning

Learning by Collaborating: Convergent Conceptual Change

Co-constructivism in Educational Theory and Practice

From Intersubjectivity to Group Cognition

Homophily

Homophily: Measures and Meaning

Homophily and Ethnic Background in the Classroom

Benefits of Diversity

The Benefits of Socioeconomically and Racially Integrated Schools and Classrooms

The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies

The Truth about Diverse Teams

Groups of Diverse Problem Solvers Can Outperform Groups of High-ability Problem Solvers

Why Diversity Matters

Why Diverse Teams are Smarter

How Diversity Makes Us Smarter

Broadening Youth Participation in Computer Science & Engineering

UN Goals

UN Sustainable Development Goals

SciGirls Code Image STEM for All

STEM for All Video Showcase Featuring SciGirls Code

Computational Thinking, Computer Science, STEM, Video Showcase, Written by: Angie Kalthoff

By Angie Kalthoff

The STEM for ALL Video Showcase is an online film festival of 3-minute videos about educational projects that are really interesting to watch. It includes projects funded by the National Science Foundation (NSF) and other organizations with a goal to highlight projects that are transforming Science, Technology, Engineering, Mathematics and Computer Science education. In 2018, there were 214 video projects shared that highlighted the work of 713 presenters and co-presenters. The showcase project brought people from over 174 countries to the site to learn and discuss.

The showcase is an interactive event. Viewers were invited to ask questions and have discussions with the people doing the research and with other viewers, right on the site in a discussion thread. You can still go read the conversations that happened on the site during the event. Conversations were also carried over to social media. To follow along the Twitter conversation, you can visit #STEMvideohall.

An additional element making this an interactive project is the awards. Projects were recognized through the following awards:

  • Facilitator Choice
  • Presenter Choice
  • Public Choice

All projects fell into one of the following themes which revolve around

Transforming the Educational Landscape:

  • Partnerships that advance education
  • Broadening participation & access to high quality STEM experiences
  • Innovative practices transforming education
  • Research informing STEM learning and teaching

As a facilitator for the STEM for ALL Videoshow case, my job was to review projects and facilitate conversations with presenters and visitors. I facilitated discussions on projects around Computer Science (CS) and Computational Thinking (CT) in education. For me, this was an incredibly exciting experience. I am  a public school educator, more specifically a Technology Integrationist. I began my teaching career in an elementary English Learner (EL) classroom before transitioning to my current position. I am constantly thinking about ways to incorporate CS and CT into elementary classrooms while creating a culture where classroom teachers confidently deliver the lessons. In my job, I have conversations on a daily basis with educators, families, administrators, our community, and students about the importance of CS and CT in education. This showcase gave me insight into projects that are currently being worked on to make CS and CT education accessible for all students in a variety of different ways.

The video  project I would like to highlight in this post is SciGirls Code: A National Connected Learning CS Model. It was the winner of Presenters Choice and Public Choice awards!


As described on the site, “SciGirls Code,” a pilot program funded by the National Science Foundation STEM + C program, uses principles of connected learning with 16 STEM outreach partners to provide 160 girls and their 32 leaders with computational thinking and coding skills. To reach this goal, SciGirls developed:

  • a nine-month curriculum centering on three tracks—mobile apps, robotics, and e-textiles;
  • role model training for female technology professionals;
  • professional development for STEM educators;
and
  • a research component that investigates the ways in which computational learning experiences impact the development of computational thinking as well as interest and attitudes toward computer science (CS.)”

Girls in the program participate in projects around apps, robotics, and e-textiles all while sharing their learning with other girls in the program across the nation. Using Flipgrid, a Minnesota startup, girls create quick videos in which they share their thoughts and experiences. Through their experience they understand that coding isn’t an individual venture, it is connected.

SciGirls Code is trying to understand the following three questions:

  • How do computational learning experiences impact the development of computational thinking? [learning]
  • How does engaging in computational learning experiences impact interest in and attitudes towards computer science? [interest]
  • How does engaging in computational participation practices impact learners’ perspectives of self and world? [participation]

What they have seen so far from girls who participate in SciGirlsCode:

  • Increased confidence with coding in girls
  • Increased interest in pursuing CS careers
  • Excitement around CS, CT, and coding in general

I loved learning more about SciGirls because prior to the showcase I had been using and sharing resources from SciGirls Code. One of my favorite ways to talk with kids about STEM+C careers (which is STEM with Computing) and why we learn about computer science, is through personal stories. I have found many of SciGirls Code profiles helpful when introducing a coding or robotics activity. I like to start my lessons in classrooms by connecting how what we are doing could relate to the world around them. It could connect to a future career or real life examples they have experienced. While many of the activities have a focus towards girls in middle school, I am able to be selective in resources and adapt them to meet the needs for kids in kindergarten or while working with students of any age.

When you have time, visit their website so you can explore the many different resources they have. They have so much in addition to coding resources. Here are a few of my favorite:

  • Profiles – Featuring a variety of young and diverse women in STEM careers through short videos that showcase their careers and experiences.
  • Educator Resources – Providing a variety of resources for classroom use, access to training, and scholarships.
  • Kid Resources – A site for kids to explore videos, games, and create their own profile.

How do you connect classroom activities on STEM+C with real world stories? Who are the female role models you look to when encouraging a more inclusive culture? How could you use SciGirlsCode resources with kids you know (in and out of the classroom)?

The STEM for All Video Showcase is funded by (Award #1642187) and done in collaboration with the following NSF-funded resource centers: MSPnet, CADRE, CIRCL, CAISE, STELAR, and CS for All Teachers.

Visit the following links to see additional projects Facilitator Choice , Presenter Choice , Public Choice

Visit the following link to view additional facilitators.

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.