Category Archives: Written by: Judi Fusco

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

October 5, 2020AI in Education, Engineering, Learning, STEM, Teachers & Researchers, Written by: Judi FuscoJudi 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:

Read the book to find out what the title means!
Machine learning is one of several AI approaches.
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.
Some algorithms “learn” with labeled examples and some without, but that’s a discussion beyond the scope of this post.

Introduction to Culturally Responsive Teaching

September 3, 2020Diverse Learners, Teachers & Researchers, Written by: Judi Fusco, Written by: Pati RuizPati Ruiz

by Pati Ruiz and Judi Fusco

At CIRCL Educators, we’re on a journey to help students and we think culturally responsive teaching is an important part of it. Since we will have more posts that fall under this topic we wanted to share a few definitions and a few of our favorite resources that have helped us start thinking and talking about culturally responsive teaching. This is a starting roadmap. The terms mentioned are similar, but distinct. In the research world different terms represent different emphases. We’ll discuss the differences more in the future. We provide this glossary of terms and full references to the articles discussed below.

Definitions

Culturally Relevant Pedagogy: credited to Ladson-Billings (1995), this term “loosely refers to teachers’ ability to incorporate knowledge of students’ background and culture in their instructional practice to enhance student learning” (Gist, 2017, p. 289). However, it seems Ladson-Billings (2014) grew dissatisfied with how her term was used saying: “What state departments, school districts, and individual teachers are now calling “culturally relevant pedagogy” is often a distortion and corruption of the central ideas I attempted to promulgate. The idea that adding some books about people of color, having a classroom Kwanzaa celebration, or posting “diverse” images makes one “culturally relevant” seem to be what the pedagogy has been reduced to” (p. 82).”

Culturally Responsive Teaching: This term comes from Genva Gay’s work, which built on the Ladson-Billings ideas, and directed the approach more toward the act of teaching. “Gay (2010) explained culturally responsive teaching by arguing that such practices are a means for unleashing higher potentials of ethnically diverse students by simultaneously cultivating their academic and psychosocial abilities.” (Gist, 2017, p. 290). Gay characterized culturally responsive teaching by the use of ‘cultural knowledge, prior experiences, frames of reference, and performance styles of ethnically diverse students to make learning encounters more relevant to and effective for them.

Culturally Responsive Pedagogy: is an umbrella term used by Gist (2017) that includes Culturally Relevant Pedagogy and Culturally Responsive Teaching as well as the intentional strategies that teachers should implement to create an environment in which all children have equitable opportunities to learn.

A related term is Culturally Relevant Education (Aronson & Laughter, 2016). This work places the work of Gay on teaching and Ladson-Billings on pedagogy at the center of an effort to create a social justice pedagogy.

Books

Gay, G. (2010). Culturally responsive teaching: Theory, research, and practice (2nd ed). Multicultural Education Series. New York, NY: Teachers College Press.
Culturally Responsive Teaching and the Brain by Zaretta Hammond

Articles

Aronson, B., & Laughter, J. (2016). The theory and practice of culturally relevant education: A synthesis of research across content areas. Review of Educational Research, 86(1), 163-206. https://doi.org/10.3102/0034654315582066

Gist, C. D. (2017). Culturally Responsive Pedagogy for Teachers of Color. New Educator, 13(3), 288–303. https://doi.org/10.1080/1547688X.2016.1196801

Ladson-Billings, G. (1995). Toward a Theory of Culturally Relevant Pedagogy. American Educational Research Journal, Vol. 32, No. 3. (Autumn, 1995), pp. 465-491.

Ladson-Billings, G. (2000). Culturally relevant pedagogy in African-centered schools: Possibilities for progressive educational reform. African-centered schooling in theory and practice, 187-198.

Ladson-Billings, G. (2014). Culturally relevant pedagogy 2.0: Aka the remix. Harvard Educational Review, 84(1), 74-84. doi:10.17763/haer.84.1.p2rj131485484751

Reports

Krasnoff B. (2016) Culturally Responsive Teaching

We’ll close this post with this quote from Gist (2017, p. 290)

In both Ladson-Billings’ (1995) and Gay’s (2010) theorizing of culturally responsive practices, common themes of high expectations, acknowledgement of student cultural capital, critical sociocultural/political consciousness, and passion and dedication are apparent. Unfortunately, terms such as culturally responsive pedagogy can become so commonplace that teacher educators lose sight of what teacher candidates need to know and be able to do when attempting to cultivate culturally responsive practices with their future students. Moreover, even if culturally responsive pedagogy is emphasized and addressed in a teacher candidate’s preparation experiences, it can be inappropriately applied in ways that differ sharply from the original intent of culturally responsive pedagogy theorists (Ladson-Billings, 2014).

Thank you to Joseph Chipps, Ed.D. for reviewing this post. You can reach us by tweeting @CIRCLEducators. Please let us know what you are reading and thinking as we take this journey.

Harnessing Educational Data: Discussing Dr. Safiya Noble’s Keynote from Cyberlearning 2019

July 21, 2020AI in Education, Book Club, Cyberlearning, School Administrators, Teachers & Researchers, Written by: Amar Abbott, Written by: Angie Kalthoff, Written by: Judi Fusco, Written by: Pati Ruiz, Written by: Sarah HamptonPati Ruiz

By Pati Ruiz, Sarah Hampton, Judi Fusco, Amar Abbott, and Angie Kalthoff

In October 2019 the CIRCL Educators gathered in Alexandria, Virginia for Cyberlearning 2019: Exploring Contradictions in Achieving Equitable Futures (CL19). For many of us on the CIRCL Educators’ team it was the first opportunity for us to meet in person after working collaboratively online for years. In addition, CL19 provided us with opportunities to explore learning in the context of working with technology and meet with researchers with diverse expertise and perspectives. We explored the tensions that arise as research teams expand the boundaries of learning, and explored how cyberlearning research might be applied in practice.

One of the topics, we thought a lot about at CL19, is algorithms. We had the opportunity to hear from keynote speaker Safiya Noble, an Associate Professor at UCLA, and author of a best-selling book on racist and sexist algorithmic bias in commercial search engines, Algorithms of Oppression: How Search Engines Reinforce Racism (NYU Press). In her Keynote, The Problems and Perils of Harnessing Big Data for Equity & Justice, Dr. Noble described the disturbing findings she uncovered when she started investigating algorithms related to search. She was not satisfied with the answer that the way algorithms categorized people, particularly girls of color, was what “the public” wanted. She dug in deeper and what she said really made us think.

This keynote is related to some of the conversations we’re having about Artificial Intelligence (AI), so we decided to re-watch the recorded version and discuss the implications of harnessing Big Data for students, teachers, schools, and districts. Big Data is crucial in much work related to AI. Algorithms are crucial. We bring this into our series on AI because even though math and numbers seem like they are not culturally-biased, there are ways that they are and can be used to promote discrimination. In this post, we don’t summarize the keynote, but we tell you what really got us thinking. We encourage you to watch it too.

Besides discussing algorithms for search, Dr. Noble also discusses implications of technology, data, and algorithms in the classroom. For example, Dr. Noble shared how she breaks down how a Learning Management System works for her students so that they know how the technology they are using can inform their professors of how often and how long they log into the system (among other things). She said they were often surprised that their teachers could learn these things. She went on to say:

“These are the kinds of things that are not transparent, even to the students that many of us are working with and care about so deeply. “

Another idea that particularly resonated with us, as teachers, from the talk is the social value of forgetting. Sometimes there is value in digitally preserving data, but sometimes there is more value in NOT documenting it.

“These are the kinds of things when we think about, what does it mean to just collect everything? Jean–François Blanchette writes about the social value of forgetting. There’s a reason why we forget, and it’s why juvenile records, for example, are sealed and don’t follow you into your future so you can have a chance at a future. What happens when we collect, when we use these new models that we’re developing, especially in educational contexts? I shudder to think that my 18-year-old self and the nonsense papers (quite frankly who’s writing a good paper when they’re 18) would follow me into my career? The private relationship of feedback and engagement that I’m trying to have with the faculty that taught me over the course of my career or have taught you over the course of your career, the experimentation with ideas that you can only do in that type of exchange between you and your instructor, the person you’re learning from, that being digitized and put into a system, a system that in turn could be commercialized and sold at some point, and then being data mineable. These are the kinds of real projects that are happening right now.”

We are now thinking a lot about how to help students and teachers better understand how our digital technology tools work, how we should balance the cost of using technology to help learners with the potential problem of hyper-datafication of saving everything and never letting a learner move past some of their history.

As we think through this tension, and other topics in the keynote, some of the questions that came up for us include:

What information is being collected from our students and their families/homes and why? Where does the information go?
Who is creating the app that is collecting the data? Are they connected to other programs/companies that can benefit from the data?
What guidelines for privacy does the software company follow? FERPA/COPPA? Do there need to be more or updated standards? What policies aren’t yet in place that we need to protect students?
What kinds of data is being digitally documented that could still be available years after a student has graduated? How could that impact them in job searches? Or, what happens when our students, who have documented their whole lives digitally, want to run for public office?
There are well-documented protocols for destroying students’ physical work, so what documented protocols are in place for their digital work?
Are school devices (e.g., Chromebooks or iPads) that contain student sensitive data being shared? Are all devices wiped between school years?
- Students clean out their desks and lockers at the end of the school year, should we be teaching them to clean out their devices?
- Do students have an alternative to using software or devices if they or their families have privacy concerns? Should they?
Is someone in your district (or school) accountable for privacy evaluation, software selection, and responsible use?
- How are teachers being taught what to look for and evaluate in software?

In future posts, we’ll cover some more of what Dr. Noble suggested based on her work including the following points she made:

(Re)consider the effect of hyper-datafication
Resist making issues of justice and ethics an afterthought or additive
Protect vulnerable people (students) from surveillance and data profiling
Fund critical digital media research, literacy programs, and education
Curate the indexable web, create multiple paths to knowledge
Reduce technology over-development and its impact on people and the planet
Never give up on the right things for the planet and the people

Finally, some of us have already picked up a copy of Algorithms of Oppression: How Search Engines Reinforce Racism and if you read it, we would love to hear your thoughts about it. Tweet @CIRCLEducators. Also, let us know if you have questions or thoughts about the keynote and/or algorithms.

Strengthening Education Research: Connecting Teaching and the Learning Sciences

June 22, 2020Learning, Teachers & Researchers, Webinar, Written by: Judi Fusco, Written by: Pati RuizPati Ruiz

Take a look at the recorded session Digital Promise learning sciences researchers did for ICLS 2020. At Digital Promise, learning sciences researchers investigate the why, what, and how of learning across ages, backgrounds, and contexts through four projects. We will provide examples of how our research includes a wide range of education stakeholders across K-12 and higher education and how this work gives rise to promising learning innovations, processes, and outcomes.

CIRCL Educators Judi Fusco & Pati Ruiz presented as part of the group, watch the whole session or go to 14 minutes in for our talk titled Bridging Practice and Research: Connecting Teaching and the Learning Sciences. https://youtube.com/watch?v=iTzIiN

Find our syllabus here.

Tweet @CIRCLEducators and let us know if you have questions or thoughts about this presentation.

Teaching and Beliefs about Learning

June 19, 2020Learning, School Administrators, Teachers & Researchers, Written by: Judi FuscoJudi Fusco

By Judi Fusco

This post features the dissertation work of Michaela Jacobsen, Ed.D (completed March, 2019). She is currently Assistant Principal at Louis E. Stocklmeir Elementary School in the Cupertino Union School District.

In her dissertation, she investigated:
1) What supports teachers need when they are actively leading and designing their own professional learning.
2) How teacher beliefs about learning relate to how they participate in an active professional learning program.
3) How teachers beliefs about teaching and learning change from beginning to end of the experience.

We are currently in a time of uncertainty about so many issues. During this past spring, teachers experienced a time when everything changed. The work by Dr. Jacobsen looks into the importance of thinking about beliefs during a change process. While her work looked at a set of specific conditions around change, she found important considerations for any situation where people are asked to change.

We know from past research that effective professional learning promotes active learning, emphasizes collaboration, is sustained over time, is related to teachers’ specific contexts and curriculum, and is coherent with the school as a whole. Over the school year, Dr. Jacobsen worked with the three teachers. The school principal and vice principal also offered support. The three teachers and Dr. Jacobsen, who acted as a facilitator for the group, devoted much of their school-based professional learning time to work together. A problem-based learning (PBL) approach was the method.

In PBL, learners work to solve authentic, ill-structured problems with a facilitator. The facilitator helps establish a culture of collaboration in developing a deep shared understanding of the problem and possible solutions. Facilitators also model good problem solving strategies and refrain from giving answers. In PBL, learners gain knowledge as they work together and discuss and reflect around the problem to be solved. PBL was chosen because it promotes active inquiry, the acquisition and deepening of problem-solving skills, self-direction, reflective practices, and collaboration and communication skills. These are important for all learners, but especially important for professionals.

Together, the three teachers chose a problem around how to adopt a new practice, specifically how to help students become better problem solvers in math. All the teachers felt that learning how to help students become better problem solvers would be challenging, but agreed it would be an important problem to solve. Math was taught in a very traditional instructional manner in their school and the new practice of putting the learner at the center did not fit particularly well in the school’s established culture. Through interviews and questions, Dr. Jacobsen learned that for two of the teachers, the new practice did not fit into their belief systems of teaching and learning. One of the teachers had beliefs that aligned with the methods and practices necessary to help students become better problem solvers.

For the teacher with beliefs that were consistent with the new practice, she worked to fully understand what it meant for a student to be a better problem solver and then planned and worked to implement many aspects of the new practice in her classroom. Over the year, she planned and implemented many changes in her classroom practice. She also reported seeing changes that she felt were positive in her students as they became better problem solvers.

For the two teachers with conflicting beliefs to the new practice, there was little change in their understanding of the new practice or how to adopt it. In fact, to avoid a conflict between what they were supposed to do in the new practice and their beliefs, they joined forces and developed their own understanding of how to help their students become better problem solvers. They spent time together and constructed a way to make a different minimal change that was not in conflict with their beliefs. They also reported how they saw their students as being different than the students of the teacher who had success with the new problem solving methods. They used this “difference” to further reinforce their beliefs that the new methods couldn’t work with their students. They did not interact more than necessary with the facilitator, the third teacher, or the principal or vice principal all of whom could have challenged their thinking and given new issues to consider.

How the classroom practices of the three teachers changed or not depended on their beliefs around teaching and learning before the project started. The teacher who had beliefs that aligned with the new practice was able to understand it more deeply and move it into practice. The two teachers who started with beliefs that clashed with the new practice reinforced each other as they minimized how they would implement the new practice. These two teachers also used the “culture” of the school as a basis for defending their position and avoided the facilitator, the third teacher, and the principal and vice principal who were interested in making changes.

What does all this mean? If teachers are asked to make a change that does not align with what they believe about how students learn, they will most likely change “how they are being asked to change” to a way that matches their beliefs. When teachers are making a change, they need much support to help them understand the change. They need even more support when the change does not align with beliefs. Dr. Jacobsen outlines three strategies to help change teachers beliefs:

1) have them reflect on their beliefs in collaboration with others to think about pedagogical practices,
2) have a peer or coach (gently) challenge their beliefs and give feedback, and
3) give assistance while the teacher is making a change so that they can fully understand what needs to occur.

Additionally, experiencing a new pedagogy as a learner can be very effective. When teachers are put into a situation to be a learner, they can experience and really understand how the pedagogy works to promote learning.

Dr. Jacobsen’s dissertation citation is:

Jacobsen, M. (2019). A Multi-case Study of a Problem-based Learning Approach to Teacher Professional Development (Doctoral dissertation, Pepperdine University).

If you have questions, comments, or suggestions for us, please share via Twitter at @circleducators and #CIRCLedu

Remote Learning During the Pandemic: No one was trained for this and it’s changing by the hour

April 2, 2020Classroom Technology, Learning, School Administrators, Teachers & Researchers, Written by: Judi Fusco, Written by: Pati RuizPati Ruiz

By Judi Fusco and Pati Ruiz

During this uncertain time, we share stories about what different schools, districts, and educators are facing. As we spoke to educators, one sentiment that came through is that we’re all experiencing something new. Even educators with experience teaching online are supporting colleagues who haven’t done this before. All of the educators shared how going remote means you can’t do the same things as you do in a brick and mortar school. A half-full perspective says this is an opportunity to bring in new methods and think more about centering the student(s).

We spoke to three education leaders who have been thinking about online/remote learning for many years. Dr. Joy Lopez, Director of Technology at Sacred Heart Schools in CA helped create the SHP Flexible Plan for Instructional Continuity with Dr. Diana Neebe. Dr. Colleen Murray at Haddonfield Schools in New Jersey used the SHP plan to help create a guide for her district. At the Riverside County Office of Education, Dr. Steve Hickman helped develop remote learning guidance for the State of California. The three leaders had different perspectives depending on the people they serve; each discussed their plan as a starting point, and that each district, school, and teacher will need to figure out a solution for their unique situation. All of the educators spoke about the importance of making sure the people are the first priority. Dr. Lopez points out that this is a massive change and it’s not surprising that teachers and students feel like they are starting over.

We also spoke to Dr. Kip Glazer, a principal at a high school in Santa Barbara, CA who discussed the huge digital divide she sees; her high school is 51% free and reduced lunch. The school has been closed for a week, with the exception of providing meals for students, and will stay closed through spring break. Upon return, the district will move to remote learning. Right now, the focus is determining what they can do to deliver remote learning equitably. Because of the huge disparity in her district, Dr. Glazer has been considering, “What does remote learning look like for a kindergartner who is homeless, or for students with dangerous domestic situations?” In contrast, she has parents worried that their child won’t pass an AP test.

Dr. Glazer would love for people to understand that school is more than a place of testing, how it’s the heart and soul of a community. She sees students wandering around the school because they miss it. Drs. Murray and Glazer also discussed how the switch is causing some teachers and assistants, who are new to the digital world, to feel uncomfortable and uncertain about their role and what they can do to support students.

Remote learning is a new opportunity that will require learning on everyone’s part, creativity, compassion, and caring, and will continue to change in the next few weeks. We heard ideas for new classroom tactics. Dr. Lopez described how in situations with multiple teachers at the same grade level, they can team up for redundancy. She hopes none of her teachers get sick, but this could help mitigate coverage issues. Also, one kindergarten teacher got creative and put her iPad on a chair while talking to students to give the same view they have from the circle-time rug.

Sarah Hampton, a middle school math teacher is making ShowMe videos for students to help them understand operations with exponents. She discussed how her ShowMes have an advantage over those made by others because she can say things in ways her students are used to hearing. She further personalizes by saying names during the videos to direct their attention. Kristyn Palazzolo, a Library Media Specialist, is working to support families. She is building a parent website with virtual field trips, sample daily schedules, curated lists of shows, enrichment activities (at home crafts and science activities), and other resources. Kristyn is also creating a reading challenge where parents take pictures when they catch their children reading and STEAM video challenges; the first was to create a Rube Goldberg machine.

Thank you, educators, for sharing. We know how much you miss your students, and we look forward to seeing more in this new digital space.

Going to ICLS!

We’re thrilled to announce we’re going to the International Conference of the Learning Sciences. We’ll be in the practitioner strand and are looking forward to great conversations. When we get our poster done on Bridging Practice and Research: Connecting Teaching and the Learning Sciences, we’ll share it here.

Constructionism and Epistemology

February 22, 2019Book Club, Collaboration, Constructivism, Written by: Angie Kalthoff, Written by: Judi FuscoJudi Fusco

By Judi Fusco and Angie Kalthoff

In our book club, a question came up that is important. Where’s the epistemology in constructionism? Constructing something doesn’t seem like epistemology. Is it? If you’re not in the book club, that’s okay, keep reading as we’re talking about the question that was asked and not the book.

First, great question — we should really think about it! Before we answer that question, let’s make sure we’re all in agreement of what epistemology is. It’s a tough word. There are many papers that spend a long time struggling with how to define it. Since this is a blog and not a class discussion where we can write on a whiteboard (physical or virtual) and really go back and forth, here’s a simple definition with elements that we think are good for starting this discussion. (Feel free to let us know if you think something should be added to it.)

Epistemology: the theory of knowledge, including how it is obtained, how it develops and changes, what it is, and how the knowledge is verified or justified

Whew, that’s a lot. It’s all about knowledge. What do you think?

The original question was about how does epistemology relate to constructionism? As constructionism starts with creating or building something, where’s the epistemology? In a creative act of building or making something, a person has to get the knowledge that is in their head into an artifact. Because of this, the creation of an artifact is an epistemological act. The creator demonstrates their understanding (knowledge) in the artifact. They also may be verifying it or justifying their knowledge. (Again, feel free to disagree or think with us here.)

For example, when making a Scratch Program, the creator may work for a long time on making sure that the size of a character (sprite) is correct, or that two characters have a certain size relationship between them, or that the program moves the character to the right place on the screen. The creator may plan before they create their artifact or act as a bricoleur.

bricoleur — a person figuring it out as they are doing it with “whatever” materials are there

Both approaches, planning and bricolage, are ways to create. Students approach Scratch programs in both of these ways. In both approaches, the creator may try and fail multiple times. There’s a lot to be learned when you try and fail. When you fail, but you want to succeed, you try something different. If you really like something you’ll keep trying and building up more knowledge about what works and what doesn’t. (Constructionism talks about the work being personally relevant, if it’s personally relevant, you probably like what you are doing and are invested in the act of improving it.) The process of trying and failing as you create is an epistemological act. If you try multiple times it continues to be an epistemological act. (We’ll discuss failing in a future post as it’s also a huge important topic!)

As your students begin to work through issues, think about how you can be supportive in this process of trying and failing. How can you create a culture that values failure in your classroom? When working with students who have questions about “the right answer,” one way is to help them to think in another way about the issue. At first, this is met with frustration from students. All they want to know, in that moment, is if their work is “right.”

Learning to work in this new way can be very challenging for both students and teachers. It’s hard not to give the “right answer.” If something is open-ended and doesn’t have one answer, for example when designing things, it can be easier to work in this new way because you can think through trade-offs with students. But it can still be hard not to point students in one direction when they are asking. It can also be hard to let students “fail.” Going back to the relationship with epistemology, students and teachers have a lot of experience in instructionist-style classrooms where teachers give the answer; moving to a constructionist style classroom takes time and practice. One of the things you have to learn to do is to hold back on giving the right answer. It can feel like you’re not doing your job, but you absolutely are. You will still guide, you will ask questions, but you won’t just tell them the answer.

After Creating the Artifact
After we have the object, another part of the process of constructionism occurs. People interact around the object. Last week, Judi wrote: A lot of people talk about constructionism as learning by doing, and it absolutely is, but while we create, we should also discuss, iterate, and learn (create new knowledge structures, or modify old ones in our heads). Setting up conditions so students can “make sense” and learn is so very important in constructionism.

To me (Judi), this part of constructionism is equally important as the creation part. It’s also an epistemological act. If you create, you will absolutely learn, but if you take time to hear what another person thinks about the object, what they think you got right and what you need to work on, that’s really magical. It can be really hard to get the conditions right where people will work together and give real, honest, informative feedback on something. This part of the process really requires that people trust each other, get into a shared intellectual space, and then think together.

How do we put constructionism into practice?
Reading more about constructionism gives me ideas about how to get this to happen in a classroom. Of course, there’s not just one thing I can point to say “this” is how you do it. It takes time to develop this in your classroom. The first time you try, it might not be so good. I always encourage people to start small, but with something meaningful and to keep reflecting on what is working or not. Don’t try and change your practice overnight. One important thing to remember as you try promote constructionist interactions and use this powerful learning method in your classroom, you need to trust your students and they need to trust you and their classmates. Constructionism came out of constructructivism; remember we are trying to get learners to construct their knowledge and understanding in the head and in the real world. Knowledge is complex, is constructed by the learner, and learning happens gradually. (One more thought about shared intellectual space, take a look at another recent blog post for more information about what that means; a shared mental space is so important in learning.)

More on Epistemology
Angie adds: I remember reading Mindstorms by Seymour Papert and first coming across the word epistemology. I was making notes and highlights and then I encountered the word epistemology. I dug deeper into this word and went online to see what else I could find. I hadn’t yet heard of this word and was trying to find meaning in the work I was doing as a Technology Integrationist. This was it! This was what I was trying to capture. Yes, I could see how technology, when used as a learning and creation tool, can really transform learning for students. But I was seeking the why. I knew there was more going on behind the scenes than just adding equipment. In fact, just adding technology doesn’t necessarily change the way learning occurs. The thought of epistemology, as a way that changes how we acquire knowledge, started me down the journey of computational thinking and coding in classrooms, as early as kindergarten. And here I am now, digging into as many things as I can find to help and share what is happening beyond using a tool.

Constructionism really is a way we can help students engage in meaning-making processes for themselves. The more we can help them do this, the more they learn. Epistemologically speaking, we’re not giving students “knowledge,” they are constructing it in in the world as objects to share with others and in their heads with the help of those artifacts, classmates, their teachers, parents, and others. We hope this helped with the question; we’d love to hear from you as discussion is so important in learning! As we listen to the book club entries, we’ll try to capture tips and suggestions and make another post about constructionism in the near future. If you have a question, or anything you think we should include or discuss, tweet #CIRCLEdu.

Constructionism (and Constructivism)

February 5, 2019Book Club, Computational Thinking, Constructivism, Written by: Judi FuscoJudi Fusco

by Judi Fusco

This post was written during our book club and discusses some concepts that were not covered in the book but are important as we think about constructionism.

We’re going to discuss constructionism and also think about constructivism; they are similar words and Papert’s constructionism grew out of Piaget’s constructivism. Note, we’ll talk more about Piaget’s constructivism (and Vygotsky’s social constructivism) in another post soon.

Our book club book, Coding as a Playground, discussed how Papert didn’t want to define constructionism rigidly. Marina Bers gives us some of the dimensions he discussed and some help thinking about it.

On page 21, she writes:

Seymour Papert refused to give a definition of constructionism. In 1991, he wrote, “It would be particularly oxymoronic to convey the idea of constructionism through a definition since, after all, constructionism boils down to demanding that everything be understood by being constructed” (Paper, 1991). Respecting his wish, in my past writings I have always avoided providing a definition; however, I have presented four basic principles of constructionism that have served childhood education well (Bers, 2008):

Learning by designing personally meaningful projects to share in the community;
Using concrete objects to build and explore the world;
Identifying powerful ideas from the domain of study;
Engaging in self-reflection as part of the learning process.

Bers goes on to discuss how constructionism is in line with ideas about how important “learning by doing” is for young learners. In another paper, Karen Brennan (2015) also discusses how important it is to let learners to design, personalize, share, and reflect during the constructionist process.You can see those ideas in the principles Bers discussed.

Karen Brennan also writes “Constructionism is grounded in the belief that the most effective learning experiences grow out of the active construction of all types of things, particularly things that are personally or socially meaningful (Bruckman, 2006; Papert. 1980), that are developed through interactions with others as audience, collaborators, and coaches (Papert, 1980; Rogoff, 1994), and that support thinking about one’s own thinking (Kolodner et al., 2003; Papert, 1980).”

Papert’s Paper Airplane: construction(ism) plus sharing the creation to discuss it with others, to think about what’s important and not important, and then working alone or with others to make the creation better.

I’m going to digress a little from thinking about elements of constructionism and give a little background on constructionism and constructivism. Papert was the father of constructionism and he worked with Jean Piaget, the genetic epistemologist who developed theories of constructivism to help us understand how young children acquire knowledge (background: genetic epistemologist, genetic = genesis or beginning; epistemology = study of knowledge). Bers tells us how constructionism is a play on and tribute to constructivism. Constructivism and constructionism are two terms that have caused much confusion in many folks. A few years back, my graduate students and I came up with a mnemonic to help them remember who developed the different ideas, and what constructionism and constructivism mean.

The mnemonic: Papert, his last name looks like “paper” with a t and you can construct a paper airplane because you like to make them, which makes it personally meaningful. Key here is you don’t constructivize them, you construct them.

When you’ve made your paper airplane you can show it and demonstrate how it flies to your friends and they can give you feedback on the design of the airplane. As you talk about it, you might discuss something that improves it, and then you can refine it. This whole process, making, discussing, and learning from it is constructionism. You learn because you make something, share it, discuss it, reflect on it, and continue to improve it. (You might have to use another sheet of paper for another paper airplane, though.)

This is in contrast to Piaget’s constructivism, which is all about what is happening in the mind: If you put an m (for mind) on top of a v (for constructivism) you can see how much we love constructivism.

Piaget’s constructivism is a theory about what happens in the mind as you actively create structures in the mind. Here’s the mnemonic: if you put an m (for mind) on top of a v (for constructivism) you can see how much we love constructivism. (Work with us here, it’s a mnemonic — also, there’s a v in love, too.) (See picture.)

Piaget’s constructivism is all about what is happening in the mind, whereas constructionism discusses the process that brings learners together to think about something tangible and specific. Of course, when we have learners work together, create, and build, we also hope they add new things to their minds (constructivism); the two should absolutely go together. (And it gets fuzzy here! Where does constructionism end and constructivism begin?) A lot of people talk about constructionism as learning by doing, and it absolutely is, but while we create, we should also discuss, iterate, and learn (create new knowledge structures, or modify old ones in our heads). I constructed this blog post to help us have something to talk about. Please join me and discuss so we can learn more together.

The perfect place to discuss is in our Book Club on Coding as a Playground, talk to about this post or even better, we’d love for you to share your real life examples of constructionism in classrooms as you work with students to help them learn to code or to think computationally. I’d love to know how you think about these terms and how you get your learners to design, personalize, share, and reflect on important parts of the work they are doing for their learning in your classroom! Tweet #CIRCLEdu or come share in the Book Club!

Resources

If you’d like to know more about Constructivism and Constructionism see:

http://fablearn.stanford.edu/fellows/blog/science-teacher’s-take-constructivism-constructionism

http://fablearn.stanford.edu/fellows/blog/constructivist-science

http://fablearn.stanford.edu/fellows/blog/constructionism-learning-theory-and-model-maker-education

Reference: Brennan, K. (2015). Beyond Technocentrism. Constructivist Foundations, 10(3).

Free, open, and high quality resources on the learning sciences

January 2, 2019Learning, Teachers & Researchers, Written by: Judi Fusco, Written by: Pati RuizPati Ruiz

By Judi Fusco and Pati Ruiz

Below are some readings that can be used to introduce the learning sciences to a wide audience. We (Pati and Judi) have been developing a course on the learning sciences for educators (see below for more on the target audience). We made it our goal to find free, open, and high quality resources and that were written for a wider community. Please take a look and let us know what you think.

If you’re a practitioner, have you read any of these? If you’re teaching a course on the learning sciences, have you used any of these? If not, what have you used? Are there any readings would you add? We’d love to hear from you — Tweet to @CIRCLEducators or use #CIRCLEdu.

Here’s a little more information about the course we are developing:

Purpose: Connecting educators and research(ers) in the learning sciences to create learning environments that use technology in ways to deepen learning and inspire students.

Objectives: Educators will be able to:

Describe from a learning sciences perspective what is known about topics such as motivation, identity, power and privilege, cognitive principles to enhance learning, collaboration and convergent conceptual change, constructivism (theory and pedagogical approach), inquiry, and other active learning approaches
Identify a range of learning theories and connect them directly to their own classroom practices
Understand affordances and constraints of technology for learning
Engage in conversations with other educators to discuss and make connections between practice and research
Apply findings from learning sciences research to design learning environments that use technology to strengthen learning

Target Audience: This course is designed for instructional coaches and mid-career and experienced educators (with at least 2 years of classroom experience) who are ready to examine and reflect on their practice. This course is created as a Masters level course, but we are interested in working to potentially create a similar course to be an advanced course or a capstone course in a credential program.

Course Format: We are developing the course in modules and the modules could be used in any course for teachers, including pre-service, with a professor facilitating. We hope to offer the course (through a university) this summer or fall. As we develop materials for it, we will share them. Please do let us know if you are interested in talking with us about the course, learning more about the modules we’re developing, or trying anything out in your course.

Texts and Materials (all free and open)

How People Learn (2000)

How People Learn II (2018)

Developing Minds in the Digital Age (2019)

Learning Sciences – CIRCL Primer, other Primers, and Posts from CIRCL Educators

Cyberlearning Community Report: The State of Cyberlearning and the Future of Learning With Technology

Innovating Pedagogy 2019; Innovating Pedagogy 2017; and Previous Reports

2018-2015 STEM for All Video Showcase videos

2019 STEM for All Video Showcase videos

DML Connected Learning Report

Naples Videos

Technology in Education What Teachers Should Know By Pedro De Bruyckere, Paul A. Kirschner, Casper D. Hulshof