All posts by Pati Ruiz

Assessment Webinar Resources

AI in Education, Assessment, EducatorCIRCLS

Educators, Artificial Intelligence, and the Future of Learning

Watch the recording.

AI products discussed:

Meet the Practitioner Panelists:

Aaron Hawn HeadshotAaron Hawn
Research Affiliate, The Penn Center for Learning Analytics
Co-Founder and Managing Member, Thirteen Ways Consulting, LLC
Twitter: @hawn_aaron

Aaron’s Statement on AI:

As a former teacher/testing administrator and current researcher, I see the potential for AI to rewire schools’ relationship with assessment and accountability, winning back time for instruction, trust in results, and opening new windows onto student skills. At the same time, I see that potential passing us by if teachers, education leadership, communities, and students are not engaged as partners from the start, designing AI tools for how real classrooms work and towards impacts that matter.

Nancy Foote HeadshotNancy Foote
Conceptual Physics Teacher,
Higley Unified School District (AZ)
Twitter: @MrsFoote

Nancy Foote, MEd, is currently a Conceptual Physics teacher in Gilbert AZ. She worked as an Industrial Chemist for the Sherwin Williams Company before obtaining her Master’s degree and teacher certification. Nancy has been in education for more than 30 years as a teacher, principal, staff development coordinator, teacher on special assignment. and curriculum coach. A National Board Certified Teacher, Nancy is also a recipient of the Presidential Award for Excellence in Mathematics and Science Teaching.

Nancy’s Statement on AI:

Before I met Inq-ITS, and through them AI, I was floundering in the dark. I was trying to grade hundreds of lab reports, trying to determine who understood what, how to intervene when necessary, and how to help my students think like scientists. That wasn’t even taking the quality of the writing into consideration. Now, thanks to Inq-ITS and their masterful use of AI, I can be a teacher again. I can intervene at the perfect time. I can help students exactly when they need it with the intervention that they need. I have become a mind reader. Most importantly, my students are thinking like scientists.

Educators, Artificial Intelligence, and the Future of Learning

EducatorCIRCLS

Educators, Artificial Intelligence, and the future of Learning

Start with a blog post that considers How Does Artificial Intelligence Fit into the Future of Education?

General Resources:

Assessment Webinar Resources
Watch the recording

Teacher Support Webinar Resources
Watch the recording

Learning Environments Webinar Resources
Watch the recording

This work was supported by the National Science Foundation under grant number #2040753. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.

Pedagogy Really Matters

EducatorCIRCLS, Learning Technologies, Teachers & Researchers, Written by: Sarah Hampton

book and tiled Zoom on laptop screenby Sarah Hampton

Last January, we were lucky enough to have a conversation with Mike Sharples, the author of Practical Pedagogy 40 New Ways to Teach and Learn, 1st Edition. While we apologize for the delay in posting — we got a little busy with transitioning to remote and hybrid teaching — we think that pedagogy is more important than ever and want to share some timely insights from the conversation. This is the first of a series of posts and is a little about math and a lot about pedagogy. If you’re here for the pedagogy but not the math, just stick with us past the example from my own math teaching journey.

I’ve always liked math as a subject, but as a student math class was never my favorite. Every year, math class went something like this.

  • I showed up for class.
  • I took out my home work and we reviewed it.
  • My teacher would go over questions.
  • I’d sit and listen to a lecture while I took notes.
  • I tried a few guided practice questions.
  • I went home and did my homework.
  • Wash, rinse, repeat.

When I accidentally fell into teaching math, that was all I had ever known so that’s how I taught, too. Fortunately, a few years into teaching, I was introduced to a professional development program specifically for math teachers hosted by a local college. The program professors allowed me to experience a different kind of math classroom! I learned new concepts by exploring first, then reflecting and articulating my nascient thoughts and defending my reasoning. In fact, the entire process was accomplished by me, the learner. That’s not to say that the professors were absent or that their roles weren’t important. They…

  • created the learning environment and tasks
  • motivated me
  • intervened at critical moments
  • prodded me to reflect and refine my thoughts
  • helped me internalize the learning.

This experience changed how I thought math class could look. That summer, I fully understood that how we teach is just as important as what we teach. In other words, pedagogy really matters.

We all use pedagogies every day, but it may be something we do unintentionally. Take a minute to think about your “go to” approach to teaching and learning. What happens on a typical day in your classroom? Maybe you’re likely to teach through lectures followed by guided practice. Maybe you facilitate class-wide conversations about your content. Maybe you organize your classroom into pods of students (or breakout rooms these days!) for collaborative learning.

Something to consider–no matter what you typically do, that teaching approach is well-suited for some types of learning goals but ineffective for others. You know the typical math classroom I talked about in the beginning of the post? That’s a type of direct instruction pedagogy. In fact, parts of it are really effective for some things. For one, teachers can disseminate information quickly. For another, it’s great when students have very little prior knowledge about a topic. Unfortunately, this pedagogy is not the most effective for things like long-term retention or transfer. By contrast, constructivist pedagogies like those used by the program professors are effective for deep learning, motivation, and engagement. (You can read more constructivist pedagogies in three previous posts–Learning Scientists and Classroom Practice, Practitioner POV of Constructivist Approaches, and The Benefits and Obstacles of Constructivism.)

Too often, we get stuck in a pedagogical rut and force our daily learning goals to fit our routine teaching style. Instead, we need to start purposefully thinking about which pedagogies best support our daily goals. In this series, I want to draw your attention to the pedagogies you use and introduce you to some you may not be familiar with so you can expand your teaching toolkit.

Teaching should be about meeting students where they are, and different pedagogies help us reach different students at different points in their learning journeys. The more learning theory and instructional strategies we understand, the more intentional we can be about selecting approaches that engage more of our students and meet their needs.

The more pedagogies we know → the more we can choose from → the more targeted we can make the approach to hit the learning goals → the better our students can learn

How often do you change up your pedagogies? When are you most likely to make changes to your pedagogies? Are you in a teaching rut now? Think about the best teacher you’ve ever had. What pedagogies did that teacher use?

In the next post, we’ll look at the role of pedagogy when teaching with technology and how we can use different pedagogies to up our pandemic teaching game. If necessity is the mother of invention, then learning about different pedagogies is more important now than ever. You don’t have to be an expert in a new pedagogy to use it in your classroom. I hope you find one that you are excited to try!

Related Resources:
Innovating Pedagogy 2021
Innovating Pedagogy website with links to all Open University Innovation Reports
Mike Sharples Keynote at Cyberlearning 2019

What do you think? Let us know @EducatorCIRCLS.

This post is part of the Practical Pedagogy Series
In Educator CIRCLS, we’ve been doing the messy, fun, and challenging work of learning through discussions of our reading of Practical Pedagogy 40 New Ways to Teach and Learn, 1st Edition. We were lucky enough to have a conversation with Mike Sharples, the author. We feel we are emerging from those conversations as more informed and effective educators! We would love you to share your thoughts and join the conversation.

Data Science in Ambitious Mashups

AI in Education, EducatorCIRCLS, STEM, Written by: Merijke Coenraad

by Merijke Coenraad

This post will focus on Trends at NSF and Beyond: Data Science.

No matter what subject you teach, it is likely that data comes into play in your classroom. Whether it is statistical analysis of data in math, collecting and analyzing data in science, or analyzing historical and contemporary data to understand the present, data can be found in many classroom activities. A trend within CIRCL projects was harnessing the data revolution. With more and more data collected each day and the accessibility of data for you and your students, there are many ways you can learn from these projects and bring them into play within your classroom. For example, check out these two projects: STEM Literacy through Infographics and Data Clubs.

STEM Literacy Through Infographics

Created by a team of researchers from across the US, STEM Literacy Through Infographics focuses on helping students create infographics in both classroom and out of school settings to help students make visual, argumentative claims (watch a 3-minute video about the project). The project aims to provide students with the skills they need to ask and answer questions about their own lives and communicate that data to others through data journalism. This ambitious project brings together experts in educational technology, mathematics, and learning and mashes up data science, data visualization, and citizen science opportunities to help students make sense of the data that is available to them. If you’re interested, you can try out infographics in your classroom using their helpful step by step guide “How to Make Infographics”, classroom lesson plans and resources, and asynchronous professional development workshop.

Data Clubs

Data Clubs are designed by a team of researchers at TERC and SCIEDS to provide middle school students with data skills that allow them to visualize and analyze data about life-relevant topics. Within the lessons, students write their own questions, collect their own data, and learn how to represent their data by hand and using computer software. This ongoing ambitious project uses design-based research collecting data about students’ data dispositions and interviewing them about their experiences. It mashes up mathematics, informal learning, data visualization, and statistics to help students think about the who, when where, how, and why of data. Try out the currently available modules with your students!

These projects demonstrate the importance of quality data experiences for students and the role that data visualization can play in students learning from the large data sets that are available to them. Besides trying out materials from these projects, how can you use data science in your classroom? Here are some ideas:

  • Explore infographics on Information is Beautiful and have students create their own by hand (as seen in Dear Data) or using a computer program.
  • Engage students with visualization of climate change on Climate.org run by NOAA. The platform provides a number of data visualization environments in which students can explore climate data.
  • Explore the Johns Hopkins US or World Coronavirus maps to discuss current trends (click on counties to see more specific data)
  • Explore data visualization of the 2020 election from Statista or CISA to discuss trends in voting and the role that data visualizations play in data communication (consider showing this clip of CNN analyzers using live data visualizations to discuss visualizations in election reporting)
  • Allow students to use data from Our World in Data and/or the CODAP platform to explore data and create their own visualizations
  • Lead students in a discussion about data collection in their lives and the amount of data collected from their use of social media, online shopping, and other internet-connected activities. Provide students with the opportunity to critically analyze how companies are making money off of their data collection and what they could do to advocate for and protect themselves from harmful data use.

How do you use data in your classroom? Tweet us @EducatorCIRCLS and tell us about your innovative technology use and stay tuned for future blogs in this series about CIRCL Ambitious Mashups.

Introduction to Ambitious Mashups

AI in Education, EducatorCIRCLS, Learning Technologies, Written by: Merijke Coenraad

by Merijke Coenraad

As an educator, you know better than anyone else how much educational technology is changing, particularly within the last year. The Center for Innovative Research in Cyberlearning (CIRCL) has worked with researchers for the last eight years as they have developed and investigated learning environments and technology that pushed the boundaries between technology and education. This community of researchers (and their partner teachers) has focused on how emerging technologies could be important for learners and adapted into the learning tools that would positively impact the education of students five or ten years later.

The recent Ambitious Mashups report examines the work researcher teams did. You might have also seen our previous post encouraging you to attend the Ambitious Mashups Webinar. In case you missed it live, you can watch it here. As we reviewed all of the projects, we discovered that they together researchers with computer science expertise, knowledge of learning sciences theories and methods, and a firm commitment to investigating equity. More than just focusing on emerging educational technologies, CIRCL projects had a strong focus on groups that are marginalized within society and underrepresented in STEM professions such as students from marginalized races, girls, low-performing schools, low-income settings, students with disabilities, and students who are learning English.

Looking across projects, the CIRCL team found that researchers weren’t concerned with just one technology, research method, or learning theory. These projects were ambitious, pushing the frontiers of research and technology and studying big learning goals, and they were interdisciplinary mashups, involving many elements together in novel integrations. Therefore, we have deemed the results of CIRCL to be ambitious mashups and worthy of review by not only researchers, but by educators as well. These ambitious mashups bring together a set of novel technologies in unimagined ways to tackle learning challenges. As educators who will soon be encountering these emerging technologies in the classroom, this report points to what you can expect from ed tech and questions to start asking yourself as the research ambitious mashups of the past eight years become the technologies of the next decade.

So, what did we learn from looking at all the cyberlearning research? Reviewing the research projects completed through CIRCL, the team identified five themes representing the elements of the cyberlearning research community:

In this series of posts, we are going to look across some of these themes because we at CIRCL Educators believe that there are many things to think about as the emerging technologies of cyberlearning begin to enter the classroom and there are already exciting findings that can influence your teaching!

After eight years of researching together, the CIRCL community has learned a lot about what it means to do innovative research at the forefront of educational technology. Being a CIRCL Educator, what have you learned? How can you create an ambitious mashup in your classroom? Tweet us @EducatorCIRCLS and tell us about your innovative technology use and stay tuned for future blogs in this series about CIRCL Ambitious Mashups.

AI and Formative Assessment

AI in Education, Assessment, EducatorCIRCLS, Written by: Sarah Hampton

by Sarah Hampton

In my last post, I talked about effective formative assessments and their powerful impact on student learning. In this post, let’s explore why AI is well-suited for formative assessment.

  1. AI can offer individualized feedback on specific content.
  2. AI can offer individualized feedback that helps students learn how to learn.
  3. AI can provide meaningful formative assessment outside of school.
  4. AI might be able to assess complex and messy knowledge domains.

Individualized Feedback on Content Learning

I think individualized feedback is the most powerful advantage of AI for assessment. As a teacher, I can only be in one place at a time looking in one direction at a time. That means I have two choices for feedback: I can take some time to assess how each student is doing and then address general learning barriers as a class, or I can assess and give feedback to students one at a time. In contrast, AI allows for simultaneous individualized feedback for each student.

“AI applications can identify pedagogical materials and approaches adapted to the level of individual students, and make predictions, recommendations and decisions about the next steps of the learning process based on data from individual students. AI systems assist learners to master the subject at their own pace and provide teachers with suggestions on how to help them.” (Trustworthy artificial intelligence (AI) in education: promises and challenges)

Going one step further, AI has the ability to assess students without disrupting their learning by something called stealth assessment. While students work, AI can quietly collect data in the background such as the time it takes to answer questions, which incorrect strategies they tried before succeeding, etc. and organize them into a dashboard so teachers can use that data to inform what to focus on or clear up the next day in class. Note: As a teacher, I want the AI to help me do what I do best. I definitely want to see what each student needs in their learning. Also, as a teacher, I want to be able to control when the AI should alert me about intervening (as a caring human) instead of it trying to do something on its own that it isn’t capable of doing well.

Feedback That Helps Students Learn How to Learn

“Two experimental research studies have shown that students who understand the learning objectives and assessment criteria and have opportunities to reflect on their work show greater improvement than those who do not (Fontana & Fernandes, 1994; Frederikson & White, 1997).” (The Concept of Formative Assessment)

In the last post, I noted that including students in the process of self-assessment is critical to effective formative assessment. After all, we ultimately want students to be able to self-regulate their own learning. But, as one teacher, it can sometimes be difficult to remind students individually to stop and reflect on their work and brainstorm ways to close the gap between their current understanding and their learning goal. By contrast, regulation prompts can be built into AI software so students routinely stop and check for understanding and defend their reasoning, giving students a start on learning how to self-regulate.

For example, this is done in Crystal Island, an AI game-based platform for learning middle school microbiology, “students were periodically prompted to reflect on what they had learned thus far and what they planned to do moving forward…Students received several prompts for reflection during the game. After completing the game or running out of time, students were asked to reflect on their problem-solving experience as a whole, explaining how they approached the problem and whether they would do anything differently if they were asked to solve a similar problem in the future.” (Automated Analysis of Middle School Students’ Written Reflections During Game-Based Learning)

In-game reflection prompt presented to students in Crystal Island

Meaningful Formative Assessment Outside of School

Formative assessment and feedback can come from many sources, but, traditionally, the main source is the teacher. Students only have access to their teacher inside the classroom and during class time. In contrast, AI software can provide meaningful formative assessment anytime and anywhere which means learning can occur anytime and anywhere, too.

In the next post, we’ll look at how one AI tool, ASSISTments, is using formative assessment to transform math homework by giving meaningful individualized feedback at home.

Assessing Complexity and Messiness

In the first post of the series, I discussed the need for assessments that can measure the beautiful complexity of what my students know. I particularly like the way Griffin, McGaw, and Care state it in Assessment and Teaching of 21st Century Skills:

“Traditional assessment methods typically fail to measure the high-level skills, knowledge, attitudes, and characteristics of self-directed and collaborative learning that are increasingly important for our global economy and fast-changing world. These skills are difficult to characterize and measure but critically important, more than ever. Traditional assessments are typically delivered via paper and pencil and are designed to be administered quickly and scored easily. In this way, they are tuned around what is easy to measure, rather than what is important to measure.”

We have to have assessments that can measure what is important and not just what is easy. AI has the potential to help with that.

For example, I can learn more about how much my students truly understand about a topic from reading a written response than a multiple choice response. However, it’s not possible to frequently assess students this way because of the time it takes to read and give feedback on each essay. (Consider some secondary teachers who see 150+ students a day!)

Fortunately, one major area for AI advancement has been in natural language processing. AIs designed to evaluate written and verbal ideas are quickly becoming more sophisticated and useful for providing helpful feedback to students. That means that my students could soon have access to a more thorough way to show what they know on a regular basis and receive more targeted feedback to better their understanding.

While the purpose of this post is to communicate the possible benefits of AI in education, it’s important to note that my excitement about these possibilities is not a carte blanche endorsement for them. Like all tools, AI has the potential to be used in beneficial or nefarious ways. There is a lot to consider as we think about AI and we’re just starting the conversation.

As AI advances and widespread classroom implementation becomes increasingly more possible, it’s time to seriously listen to those at the intersection of the learning sciences and artificial intelligence like Rose Luckin. “Socially, we need to engage teachers, learners, parents and other education stakeholders to work with scientists and policymakers to develop the ethical framework within which AI assessment can thrive and bring benefit.” (Towards artificial intelligence-based assessment systems)

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.

We are still at the beginning of our conversation around AI in Education. What do you think? Do the possible benefits excite you? Do the possible risks concern you? Both? Let us know @EducatorCIRCLS.

From CIRCLEducators to Educator CIRCLS

EducatorCIRCLS

Welcome to the Educator CIRCLS blog! Educator CIRCLS builds on 6 years of previous work to bridge research on emerging technologies for learning with classroom practice. We invite teachers to join us or share this information with teachers you think may be interested in joining. We are looking for a diverse group of classroom teachers who are interested in sharing their experiences implementing innovative learning technologies in their classroom. If you are interested in joining, please fill out this form.

We also invite readers of the blog to share feedback and ideas through comments. We hope this blog is a useful resource for people interested in the design and development of innovative learning technologies that are informed by and inform our understanding of the processes of learning.

Please visit CIRCLEducators for more posts about technology and learning.

Let us know what you think @EducatorCIRCLS.

two VR goggles hang from hooks

Virtual Reality in K12 Education: A Reality Check

Guest Author, Virtual Reality

by Aditya Vishwanath

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

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

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

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

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

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

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

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

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

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

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

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

path

Building Classroom Community through Trust

Culturally Responsive Teaching, Written by: Angie Kalthoff

By Angie Kalthoff

Neuroscience tells us the brain feels safest and most relaxed when we are connected to others we trust to treat us well.

I recently participated in an informal conversation with other educators where we were discussing teaching and learning in a distance learning setting. Current teachers were sharing ice breakers and back to school activities that they were finding for their very different-than-normal back to school. I asked for resources around how to talk to kids about their current situations due to the state of the world. People are dealing with a lot of emotions right now. World events like a pandemic, wildfires, and social justice conversations around the murder of George Floyd are a lot for adults to digest. I can’t even imagine how children or teens are processing it all. In this conversation, no one had a resource to share that was specific to online learning but we did talk about Culturally Responsive Teaching and the Brain by Zaretta Hammond. I learned about this book when I was a technology integrationist. Additionally CIRCL Educators has been focusing on it, and other books and topics related to social justice, bias in algorithms, techequity, and other anti-racist practices over the past few months.

In Ms. Hammond’s book, I learned about the importance of trust. Research shows that a positive relationship between students and teachers is crucial for students to reach their fullest potential. Of course! Ask any educator and they can talk to you about the importance of relationships and trust. I experienced this early on in my teaching career. But, if you would have asked me to explain why, I wouldn’t have been able to connect it to the research and history shared in this book. This phenomenon is rooted in our history, from the time when humans roamed the earth and started to live in communities to get protection from animals. From these experiences, it is thought that the brain created a social engagement system to ensure humans form communities, build trustful relationships, and work to maintain them. In this post I will present an introduction to help you understand how to use the research around neuroscience in your classroom to influence positive behaviors, discuss why we developed these systems, and how this relates to your classroom with a culturally responsive response in mind.

To start, if you are new to Culturally Responsive Teaching (CRT), one of the questions I continually ask myself is “am I thinking of my students whose lived experiences are different than mine and what perspectives am I not thinking about?” in her books she focuses on  “How do I treat my students who are different from me? They could have a different skin color, they could speak a different language, they could have different abilities than I do, and have different lived experiences. And, am I building their self esteem or am I creating the positive affirmations that will benefit them in life outside of my classroom?” Ms. Hammond defines CTR as the process of using familiar cultural information and process to scaffold learning. She emphasizes communal orientation and focuses on relationships, cognitive scaffolding, and critical social awareness. 

I began my teaching career as an English as a Second Language (ESL) teacher in 2008. This title has now transitioned to Multi-Lingual and has also been referred to as English Language (EL) teacher and teacher to English Language Learners (ELL). Many of my students spoke more than one language and I appreciate the thought that has gone into the transition of the title. I learned a lot about teaching and the importance of relations early in my career. As a white teacher, who grew up in the MidWest, my background and lived experiences are very different than many of my students. While students in my classroom moved to Minnesota from all over the world, a large part of my student population came from refugee camps in Somalia. It was during this time I learned about the importance of building trust with students and families. I wish I had a resource like Culturally Responsive Teaching and the Brain but I didn’t. In this post, I will share specific research based practices that you can take into your classroom whether it is online in a virtual settings or in person in a physical building.

Neuroscience for Teaching Practice

Affirmation

When your brain feels safe and relaxed it sends oxytocin (the bonding hormone) out which in turn makes us want to build trusting relationships with the people we are engaging with. Neuroscience tells us the brain feels safest and most relaxed when we are connected to others we trust to treat us well. How does the brain know when to do this? In most people, the brain releases oxytocin when any of these actions happen:

  • Simple gestures
  • A smile
  • Nod of the head
  • Pat on the back
  • Touch of your arm

Affirmation in your school environment.

One way that you can bring this into your learning situation is through an affirmation. In the book, a study is described where a principal takes the time to greet each student by giving them her full attention, getting to their level, and offering a bow. Students in this study would light up based on this affirmation and respect, both figuratively and literally.

Mirror Neurons

When we are around others in that we have a trusting relationship with, mirror neurons may help  keep us in sync with them. Some researchers think mirror neurons help us have empathy with others. Additionally, they may help us make and strengthen bonds. Have you ever thought about why you smile when someone smiles at you? This action may be connected to the mirror neuron system. Early studies showed that mirror neurons mirrored what you see. For example, when we see a behavior such as smiling, mirror neurons in the region of our brain that relate to smiling activate. Some researchers believe that we also mirror the behavior we see by also performing the behavior (smiling in this example) and that this mirroring signals trust and rapport.

This section had me searching the Internet for more information and one analogy that often came up was “Monkey See, Monkey Do.” This makes me think about young children and babies. Have you ever had an interaction with a young one where they try to copy a noise, facial expression, or gesture, it may be related to the mirror system. You can watch this introductory video if you want to learn more. (It’s from early on when we were just starting to learn about mirror neurons, but it presents many questions that researchers are still investigating.) Note, the mirror system is fascinating but there is still much research to be done to fully understand it.

Mirror Neurons in your school environment.

While researchers are still learning more about how the mirror system works, many of the big ideas discussed are important for practice. We definitely have areas in our brains that help make us feel connected to others. It may well be that the synchronized dance of mirror neuron systems between people is what is responsible, or it may be something else. Regardless, there is no doubt that connections are related to feeling more relaxed and trusting — important for learning. As a teacher, it really is important to make a personal and authentic connection with your students.

To apply the research from this chapter and begin building a different kind of relationship there are two things you can start working on today that relate to empathy and connection; listening with grace and building trust.

To Listen with Grace

In chapter five there are a few examples of how to listen with grace. They include:

  • Give one’s full attention to the speaker and what is being said
  • Understand the feeling behind the words and be sensitive to the emotions being expressed
  • Suspend judgement and listen with compassion
  • Honor the speaker’s cultural way of communicating

I know we are all so busy that it’s hard to sometimes take the time to be fully present, but listening and connecting in whatever ways we can is even more important in the online space.

Trust Generators

In the book, Zaretta Hammond shares five ways to help create trust, I will discuss one of those, Selective Vulnerability. I chose Selective Vulnerability due to the state of the world we are living in as we live through a pandemic. Our lives and routines have changed. For many, this means taking what we have known as education and changing it drastically. Educators who have been teaching in classrooms for their whole careers are now expected to move to an online environment. Children who have benefited from the in person learning environment are now having to learn from a device outside of school. I think, as a learning community, we might all benefit from selective vulnerability. CIRCL Educator Sarah Hampton and I both agree that there is room to grow in being transparent with students in our own growing pains as learners.

Trust Generator: Selective Vulnerability

Definition: People respect and connect with others who share their own vulnerable moments. It means showing your human side is not perfect.

What It Looks Like: Sharing with a student a challenge you had as a young person or as a learner. Sharing new skills you are learning and what is hard about it. In either case, the information shared is carefully selected to be relevant. Think about who you are talking to and what you have in common. The goal here is to connect and show that you are a fallible human being. A student with a very different background may not be able to understand certain examples and there is the possibility that your example could alienate rather than build rapport.

As I mentioned before, one of the important questions in the book is “How do I treat my students who are different from me?” I think the focus of thinking about the perspective of the person in the interaction is so important. This year has brought so much for all of us to deal with, and as teachers, we need to know who we are talking to and what experiences have shaped them, so that we can work to make connections as a foundation for teaching and learning. If you want to dig deeper into listening with grace and building trust, Ms. Hammond has that and so much more in her book.

What do you think? Connect with us on social media @CIRCLeducators and share how you show affirmation to your students!

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Algorithms, Educational Data, and EdTech: Anticipating Consequences for Students

AI in Education, Culturally Responsive Teaching, Cyberlearning, Written by: Amar Abbott, Written by: Pati Ruiz

By Pati Ruiz and Amar Abbott

The 2020-2021 school year is underway in the U.S. and for many students, that means using edtech tools in a fully online or blended learning environment. As educators, it is our responsibility to consider how students are using edtech tools and what the unanticipated consequences of using these tools might be. Before introducing edtech tools to students, administrators should spend time considering a range of tools to meet the needs of their students and teachers. In a recent blog post, Mary Beth Hertz described the opportunities for anti-racist work in the consideration and selection of the tools students use for learning. Hertz identified a series of questions educators can ask about the tools they will adopt to make sure those tools are serving the best interest of all of their students. Two of the questions in Hertz’s list ask us to consider data and algorithms. In this post, we focus on these two questions and Hertz’s call to “pause and reflect and raise our expectations for the edtech companies with which we work while also thinking critically about how we leverage technology in the classroom as it relates to our students of color.” The two questions are:

  1. How does the company handle student data? and,
  2. Has the company tested its algorithms or other automated processes for racial biases?

To help us better understand the issues around these two questions, we will discuss the work of two researchers: Dr. Safiya Noble and Dr. Ruha Benjamin. This post expands on our previous post about Dr. Noble’s keynote address — The Problems and Perils of Harnessing Big Data for Equity & Justice — and her book, Algorithms of Oppression: How Search Engines Reinforce Racism. Here, we also introduce the work of Dr. Ruha Benjamin, and specifically the ideas described in her recent book Race After Technology: Abolitionist Tools for the New Jim Code.

Student Data

In order to understand how companies handle student data, we need to first consider the concept of data. Data are characteristics or information that are collected in a manner capable of being communicated or manipulated by some process (Wiktionary, 2020). In Dr. Noble’s keynote speech, she discusses the social construction of data and the importance of paying attention to the assumptions that are made about the characterization of data that are being collected. In her book, Dr. Noble shows how Google’s search engine perpetuates harmful stereotypes about Black women and girls in particular. Dr. Benjamin describes the data justice issues we are dealing with today as ones that come from a long history of systemic injustice in which those in power have used data to disenfranchise Black people. In her chapter titled Retooling Solidarity, Reimagining Justice, Dr. Benjamin (2019) encourages us to “question, which humans are prioritized in the process” (p. 174) of design and data collection. With edtech tools, the humans who are prioritized in the process are teachers and administrators, they are the “clients.” We need to consider and prioritize the affected population, students.

 

When it comes to the collection and use of educational data and interventions for education, there is much work to be done to counteract coded inequities of the “techno status quo.” In her keynote, Dr. Noble offered a list of suggestions for interventions including:

 

  1. Resist making issues of justice and ethics an afterthought or additive
  2. Protect vulnerable people (students) from surveillance and data profiling

 

Center Issues of Justice and Ethics

As described by Tawana Petty in the recent Wired article Defending Black Lives Means Banning Facial Recognition, Black communities want to be seen and not watched. The author writes:

“Simply increasing lighting in public spaces has been proven to increase safety for a much lower cost, without racial bias, and without jeopardizing the liberties of residents.”

What is the equivalent of increasing light in education spaces? What steps are being taken to protect students from surveillance and data profiling? How are teachers and students trained on the digital tools they are being asked to use? How are companies asked to be responsible about the kinds of data they collect?

Schools have legal mandates meant to protect students’ rights, such as the Family Educational Rights and Privacy Act (FERPA) in the U.S. and other policies that protect student confidentiality regarding medical and student educational records. Although a lot of forethought has gone into protecting students’ confidentiality, has the same critical foresight implemented when purchasing hardware and software?

 

In Dr. Noble’s keynote speech, she described the tracking of students on some university campuses through the digital devices they connect to campus Internet or services (like a Library or Learning Management System). The reasoning behind tracking students is to allocate university resources effectively to help the student be successful. However, in this article, Drew Harwell writes about the complex ethical issues regarding students being digitally tracked and an institutions’ obligation to keep students’ data private. So, before software or hardware is used or purchased, privacy and ethics issues must be discussed and addressed. Special energy needs to be dedicated to uncovering any potential “unanticipated” consequences of the technologies as well. After all, without the proper vetting, a bad decision could harm students.

Protect Vulnerable Students

Protecting vulnerable students includes being able to answer Hertz’s question: “Has the company tested its algorithms or other automated processes for racial biases?” But, even when the company has tested its algorithms and automated processes, there is often still work to be done because “unanticipated” results continue to happen. A Twitter spokesperson Liz Kelley recently posted a tweet saying: “thanks to everyone who raised this. we tested for bias before shipping the model and didn’t find evidence of racial or gender bias in our testing, but it’s clear that we’ve got more analysis to do.”

She was responding to the experiment shown below where user @bascule posted: “Trying a horrible experiment…Which will the Twitter algorithm pick: Mitch McConnell or Barack Obama?”

Twitter’s machine learning algorithm chose to center the white face instead of the black face when presented with where the white profile picture was shown on top, white space in between, followed by the black profile picture. But it did the same when the black profile picture was shown on top, white space in between, followed by the white profile picture.

A horrible twitter experiment with face recognition. The algorithm selects the white face regardless of placement

As we can see, the selection and use of tools for learning is complicated and requires balancing many factors. As CIRCL Educators we hope to provide some guidance to ensure the safety of students, families, and their teachers. Additionally, we are working to demystify data, algorithms, and AI for educators and their students. This work is similar to the work being done by public interest technologists in the communities and organizations described by both Noble and Benjamin. We don’t have all of the answers, but these topics are ones that we will continue to discuss and write about. Please share your thoughts with us by tweeting @CIRCLEducators.

 

References

Benjamin, R. (2019). Race After Technology: Abolitionist Tools for the New Jim Code. Cambridge, UK: Polity Press.

data. (2020, August 12). Wiktionary, The Free Dictionary. Retrieved 15:31, August 26, 2020 from https://en.wiktionary.org/w/index.php?title=data&oldid=60057733.

Noble, S. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York: NYU Press.