Category Archives: EducatorCIRCLS

Educators, Artificial Intelligence, and the Future of Learning

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

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

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

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

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

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.