The Pedagogy & the Pendulum

"We all watch the pendulum swing back and forth when it comes to pedagogy and best practices in instruction and assessment."

Bell, Kasey. Shake Up Learning: Practical Ideas to Move Learning from Static to Dynamic (Kindle Locations 366-368). Dave Burgess Consulting, Inc.. Kindle Edition.

In her new book Shake Up Learning, Kasey Bell asks readers to reflect on their career and react to the pendulum of pedagogy. Specifically, she asks how we have reacted to these changes. I’d like to look specifically at how technology has changed my what I do in the classroom.

There are some basic science skills that we expect students to become proficient at.  These have recently been formalized as a part of the Next Generation Science Standards. These practices include ones that are highly related to technology in the classroom such as

• Developing and Using Models
• Planning and Carrying Out Investigations
• Using Mathematical and Computational Thinking
• Constructing Explanations and Designing Solutions
• Obtaining, Evaluating, and Communicating Information

In my time, I have seen the pendulum swing between emphasis on content vs skills, we are getting closer to a true compromise of a focus on content skills to uncover knowledge. Technology helps us do this more efficiently, but it also changes what these skills look like.

Developing and Using Models

A practice of both science and engineering is to use and construct models as helpful tools for representing ideas and explanations. These tools include diagrams, drawings, physical replicas, mathematical representations, analogies, and computer simulations.

Think about the ways technology has allowed us to present models to learners. We’ve gone from static 2D models to animated and interactive 3D models using both augmented reality and virtual reality.  These are modes that can be presented in the classroom today. These representations give access to learners who may not have had the skills to translate visuals spatially.

In terms of creating their own models, learners can go beyond making static analogue representations to complex models using digital tools.  No need for clay and glue with the tools we have. These new tools allow for different modes of creation. In addition, they allow for creation of more complex models. Rather than the available tools holding students back from complex representations, they are allowing students to dig deeper in their representations and create more intricate models.

Planning and Carrying Out Investigations

Scientists and engineers plan and carry out investigations in the field or laboratory, working collaboratively as well as individually. Their investigations are systematic and require clarifying what counts as data and identifying variables or parameters.

Data collection tools have changed so much in the classroom it is amazing. Digital probes and apps have increased accuracy of measurements. In addition, we can complete many more trials of data to increase accuracy. This allows us to have conversations about looking at large data sets.

These tools have the potential of creating a disconnect between the act of collecting the data and what the data collected is telling us.  By that I mean, some may see that if students are just pushing a button to collect the data do they really know what they are measuring? This is where we realize we need to change the structure of data collection. These new tools allow students to collect data more quickly and efficiently. This allows for the opportunity for students to play a bigger role in the experimental design process. They will have a better idea of the purpose of the tools because they are deciding what to collect and what tools they will be using.  So the technology doesn’t just give us more accurate results, it gives learners more opportunity to design their own experiments.

Using Mathematical and Computational Thinking

In both science and engineering, mathematics and computation are fundamental tools for representing physical variables and their relationships. They are used for a range of tasks such as constructing simulations; statistically analyzing data; and recognizing, expressing, and applying quantitative relationships.

As the computational tools available to students have become more powerful, we’re beginning to realize that plugging numbers into an algorithm is not the skill we want students to have. I’m simply amazed at the free software available to us to plot data and perform curve fits on the data. I remember spending a whole class period having students plot the data collected in a lab on a piece of graph paper, trying to set-up axes with the correct scale, plot points and then drawing in a best-fit line. Yes, it’s important that they don’t take what the programs automate for granted. But based on the technology we have today, these skills won’t be the ones that will be most relevant. The ability to choose what tools to use and interpreting what they show are the skills we need learners to have.

Constructing Explanations and Designing Solutions

The products of science are explanations and the products of engineering are solutions.

Designing solutions is where the maker movement really comes to our classrooms. The design thinking process has been gaining lots of steam. But the products students are able to make have their limits without some of the tools that are available. 3D printers and coding options allow for designing prototypes and actual products through iterative processes. The solutions have the possibility to go beyond a simple classroom project to a real world solution.

Obtaining, Evaluating, and Communicating Information

Scientists and engineers must be able to communicate clearly and persuasively the ideas and methods they generate. Critiquing and communicating ideas individually and in groups is a critical professional activity.

Community and collaboration have been greatly extended via the access to technology. The ability for learners to connect with professionals and view real data sets has been extended thanks to the internet. But this is not simply a one way street, students have the ability to share their creations with a public audience. In addition, learners can more easily collaborate with peers digitally on a single document in real time. The use of digital documents allow for faster revisions and the ability to collaborate on these revisions while receiving digital feedback.  

What’s interesting to see is that the names of these skills may be similar to categories we could have listed 10 years ago.  But, what they entailed would be very different. Our goal as educators is to realize that what the skills look like change with the advancement of technology. This means that we can’t keep doing the same things to help students master these content skills. Why would I ever teach students to plot on piece of graph paper when I could teach them to make a spreadsheet? Are we willing to drop what is no longer relevant to student’s lives even if we think we have a great lesson for it? We really need to work at not simply teaching skills to identify the relevant skills and teach those. And always remember what is relevant today, might be obsolete tomorrow.