When we talk about making, there is a tendency to overlap our terms, like saying we’re going to “do makerspace”. I think unpacking these terms help uncover underlying assumptions, especially when designing new spaces and learning opportunities. I see this as four distinct aspects that work together:
Place – Makerspace, hackerspace, Fab Lab, Techshop, shop, science lab, open classroom, studio
By looking at these four aspects, we can untangle some of the confusion about what “making” in education is. These can combine in interesting ways – you can have a Design Thinking program that is strongly teacher directed in a makerspace that has a green eco-streak that permeates the projects. The place doesn’t dictate the process, which is good and bad.
Many times, when designing new learning opportunities or spaces it is assumed that their current culture will transform as well. Space planning doesn’t magically transform pedagogy. You can’t assume that just because you build a flexible space with terrific materials, it will magically be filled with wonderful student-centered, open-ended projects.
Here’s a “cheat sheet” for the four aspects.
Place
Both formal (credit-bearing courses, primarily at schools) and informal (extra-curricular activities, clubs, libraries, museums, community organizations, commercial spaces)
Hackerspace – “Hacking” indicates both an activity and political belief that systems should be open to all people to change and redistribute for the greater good. (roots in the 1960’s). More prevalent in Europe than US.
Makerspace – MAKE magazine (2005 – present). Popular Science for the 21st century. DIY and DIWO. Maker Faires. Adopted as a softer, safer alternative to hackerspace. Can be a separate room or integrated into classrooms.
Fab Lab – Spaces connected to the MIT Center for Bits and Atoms (565 worldwide) with a common charter and specific requirements for space and tools. Fablab also used as a generic nickname for any fabrication lab.
TechShop (and others) – non-profit or commercial organizations offering community tool sharing, classes, or incubation space.
Shop, science lab, classroom, studio – traditional names for school spaces for learning via hands-on activities.
Culture
Maker movement – technology-based extension of DIY culture, incorporating hobbyist tools to shortcut a traditional (corporate) design and development process, and the internet to openly share problems and solutions. Maker mindset – a positive, energized attitude of active tinkering to solve problems, using any and all materials at hand.
Hacker/hacking – Essential lessons about the world are learned “..from taking things apart, seeing how they work, and using this knowledge to create new and even more interesting things.” – Steven Levy
Green – values of ecology, conservation, and respect for the environment.
Citizen/amateur science – participation of non-professional scientists in gathering and interpreting data or collaborating in research projects.
Artisanal/craft movements – engaging in mindful and ethical practices to humanize activities, products, and production.
Process
Making – the act of creation. “Learning by making happens only when the making changes the maker.” – Sylvia Martinez
Tinkering – non-linear, iterative approach to reaching a goal. “messing about” with materials, tools, and ideas. “Making, fixing, and improving mental constructions.” – Seymour Papert
Design Thinking – customer-centered product design and development process popularized by IDEO and the Stanford d.school
Design – “to give form, or expression, to inner feelings and ideas, thus projecting them outwards, making them tangible.” – Edith Ackermann
Genius Hour – specific classroom time devoted to tinkering and open-ended projects. Patterned after companies (Google and FedEx, primarily) that allow employees to work on non-company projects on company time, thereby boosting morale and possibly resulting in products useful to the company.
Project-based Learning (PBL) – Projects are…“work that is substantial, shareable, and personally meaningful.” – Martinez & Stager
Beliefs about teaching and learning
Instructionism – Belief that learning is the result of teaching. Lecture, direct instruction.
Behaviorism – Belief that behavior is a result of reinforcement and punishment. Rote learning, worksheets, stars/stickers, grades.
Constructivism – Piagetian idea that learning is a personal, internal reconstruction—not a transmission of knowledge. Socratic method, modeling, manipulatives, experiments, research, groupwork, inquiry.
Constructionism – Seymour Papert extended constructivism with the idea that learning is even more effective when the learner is creating a meaningful, shareable artifact. PBL, making, citizen science.
Learning is an engagement of the mind that changes the mind.
—Martin Heidegger
One of the biggest issues I have with many descriptions of “making” in education is that it’s about students just being creative with tools or materials. I strongly disagree. Making is not just the simple act of you being the difference between raw materials and finished product, as in “I made dinner” or even “I made a robot.” I don’t think we always need to ascribe learning to the act of making — but the act of making allows the maker, and maybe an outsider (a teacher, perhaps) to have a window into the thinking of the maker.
So, do you always need a teacher for learning to happen? No. Some people are good at thinking about their own process and learning from that (“Wow, that butter made the sauce so much better.” “Next time, I’ll test the circuit before I solder.”) and some people are less likely to do that. But if I watch you cook, I will see certain things – how you organize your ingredients, how you react when you make a mistake, how you deal with uncertainty — and that is what teaching is about. A teacher who is a careful observer can see these kinds of signs, and then challenge the learner with harder recipes, a question to make them think, more interesting ingredients, or a few tips — all with an eye towards helping the other person learn and grow.
Technology like Arduinos and 3D printers have not become intertwined with the maker movement in education simply because they are new, but because they are some of the most interesting ingredients out there. Many of these “maker materials” rely on computational technology, which supports design in ways not possible otherwise. The command “Save As..” is possibly the most important design tool ever invented. Saving your design file or code means you can “do again” without “doing over,” supporting the iterative process and encouraging increasingly complex designs.
Complex technology, especially computational technology also allows educators to answer the question, “Isn’t this just arts and crafts?” And of course after defending arts and crafts – we can say that computational technology allows these same mindful habits to connect with the powerful ideas of the modern world that we hope children learn. Design and making are not just important for the A in STEAM, they are essential, but here’s a bigger idea, they are also essential for the T & E — and for them all to come together.
There is simply no technology without design; the definition of the word is literally “things in the designed world.” Making is a way to realize the “logo” part of the word – from the Greek word (logos) that means “word” but specifically words that express the order and reason of the universe. To Greek philosophers, a word was more than a sound or a mark, it was the embodiment of an idea — an idea made real. And yes, the Logo programming language owns this derivation as well.
The power of using computational technology in education is that the versatility and transparent complexity allows learners to make their ideas real, to make sense of the world, and to see their own capacity grow. This visible process also allows teachers to support and scaffold learners on their journey.
Learning by making happens only when the making changes the maker.
In a recent paper, “Realizing the Potential of Learning in Middle Adolescence,” cognitive psychologists Robert Halpern, Paul Heckman, and Rick Larson remind us:
Good learning involves direct experience, “deep immersion in a consequential activity” (Bruner, 1966).
Learning works best when young people can focus in depth on a few things at a time; when they see a clear purpose in learning activities; and when they have an active role—co-constructing, interpreting, applying, making sense of something, making connections.
Motivation is a powerful engine for learning, and the right conditions can foster it. Motivation to learn is stronger when it emerges from the young person’s prior knowledge and interests, when it springs not from reward or punishment but from the task itself, and when it is driven by a desire for mastery and by identification with
others who do it well.
Learning is often most effective when it is social; when it occurs as a shared activity within meaningful relationships; and when it allows for increasingly responsible participation—within a tradition, or a community of fellow learners, or one’s culture at large.
The bottom line: Young people can be—and want to be—fully engaged learners. The evaluation research on longstanding school networks that put these principles into practice—like Expeditionary Learning, Big Picture, Early College High School, and High Tech High—finds deeply engaged students motivated to do their best (National Research Council and the Institutes of Medicine, 2004; Castellano, Stringfield & Stone, 2003; Kemple, Hirliahiy & Smith, 2005).
The prevailing narrative, however, is one of student disengagement.
You may have heard that it’s best to “ease” into hands-on project-based learning at the start of the school year. Maybe you feel your students aren’t ready, need some skills development, or just need to have a few weeks of settling down before getting started with more independent work.
Good teachers know that students learn a lot more when they get their hands on real materials, and get to do their own projects and experiments. But sometimes we get frustrated thinking about the students who won’t cooperate, don’t clean up, waste materials, or misbehave during our hands-on learning time. In my work as a science teacher and coach, I’ve seen teachers who decide to delay lab activities until behavior is rock-solid. Instead of starting off with a bang, they tiptoe toward inquiry learning.
The author, Anthony Cody is an award-winning science teacher, and this article has some great ideas, tips and practical suggestions for all grades and subject areas. He goes on:
My experience is in science, but many teachers of social studies, English, math, and other subjects also have great success with hands-on, minds-on activities. I’d bet some of my colleagues in these other content areas also feel the urge to keep kids in lockdown mode until full teacher authority has been established.
I think this is a big mistake.
Here are his reasons:
You need to lead with your best foot.
When you introduce cool activities the first few weeks, you are setting the stage for an exciting year.
I’m also sure that many teachers feel that they have students who aren’t “ready” for a more independent approach to learning. However, how will they get ready if they don’t practice it? Many teachers tell me that students have to be “unschooled” out of practices like constantly expecting to be told what to do. So why not start to build those habits and expectations on day one?
That doesn’t mean that you have to start with a monumental project. Start with something small. Give the students time to explore, invent, and tinker sooner rather than wait. If it’s chaos, you can add some constraints, but don’t give up! Give them time to learn the tools you want them to get good at with smaller, more contained projects that will build their confidence and skills.
Empowering students to believe in themselves as capable of making things that matter, both in the physical and digital world, is a crucial part of learning.
So whatever you call it, making, project-based learning, hands-on, or inquiry learning – the time to start is always NOW!
A lot of people know that in a previous career I was a video game designer. That means that I get asked all the time about educational games. So here’s a wiki I’ve just created with some of the resources about that topic, including a 20 min presentation. I think that there is a lot of hype about games in education, and it’s important not to just take it so literally.
My hope is that educators take the time to really explore what games can offer in the classroom – not because games are going to “save” or “revolutionize” education, but that they offer a metaphor of what learner-centered education can be.
By learning more about games, educators can decide for themselves if a particular game is something they want to introduce into their classroom because it supports their beliefs about learning, not because it’s all the rage. Or, they can learn how games carefully balance frustration with success to create engaging challenges.
Finally, I always say that the best way to bring games into the classroom is to let students design their own games. It puts the agency even further into the learner camp. Playing games is fun, but you are always playing by someone else’s rules. Making your own game means that you are in charge, and that’s where real learning can happen.
Emerging research suggests that, contrary to what students may think, material that’s easy to understand is not always easy to learn—and working harder can help them hold on to what they’ve learned.
This Education Week article summarizes several research studies on “stability bias” – where people confuse things that are easy to process with things that are easy to remember.
The stability bias works both ways: Not only do students give too little credit to effective study strategies that feel more difficult, but they can give more weight to ineffective strategies that make content feel easier to learn.
It’s like assuming that food that is easy to eat is the healthiest.
My recent post about the differences between Salman Khan and Conrad Wolfram’s TED Talks (Compare and contrast: using computers to improve math education) brought a lot of traffic to the blog, some great comments, and more than a few Twitter conversations about how to teach math.
So I’d like to get more specific about what I think is wrong about the Khan Academy approach by writing about things I see as wrong with the way we teach math in the US.
No matter if we agree or not about Khan Academy, I’m fairly certain we can agree math learning is not going as well as we’d like (to say the least.) Too many people are convinced by the system that they “hate math”, and even students who do well (meaning, can get decent test scores) are often just regurgitating stuff for the test, knowing they can safely forget it shortly afterward.
There is plenty of blame to go around… locked-in mile-wide inch-deep curriculum, focus on paper and pencil skills, lack of real world connections, assessments that are the tail that wag the dog of instruction, a culture that accepts “bad at math” as normal, teacher education programs that have don’t have enough content area specialization, … you can probably add to this list.
I can’t tackle all of these. But if you are interested, I’d like to share my thoughts about Khan Academy and a few epic math myths that are relevant to a discussion of the Khan Academy. In America, these myths are so pervasive that even people who were damaged by the way they were taught themselves accept them and insist that their children be taught using exactly the same methods.
I think these myths explain both the widespread acceptance of Khan Academy as a “revolution” and also why in reality it’s not going to change anything.
Myth: Learning math is about acquiring a sequential set of skills (and we know the sequence) I think people have a mental image of math that looks something like a ladder. You learn how to add single digit numbers – rung one. You learn 2 digit addition – rung 2. You learn 3 digit addition – rung 3. In this model, you get to rung 3 by throughly learning rung 1 and then rung 2.
The myth continues with the idea that the march up the ladder goes faster if we tell children exactly how to do the problems step-by-step. In the language of math instruction, these step-by-step processes are called algorithms. Some kids “get it”, some don’t, but we accept that as a normal way that learning happens, and “help” the ones who don’t get it by drilling them harder in the step-by-step process, or devising additional tricks and supports to help them “remember” how to solve the problem.
If they don’t learn (meaning pass tests), we take this as evidence that they haven’t practiced the steps well enough, and prescribe more of the same.
Khan Academy plays perfectly into this myth. Here are a convenient set of videos – you just find the one you need, push play and the missing rung in your mental math ladder is filled in.
A corollary to this myth is that we can test students for these discrete math skills, see which “rungs” are missing, and then fix that problem with more instruction and practice on that specific skill.
Let’s diagnose how we think about learning a simple math skill
When we teach 2-digit addition, we immediately introduce the algorithm of “carrying”. You should know, though, that the U.S. form of carrying is just one of many addition shortcuts, not handed down on stone tablets. It’s not used world-wide, nor is it something that people naturally do when adding numbers. But it’s cast in concrete here, so we teach it, then we practice that “skill”. With our ladder model in mind, if a child can’t answer the 2-digit problems correctly you do two things: 1) Do more practice on the rung under it, and 2) do more practice in the algorithm, in this case, carrying.
The problem is that if a student has simply memorized the right answers to rung 1 without real numeracy, reviewing carrying will not increase that understanding. In fact, it will reinforce the memorization – because at least they are getting SOMETHING right. They are like the broken watch that’s right twice a day. This issue gets worse as the math gets more complex – the memorization will not be generalizable enough to solve more complex problems.
If this is true, and since these administrative skills are not sequential, it makes it less likely that we really learn math in a sequential way. I think we’ve all had similar experiences, where a whole bunch of stuff suddenly makes sense.
This different vision of how people learn is called “constructivism“. It’s a theory of learning that says that people actively construct new knowledge by combining their experiences with what they already know. The “rungs” are completely different for each learner, and not in a specific order. In fact, rungs aren’t a very good metaphor at all.
“…constructivism focuses our attention on how people learn. It suggests that math knowledge results from people forming models in response to the questions and challenges that come from actively engaging math problems and environments – not from simply taking in information, nor as merely the blossoming of an innate gift. The challenge in teaching is to create experiences that engage the student and support his or her own explanation, evaluation, communication, and application of the mathematical models needed to make sense of these experiences.” – Math Forum
Learning theory? What’s the point?
We need to talk about learning theory because there are different ones at play here. And to be complete, we are also going to need to talk about teaching theory, or pedagogy, along the way. Constructivism doesn’t mandate a specific method of teaching, but is most often associated with open-ended teaching, constructionism, project-based learning, inquiry learning, and many other models. Most of these teaching models have at the heart an active, social view of learning, with the teacher’s main role as that of a facilitator.
However, the teaching theory underlying most of American math education is instructionism, or direct instruction – the idea that math is best taught by explicitly showing students how to solve math problems, then having students practice similar problems. Direct instruction follows when you believe that math is made up of sequential skills. Most American textbooks use this model, and most American teachers follow a textbook.
This is important distinction when talking about Khan Academy. Khan Academy supports teaching by direct instruction with clear (and free!) videos. If that’s your goal, you’ve found the answer…. but wait…
Is clarity enough? Well, maybe not. Even if you believe in the power of direct instruction, watch this video from Derek Muller, who wrote his PhD thesis on designing effective multimedia for physics education. Really, if you are pondering the Khan Academy question, you must watch this video.
“It is a common view that “if only someone could break this down and explain it clearly enough, more students would understand.” Khan Academy is a great example of this approach with its clear, concise videos on science. However it is debatable whether they really work. Research has shown that these types of videos may be positively received by students. They feel like they are learning and become more confident in their answers, but tests reveal they haven’t learned anything. The apparent reason for the discrepancy is misconceptions. Students have existing ideas about scientific phenomena before viewing a video. If the video presents scientific concepts in a clear, well illustrated way, students believe they are learning but they do not engage with the media on a deep enough level to realize that what was is presented differs from their prior knowledge. There is hope, however. Presenting students’ common misconceptions in a video alongside the scientific concepts has been shown to increase learning by increasing the amount of mental effort students expend while watching it.” – Derek Muller, Khan Academy and the Effectiveness of Science Videos
Derek makes an interesting point – clarity may actually work against student understanding. Videos that slide too smoothly into an explanation do not give a student a way to process their misconceptions and integrate prior knowledge. The very thing that makes the videos so appealing – Khan’s charisma, sureness, and clarity may lull the viewer into comfortable agreement with the presentation without really absorbing anything (Research references and Dr. Muller’s PhD thesis on this subject)
Hooks, not ladders
This goes back to my original point. People learn by reorganizing what they already have in their head and adding new information that makes sense to them. If they don’t have a “hook” for new knowledge, it won’t stick. The tricky part is, though, that these hooks have to be constructed by the learner themselves.
Wishful thinking about downloading new information to kids is just that – wishful thinking.
There is no doubt that Khan Academy fills a perceived need that something needs to be fixed about math instruction. But at some point, when you talk about learning math, you have to define your terms. If you are a strict instructionist – you are going to love Khan Academy. If you are a constructivist, you are going to find fault with a solution that is all about instruction. So any discussion of Khan Academy in the classroom has to start with the question, how do YOU believe people learn?
I have more to say about Khan Academy and math education in the US — this post turned into 4 parts!
My context for these posts: I fully admit I’m not an expert in math or math teaching, just an interested observer of K-12 education in the U.S. In my work, I have unique opportunities to see lots of classrooms in action and talk to lots of teachers. It means I get to see patterns and similarities in classrooms all over the country. I don’t intend to do a literature review or extensive research summary in these posts. This comes from my personal experience, my master’s degree in educational technology and draws from a subjective selection of research and sources that have had a deep impact on my thinking about learning. Finally, I am NOT trying to tell teachers what to do. I’m not in your classroom — that would be silly.
This may be old news for some of you, but I just came across a website – Child Trends that seems like it would be a really useful resource for planning new school programs or for writing grants. It covers research on children in many areas including child health, education, behavior, and more. Although not technology related, often it helps to reach out to other areas of research to justify practices that support technology use with youth.
For example, teaching children about online safety, dealing with cyberbullying and other online risks is not just about teaching technology. And looking to research to find out “what works” to prevent face-to-face bullying or preventing risky behavior means you aren’t reinventing the wheel.
Here are just a couple of their reports on youth development that offer some lessons for the design and support of well-rounded cybersafety programs:
There’s a belief among theater folks that if you have a bad dress rehearsal, it means you will have a good performance opening night. I’m hoping that proves to be true in regards to conference presentations too!
I’ve been working on my keynote presentation and thought it would be a good idea to test some of it at PETE&C, the wonderful Pennsylvania state educational technology conference. I added a lot of video of student work, students talking about how their leadership opportunities using technology changed their lives, and more. I always like to SHOW the results of student empowerment rather than just TELL about it.
But as my friend Gary Stager likes to say, multimedia is just Latin for “doesn’t work in front of an audience.” Just a few minutes into my presentation my speakers went dead. Now I’m faced with a dilemma – do you stop what you are doing to do tech support in front of 100 people? Do you just skip the video? Do you try to paraphrase what’s happening in your now silent video? ACK!
I asked if anyone in the audience had any speakers – and one woman came up with hers. Success! Wonderful sound….for about 20 seconds. Then the battery light started blinking, the sound faded away and she apologetically said she had forgotten to charge them up. Back to square one. I fumbled my way through the rest of the presentation, hoping my enthusiasm would make up for the lack of real examples.
By the end of the talk I was pretty discouraged, feeling sad that people didn’t see all the marvelous goodies I had to share and thinking about all the things I should have done differently. It was very heartening that several people came up to me and said that the session had been very inspiring and they were already thinking about some new ways to empower their students with technology. I also saw some very nice tweets about the session. Other people cheered me up with stories about much worse technical calamities that they had endured at conferences or in the classroom. There seems to be relief in shared pain!
But bottom line (and new speakers in hand) I am ready to prove the old theater adage completely right. The bad dress rehearsal surely means that my keynote for New Zealand will be great! Kia ora!