Science, UDL, and Lesson Design (Maker Experiment 2)

This post is a revision of the original experiment I posted two weeks ago. The main purpose of this is to add more elements of Universal Design for Learning and to elaborate more on the process used to help students build their own understanding of speed based on experimentation.


Additions

This activity will have a larger scope than the immediate physics relationship. Students will work with their biology (and health?) teachers to study human physiological reactions to activity. Things like heart rate, muscle fatigue, breathing patterns, etc can all be studied. Students will be asked to take factors like exercise patterns, sleep habits, and nutrition and evaluate their effect on physical tasks. The bicycle can then be used after a period of experimentation to take new data and draw conclusions.

To address the process of encoding and decoding graphs, I’ll be adding an activity from David Wees, a math teacher who often does experiments with web tools being used to teach through inquiry and games. Not long before I wrote the original experiment, David shared an interactive graphing game that I referenced, but didn’t pay much attention to. The player is asked to move a stickman in such a way that a real-time graph matches a pre-determined line. The graph is labeled and clearly shows the effect of any action in the game. Students can use this to form explanations of the components of graphs and how they relate to one another.

This leads into the bicycle hooked to the Raspberry Pi. The parameters are similar (distance over time) but we’re adding the physical act of pedaling as well as the physics component (speed) as outlined.


Reflection

I have to admit, this re-write is challenging. The components of UDL all seem to focus on choice, multiple means of acquisition and sharing, and multiple opportunities for learning. Rewriting an activity to include more components of UDL by adding parameters seems to be counterproductive.

That being said, my original plan did not do a whole lot to support the task of reading and creating graphs, and I think the addition of David’s stickman game will address that problem. I also think this was more an exercise in writing clearly than it was about incorporating principles of UDL. My original intent was to have simple prompts with multiple points for experimentation, assessment and revision, and I think that has been maintained (for the most part) in this update. Perhaps the wider picture is something I envision frequently, but communicate rarely.

My teaching has always focused on openness…BYOD, open Internet assessments, open-ended assignments…I think all of these things are supported by the UDL framework and are not things I articulate in new lessons. Science is a story…exploration and experimentation help us navigate that narrative. This entire activity is designed to have students do something they’re familiar with and apply it to a new idea.

Standards and goals for activities are good guides for learning, but too much of a focus on how to get students down that path robs them of authentic opportunities to experiment and defend their ideas. Rather than approaching UDL as a checklist for lesson design, we need to look beyond the components and find ways to promote the ideas they represent. Do we need a specific line in a plan that says, “Students will create an online resource for [fill in the blank]?” Or, should we allow them to come to us with the ideas for sharing and support them in that goal?

The most exciting phrase to hear in science, the one that heralds new discoveries, is not ‘Eureka!’ but ‘That’s funny…’

Isaac Asimov’s words hit home (thanks David Grossman for sharing!) I would argue that we replace “science” with “learning.” It doesn’t happen by having a section in a lesson plan for “provoking sustaining effort or persistence,” and achieving that mindset takes a serious mental shift for the teacher (and student) to achieve.

All this to say: we need to focus on providing the means to support multiple opportunities for students to learn in their own way. I don’t want to worry about what each student “prefers.” I’d rather be open enough so that each can go his or her own way and be successful.


Resources

Graph Game. [Digital]. Retrieved from http://davidwees.com/graphgame/

Google Voice Search Coming to Chrome

I’ve been ensconced in Chrome lately. I worked with the team at TechSmith who brought Snagit to Chrome and now, I’m researching different ways to make learning more accessible through Chrome apps and extensions. I’m not going to get into the argument of why it is or isn’t a big deal. I’ll just say that yes, I think it is a big deal, but save the why for another post.

Last night, Google published an extension that brings Google Now-like voice searching to Chrome. It runs in the background and lets you use the “OK Google” trigger to search for anything.

You should grab the extension to try it yourself.

Like I said in the video, other than feeling like I’m in Star Trek, talking to my computer and having it talk back, what implications does this have for learning? If students can do a search for anything without even using their hands, it should really change the way we think about technology in classrooms.

What ideas do you have?

Application of Intent – Design Experience #1

Design is the application of intent – the opposite of happenstance, and an antidote to accident.

The quote I open this post with is from Robert L. Peters, a designer, thinker, and professor originally from Canada, but teaching globally. This is especially apropos because of the task this week, designing a classroom, and because this is something I thought about constantly while teaching. Design influences frame of mind, expectation, and ultimately, behavior in any given space. Schools, in my opinion, haven’t paid enough attention to design, which is why we struggle to accomplish collaborative learning or inquiry-driven learning goals.


Greg Green is the principal of Clintondale High School in Detroit. Greg and I spent time together working with a team on the Four Pillars of Flipped Learning. We were tasked with explaining and classifying Flexible Environments. Greg and I talked about the types of spaces that must be present in any classroom to support all types of student learning needs. Because I am not currently in the classroom, I took some creative liberty and designed the ideal classroom space based on my discussions with Greg. The four areas we identified were:

  1. Individual space
  2. Group (collaborative) work spaces
  3. Small group instruction
  4. One on one instruction

Obviously, these could be accomplished in any variety of ways, and I approached it through an intentional floor plan, furniture, flow, and available resources.

Each area of the classroom is designed to meet a particular need. It is also easy to get up and move around as needs change throughout the course of a class. A student could begin working individually, but easily move to another area of the building to join his or her group, or get some extra help from the teacher.

A main argument for the need of varying learning spaces comes from Howard Gardner’s Multiple Intelligence Theory. According to Garnder, people have cognitive strengths they pull from to solve problems (Brualdi 1996). We’re all familiar with classifying students as “visual” or “kinesthetic” learners. However, there is no evidence suggesting that focusing on particular facets of intelligence described by learning style theorists helps students succeed (Riener, Willingham 2010). Design as an effort to meet these multiple intelligences is shortsighted and doesn’t address the needs of learning as a practice.

For such an ambitious undertaking, the entire community would need to be involved. School leaders, teachers, designers, parents, and most importantly, students, should have a say in the way the space is structured and implemented. More often than not, students know their comfort zones and how to address their own needs. Without the correct space, for example, a student can create a space of individual learning by using earbuds in a noisy room. It is the task of the teacher to help students evaluate what kind of environment is most conducive to learning. The space should support the behavior we want to see in a given situation.

Placing a cost estimate is nearly impossible because of all the variables involved. We can go for top of the line digital tools and put the cost into a prohibitive zone, or we can evaluate the needs of the space and work to solve those needs effectively. Aside from furniture, this learning space only has large televisions for presentations or discussion on digital media. Multiple whiteboards are included for on-the-fly collaboration, problem solving, or brainstorming. There are no computers in this space because learners are often using their own device(s). Comfort is important, and the task of learning an unfamiliar tool can often get in the way of focusing on the work being done.

Large projects are very difficult to implement all at once. With this particular project, I think the mindset of what schools should look like and do will be a major barrier. Schools in their current form have been around since the early 20th century. The system of compartmentalized education is such a part of our culture, that a shift in a direction that gives students freedom and choice in their learning path is a major uphill battle. If we can begin talking about schools the same way we talk about libraries and community centers, design change will follow close behind.

References

Brualdi, A. 1996. Multiple intelligences: Gardner’s theory. ERIC/AE Digest Series EDO-TM-96-01. Retrieved from http://www.springhurst.org/articles/MItheory.htm

Riener, C., Willingham, D. 2010. The myth of learning styles. [Digital] Change: The Magazine of Higher Learning. September-October 2010. Retrieved from http://www.changemag.org/Archives/Back%20Issues/September-October%202010/the-myth-of-learning-full.html

What Are You Thankful For?

I’ll admit right at the beginning that this post is a shameless use of all facets of my network. This blog is one of those. So, if you’re someone who doesn’t like it when people do that, you can stop reading, I’m sorry. But, I do ask that you give me a shot.


Thanksgiving is upon us, and customarily, people are sharing out their quips of thanks for the season. Some go through each day and give one thing they’re thankful for.

I think this is something we need to do more often in education. It is very easy in today’s climate to get beaten down and complain about the things going wrong in our schools. I count myself in that group. There are a lot of posts on this blog in which I extol the adversity in my classroom and building. However, I would like to invite everyone to share something they’re thankful for in education. There are more wins out there than losses, and I want to make those as public as I can.

If you’re not familiar with what I do nowadays, I work with TechSmith Education. Part of my job is to host a weekly podcast on the EdReach Network titled Chalkstar to Rockstar: Revolutionary Ideas in Learning. I get to share out stories of teachers doing amazing things in their classrooms each week, and I’ve had the chance to interview some amazing people.

Next week is the Thanksgiving episode. It goes live on Wednesday, Thanksgiving Eve, and I want to share as many stories of thanks in education as I can. To do that, I need your help. Please take 30 seconds to fill out a two question survey, of which only one question is mandatory. I’ll be sharing all of the responses on the podcast as well as an accompanying blog post. If you could fill out the embedded form below and then pass it along, I’d be much obliged.

You can also share on Twitter using #eduthanks. If you want to pass the survey, you can use http://bit.ly/eduthanks.

For me, I’m thankful for teachers who continue to fight the good fight against overwhelming odds. You all are an inspiration daily (and I’m not just saying that). Happy Thanksgiving, everyone.

I’ll Take it to Go

CEP 811 is steaming forward at full speed and we’re now getting close to finishing week four of the course. This week, we’ve been tasked with creating an outline for a MOOC. After many days opening a new blog post and staring at it, I think I’ve finally landed on a format and topic. So, without further ado, I humbly submit for your consideration…

In I’ll Take it to Go, my peers will explore mobile creation skills by working only on mobile phones for the course and through open communication, feedback, and remixing by peers.

Course topic: facilitating active learning on mobile devices.

Students are coming into schools with mobile devices which are not being utilized for a variety of reasons, one of which is not knowing how to effectively engage students in higher order thinking skills. Often, mobile apps and tools are dismissed as only having entertainment value. We are missing a huge opportunity to leverage the computing power in their pockets.

So, the question is, “Why mobile devices?” Consider the amount of time you use your device each day. Directions, research, quick communication…all done on the go. We capture moments through photos and video, we share our lives with one another as we move from place to place. These simple (and often free) tools can be repurposed to support students and the learning process. Nearly all students have experience with mobile devices, so the time spent teaching complicated tools can be eliminated. Remember, Cognitive Load Theory states that learning can only occur when the student can apply sufficient working memory resources (Sweller, Merrienboer, and Paas, 1998). Too often, new tools command the student focus rather than the learning task given. By using familiar tools, accentuating process and encouraging connections, the course will push learners into higher-order application of ideas and skills.

This is meant for all educators and students. Tools that can be used by students can (and should) also be used by teachers and other staff to engage, encourage, and support learning. This won’t be a typical MOOC. The course will be decentralized and focus on skill building and innovative application of mobile learning techniques. Learning targets will have suggested tasks to complete, but participants will be able to network, explore, and create their own products for completion. Peer evaluations will be used as benchmarks for progress through the course, and the course can be taken in any sequence. That being said, the length of the course may vary from one person to another.

Participants in the course will be expected to use their mobile device to create a history of artifacts to demonstrate their learning. Areas of focus will include photography, video, audio, social media, and blogging. While all tasks can be done on a traditional desktop or laptop computer, the main objective of the course is to immerse learners in the world of mobile tech so they can bring their experiences back to the classroom to more successfully engage their students. The time it takes to complete is partly determined by the depth of exploration that occurs within each topic and the resulting peer assessment, revision, and remixing. There is no prescribed “time on task,” and learners will have an opportunity to explore ideas as in depth as they would like.

Putting it together

The majority of MOOCs focus on using the Internet as content delivery…a large pipeline through which information can be delivered from one person to thousands. The problem is that the Internet doesn’t work like a pipe. It works like a network, with information criss-crossing from one person to another. If we want to design effective online classes, we need to build courses to mimic that network. As long as MOOCs focus on technology (the LMS used for delivery) and the content (top-shelf professors), their design and effectiveness will continue to suffer. Pedagogy must has as much importance as the others, if not more, in order to truly innovate in online education.

Resources

TPACK self-assessment. [Digital]. Retrieved from http://caryacademy-sti.wikispaces.com/TPACK+Self-Assessment

Sweller, J, Merrienboer, J, Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review. 10-3, 251-296. Retrieved from https://docs.google.com/file/d/0B68p5ayLtLuqZ2wtTTNueElZUHc/edit?usp=drive_web

Listening Past the TED Talk

I watched a TEDxBeaconStreet talk the other evening entitled “Reimagining Learning.” It started off well enough, with some good points about the challenges of teaching in a digital age. I really liked Richard’s opening point:

There’s a more serious digital divide that we face in this country. That is the divide between those who know how to use technology to reimagine learning and those who simply use technology to digitize traditional learning practices.

Not too bad, consider I’ve even written about reimagining schools through Flipped Learning.

He then made some jokes and quips about scanning photos and using projectors as really fancy chalkboards. Ha ha.

He argue that the way to really change schools is to personalize learning. Again, something I can get on board with.

And then he dropped this bombshell:

< crashandburn >

My heart fell. There are so many things in this story that put Richard, in my mind, solidly in the camp of “digitizing traditional teaching practices.”

The students walk in every day and they see on these screens, their names…and they see where they’re supposed to go to learn that day.

I don’t know about you, but the first thing I want my students to see when they walk in is me, smiling, welcoming them back to the room to learn together. Step one in this case is digitize the teacher.

And then they go, like this group of girls right here, and they learn whatever they’re doing. At the end of the period, they stop a few minutes early, and they take a quick three-question test.

Their performance goes into an algorithm that customizes their schedule for the next day.

Rinse, wash, repeat. (And, I bet if a teacher were around in that picture, they could tell you what the girls were working on that day.)

He then goes on to talk about MOOCs (attributing the idea improperly) and how “reimagining learning” is really just opening it up to hundreds of thousands of people. No mention of the massive attrition rate of students nor the fact that MOOCs aren’t solving real problems in higher education.

I think I’ve come to the conclusion that most of the widely-publicized talks on education are either 1) given by people with lots of money, or 2) given by people who want to make lots of money. There have been very few compelling TED talks lately that have really communicated some of the major change that can come to education when we really think hard about what technology can help us do.

I’m not saying there aren’t any. Ramsey Musallam’s “Three Rules to Spark Learning” and Kristin Daniels’ talk on reinventing professional development are top notch. I’m convinced they are because they’re teachers. Not venture capitalists. Not entrepreneurs. Not CEOs or filmmakers.

Maybe I’m just watching the wrong talks, but I know that I’m waiting for TED to look past the hype and bring back some great ideas.

Maker Experiment #1

Another post in the series for CEP811, we’re really getting serious now as we begin to develop potential plans for our maker kits.

Last week, I wrote about a potential activity using an old exercise bike and a Raspberry Pi hacked together. (It even had a super-fancy animated GIF as a bonus.) In short, the idea was to have the students pedal an exercise bike, send some data to the Pi, and have it graph (in real time) the student’s speed as a function of time.

A lot of this project comes from my longing for a better experience with physics and math in high school. Both were drab, disconnected, and frustrating for me. Since joining Twitter in 2011 and following people like Frank Noschese, Dan Meyer, and Ramsey Musallam, I really wish I had an experience like what they give their students.

I want to focus on one theory in particular: Cognitive Load Theory (CLT). According to CLT, working memory constraints are the determinants of instructional effectiveness (Sweller, Merrienboer, and Paas, 1998). The authors break cognitive load into three types of “load”: Intrinsic, Extraneous, and Germane.

Intrinsic load is related to the nature of the content being taught. Extraneous load is related to the instructional methods and conditions, and germane is the formation of learning schema (Sweller et al., 1998). Tasks with low interactivity contain elements that do not interact with each other, can be learnt in isolation, and require relatively low working memory load (Ayers, 2006). A high working memory requirement comes from tasks that have multiple interacting elements that need to be learned simultaneously rather than in isolation (Ayers, 2006; Sweller, 1999; Sweller & Chandler, 1994). In addition, Marcus, Cooper, and Sweller (1996) state that understanding “is applied only when dealing with high element interactivity material.”

With this in mind, my activity is designed to reduce the cognitive load placed on students as they explore the concept of speed using an exercise bike and a Raspberry Pi.


In order to introduce speed, students need an understanding of how to graph. (I deliberately use the term “understand” here because of the relationships required to produce proper graphs.) Sweller et al. (1998) suggest students that may not have this content processed automatically in existing schema could experience a high cognitive load on the wrong material and be unsuccessful in the goal of the activity.

At the start of the activity, students will be asked to pedal an exercise bike for a period of time. They will not be given direction on how fast to pedal because the second part of the activity will ask them to analyze their graph. The Raspberry Pi will automate the graphing process so students can focus solely on the task of creating a working definition of “speed.” Students will also have an opportunity to repeat the experiment as often as needed in order to confirm their result.

This activity can also be used to introduce the idea of average speed in relation to instantaneous speed. The analysis of the graph will ask students to plot a best-fit line in order to report the average speed of their trial. Typically, this activity is done where students take all the data, create the graph, and then attempt to draw conclusions. I am automating data collection and graphing so students can focus on coming to the correct conclusion rather than filling their working memory with procedural components.

Materials for this activity are difficult to produce because of the exploration that students need to do. By deliberately witholding information and direction, students are more likely to take risks and form hypothesis that can be tested further throughout the class. Science is all about exploration and hopefully, this activity will allow them to explore freely.

In the future I hope to incorporate more ideas around inquiry and perplexity, but that will have to be in another post. For now, consider this TED talk by Ramsey Musallam on the unique opportunity we have every day to perplex and engage students in critical thought and exploration.


Resources

Ayers, P. (2006). Impact of reducing intrinsic cognitive load on learning in a mathematical domain. Applied Cognitive Psychology. 20, 287-298. Retrieved from https://docs.google.com/file/d/0B68p5ayLtLuqRml2MTJHUlRBbFE/edit?usp=drive_web

Sweller, J, Merrienboer, J, Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review. 10-3, 251-296. Retrieved from https://docs.google.com/file/d/0B68p5ayLtLuqZ2wtTTNueElZUHc/edit?usp=drive_web

Thrifting Brainstorms

I went to Goodwill this evening with Lindsey and Meredith. I had wanted to go for a while, and after not finding much in the clothing, I turned towards the assorted gadgets in the back to hunt for some cool toys for this assignment.

As luck would have it, there was a great old exercise bike there.

It even had a working pressure dial and speedometer on it.

I bought a Raspberry Pi for the course and I’ve already started working on a project coding in Python and using my telescope. There is a ton you can do with some cheap switches and circuit boards, so I thought it would be cool if my classroom (someday) had a way to introduce graphing using a manipulative. I have to admit I was in a frame of mind for graphing for a couple of reasons.

First, Dan Meyer had a blog post rounding up some great classroom action he saw in the blogs this week. One was referencing novel ways to introduce students to graphing. Dan posted a quote from the original, which I am reposting here:

…a comment laced with negativity that resonated with Lauren and me was an outburst that “graphing used to be so easy, and this just made it hard.”

The second reason I was thinking about graphing this evening was because of a link from Ramsey Musallam to an interactive graphing game by David Wees. I spent a good time playing the game, learning, experimenting, and working to connect the physical act of moving the stick figure to the way the line was being drawn.

So, I came to this idea: Students could ride the bike, which has a controller hooked to the Rasperry Pi, to create a graph velocity for the time bike is pedaled.

In order to get the tachometer on the bike to talk with the computer, you’d need some kind of controller.

Process

  • Take the backing off the exercise bike tachometer to mount the electric switch.
  • The switch will need to mount inside the casing somehow. You would want it to make contact each time the gear rotated once. This could be done by mounting a trigger arm on the gear to contact the switch to complete the circuit.
  • Run the lead from the switch to the Raspberry Pi. I’m not sure if you would need some kind of intermediate step here before it feeds to the computer. I’m still researching.
  • A simple Python script on the computer would count the number of times the switch is activated for a given period of time to calculate the RPM value.
  • The value would be given in a graph vs time as long as the bike is running.

I’m still learning python, but you could start with this snippet of code to get the momentary velocity.:

`r = raw_input(‘Radius [meters]> ‘)
RPM = raw_input(‘RPM> ‘)
rad = float(0.10472)

v = float(RPM) * float(r) * rad

print v," m/s"` By wrapping this function in a `while` loop, you could probably create a pretty nice graph for the time the student was riding the bike. You could then even take it into an experiment where they measure the change in velocity as more resistance is applied to the wheel. ### Resources Yenca, C. (2013, October 31). Giving graphingstories.com a go. _mathycathy_. Retrieved from