You might notice in the screen shots for this post that I started roughing in the walls and floor of the classroom itself. I put some windows to the student’s left and have some dynamic sunlight coming through. I also added a dynamic ceiling light. Not totally sure what to do with the walls at this point, looks pretty bare. Maybe a bookshelf, or a bulletin board, maybe the overall room is too large, I don’t know. That’s why they call it a work in progress.
In my last post I mentioned that I finally had my first “ah ha” moment considering the viability of this project. The path of progression had, for the first time, lead to something that had true potential for doing something unique and useful. This happened when I realized that we were starting to replicate real world problems faced by any teacher in any classroom. We also are now starting to develop ways of capturing input that can lead to, at the very least awareness of, and at best, solutions to these problems.
My second “ah ha” moment came when I read an article that popped up on Twitter one day. The article is from edutopia.org and is titled Teaching Empathy: Are We Teaching Content or Students. For me, the stand out quote from this article is “Without empathy, you’re teaching content instead of students.”
That quote really started to put this project into perspective for me. One of, if not the primary, goal of this project was to give soon to be teachers a chance to practice in front of a classroom of students. The content that they teach will vary but techniques for focusing on the students could be universally the same. “Empathy” might be the overarching theme for this project. With that in mind, I started building some things into the simulation that should allow the user to engage with the individual students.
The first thing I did was to add a Depth of Field effect on the camera when the user calls on, and begins talking to, one of the students individually. I also chose to slightly narrow the Field of View when talking to an individual.
The combination of these two camera adjustments helps to simulate the tunnel vision that can happen when a teacher chooses to focus their attention on one student rather than the class as a whole. Although the effects of this action on the metrics of the simulation are yet to be determined, it definitely opens the door to both positive and negative results. This is good because, as I mentioned before, we want to be replicating real world situations while providing methods of interaction.
You might have noticed in the screen shot that I have also started to create a style for overlay graphics. In the top left you can see the name of the student the user is currently talking to. If the user is currently addressing everyone at once then the graphic will say “Class.” This used to be just text but now these are graphic sprites placed on an overlaying Canvas game object in Unity. The nice thing about the Canvas is that it scales nicely with different resolutions. This will be useful for the final compiling of the application.
I have also added a second overlay graphic on the top right of the screen which looks like a pencil. This will eventually be some sort of meter that will measure something about an individual student or the class as a whole.
What this graphic is ultimately used for is yet to be determined. It might even vary from module to module depending on what the teaching goal is. One possibility might be to use the pencil meter to keep tabs on how well a student is paying attention. At the same time, the class’s pencil meter might be used to keep an average of all the students’ level of attention.
This type of graphic overlay is typical in games but it certainly isn’t very real world. Typically students don’t have an attention meter floating somewhere above their heads. To make this more real world I needed some ways for the students to convey they are not paying attention using body language.
Early on I had key framed out a nervous finger taping and foot shuffling animations, so those still exist. These animations are pretty subtle and probably would be used to indicate only a minor drop in a student’s attention. I also needed something more evident.
To provide the students a more obvious way of displaying lack of attention I animated two different slouching poses. In the first slouch, the student simply just slides their butt forward and sinks lower into their chair.
In the second slouch pose, the student can place their elbow on the desk while resting their head on their hand.
In addition to key framed animations, I also wanted to add the ability for students to dynamically change what they are looking at. A student looking at something other than you should be a clear indication of not paying attention. So I wrote code that allows any student to not only look at the user/camera/teacher but to look at any other student as well. For now, this look at change is trigger by voice commands.
Most likely, as the simulation progresses, there will be additional physical indicators added as well as additional distractions for the students to look at. We’ll want to add as many real world possibilities as we can to keep the simulation fresh, varied, and more life like, but for now, this is a good start.
Eventually all these indicators, individually or in combination, could be tied to a student’s attention meter. As the meter drops, some sort of body language indicator will be trigger or vice versa; as an indicator is triggered the attention meter will drop.
With all this effort put into indications for lack of attention, I thought I had better create some indictors for the opposite side of the spectrum as well. What are some things a student might physically do when they are paying attention? Some of these things we already have. Students sit up straight, they look at you, their eyes follow you as you move, they respond to voice commands, they smile and frown but, what else could they do?
Raising a hand, nodding yes and nodding no are the three additional abilities that I ended up adding to the students. All three could serve as indicators that they are paying attention. These actions are all triggered by voice commands.
For variety, I added a bit of randomness in the speed of these actions. It looked very strange, and unrealistic, to see the entire class raise their hands at the exact time and speed. It also look very strange for the entire class to nod their heads in synchronization. A bit of randomness really helped the believability here.
I believe we are now reaching a cross roads in the development of this project. We now have the tech and mechanics in place to create scenarios where necessary intervention by the user can be indicated and be required. The difficulty that remains lies in structuring scenarios where input from the user can be sufficiently judged. Once the user has identified a student who is struggling, what does the user do? How do we know what the user has done worked? Are there ways for the user to get more information as to the cause of the struggle that may lead to a clear course of intervention? Can we capture that intervention?
These are some of the tough questions we will be trying to answer as we move forward.
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