Posts tagged learning

A Quality Learning Experience

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Halfway through my first semester of the EDTECH program at Boise State, I realized that I was going to have a high-quality online learning experience, because online teaching is a chunk of what the program is about. The professors practice what they preach. The two ingredients for me that have made the program a success so far are the engagement and the project-based learning.
My first memories of online courses date back to about 2001, when my undergraduate school was first implementing online learning. It was a prime example of what not to do: no collaboration, faulty assessment tools, and no interaction with the teacher. There were few, if any opportunities to interact with the other students online. The assessments were basically just the same quizzes used in the brick-and-mortar version of the class, but with a time limit slapped on and the ability to “cheat” by reading your textbook. And the teacher was unavailable, and wouldn’t respond to emails for three or four days at a time.
Contrast that with the highly constructivist, collaborative, project-based learning model Boise State’s EDTECH program has adopted in its classes. It is an engaging experience. I’m finding that I’m learning and retaining more knowledge than I have before. The collaboration is invaluable as I develop and refine my projects, not to mention the enjoyment that comes from sharing one’s hard work with peers. Being able to create projects that I can directly use in my own line of work is motivation to finish them and do my best. For me, at least, I consider that an indication of this instructional model’s efficacy.
In our school district’s summer technology conference, all learning follows a similar hands-on learning model. Participants are expected to create content, rather than simply learn about it. There is still an approach where the instructor is more a lecturer than a facilitator, but every participant sits at a computer, learns about the technology tools, and constructively uses them during the instruction.
 

Engaging Learners Through Video Game Principles

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In a TED Talk from 2010, Tom Chatfield describes seven aspects that lend to the creation of effective, engaging games. They can particularly be applied to how we learn in general. The video is shown below, and he starts describing the seven aspects around the 8:30 mark.

These ideas apply directly to how learning-oriented games can be designed, and to a large degree apply to the physical classroom environment as well. Chatfield’s list is as follows:
1. Experience bars measuring progress
Instead of assigning grades, some teachers have turned to an experience point system. This is a familiar aspect of games, and measures a student’s steady progression through tasks (or “quests”). This system can apply to traditional classroom learning as well, and a teacher could accomplish this by putting experience bars up on a board, or manage it with online student profiles. Experience points are great at measuring progress over time in a nuanced, quantified manner, perhaps moreso than a flat list of assignments on a student’s progress report can do.
2. Multiple long and short-term aims
Students should be allowed to participate and choose different types of quests. Different quests can lead to larger goals, but students should be allowed to guide their progress, and take ownership of what they choose to accomplish. With enough “subquests,” students feel as though they are continually progressing, and have a clear end in sight.
3. Reward for effort
This goes back to standard behaviorist principles. If desired behavior is rewarded, the behavior will be reinforced and more likely to be repeated. We shouldn’t punish students when they fail, but instead recognize their achievements as they learn. Games teach us that we should turn “failure” into “success not yet realized.”
4. Rapid, frequent, clear feedback
One of the advantages of games is that they allow players to link consequences to actions. Even in cases where a game’s storyline is progressive and linear, a clear cause-and-effect chain is implied. For open-ended games, the player can alter the state of the world through their own choices. It is essential to learning that students are given prompt feedback following activities, so they know if their attempt was successful, or what could have caused unintended outcomes.
5. An element of uncertainty
People should not always expect everything, and the consequences or outcomes should not always be expected. This adds to excitement and encourages people to keep coming back. When applied to education, it keeps students entertained and willing to keep engaging in the learning process.
6. Windows of enhanced attention
Find moments in a learner’s play where they will be most receptive to learning, and identify areas where learners will gain confidence as they play. This can relate to how Kiili (2005) describes flow theory, or the ideal state at which a participant is absorbed in the learning material, the optimal experience in which full attention is placed on the activity, and nothing else seems to matter. If we can create these types of experiences in our games, students will be more receptive to what is being taught.
7. Other people
Students will invariably possess different competency levels in any game they play, and as they learn, their skills will evolve at varying speeds. Hunicke (2005) discusses this at length as a mechanism for creating an effective gaming environment without disrupting player experience. A balance must be formed between the game’s ease and difficulty. In other words, the game must be “gamed” in such a way that learners are not bored or frustrated with the ease or difficulty.
References
Hunicke, R. (2005). The case for dynamic difficulty adjustment in games. Proceedings of the 2005 ACM SIGCHI International Conference on Advances in Computer Entertainment Technology, 429-433.
Kiili, K. (2005). Digital game-based learning: Towards an experiential gaming model. The Internet and Higher Education, 8(1), 13-24.

How Complex Is Your Learning Environment?

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In one study, it was shown that rats who grow up in complex environments acquired an increased capacity to learn (Bransford, Brown, & Cocking, 1999). A “complex environment” involves different tasks to perform at frequent intervals, new situations presented every day, and ultimately a rich set of experiences from which to draw information. Compared to rats who grew up in individual cages with limited stimuli, the animals from the complex environment, once introduced to a unique learning experience, performed better with fewer mistakes. With reward-based motivation, they even performed better on complex tasks. Interestingly, the animals from the complex environment had 20-25% more synapses per nerve cell in their visual cortices at the end of the study. The wiring in their brains had more connections than the individually-caged rats.
Now, just how closely these animal studies relate to humans is up for debate, and I recognize our students have quite a bit more advanced brains than mere rats. But how do you think our schools fare? Do we create “complex environments” involving a rich set of experiences from which our students can draw information? Or are we still stuck in the boring lecture rut, where students stare aimlessly at yet another meaningless PowerPoint while an instructor drones on about who-knows-what?
I’ve been redesigning our district’s online professional development portal, and it occurred to me that online learning can’t simply fall within the same routine pattern either. This is, of course, much easier said than done. It’s almost impossible to avoid if we’re providing self-directed, instructor-free classes, which has basically been the extent of our online learning delivery in the past. It can make formative evaluation less effective and difficult when direct interaction is not possible. Technology tools such as video conferencing could provide visual cues, and requiring the learners to produce reflective updates can illuminate personal growth, but there is something to be said about being in a physical classroom interacting with actual students in person.
On a related note, I’ve been reading and considering how adopting a cognitive load theory can influence how online learning is developed. Cognitive load theory refers to the “mental burden” of accomplishing various tasks. Think of it like the CPU of a computer. If you start loading up a ton of programs, the system is going to slow down because all the applications are hogging the CPU’s processing power. It’s the same idea here. The brain can only handle so much thinking at a time. The idea is to minimize the “cognitive load” on the learners. This isn’t to say that “cognitive load” is something that happens as instantaneously as a computer’s CPU, as the load can be spread out over time, but the solution is straightforward. Simplify the tasks, so to speak, by identifying different forms of instruction which have a similar effect on learning, and choosing the simplest one. As it relates to online learning, the “variability of problem situations encourages learners to construct cognitive schemas, because it increases the probability that similar features can be identified, and that relevant features can be distinguished from irrelevant ones” (Van Merrienboer & Ayres, 2005, p. 7). It’s a similar issue to the necessity of creating a complex environment. We want to create a variety of situations that will increase the chances that the learning will “take hold.” The focus should be on creating a variable environment to stimulate more learning opportunities.
One aspect that cognitive load theory implies for instructional design is that methods which work well for novice learners may have no effect, or even a negative effect on experienced learners (Van Merrienboer & Ayres, 2005, p. 8). This could provide a rather valuable insight to one of our district’s professional development events. In our yearly BrainBlast conference, the general goal is to provide workshop-based classes suitable for all learners. We do not let the participants choose their own classes. Instead, we randomly choose classes for them. We want to give teachers exposure to topics to which they may not initially see the value. The downside is that this necessitates a nonexclusive course design.
Our approach requires a trade-off, because if we accept the statement that teaching methods work differently for different levels of learners, the instructional effectiveness is stifled by the fact that we must resort to a limited set of general methods that we believe will work well for everyone. At the very least, in the coming years we should request all participants fill out a survey to determine their technological aptitude. Then our courses can be divided into different levels of learning (e.g. beginner, intermediate, advanced). Ideally, we would subdivide these into different skills our participants possess for different technology tools.
A complex learning environment does not refer to a situation where there is over-stimulation. We don’t want cognitive overload, after all. Learning should be reduced to the simplest cognitive form, but also provide complexity in the form of a diversity of learning stimuli and experiential opportunities.
References
Bransford, J. D., Brown, A. L., & Cocking, R. R. (Eds.). (1999). How people learn: Brain, mind, experience, and school (pp. 102-116). Washington, D.C.: National Academy Press. Retrieved from http://books.nap.edu/openbook.php?record_id=6160&page=102

Van Merrienboer, J. J., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-learning. Educational Technology Research and Development, 53(3), 5-13.

Educational Technology and Learning

A presentation about the relationship between educational technology and learning.

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