Wrapping up Learning about Learning (for now)

As I explored learning theory these past 8 weeks, what struck me most was that I could improve the way I learn by learning about learning…in other words applying metacognition.. I was never consciously aware of learning strategies. I’m sure we covered such strategies throughout my school years, but somehow they never really sunk in. That may have been because I had learning challenges and never felt like the standard techniques worked for me, so I did everything my own way. Now, with the wisdom of maturity, I can see how learning how to learn is actually useful…proven by the fact that I did better at absorbing the information in this class as a result of the class itself.

I was specifically struck by the stage theory of information processing. I always saw remembering new information as an onerous, rote process. I never realized that it could be much easier by understanding how memory happens. Now, when I take in new information , I consciously “store” it, connecting the new information to other ideas so that I can retrieve it easier. I think it is working. Time will tell.

One of my big realizations has to do with interactive learning. In my experience designing instruction by seat of pants, I always steered away from lectures and towards active learning, where participants are given challenges to work through. It instinctively seemed to me to be the best way to teach, because in my experience, it has been the most effective way I learn. Now that I have the theory behind it, I understand that at the core of this instructional strategy is the learning theory of Constructivism. When learners construct knowledge for themselves, rather being passively spoonfed, the learning is deeper and more impactful.

The relationship between learning theories, learning styles, educational technology and motivation is quite interesting. Learning theories have provided insight into how we learn, but I feel like we’ve just scratched the surface in this course. In terms of explaining exactly how we humans learn, I think Cognitivism is the most complete and comprehensive theory. I realize that the computer-oriented information processing model is no longer in vogue, but I find some comfort in transforming this vague thing we call learning into discrete processes that make logical sense. I realize it is oversimplification, but it is a helpful model. While Learning theories explain the mechanics of how we learn, learning styles address preferences for how we take in information. I think learning styles align most closely with Cognitivism, as Cogntivism directly addresses sensory input and information processing, which are key to the learning styles. Educational technology crosses all of these concepts, as technology has become the underpinning for everything we do in learning or anything else in life. While technology is most directly related to Connectivism, it plays a role in support learning processes that are based on any of the theories. Finally, motivation is directly addressed in Cognitivism and Behaviorism, but since motivation is a core issue in learning, it becomes a factor whether one is trying to understand how people learn, trying to reach individual learning styles, or exploring the use of technology to engage learners.

As I embark on my career in Instructional Design, I expect that I will refer often to the concepts presented in this course. Now that I have been exposed to the literature around learning theories, I know I have a vast body of knowledge I can turn to when trying to not just deliver training, but design an experience that is fully and deeply effective. While I believe I will always rely on my gut instincts for inspiration and direction, I now have conceptual models to test and validate my ideas.


A mirror on my learning

For the past seven weeks I have been studying learning theory at WaldenU. I’ve learned about behaviorism, cognitivism, constructionism, connectivism, and multiple intelligences, all in the pursuit of my ability to design effective and impactful learning experiences.

During the first week of the course, I wrote a reflection about how I learn. I addressed my lifelong challenges with learning as a person with ADD, and I used an example of my recent attempt to learn a language to examine how behaviorism and cognitivism explain how I learn. Now that I am an “expert” on learning theory (note the sarcasm), I am re-examining this understanding.

I believe even more strongly than I did at the beginning of the course that how I learn is inextricably linked with what I am learning. When I think about learning something that involves remembering new information, I draw upon what I now know about both behaviorism and cognitivism. For me, attempts to associate stimuli and responses are very difficult, and has gotten more difficult as I’ve aged. My understanding of cognitivism and brain function has given me much more insight into my learning process and explains why I find rote learning difficult. My personal shortcomings with memory means I need to consciously use elaboration, rehearsal, and organizing techniques to encode new information into long term memory in such a way that I can retrieve it when needed.

When I think about learning more complex information, such as new behaviors, new concepts, or problem solving, Constructivism explains how I learn best. I’ve always found most value in working through challenges, on my own or with others, and coming to the conclusions that become part of me. It is so different than passively receiving information disseminated by an expert. I have been through experiential learning that absolutely changed my way of thinking. That has never happened through a lecture or e-learning experience. The struggle, experimentation, and push and pull with others creates new learning in a deep and powerful way.

When I switch to thinking about how I keep up with fast changing information and learn to know what I need to know, it’s all about Connectivism. In the days before the Internet (yes, I lived and worked through them), our connections were few and slow. Information crept along by word of mouth. News came out in daily doses. And the librarian was your best friend if you had to actually learn about something specific. Today there is a vicious (or perhaps virtuous) cycle of more technology and more connections creating so much content so fast that the network itself has become the knowledge.

In addition to better understanding how I learn through the various learning theories, I also broadened my self-understanding through multiple intelligence theory and learning styles. Sadly, when I took the MI online quiz, I scored low on everything (it was a bad day). MI theory did help me see the things that come more naturally to me (language and emotional intelligence) and those that would leave me broke and homeless if I had to depend on them for a living (math and spatial). This helps me not only cultivate those strengths, but even see my weaknesses in a new light – as areas to work on, rather than failures. From a learning style perspective, I am clearly a visual learner, and knowing that leads me to create visual models of information, which help me understanding complex ideas.

OK, now that I’ve thoroughly examined my own learning, I’m ready to take on the world!

Mapping my ID Learning Network

As a baby boomer and “digital immigrant,” I have one foot in the world of network connections and one foot lagging in the world of traditional learning. I’m learning to use new tools and technologies, but I remain attached to the learning methods I grew up with.

I still love a good book. Books feel real and substantial to me. I can hold them, flip through them, smell them and keep a particularly good one on my bedside table for a few minutes of delicious reading before I drift off to sleep. I love libraries and bookstores.

But I recognize, appreciate and take advantage of network connections. If I have a question about anything, from a learning theory to a good recipe for a refrigerator full of zucchini, my first stop is Google. I am constantly amazed by the ease at which millions and millions of websites full of content can be pared down by a well-chosen search term to just the information I need. I am old enough to remember life before the internet, when searching for information was extremely time-consuming and fraught with dead ends.

Once online, I’ve discovered countless ways to connect. Blogs and communities are rich resources that connect me not just to information, but to people I can turn to with questions or to share my thoughts and reflections. I’ve developed relationships with others who are seeking knowledge on the same topics and struggling with the same challenges. I’ve also connected with experts in their field—accessibility that was almost impossible when I was learning how to learn.

But there are dizzying options beyond how I connect today, and I wonder if I’ll ever be comfortable with them. I dabble a bit with Twitter. I use Facebook, but not for serious learning or connections. I have a LinkedIn account, but I don’t really use it much. I’ve never used a social bookmarking site. While I read blogs, I don’t follow any regularly. And I have no clue about the thousand other ways to learn and connect that are emerging today.

Even though I’m a long way from the level of connection of my kids’ generation, I think my personal learning network does support the central tenets of connectivism. For example, George Siemens, the originator of connectivism, posits that the capacity to know more is more critical that what is currently known (Davis, Edmunds & Kelly-Bateman, 2008). This is one of the major changes I’ve observed in the accumulation and use of knowledge over the years. In the past, what I knew was an asset, while today, my ability to use my network to access information is much more valuable than what I have stored in my memory. Another of Siemens’ points states that the ability to see connections between fields, ideas, and concepts is a core skill (Davis). These kinds of connections are central to the way I think and process information, as I continually look to understand such relationships.

I don’t know if I’ll ever be as connected as a Digital Natives, but learning about Connectivism has made me aware of the value of my network, and inspired me to build it further.

Davis, C., Edmunds, E., & Kelly-Bateman, V. (2008). Connectivism. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. Retrieved from http://projects.coe.uga.edu/epltt/index.php?title=Connectivism

Getting smarter about the brain

In order to deepen my understanding of learning and the brain, I read two excellent papers.  These resources expanded what I learned from the course videos and text and I feel way smarter now.  Yahoo!

Ashish Ranpura is a science journalist and researcher on cognitive development.   He wrote a clear and highly effective paper posted on Brain Connection, which describes itself as “dedicated to providing accessible, high-quality information about how the brain works and how people learn.”

How We Remember and Why We Forget,” explains the fundamentals of how memory works.  I found Ranpura’s explanations clear and insightful. He contrasts computer “memories” (discrete and informationally simple) with human memories (tangled together and informationally complex).   Our memories are stored as combination of the sights, smells, sounds and impressions of an event.  These various components are spread over the whole brain.

How these memories are actually formed depends on reinforcement, which can come in the form of repetition or emotional arousal–we remember events with high emotional content.  Memories are also reinforced by paying attention and consciously attempting to remember.

Ranpura provides a detailed explanation of the memory process, using the example of meeting someone for the first time.  He shows how an experience moves from immediate memory to working memory, and then how it gets encoded into long term memory.  His explanations relate these functions to the physical structures of the brain: the prefontal lobe for working memory, the hippocampus for converting from working to long term memory, and the cerebral cortex for storing the memories.  These explanations were particularly effective in helping me visualize the physical brain structures and associate them with functions.

From an instructional design perspective this article clarified why it is so important that instruction captures attention and is emotionally engaging.  As I work to develop learning experiences, I will have a deeper and more relevant understanding of the operation of learning and memory.

The second paper is “The Information Processing Approach to Cognition” by W. Huitt, published in Educational Psychology Interactive.   He provides an overview of cognitive theory of learning and its relevance to instruction.

Huitt introduces and contrasts the widely accepted “stage” (sensory, short term and long term memory) theory with three alternatives:  “levels-of-processing”, “parallel-distributed processing”, and “connectionist” theories.  These theories vary in their explanations of how new information is processed and stored in memory, but all agree on some general principles – that there is a limited capacity in the mental system, that a control mechanism is required to oversee the processing of information, that there is a two-way flow of information between the senses and long term memory, and that humans are genetically disposed to process and organize information in specific ways.  By contrasting the various theories and showing the commonalities among them, Huitt provided the context that helped me organize the information in a way that I could visualize and use as relevant.

He details the stage theory with clear explanations of how information passes from the senses into short term memory (STM), the characteristics and limitations of STM, and finally, how information moves into long term memory (LTM).  At this point I have read multiple descriptions of this information, each providing a useful layer of meaning.  Huitt’s explanations helped solidify my knowledge.

Relevant to instructional design, Huitt identifies instructional techniques that enable information to be retained in STM, such as providing strong organization structure, chunking pieces of data into units, and repetition.  Repetition, he notes, must be done after forgetting begins in order to be effective.

He also indicates techniques that help elaborate information so it can be encoded into LTM, such as creating mental images, rhyming schemes, and mnemonics.

Finally, Huitt addresses instructional techniques that aid in the formation of concepts.  This was the most abstract and least useful section of the paper for me, and left me on a quest to better understand this topic.  His suggestions of principles that lend themselves to concept development included advanced organizers, guided discovery, giving examples and non-examples, using both inductive and deductive reasoning.

Huitt’s article was particularly useful to me as an instructional designer as it concluded with a table that provided very specific examples of how to use the information processing approach in instruction.  This table will be a handy reference guide going forward.

My favorite ID and ELearning blogs (so far)

After exploring about 20 different Instructional Design and ELearning blogs (I plan to be an elearning developer), I selected the following three to critique and reflect upon.

1)     BigDogLittleDog

The Big Dog Little Dog website  is the “pet” project of consultant Donald Clark.  Clark has been running the site since 1995 and it is chock full of information on every aspect of learning and instructional design.  In the BDLD blog, Clark covers the latest thinking in instructional design topics. For example, in the most recent post he covers ADDIE 3.0, the newest iteration of this famous model. He explains how ADDIE has evolved over the years and shows how it has become a much more flexible and iterative process that includes the use of other models, such as Action Mapping, Prototyping and 4C/ID (all of which are new to me and the mention of which spurred further investigation).  In an earlier post he introduces a table of design models (Instructional System Design, Design Thinking, Agile Design, System Thinking, or XProblem), which explains their definitions, goals, main steps and links to further reading.  Again, these terms were all new to me and offered a lot of new information to discover.

I find the blog and the website hugely helpful as I embark on this new field. Clark’s explanations and visuals are clear and compelling.  He conveys an expertise that engenders trust and an eagerness to share knowledge that is downright heartwarming.

I see this blog as an absolute go-to place to learn and stay abreast of this dynamically changing field.

2)      Custom Training and eLearning Blog

This blog is published by CommLab India, an elearning consultancy out of India.  There is a significant blog posting every single working day, which equates to an enormous amount of content.   But is it useful?  Yes, very useful.  The information is practical and addresses a wide variety of elearning topics.  The writing is somewhat dry and formal, but not difficult to read.  In the past 5 days, they’ve covered content types, factoring in the learner’s prior experience, presenting to GenXers, engaging learners, and the value of customer training.

Each post is brief, but includes substantive information that can be applied readily. For example, the post on content types explains how the type must be considered in designing elearning.  It describes the five types: Facts, Concepts, Principals, Process, and Procedure with a short, clear paragraph on each.

This blog archive is a searchable encyclopedia of information that I expect will be a highly valuable resource as I am learning this field.  I suspect that once I pass the beginner stage the blog will become less valuable, although its treatment of new developments (such as MLearning) will always be interesting.

3)      Clive on Learning

This blog is written by Clive Shepherd, a consultant specializing in workplace learning and communication.  I love this blog!  Shepherd addresses current, real world issues in instructional design and learning and he does it in a clear, coherent, highly-readable style.  A recent post on how “video trumps elearning” was referenced on an elearning LinkedIn group and stirred up quite a controversy, as practitioners debated the virtues of each learning solution for different applications.   A post I found personally fascinating was on the use of learning resources vs. full blown learning content.  With my background in marketing and sales support, I experienced a disconnect between formal learning and the kind of performance support tools that we built out of marketing. Both functions supported the same goal, yet we worked in silos.  In this post, Shepherd explains how he is being asked more and more to develop these kinds of support resources rather than full elearning.

This blog will certainly be part of my ongoing education in instructional design and elearning.  I believe I will gain most value from it after I am a bit more seasoned as he challenges the status quo.  I need to get a little more of that status quo under my belt before I can fully appreciate the value of this work.