Implications of Learning Theories on Instructional Design — from by Jon-Erik Oleyar-Reynolds
Are you interested in becoming an Instructional Designer? Or are you just starting out in the world of learning theories? The focus of this article is to inform the reader of 3 unique learning theories while discussing the implications they have had in the field of Instructional Design (ID).


Behaviorist Learning Theory
Behavioral learning theory can be summarized as learning that occurs through the behavioral response to environmentally sourced stimuli. The foundation of this theory is built upon assumptions that “have little regard for the cognitive processing of the learner involved in the task”.

The focus of behavioral learning theory resides in the use of reinforcement to drive behavior. Instructional Design can benefit from the use of reinforcement as a means to train learners to complete instructional objectives that are presented to them.

Cognitive Learning Theory
The primary focus of learning is on the development of knowledge by the creation of schemas. Schemas are like catalogs of information that can be used to identify concepts or experiences through a complex set of relationships that are connected to one another. In short, the catalogs act like a database of knowledge for the learner. 2 prominent theories that will be discussed are Gestalt theory and information processing theory; these 2 have paved the way for cognitivism and its impact on the field of Instructional Design.

Information processing theory further supports cognitive learning theory. Similar to Gestalt theory, the focus of learning is on the individual. The processing of information by the learner is similar to the way a computer processes information. The memory system is broken into 3 stages based on this approach:

  • Sensory memory
  • Working memory
  • Long-term memory

…the working memory may require more rehearsal to establish a clear connection to the concept and store it in long-term.

One of the most widely used strategies could arguably be a rehearsal. The expression “practice makes perfect” may seem cliché, but it does fit very well when discussing cognition and development. As one rehearses, the working memory is exercised.

While working memory has a limit of 7 (plus or minus 2), creating a chunk of information increases the amount that can be worked with.

Instructional Design shifted in the presence of cognitivism and includes a more system-like design approach with a focus on the learners.


Social Learning Theory
Social learning theory focuses on the impact of learning based on factors related to the social environment. In other words, learning occurs in the context of a social situation that the learner is placed in.

Think of the expression “perhaps it rubbed off on me”. This has a direct relationship to social learning theory. Self-efficacy can be influenced by the design of lessons that allow for learners to view others of similar ability succeeding at instructional tasks. This could be achieved in a number of creative ways, but generally is most effective in collaborative activities where learners work in small groups. Overall, self-efficacy is the belief that one can be successful at particular tasks.

Collaborative learning groups and the use of peer review are widely used in many settings in which learning occurs.



From DSC:
I wanted to briefly relay an example that relates to the Cognitive Learning/Processing Theory — and more specifically to a concept known as Cognitive Load.  The other day I was sitting at the kitchen table, trying to read an interesting blog posting. But at the very same time, the radio was (loudly) relaying an item re: Virtual Reality (VR) — which also caught my ear and interest.

Which “channel” do I focus on? My visual channel or my auditory channel?

For me, I can’t do both well — perhaps some people can, but our visual and auditory channels can only handle so much at one time. Both channels request our attention and processing resources. I ended up getting up and shutting off the radio so that I could continue reading the blog posting. But for me, I think of it like a traffic jam. There are only so many cars that can simultaneously get through that busy highway that leads downtown.

So another application of this is that it’s helpful NOT to have a lot of auditory information going on at the same time as a lot of visual information. If you have PowerPoint slides, use graphics, photos, and/or graphs and use your audio voiceover to speak to them…but don’t list a long paragraph of text and then simply read that text and then also ask the learner to absorb other visual information at the same time. 




A Microlearning Framework — from and Pablo Navarro
This infographic is based on the experience of different clients from different industries in different training programs.


From DSC:
I thought this was a solid infographic and should prove to be useful for Instructional Designers, Faculty Members, and/or for Corporate Trainers as well. 

I might also consider adding a “Gotcha!” piece first — even before the welcome piece — in order to get the learner’s attention and to immediately answer the WHY question. WHY is this topic important and relevant to me? When topics are relevant to people, they care and engage a whole lot more with the content that’s about to be presented to them. Ideally, such a piece would stir some curiosity as well.





Why Professors Doubt Education Research — from by Jeff Young


You found that professors really care about their teaching, and yet they are skeptical of education research. It sounds like a lot of people ended up teaching the way that they had been taught, or the way that they felt good as a student in classes they had had.

That’s right. People sometimes ignore the research precisely because they care about teaching. Different faculty arrive at the point where they’re teaching college students from wildly different experiences of their own. Some have wanted since they were small children to be professors at a university, and some fell into it later in a career.

For faculty who think that research is a good way to learn how to teach, they will devour the literature on learning sciences. They’ll reach out to experts across a number of disciplines and within their own discipline to try and learn what the best way to teach is

For faculty who believe that teaching is an art, that it is just something that you develop with experience and time, that you can’t learn from a book, you need to learn by doing more or learn from your students, no amount of exposure to learning science research is going to disrupt their sense that this is something they learn by doing, or that they need to follow their gut on.

Do you have any advice for someone who wants to change someone’s mind to either adopt or consider more of this evidence-based research?

People can always change their perspective. If you’re trying to communicate the value of a technology or an approach, or even of learning science or education research as a field, you have to start with the person you’re speaking to. They may come to that conversation with a sense of, “I know that people get PhDs in education. People get PhDs in curriculum design, and I’ve never even taken a class where we’ve talked about curriculum design. I would like to know what they know.”

Then there are people who will say, “I’ve been teaching since I was a graduate student. My students are very happy with the teaching. I feel pretty good about my teaching. I understand that you have a PhD in curriculum design, but I don’t really need that.”

You need to approach those two different faculty members differently, understanding that there are some people who are interested in hearing about evidence-based practices, and just pointing them towards the resources is great.

Excerpt from the question:
What about your own teaching? I’m curious. Are you someone that tries different techniques that are based on research?

There is so much literature, and there are so many right ways, and there are so many recommendations that incorporating all of them into your practice at the same time is literally impossible. Many of them are contradictory. You have to choose a suite that you’re adhering to, because you can’t do the others if you’re doing these. Trying to embody best practices while teaching is really complex. It’s a skillset that you develop. You develop with time, and instruction, and you can master, but you’re always going to have to continue to perfect it.



Also see:

Personalized Faculty Development: Engaging Networks, Empowering Individuals — from by Jill Leafstedt


During the meeting, I chose to spend my time focused solely on sessions in the Faculty Development and Engagement track. My goal: return to my home campus energized and ready to tackle the age-old problem of how to move faculty from being content experts into dynamic educators.

Luckily for me, I was not the only one looking for this inspiration. The faculty development sessions were packed with people trying to answer questions such as, “Why don’t faculty want help?” or “Why don’t faculty attend my workshops?” On the whole, the sessions reaffirmed my belief that faculty development does not happen in a workshop, nor does it happen through training. Improving teaching is a long, messy, reflective process that must be approached from multiple angles with many entry points.

Sound challenging? It is, but there is reason to be hopeful; our colleagues are working hard to find and share answers. Two themes came through loud and clear from the sessions I attended. First, meet faculty where they are. Don’t expect them to come to you ready to learn; go to them and start where they are. Second, build networks for ongoing learning.


From DSC:
Both of the above articles present a HUGE issue in terms of improving the level of teaching and learning. Both articles seem to be saying that anyone interested in really improving the teaching and learning that’s going on needs to meet with each individual faculty member in order to meet them where they are at. When you have hundreds of faculty members plus an over-flowing job plate that’s asking you to wear numerous hats, that’s a very tall order indeed.





Who’s Teaching the Teachers? — from by Elizabeth Alsop

Excerpts (emphasis DSC):

Last fall, the academic career coach Jennifer Polk conducted an informal Twitter poll: How many of you, she asked her followers, received any meaningful pedagogical training during graduate school?

Replies ranged from the encouraging to the mostly dispiriting, with one doctoral candidate noting that the only training the program had offered took the form of “trial by fire.” Just 19 percent of the 2,248 respondents said they had received at least “decent” training — a number that, however unscientific, is also symptomatic.

This statistic reflects something that many of us could confirm firsthand: Teaching remains undervalued in the context of doctoral training and the profession at large. The result, by this anecdotal reckoning, is that less than one-fifth of aspiring college teachers are effectively taught how to teach.

The American Association of University Professors estimates that over 70 percent of all faculty positions are non-tenure-track, so these are teaching, not research, appointments.

Ennobling as such rhetorical constructs may be, they obscure not only the very real labor of teaching, but the fact that teaching is teachable: something that results not from divine, Dead Poets Society-like bursts of inspiration, but, as in other career fields, from study, apprenticeship, and practice. There are any number of books — including Ken Bain’s What the Best College Teachers Do, John Bean’s Engaging Ideas, and Cathy Davidson’s The New Education — that offer excellent advice for college instructors.

It’s also worth noting that the resistance to addressing pedagogy in graduate education may be practical, as well as philosophical: Teaching someone to teach is hard. Like writing, teaching is a craft, learned not just in a single class, practicum, or workshop. Rather, it’s a recursive process, developed through trial and error — and yes, by “fire” — but also through conversation with others: a mentor, a cohort, your peers.





PD is getting so much better!! — from by Jennifer Gonzalez




1. Unconferences
2. Intentional professional learning communities (PLCs)
3. Choice Boards
4. Personal Action Plans
5. Voluntary Piloting
6. Peer Observation
7. Microcredentials
8. Blended Learning
9. Lab Classrooms




From DSC:
Why aren’t we further along with lecture recording within K-12 classrooms?

That is, I as a parent — or much better yet, our kids themselves who are still in K-12 — should be able to go online and access whatever talks/lectures/presentations were given on a particular day. When our daughter is sick and misses several days, wouldn’t it be great for her to be able to go out and see what she missed? Even if we had the time and/or the energy to do so (which we don’t), my wife and I can’t present this content to her very well. We would likely explain things differently — and perhaps incorrectly — thus, potentially muddying the waters and causing more confusion for our daughter.

There should be entry level recording studios — such as the One Button Studio from Penn State University — in each K-12 school for teachers to record their presentations. At the end of each day, the teacher could put a checkbox next to what he/she was able to cover that day. (No rushing intended here — as education is enough of a run-away train often times!) That material would then be made visible/available on that day as links on an online-based calendar. Administrators should pay teachers extra money in the summer times to record these presentations.

Also, students could use these studios to practice their presentation and communication skills. The process is quick and easy:





I’d like to see an option — ideally via a brief voice-driven Q&A at the start of each session — that would ask the person where they wanted to put the recording when it was done: To a thumb drive, to a previously assigned storage area out on the cloud/Internet, or to both destinations?

Providing automatically generated close captioning would be a great feature here as well, especially for English as a Second Language (ESL) students.




From DSC:
After seeing the article entitled, “Scientists Are Turning Alexa into an Automated Lab Helper,” I began to wonder…might Alexa be a tool to periodically schedule & provide practice tests & distributed practice on content? In the future, will there be “learning bots” that a learner can employ to do such self-testing and/or distributed practice?



From page 45 of the PDF available here:


Might Alexa be a tool to periodically schedule/provide practice tests & distributed practice on content?




Deeper Thinking about Active Learning — from by Maryellen Weimer

Excerpts (emphasis DSC):

I keep worrying that we’re missing the boat with active learning. Here’s why. First, active learning isn’t about activity for the sake of activity. I fear we’ve gotten too fixated on the activity and aren’t as focused as we should be on the learning. We’re still obsessed with collecting teaching techniques—all those strategies, gimmicks, approaches, and things we can do to get students engaged. But what kind of engagement does the activity promote? Does it pique student interest, make them think, result in learning, and cultivate a desire to know more? Or is it more about keeping basically bored students busy?

Teaching techniques are an essential part of any active learning endeavor. But they aren’t the center or the most important part of student learning experiences. Techniques provide the framework, the structure, the context. What really matters is what we put in the structure—what students are thinking about and sharing when they’re pairing.

Larry recommends selecting things that confront students with their ignorance—so they see clearly what they don’t know, can’t understand, don’t see the reason for, or can’t make work. When you’ve got an artifact in front of you, there’s motivation to deal with it. 


Think for a moment of what happens when you give most any of those millennial students a new electronic device. Usually, without the instructions and no attention to technique, they start playing with it to see how it works. Do they mess up and make mistakes? Do they give up or worry about looking stupid? Does active learning in our courses look anything like this?



From DSC:
This article reminds me of a great conversation that I had with an elderly gentleman a few months ago. He’s still involved with instructional design, after several decades of related work experiences. He said to me that learners need to truly ***engage*** with the content to make it meaningful to them.

And then I read a quote from Robert Greenleaf’s book, On Becoming a Servant Leader (p. 304), that said:

Nothing is meaningful to me until it is related to my own experience.





Personalized Learning Meets AI With Watson Classroom

Personalized Learning Meets AI With Watson Classroom — from by Erin Gohl

Excerpt (emphasis DSC):

Teaching is truly a Herculean challenge. Even the very best teachers can keep only so many of these insights in their heads and make only so many connections between expectations and circumstances. They can be aware of only a fraction of the research on best practices. They have only so much time to collaborate and communicate with the other adults in a particular student’s life to share information and insights. To be the best of themselves, teachers need to have access to a warehouse of information, a research assistant to mine best practices, note takers to gather and record information on each student, a statistician to gauge effective practices, and someone to collaborate with to distill the next best step with each student. In recent years, a plethora of vendors have developed software solutions that promise to simplify this process and give schools and teachers the answers to understand and address the individual needs of each student. One of the most promising, which I recently had a chance to learn about, is IBM’s Watson Classroom.

IBM is clear about what makes Watson different than existing solutions. First of all, it is a cognitive partner; not a solution. Secondly, it does not require proprietary or additional assessments, curriculum, or content. It uses whatever a district has in place. But it goes beyond the performance of tiering difficulty, pace, and reading level that is now standard fare for the solutions promising individualized, adaptive and personalized learning. Watson takes the stew of data from existing systems (including assessments, attendance records, available accommodations), adds the ability to infer meaning from written reports, and is able to connect the quality of the result to the approach that was taken. And then adjust the next recommendation based on what was learned. It is artificial intelligence (AI) brought to education that goes far beyond the adaptive learning technologies of today.

Watson Classroom is currently being piloted in 12 school districts across the country. In those classrooms, Watson Classroom is utilizing cutting-edge computing power to give teachers a full range of support to be the best versions of themselves. Watson is facilitating the kind of education the great teachers strive for every day–one where learning is truly personalized for each and every student. Bringing the power of big data to the interactions between students and teachers can help assure that every student reaches beyond our expectations to achieve their full potential.




Learn with Google AI: Making ML education available to everyone — from


To help everyone understand how AI can solve challenging problems, we’ve created a resource called Learn with Google AI. This site provides ways to learn about core ML concepts, develop and hone your ML skills, and apply ML to real-world problems. From deep learning experts looking for advanced tutorials and materials on TensorFlow, to “curious cats” who want to take their first steps with AI, anyone looking for educational content from ML experts at Google can find it here.

Learn with Google AI also features a new, free course called Machine Learning Crash Course (MLCC). The course provides exercises, interactive visualizations, and instructional videos that anyone can use to learn and practice ML concepts.



7 Ways Chatbots and AI are Disrupting HR — from
Enterprises are embracing AI for automating human resources


Chatbots and AI have become household names and enterprises are taking notice. According to a recent Forrester survey, roughly “85% of customer interactions within an enterprise will be with software robots in five years’ time” and “87% of CEOs are looking to expand their AI workforce” using AI bots.

In an effort to drive increased labor efficiencies, reduce costs, and deliver better customer/employee experiences enterprises are quickly introducing AI, machine learning, and natural language understanding as core elements of their digital transformation strategy in 2018.

Human resources (HR) is one area ripe for intelligent automation within an enterprise. AI-powered bots for HR are able to streamline and personalize the HR process across seasonal, temporary, part-time, and full-time employees.

There are 7 ways in which enterprises can use HR bots to drive increased labors efficiencies, reduced costs, and better employee experiences:

  1. Recruitment
  2. Onboarding
  3. Company Policy FAQs
  4. Employee Training
  5. Common Questions
  6. Benefits Enrollment
  7. Annual Self-Assessment/Reviews


From DSC:
Again, this article paint a bit too rosy of a picture for me re: the use of AI and HR, especially in regards to recruiting employees.




Implementation of AI into eLearning. Interview with Christopher Pappas — from by Darya Tarliuk


Every day we hear more and more about the impact that Artificial Intelligence gains in every sphere of our life. In order to discover how AI implementation is going to change the eLearning we decided to ask Christopher Pappas to share his views and find out what he thinks about it. Christopher is an experienced eLearning specialist and the Founder of the eLearning Industry’s Network.

How to get ready preparing course materials now, while considering the future impact of AI?
Christopher: Regardless of whether you plan to adopt an AI system as soon as they’re available to the mass market or you opt to hold off (and let others work out the glitches), infrastructure is key. You can prepare your course materials now by developing course catalogs, microlearning online training repositories, and personalized online training paths that fall into the AI framework. For example, the AI system can easily recommend existing resources based on a learners’ assessment scores or job duties. All of the building blocks are in place, allowing the system to focus on content delivery and data analysis.




Can You Trust Intelligent Virtual Assistants? — from by Gary Audin
From malicious hackers to accidental voice recordings, data processed through virtual assistants may open you to security and privacy risks.


Did you know that with such digital assistants your voice data is sent to the cloud or another remote location for processing? Is it safe to talk in front of your TV remote? Are you putting your business data at risk of being compromised by asking Alexa to start your meeting?





Thanks, Robots! Now These Four Non-Tech Job Skills Are In Demand — from by Christian Madsbjerg
The more we rely on AI and machine learning, the more work we need social scientists and humanities experts to do.


Automation isn’t a simple struggle between people and technology, with the two sides competing for jobs. The more we rely on robots, artificial intelligence (AI), and machine learning, the clearer it’s become just how much we need social scientists and humanities experts–not the reverse.

These four skills in particular are all unique to us humans, and will arguably rise in value in the coming years, as more and more companies realize they need the best of both worlds to unleash the potential from both humans and machines.






Why Students Forget—and What You Can Do About It — from by Youki Terada
Our brains are wired to forget, but there are research-backed strategies you can use to make your teaching stick.


5 Teacher Strategies
When students learn a new piece of information, they make new synaptic connections. Two scientifically based ways to help them retain learning is by making as many connections as possible—typically to other concepts, thus widening the “spiderweb” of neural connections—but also by accessing the memory repeatedly over time.

Which explains why the following learning strategies, all tied to research conducted within the past five years, are so effective:

  1. Peer-to-peer explanations: When students explain what they’ve learned to peers, fading memories are reactivated, strengthened, and consolidated. This strategy not only increases retention but also encourages active learning (Sekeres et al., 2016).
  2. The spacing effect: Instead of covering a topic and then moving on, revisit key ideas throughout the school year. Research shows that students perform better academically when given multiple opportunities to review learned material. For example, teachers can quickly incorporate a brief review of what was covered several weeks earlier into ongoing lessons, or use homework to re-expose students to previous concepts (Carpenter et al., 2012; Kang, 2016).
  3. Frequent practice tests: Akin to regularly reviewing material, giving frequent practice tests can boost long-term retention and, as a bonus, help protect against stress, which often impairs memory performance. Practice tests can be low stakes and ungraded, such as a quick pop quiz at the start of a lesson or a trivia quiz on Kahoot, a popular online game-based learning platform. Breaking down one large high-stakes test into smaller tests over several months is an effective approach (Adesope, Trevisan, & Sundararajan, 2017; Butler, 2010; Karpicke, 2016).
  4. Interleave concepts: Instead of grouping similar problems together, mix them up. Solving problems involves identifying the correct strategy to use and then executing the strategy. When similar problems are grouped together, students don’t have to think about what strategies to use—they automatically apply the same solution over and over. Interleaving forces students to think on their feet, and encodes learning more deeply (Rohrer, 2012; Rohrer, Dedrick, & Stershic, 2015).
  5. Combine text with images: It’s often easier to remember information that’s been presented in different ways, especially if visual aids can help organize information. For example, pairing a list of countries occupied by German forces during World War II with a map of German military expansion can reinforce that lesson. It’s easier to remember what’s been read and seen, instead of either one alone (Carney & Levin, 2002; Bui & McDaniel, 2015).

So even though forgetting starts as soon as learning happens—as Ebbinghaus’s experiments demonstrate—research shows that there are simple and effective strategies to help make learning stick.




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