cognitive psychology / computing

The definition of metacognitive skills in education [Manda]; and some personal reflections on scholarly writing

On 05/09/2011, in higher education, K-12 related, learning theories, memory, metacognition / metacognitive skills, student-related, writing, by Daniel Christian

The definition of metacognitive skills in education — ehow.com by Gilbert Manda

Excerpt:

Controlling your thinking processes and becoming more aware of your learning is called metacognition. Metacognitive skills make you aware of your own knowledge, the ability to understand, control and manipulate your own cognitive process. In short, you learn to learn. It is important to know the process of learning and understanding your own approach to it.

From DSC:
I wish that scholars would write their articles/research findings up in two formats:

1) One format being targeted to other scholars/researchers
and
2) The second format being targeted to those folks outside academia who might benefit from it

This article is not from a scholarly journal, but it references some scholarly sources such as those from Purdue University and Midwestern State University; however, it is much more readable and useful to me — and probably to many others. It is written in language that more people can understand and work with. Academia needs to start being more relevant like this — speaking to audiences outside ourselves; especially when we are asking them to pay many of the bills.

How can we help students develop better metacognitive skills? What strategies can we offer while they are studying a particular lesson?

Tagged with: cognitive psychology / computing • higher education • K-12 • learning and study strategies • learning theories • memory • metacognition • scholarly writing • student-related • writing

Metacognition: A Literature Review Research Report [Lai, April 2011]

On 04/25/2011, in learning, learning theories, metacognition / metacognitive skills, strategy, student teaching/teacher education, student-related, by Daniel Christian

Metacognition: A Literature Review Research Report — from Pearson by Emily Lai, April 2011

Abstract

Metacognition is defined most simply as “thinking about thinking.” Metacognition consists of two components: knowledge and regulation. Metacognitive knowledge includes knowledge about oneself as a learner and the factors that might impact performance, knowledge about strategies, and knowledge about when and why to use strategies. Metacognitive regulation is the monitoring of one’s cognition and includes planning activities, awareness of comprehension and task performance, and evaluation of the efficacy of monitoring processes and strategies. Recent research suggests that young children are capable of rudimentary forms of metacognitive thought, particularly after the age of 3. Although individual developmental models vary, most postulate massive improvements in metacognition during the first 6 years of life. Metacognition also improves with appropriate instruction, with empirical evidence supporting the notion that students can be taught to reflect on their own thinking. Assessment of metacognition is challenging for a number of reasons: (a) metacognition is a complex construct; (b) it is not directly observable; (c) it may be confounded with both verbal ability and working memory capacity; and (d) existing measures tend to be narrow in focus and decontextualized from in-school learning. Recommendations for teaching and assessing metacognition are made.

Keywords: metacognition, self-regulated learning

From DSC:
Also see Chapter 12 of:

Ormrod, J. E. (2008). Human learning (5th ed.). Upper Saddle River, NJ: Pearson. ISBN 9780132327497.

…which has excellent further resources, additional literature reviews, learning strategies.

Tagged with: cognition • cognitive psychology / computing • learning • learning and study strategies • learning theories • metacognition • strategy • student teaching/teacher education • student-related

Good illustration of why I say “easy is hard”

On 04/16/2011, in digital audio, engagement / engaging students, graphics, human-computer interaction (HCI), interaction design, interactivity, interface design, learning theories, memory, usability, user experience (UX), user interface design, by Daniel Christian

Why Angry Birds is so successful and popular: A cognitive teardown of the user experience — from Pulse > UX by Charles L. Mauro

Excerpt:

Simple yet engaging interaction concept: This seems an obvious point, but few realize that a simple interaction model need not be, and rarely is, procedurally simple. Simplification means once users have a relatively brief period of experience with the software, their mental model of how the interface behaves is well formed and fully embedded. This is known technically as schema formation. In truly great user interfaces, this critical bit of skill acquisition takes place during a specific use cycle known as the First User Experience or FUE. When users are able to construct a robust schema quickly, they routinely rate the user interface as “simple”. However, simple does not equal engaging. It is possible to create a user interface solution that is initially perceived by users as simple. However, the challenge is to create a desire by users to continue interaction with a system over time, what we call user “engagement”.

What makes a user interface engaging is adding more detail to the user’s mental model at just the right time. Angry Birds’ simple interaction model is easy to learn because it allows the user to quickly develop a mental model of the game’s interaction methodology, core strategy and scoring processes. It is engaging, in fact addictive, due to the carefully scripted expansion of the user’s mental model of the strategy component and incremental increases in problem/solution methodology. These little birds are packed with clever behaviors that expand the user’s mental model at just the point when game-level complexity is increased. The process of creating simple, engaging interaction models turns out to be exceedingly complex. Most groups developing software today think expansion of the user’s mental model is for the birds. Not necessarily so.

Other key items discussed:

Simple yet engaging interaction concept

Cleverly managed response time

Short-term memory management

Mystery

How things sound

How things look

Measuring that which some say cannot be measured

From DSC:
What Apple is able to do with many of their hardware and software products, what Charles describes here with Angry Birds, what Steelcase did with their Media:Scape product’s puck — and other examples — point out that creating something that is “easy” is actually quite hard.

Tagged with: cognition • cognitive psychology / computing • digital audio • engagement • graphic design • human-computer interaction (HCI) • interaction design • interactivity • interface design • learning theories • memory • scaffolding • usability • user experience • user interface design • UX

A $55 million atlas of the human brain

On 04/13/2011, in biology, learning theories, by Daniel Christian

A $55 million atlas of the human brain — from cnet.com by Elizabeth Armstrong Moore

This thin section of brain has been treated with a pink neuropathological stain
to show fine anatomic detail. Credit: Allen Institute for Brain Science.

…so it comes as little surprise that the Seattle-based Allen Institute for Brain Science announced this week a world first: a highly detailed guide to both the anatomy and the genes of the human brain that includes 1,000 anatomical landmarks backed by 100 million data points measuring the strength of gene activity at each landmark. The cost of its creation? $55 million.

Tagged with: biology • cognition • cognitive psychology / computing • learning theories

What is cognitive load? [Malamed]

On 04/07/2011, in digital learning, elearning, instructional design, learning theories, memory, online learning, by Daniel Christian

What is cognitive load? — from theelearningcoach.com by Connie Malamed

What causes too much demand on working memory? One cause comes from an abundance of novel information. More information than the person can process. But high cognitive load is also strongly influenced by the number of elements in working memory that interact with each other. Often, complex learning is based on interacting elements that must be processed simultaneously. For example, learning to drive involves understanding how several elements simultaneously interact, such as considering the pressure required to brake, the amount to turn the steering wheel and making adjustments for weather conditions and traffic.

Working memory is vulnerable to overload…

Tagged with: cognition • cognitive psychology / computing • e-learning • learning theories • memory • online learning

Quote from “Rethinking (e)learning: A manifesto for connected generations” [Sims, 2008]

On 03/17/2011, in change, elearning, generational differences, learning theories, online learning, teaching & learning, by Daniel Christian

Quote/excerpt from Sims (2008) paper entitled, “Rethinking (e)learning: A manifesto for connected generations”:

Advances in theories of human memory parallel, and perhaps depend on, advances in technology… The information processing approach has been an important source of models and ideas, but the fate of its predecessors should serve to keep us humble concerning its eventual success… Unless today’s technology has somehow reached its ultimate development, and we can be certain it has not, then we have not reached the ultimate metaphor for the human mind either. (Roediger, 1980, p. 244 as cited in Sims, 2008)

Roediger’s remarks remind us that, not only are we in a constant state of change and development, but also that there are inherent risks in arguing that we know what there is to know about teaching, learning, and e-learning. Therefore, without undermining the importance of understanding the dynamics of human learning, this article adopts the position that it is untimely to let the e of e-learning disappear, because without that e we might lose sight of the value digital technology provides, especially through social networks, to emergent forms of learning and knowledge construction.

Emergent forms of learning cannot easily be addressed by current instructional design methodologies (Kays & Francis, 2004), which are often teacher-centered. New models and strategies embracing the roles and skills of the teacher, the learner, and the design team are required to address such developments (Sims & Koszalka, 2008). Recent reports by Oblinger (2004), Irlbeck, Kays, Jones, and Sims (2006), and Siemens (2007) posit that these emergent technologies and interactions have opened doorways to new ways of learning and that these deserve new models of thinking about the very essence of the teaching and learning dynamic. While this article accepts that e is becoming more mainstream and part of the infrastructure of developed nations, the real question is whether the models we use to create learning environments and measure outcomes retain their relevance in a generation in which technology is the medium of communication for many.

Sims, R. (2008). Rethinking (e)learning: a manifesto for connected generations. Distance Education (29) 2. August 2008, 153–164.

Tagged with: change • cognition • cognitive psychology / computing • Connectivism • e-learning • generational differences • learning theories • online learning • teaching & learning

Some graphics I created: Learning theories; Instructional Design goals; love of learning

On 03/12/2011, in 21st century, 24x7x365 access, adult learning, Daniel S. Christian, graphics, instructional design, learning, learning ecosystem, learning theories, love of learning, pedagogy, personalized/customized learning, by Daniel Christian

If viewing these graphics via the Learning Ecosystems website/blog:
You may need to right-click and download the graphics to see them in their entirety.

Tagged with: 1:1 • 21st century • cognitive psychology / computing • Connectivism • customized learning • Daniel S. Christian • Graphics • instructional design • learning theories • love of learning • pedagogy • personalized learning • social learning

How technology wires the learning brain

On 03/11/2011, in internet, technology (general), by Daniel Christian

How technology wires the learning brain –– from Mind/Shift

Tagged with: cognition • cognitive psychology / computing • internet • technology (general)

The facts on higher order thinking

On 03/10/2011, in adjunct faculty, biology, faculty/staff, higher education, instructional design, learning theories, pedagogy, teaching & learning, by Daniel Christian

The facts on higher order thinking — from Faculty Focus by Maryellen Weimer, PhD

I just read a study that pretty much blew my socks off. An article highlighting the details will appear in the March issue of The Teaching Professor. I’ll give you the nutshell version here. The researchers were interested in finding out if there was empirical evidence to support the frequent criticism that introductory courses are fact filled with little content that challenges higher order thinking. Beyond anecdotal evidence, this research team didn’t find much empirical documentation so, being biologists, they decided to look at introductory-level biology courses.

Tagged with: adjunct faculty • biology • cognition • cognitive psychology / computing • faculty-staff • higher education • instructional design • learning theories • pedagogy • teaching & learning

The psychology of e-learning [UK]

On 02/28/2011, in corporate universities / corporate training, learning theories, psychology, training / L&D, vendors, by Daniel Christian

Tagged with: cognitive psychology / computing • corporate training / universities • learning theories • psychology • training • vendors

Tagged with: cognition • cognitive psychology / computing • learning and study strategies • student-related

What’s the optimum length of an online video?

On 02/18/2011, in digital video, India, pedagogy, by Daniel Christian

What’s the optimum length of an online video? — from Digital Inspiration by Amit Agarwal

Tagged with: cognitive psychology / computing • digital video • India • pedagogy

What Instructional Designers can learn from IBM’s Watson

On 02/17/2011, in instructional design, learning, learning theories, by Daniel Christian

What Instructional Designers can learn from IBM’s Watson — from kaplaneduneering.com by Karl Kapp

Excerpt:

Enter instructional design. What happens in a typically designed program? The designer creates abstracted bulleted lists or items the learner must know and apply to a situation and then, once or twice in the course of the class/e-learning event, etc. The learner is given an example. One or two examples at the most. Not enough to develop pattern recognition or to create an internal construct of how to deal with a particular situation.

That’s all wrong. Instead of giving learners abstractions of concepts or lists of rules, we need to give them examples, not one or two examples but dozens and dozens of examples.

We know expertise comes from experience with situations that build a generalization by the expert who then compares a current situation with past situations to decide how to problem-solve. Designers of instruction can create “learning experiences” using case studies, simulations, etc. to immerse the learner in dozens of similar (but not exactly the same) situations so the learner can recognize situations, not-by-rules, but by experience.

We can’t teach every rule in compliance training, or every answer to a customer’s objection in sales training or every combination of troubleshooting customer problems but we can provide example after example after example that can help learners develop the ability to recognize and address situations and the right response.

So, next time you develop instruction, provide examples, not one or two but dozens.

From DSC:
This makes sense also from a mental rehearsal standpoint — helping move things to long term memory.

Tagged with: cognitive psychology / computing • instructional design • learning • learning theories

Focusing on strengths; following one’s passions; creating Win/Win situations; other reflections re: STEM

On 02/16/2011, in economics, education reform, love of learning, passions, personalized/customized learning, STEAM-related, by Daniel Christian

From DSC:
The first portions of Kelly Tenkely’s solid blog posting — 17 ways to meet individual learning needs in the math classroom — stirred up some thoughts from a training-related session I was in earlier today. Kelly writes:

Differentiating instruction can be challenging. Student’s educational strengths and weaknesses can be widely varied, making it a difficult task to meet each student’s needs in any given lesson. Math is one such subject area where student skill levels can be very different.

…

For most students, math takes a lot of practice. Unfortunately, the students who need the most practice are the most reluctant to do so because they haven’t been successful in the past. Many of these students have convinced themselves, through negative self-talk, that “I’m just not good at math.” What is a teacher to do with such a mix of skill and comfort levels in the math classroom?

Though there could be several lines of thought that I could pursue here — such as the good and bad sides of self-efficacy, personalized/customized learning, 1:1 initiatives, other — my thought process was most influenced from a training session I had attended earlier today. That session featured a video from Marcus Buckingham’s short-film series entitled Trombone Player Wanted.

Marcus asserts that there are several myths that many of us grow up with (such as our personalities change as we grow; we grow most in the areas of our weaknesses; our teams don’t need us to show up with our strengths, instead they need us to do ____). Marcus asserts that we should identify and develop our strengths (and manage around our weaknesses) — as we seek to create Win/Win situations. This perspective is consistent with my economics training that states that everyone benefits when each one of us does what we do best.

This made me reflect on the massive, systemic pressure most of our current educational environments/policies/curriculums put on students to get everyone to be at the same place. It seems like our systems stress conformity — in the goal of “level-setting” everyone.

This made me wonder:

Why are STEM-related topics the most important topics being focused on by legislatures and policy-making bodies?
Why do we attempt to make every child pursue a STEM-related field?
Why do we assume that students should be interested in a STEM-related topic/course?
What about all of the other gifts that students bring to the table?
What if a child could pursue their own passion(s) — STEM-related or not?

I realize that there are basic skills that are very helpful for all adults — balancing a checkbook, being able to read and write, and many other skills. However, the question I started pondering today was…”At what point should we call it quits on a subject area — say that’s good enough — and then allow the students to pursue their individual strengths (rather than try to hammer out performance increases in an area they will rarely use)?”

Examples:

Does a First Violinist in an orchestra need to know everything about Chemistry?
(If not, what should they know? What is the minimum level that they should know for operations in the “real world” — really — and why?)
Conversely, does a Chemist need to know everything about Music?
(If not, what should they know? What is the minimum level that they should know for operations in the “real world” — really — and why?)
Does a Computer Systems Analyst need to know everything about Biology?
(If not, what should they know? What is the minimum level that they should know for operations in the “real world” — really — and why?)
Does a Biologist need to know everything about Computer Science?
(If not, what should they know? What is the minimum level that they should know for operations in the “real world” — really — and why?)
Etc.

Tagged with: cognitive psychology / computing • customized learning • economics/business • education reform • love of learning • passions • personalized learning • STEM

Infographic: How does the brain retain information?

On 02/15/2011, in biology, by Daniel Christian

Infographic: How does the brain retain information? — from MindFlash

Tagged with: biology • cognition • cognitive psychology / computing

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