Clark Quinn wrote an extremely interesting post, X-based learning: sorting out pedagogies and design, on activity based learning. Wanting to see how these different models would interconnect on a mindmap, I started playing with them. That is when I noticed that one of the main difference among them is that some have a known answer and/or the goal is driven by the curriculum, while others have an unknown answer and/or the goal is directed by the learners.
It then struck me that the two primary branches should (could?) be the two main types of knowledge—explicit and tacit:
This seemed to give the mindmap a real purpose, rather than just be formal vs. informal, social vs. self, or active vs. passive. Thus the map goes beyond activity based models:
I'm not sure if I have all the concepts aligned correctly, thus I am wondering what your thoughts are?
Note: I used FreeMind (free of course) to create the mindmap. The document for the mindmap is here - Learning.mm - if you want to download it and revise it. If you have trouble downing it, this is the directory of all the files used to create the mindmap, pictures, and html file - http://nwlink.com/~donclark/learning/pedagogies/. Right click on the file you want to download.
When ADDIE was first handed over to the U.S. Armed Forces it was a linear model. However, after working with it they found that they needed a more dynamic model, so they adapted it. They mastered the tool rather than become a slave to it.
For some reason instructional designers love building ADDIE into a goddess that orders them to build crappy learning platforms. For example, they pronounce that it only builds courses when the real fact is that it tells you to use a course only if a simpler method, such as a performance support tool or OJT, will not work.
From its inception, ADDIE was designed to be a lean, mean, instructional design machine. This leanness has fooled others into thinking that it is a universal model that can build strip malls and skyscrapers. Nope! ADDIE has specific steps that are strictly designed for learning. This has led others to believe that ADDIE is too lean, that it tells them what to do, but not how to to it. But as Merriënboer noted, you can add other components on to it when needed
One of the learning tools that is perhaps most often plugged into ADDIE is Bloom's Taxonomy. And of course one of the criticisms often leveled at ADDIE is that it is associated with outdated learning models. However, this plug and play feature of ADDIE does not mean it hangs on to outdated models, but rather it sheds them and goes scavenging for a better one. While Bloom's Taxonomy has been quite useful in that it has extended learning from simply remembering to more complex cognitive structures, such as analyzing and evaluating, newer models have come along.
There are at least three suitable replacements:
In the mid-nineties, Bloom's taxonomy was updated to reflect a more active form of thinking and is perhaps more accurate (Anderson, Krathwohl, 2001):
This is perhaps the easiest replacement since it is closely related to the original taxonomy, thus most designers will rapidly adapt to it.. What is interesting about the updated version is how it resembles the SOLO Taxonomy (Structure of Observed Learning Outcomes):
The SOLO taxonomy is a means of classifying learning outcomes in terms of their complexity in order to assess students' work in terms of quality (see http://edorigami.edublogs.org/2010/07/17/solo-taxonomy/)
In The Need for a Revision of Bloom’s Taxonomy, Marzano describes six levels:
It is made up of three systems and the Knowledge Domain. The three systems are the Self-System, the Metacognitive System, and the Cognitive System. When faced with the option of starting a new task, the Self-System decides whether to continue the current behavior or engage in the new activity; the Metacognitive System sets goals and keeps track of how well they are being achieved; the Cognitive System processes all the necessary information, and the Knowledge Domain provides the content (see ftp://download.intel.com/education/Common/in/Resources/DEP/skills/marzano.pdf.).
What are your replacements for Bloom's Taxonomy?
Anderson, L.W., and Krathwohl, D.R., eds. (2001). A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives. New York: Longman.
Yes I'm a few days late for David Kelly’s Learning Styles ‘Awareness’ Day, so I hope you forgive me. While most of the recent posts on using learning styles in instructional design have been mainly against using them, I'm going to take a slightly different position—not that we need to cater to each individual style, but that learning styles may be helpful when designing learning platforms.
So far the learning style debate has been mostly two tiles of a different color laid side by side—you are either fer it or agin it—we should assess student learning styles to improve learner outcome verses learning style assessments are unreliable, thus they should not never be used. However, I see the debate more as a mosaic that allows multiple patterns to occur.
Perhaps the most critical study on learning styles is Coffield, Moseley, Hall, and Ecclestone's Learning styles and pedagogy in post-16 learning: A systematic and critical review. While the authors mostly found that matching the form of instruction to individual learning styles did not improve learning, there are some interesting exceptions throughout their paper, for example, on page 67 they write:
“More positively still, Katz (1990) in a quasi-experimental study of 44 occupational therapy students in the US and 50 in Israel, hypothesised that students whose learning styles matched the teaching method would perform better (ie more effectively) and would need less time to study outside class (ie more efficiently). The findings in both countries supported the premise that ‘the better the match is between students' individual characteristics and instructional components, the more effective or efficient the learning program is’ (Katz 1990, 233). But even this conclusion needed to be qualified as it applied only to higher-order cognitive outcomes and not to basic knowledge.”
So in search of a good paper on using learning styles in higher order cognitive skills I came across this paper, An Investigation into the Learning Styles and Self-Regulated Learning Strategies for Computer Science Students, by Alharbi, Paul, Henskens, and Hannaford. For their study they use the Felder-Silverman Learning Style model that uses four dimensions:
The study was not about assessing the learners' styles and then catering to their preferred styles but rather assessing them on the above dimensions and then testing them on a core computer science course to see how each dimension performed. The author's correlation analysis showed that while three of the dimensions (Input, Processing, and Understanding) were not statistically significant; the Perception dimension had a significant impact on the students' results in the examination, with the t-tests confirming that sensing students were significantly outperformed by intuitive students.
The authors note that the majority of students in the study (65.8%) were sensing learners, with 39.5% having a moderate or strong preference to that learning style. However, 21.0% of students have a moderate or strong preference to intuitive learning over sensing learning. This suggests that there is a need for learning material for both types of learners, but the greater emphasis should be placed on reducing abstraction to better meet the requirements of the sensing learners, especially when it is seen that intuitive learners performed significantly better on the midterm examination.
While it was just one study, it did seem to follow the patterns of a couple of studies discussed in the Coffield et al. paper:
The authors write that instructors often tend to use more intuitive type instructions (abstract concepts, theories, etc.), rather than the more sensing types of instruction (such as facts, details, and problem-solving methods). While this might at first seem laudable in that they are trying to teach the learners to operate in a more complex world that seeks innovation and new ideas when solving problem, learners often need a basic scaffold of facts and basic problem-solving methods. Yes, some of the learning platforms that we might be providing are for complex environments that do not have proven problem-solving methods, but the least we should do is provide them with some simple facts and heuristics. For example, branching scenarios are often used in elearning platforms but we expect them to jump right in and guess their way through the activity.
An example of this is that one of the myths in our profession is that ISD or ADDIE was only designed for classrooms and there is a lack of rules for when classroom training should be used (we use it more often than it is needed), but the Armed Forces came up with a simple heuristic back in the 1980s - ADDIE Does More Than Classrooms. Thus this heuristic should be given to learners studying to be instructional/learning designers BEFORE they attempt to do a branching scenario or similar activity.
In the Coffield et al. paper they note that the various theories of learning styles can be placed on a continuum (pp 9-10) as shown in the chart below. The ones on the left are considered more constitutionally fixed styles (innate) while the ones to the right are considered more flexible:
The Sensing and Intuitive learning styles discussed above fall on the right side of the continuum, thus depending upon the learner's knowledge and skills, the subject or task, and/or the type of instruction, a learner could fall on either the sensing or intuitive side of the dimension (however, from the studies noted in this post, the majority seem to fall on the sensing side).
One of the styles that fall strongly on the left side of the continuum is VAK (Visual, Auditory, and Kinesthetic), which poses a conundrum in learning styles.
In an interesting study, Visual Learners Convert Words to Pictures, functional magnetic resonance imaging (fMRI) technology was used to scan subjects' brains while they performed a novel psychological task involving pictures that could be easily named and words that could be easily imagined. They found that the more strongly an individual identified with a visual cognitive style, the more they activated the visual cortex when reading words. Conversely, fMRI scans also showed that the more strongly an individual identified with a verbal cognitive style, the more activity they exhibited in a region of the brain associated with phonological cognition when faced with a picture.
Thus it seems our tendency to identify with being a visual or verbal learning is hardwired in us, however, visual preference does not always equal spatial aptitude (Ruth Clark & Chopeta Lyons, Graphics for Learning, 2004). Spatial aptitude is the ability to generate and retrain spatial images as well as transform images in ways that support visual reasoning.
Thus the conundrum—we may identify with being a visual or verbal learner (indeed, we may even be wired for one or the other), but it does not mean we are a good visual or verbal learner! Thus if we know what style our preference is, we need to think twice if we attempt to train others or learn something on our own if the learning method matches our style.
However, Clark and Lyons give us a few rules to follow:
1. Learners with low prior knowledge need graphics that are congruent with text (and preferably the text should be audio to prevent cognitive overload).
2. Learners with high prior knowledge need only words or visuals; not both, but one study did suggest that the diagram alone was best.
3. Encourage visual literacy. Some learners tend to view visuals as fluff, thus they tend to ignore them even though they might be their best means of learning. One method of encouraging their use is to use a visual and ask a question that can only be derived by examining the visual.
Sensing and Intuitive Learning Styles, The Continuum of Learning Styles, and The VAK Conundrum are my three tiles in the mosaic of learning styles. What are yours?
I had an interesting discussion with Clark Quinn on using Kirkpatrick's model in learning processes other than courses. Clark argues that use of Kirkpatrick’s model is only for courses because training is the dominant discussion on their web site. I disagree and wonder if perhaps it is more of a “not invented here” hesitation because advancing concepts to the next level has often been a primary means of moving forward. It might sound good to forget an old model, but if you do not help people relearn, then their old concepts have a nasty habit of reappearing. In addition, training is far more than just courses. So after some heavy reflection I did a rewrite on my Kirkpatrick web page and have listed some of the highlights below.
While some mistakenly assume the four levels are only for training processes, the model can be used for other learning processes. For example, the Human Resource Development (HRD) profession is concerned with not only helping to develop formal learning, such as training, but other forms, such as informal learning, development, and education (Nadler, 1984). Their handbook, edited by one of the founders of HRD, Leonard Nadler, uses Kirkpatrick's four levels as one of their main evaluation models.
Kirkpatrick himself wrote, “These objectives [referring to his article] will be related to in-house classroom programs, one of the most common forms of training. Many of the principles and procedures applies to all kinds of training activities, such as performance review, participation in outside programs, programmed instruction, and the reading of selected books” (Craig, 1996, p294).
Kirkpatrick's levels work across various learning processes because they hit the four primary points in the learning/performance process... but he did get a few things wrong:
Reaction is not a good measurement as studies have shown. For example, a study shows a Century 21 trainer with some of the lowest reaction scores was responsible for the highest performance outcomes in post-training (Results) as measured by his graduates' productivity. This is not just an isolated incident—in study after study the evidence shows very little correlation between Reaction evaluations and how well people actually perform when they return to their job (Boehle, 2006).
When a learner goes through a learning process, such as an elearning course, informal learning episode, or using a job performance aid, the learner has to make a decision as to whether he or she will pay attention to it. If the goal or task is judged as important and doable, then the learner is normally motivated to engage in it (Markus, Ruvolo, 1990). However, if the task is presented as low-relevance or there is a low probability of success, then a negative effect is generated and motivation for task engagement is low. Thus it is more about motivation rather than reaction.
As Gilbert noted, performance has two aspects: behavior being the means and its consequence being the end... and it is the consequence we are mostly concerned with.
The four levels are upside down as it places the two most important items last—results, and behavior, which basically imprints the importance of order in most people's head. Thus by flipping it upside down and adding the above two changes we get:
With a few further adjustments, it becomes both a planning and evaluation tool that can be used as a troubling-shooting heuristic (Chyung, 2008):
The revised model can now be used for planning (left column) and evaluation (right column).
In addition, it aids the troubling-shooting process. For example, if you know the performers learned their skills but do not use them in the work environment, then the two more likely troublesome areas become apparent as they are normally in the cell itself (in this example, the Performance cell) or the cell to the left of it:
The diagram below shows how the evaluation processes fit together:
As the diagram shows, the Results evaluation is of the most interest to the business leaders, while the other three evaluations (performance, learning, and motivation) are essential to the learning designers for planning, evaluating, and trouble-shooting various learning processes; of course the Results evaluation is also important to them as it gives them a goal for improving the business. For more information see Formative and Summative Evaluations.
I go into more detail on my web page on Kirkpatrick is you would like more information or full references.
What are your thoughts?
Common definitions of visualization usually read something like, “to form a mental image,” thus we often think of visualization as being a simple solo technique, such as picturing “a dog eating a bone” or “a person doing the right thing.” However in an organization context, visualization is much more complex in that while it involves an image of the working environment, it is also a complex process that is very social in nature.
Visualization is often used interchangeably with sensemaking—making sense of the world we live and operate in, and then acting within that framework of understanding to achieve desired goals. Thus visualization is not just a shared (social) image with intent, it also implies ACTION. This framework can be used for building agile or rapid learning designs, fixing performance problems, implementing informal learning solutions, etc.
Visualization Framework (opens larger image in a new window)
The start of a visualization process is often sparked by a cue from the environment, such as an increase in customer complaints; or a team charged with improving a process. The steps within the visualization or sensemaking framework include (Leedom, McElroy, Shadrick, Lickteig, Pokorny, Haynes, Bell, 2007):
1. Triggering cues (information that acts as a signal) from the environment are perceived by the people in a Community of Interest (CoI). These cues may be picked up by one or more members of the CoI. A couple of examples of triggering cues might be an increase in the number of customer complaints or an unexpected drop in production.
2.Triggering cues create a situational anomaly—facts that do not fit into the framework of familiar mental models. Detection of these anomalies violate the expectancies of the members of the CoI and creates a need for change (improvement).
Note: A mental model is a structure or frame that is built from past experience and becomes part of an individual’s store of tacit knowledge. It is comprised of feature slots that can be instantiated by information describing a current situation (such as triggering cues). Its functional purpose allows a person to assess the situation, take a course of action, follow causal pathways, and recognize constraints in order to achieve a set of goals for actively confronting the situation. Fragmentary mental models can often be linked together to form a just-in-time explanation of a situation. Examples of a mental model include a chess player reacting to a move on the chessboard, a doctor diagnosing a medical condition, or an instructional designer solving a performance problem.
3. Specific data from the information environments trigger the mental activation of familiar mental models. The members of the CoI analyze and discuss the anomalies until they discover a purposeful structure or pattern for interpreting the new information. This transforms the problem space into various solutions. This process of “pattern matching” starts the basis for constructing new or revised mental models. Since patterns differ among the members, they collaborate by telling stories, metaphors, etc. to build common understanding.
4. Activation of a specific mental model is typically triggered by matching salient facts to one or two key features that uniquely anchor a new model that the CoI can agree upon. Tacit knowledge or intuition is often used to build mental models and the degree of tacit knowledge will vary among the members, thus they use a “negotiation process” to ensure all needs are met (or at least prioritize them according to available resources).
5. An action plan is used to instill the selected mental model into the work space in order to transform it to the desired state (during the visualization process intent must always be associated with action, otherwise it is just wistful thinking). The action plan includes the final development of any needed content, material, or products. Once all the pieces are put together, the action plan is implemented.
6. New information from the transformation process is perceived by the CoI, which in turn processes it to determine if the patterns match their desired mental model.
7. If the new information does not match the CoI's newly constructed mental model (situational anomalies are again perceived and they may or may not differ from the original ones), then the visualization process begins anew.
While the visualization process does use passive information that derives from experience and expertise, it also involves the proactive use of shaping actions to reduce risk and uncertainty and probing actions to discover system effect opportunities that can then be exploited.
Probing develops greater understanding by experimentally testing the operational environment, such as asking questions, Cognitive Task Analysis, or immersing oneself in the troubled environment to discover new information. These probing actions help to illuminate key structures and linkages within the environment.
Shaping is taking an incentive action to discover new information in order to determine if it aids in transforming the troubled environment to meet the new mental model. Prototyping may be used as a shaping tool—an iterative process of implementing successive small-scale tests in order to permit continual design refinements. There are normally two types of prototypes:
Probing actions serve to illuminate additional elements and linkages within the visualization space that can then be subsequently exploited for operational advantage.
The visualization or sensemaking framework in not linear, but rather a dynamic process that may flow in any direction, for example:
Dynamics of the Visualization Framework (opens larger image in a new window)
A Community of Interest holds a vested interests when faced with a troubling situation, thus they need a dynamic model that aids them in fulfilling their mission within complex environments. The military has a term called “center of gravity,” which is defined as the source of power that provides moral or physical strength, freedom of action, or the will to act. It is seen as the source of strength of the organization. The ability to act upon and transform an under-performing environment through the use of visualization or sensemaking is an essential attribute in an rapidly moving environment in that it helps to ensure the center of gravity stays balanced.
Leedom, D. K., McElroy, W., Shadrick, S. B., Lickteig, C., Pokorny, R. A., Haynes, J. A., Bell, J. (2007). Cognitive Task Analysis of the Battalion Level Visualization Process. Arlington, VA: United States Army Research Institute for the Behavioral and Social Sciences. Technical Report 1213. Retrieved on January 5, 2012 from http://www.hqda.army.mil/ari/pdf/TR1213.pdf
NOTE: I left this comment in eLearn Magazine's, Why Is the Research on Learning Styles Still Being Dismissed by Some Learning Leaders and Practitioners by Guy Wallace. Since it wiped out most of my formatting, such as comments and quotation marks, I am posting it here for better readability.
Perhaps one of the best papers on learning styles is Coffield, Moseley, Hall, and Ecclestone's, Learning styles and pedagogy in post-16 learning: A systematic and critical review (PDF). While the paper does dismiss some types of learning styles and the importance that the recognized learning styles actually have when it comes to learning, it does leave a lot of questions opened.
One of the most profound statements in the paper, at least to me, is (p68):
“just varying delivery style may not be enough and... the unit of analysis must be the individual rather than the group.”
That is, when you analyze a group, the findings often suggest that learning styles are relative unimportant, however, when you look at an individual, then the learning style often distinguishes itself as a key component of being able to learn or not. Thus those who actually deliver the learning process, such as teachers, instructors, or trainers and are responsible for helping others to learn see these styles and must adjust for them, while those who design for groups or study them see the learning styles as relative unimportant.
In the next paragraph, the paper continues with this statement:
“For each research study supporting the principle of matching instructional style and learning style, there is a study rejecting the matching hypothesis’ (2002, 411). Indeed, they found eight studies supporting and eight studies rejecting the 'matching' hypothesis, which is based on the assumption that learning styles, if not a fixed characteristic of the person, are at least relatively stable over time. Kolb's views at least are clear: rather than confining learners to their preferred style, he advocates stretching their learning capabilities in other learning modes.”
While many find this as a reason to dismiss learning styles, I find it quite intriguing in that why do learning styles play a key component is some situations or environments, but not others? I think part of the answer is within this finding—a study that was conducted in the U. S. and Israel, found that when students' learning styles matched the teaching method they performed both more effectively and efficiently. But the authors of the paper seem too readily to dismiss it as the end the paragraph with this statement—“But even this conclusion needed to be qualified as it applied only to higher-order cognitive outcomes and not to basic knowledge.” (p67)
It seems logical that higher-order cognitive outcomes need more individual support (in this case matching the learning style the the correct learning strategy) than basic knowledge. Thus in some situations learning styles are important, while in others they are not.
Finally, in the paper's conclusion the authors note (P132-133) that:
“Despite reservations about their model and questionnaire (see Section 6.2), we recognise that Honey and Mumford have been prolific in showing how individuals can be helped to play to their strengths or to develop as all-round learners (or both) by means, for example, of keeping a learning log or of devising personal development plans; they also show how managers can help their staff to learn more effectively.”
Thus the main take-away that I get from the paper if that if you are an instructor, manager, etc. who has to help the individual learners, then learning styles make sense. On the other hand, if you are an instructional designer or someone who directs her or his efforts at the group, then learning styles are probably not that important. Note that I am both a trainer and a designer so perhaps this is why my take-away makes sense to me.
In a couple of recent posts both Ben Betts and Clive Shepherd casts their doubts about the usefulness of 70-20-10 model and wonder if it's confusing the issue. You can read their posts at The Ubiquity of Informal Learning, and Beware who's selling informal learning.
I tend to agree with them, but before I begin I want to add that if you think I'm anti-informal learning, then please note that I wrote a post defending informal learning and it was Tweeted quite heavily. In addition, I've seen in the comments of these posts and others that if you challenge the idea about the usefulness of the 70-20-10 model then either you don't want to understand it, you clearly don't get it, or you see it as a threat to your job. If this is what you really think then you may talk-the-talk of informal and social learning learning but you walk-the-walk of a lecturer—“it's my way or the highway.” I have no patience with these attitudes because they are simply attacking people rather than their ideas.
While some proponents of the model insist it is non-prescriptive, both Ben Betts and Clive Shepherd saw the model as being “prescriptive.” I saw it as being prescriptive. Jay Cross saw it the same way as he wrote in one of his posts, A model of workplace learning,“The 70-20-10 model is more prescriptive. It builds upon how people internalize and apply what they learn based on how they acquire the knowledge.”
Even the Center for Creative Leadership, where the model was developed, write that the 70-20-10 model is indeed prescriptive:
“A research-based, time-tested guideline for developing managers says that you need to have three types of experience, using a 70-20-10 ratio: challenging assignments (70 percent), developmental relationships (20 percent) and coursework and training (10 percent).”
The 70-20-10 model is a prescriptive remedy for developing managers to senior and executive positions. Parts or perhaps all of the model may be useful for developing other professionals. However, by no means is it a useful model for the daily learning and work flows that takes place within organizations because it is being applied in an entirely different context that what it was designed to do. When people see numbers applied to a model they normally assume a couple of things: 1) that it is fact based, and/or 2) this is the way it is supposed to be.
As Will Thalheimer noted in one of his posts, adding numbers to make a model look more authentic makes it both bogus and dangerous (see People remember 10%, 20%...Oh Really?). I can attest to that because in some of my posts in the past I wrote that the formal to informal ratio was 30/70. People immediately commented and insisted it was 20/80 or 10/90. They seemed determined to lock the numbers in to an exact ratio—NO EXCEPTIONS! Even the model is begriming to look more like real ratios that must be adhered to because it is now being written as 70:20:10. Where will it end?
For more on the ratios see, 70-20-10: Is it a Viable Learning Model?
Jane Hart recently posted a thought-proving article on her blog in which she argues that you “can't manage informal learning, you can only manage the social media tools.” In her post she goes to great depth to define some of the various types of learning, such as formal, non-formal, and informal, however, I think the same needs to be done for “manage” in order to get a more accurate picture, otherwise we get mental images of Dilbert's pointy-haired boss when someone speaks or writes about management.
People often equate the term “management” with “control,” that is, when you manage something, you are trying to take direct control of it. However, management and control are actually two of four distinct processes for guiding an organization. The other two are leadership and command. While these are separate processes, they need to be blended together to deal with our rapidly changing world. Note that while I define the terms based upon my military experience and training, civilian organizations often use them because the military has the resources to study and research these concepts (and their studies are often done on civilian organizations which makes them valuable to the outside world).
Command is the imparting of a vision to the organization. It does this by formulating a well-thought out vision and then clearly communicating it. It emphasizes success and reward. That is, the organization has to be successful to survive and in turn reward its members (both intrinsically and extrinsically).
An example in this case would be visioning a process that helps to increase informal learning and make it more effective. A bad vision would be implementing a social media tool, such as a wiki or Twitter. This is because they are tools or technologies that are means rather than an end-goal.
Visions do not have to come from the top, but rather anywhere in the organization. Informal leaders are often good sources of visions, however if the vision requires resources, then they normally need the support of a formal leader.
In contrast, control is the process used to establish and provide structure in order to deal with uncertainties. Visions normally produce change, which in turn produces tension.
For example, “is the tool we provided to increase the effectiveness of informal learning really working?” Thus it tries to measure and evaluate. Inherent in evaluation is efficiency—it tries to make the goal more efficient. This can be good because it can save money and often improve a tool or process. The danger of this is if the command process is weak and the control process is strong then it can make efficiency the end-goal. That is, it replaces effectiveness with efficiency.
A good example of this is our present economy that caused many organizations to perform massive layoffs. Now the same organizations are complaining that they can't find qualified workers. Efficiency over road effectiveness—they failed to realize that they would need a trained workforce in the future.
Management's primary focus is on the conceptual side of the business, such as planning, organizing, and budgeting. It does the leg work to make visions reality. Thus it helps to acquire, integrate, and allocate resources to accomplish goals and task. This is why you need to manage non-formal learning and not just the tool itself. The goal is to increase informal learning and make it more effective, not to put into place a media tool. If the tool because the goal, then the wrong polices could be put into place that decrease its value as an informal learning tool.
Secondly, if the focus is only on the tool, then other options are omitted, such as tearing down cubicles and creating spaces where people can meet.
In contrast, leadership deals with the interpersonal relations such as being a teacher and coach, instilling organizational spirit to win, and serving the organization and workers.
Thus all four processes have their place. When you manage informal learning, you are not trying to control it, but rather planning how you will put the vision in place, budgeting for the required resources, and then organizing the teams so they can make it a reality.
In the August 2010 (p.10) edition of Chief Learning Officer magazine, Michael Echols notes a survey that the number one priority of 96 percent of the CEOs they surveyed want proof that learning programs are driving their top five business measures, but only 8 percent are getting it. Thus the learning and development leaders are going to start feeling the heat to get some type of evaluation process into place. If informal learning is going to be one of the primary objectives, we are going to have to get real about actually trying to measure it. The excuse that the learners control it so it can't be done is not going to cut it for long.
