Will at Work Learning

What Work-Learning Audit Reveals

I recently completed one of the most comprehensive work-learning audits I've ever been asked to do for a major U. S. retailer. The goal of the audit was to find out how their learning programs AND work-learning environment were supporting the stores in being successful. The audit involved (1) structured and unstructured interviewing with all levels of the organization, especially with store personnel, (2) focus groups held across the country with specific groups of store personnel (e.g., clerk, store managers, assistant managers, etc.), (3) task force meetings with senior line managers and representatives throughout the company, (4) learning audits of e-learning courses, (5) learning audits of a mission-critical classroom course, (6) review of company artifacts (CEO messages, publications, databases, intranet, etc.), (7) interviews with learning-and-performance professionals, (8) discussions of business strategy, (9) discussions regarding corporate information and data-gathering capabilities, (10) job shadowing, (11) store observations, etc.

Who/What Do Workers Learn From?

One of the most intriguing results came out of a relatively simple exercise I did with focus-group participants. The following is a rough approximation of those results.

What I did was ask focus-group participants who they learned from. I would hold up a large 6 x 8 index card with a position label on it, for example, "District Manager," "Clerks," or "Corporate." The group would shout out where they thought that card should go on a large diagram I had created on the wall. I would place it on the wall in a particular category based on the verbal responses and then we would negotiate as a group to determine it's final positioning. So for example, participants could say that they learned the following amounts from that person/position, and we often compromised using in-between placement:

• Learned Most
• Learned a Lot
• Learned Some
• Learned a Little
• Learned Least
• Had Little/No Contact with

See the diagram below for a rough example. This one is actually a composite based on several focus groups and more than one position. It gives a fair representation for how frontline retail clerks responded. Note that the orange boxes represent fellow employees, while the blue boxes represent other groups of people or things that they learned from.

There are several key insights from these results:

• People learn the most from those who they work closely with.
• People learn the most from their experience doing the job.
• People learn the most from their self-initiated efforts at learning.
• The more contact, the more learning (for the most part), however there are benefits from learning from experts (e.g., store managers, head clerks), though the worker has to have at least some signicant contact with them to create this benefit. You'll notice that district staff have only a little impact and regional and corporate staff have none.
• E-learning is seen as somewhat facilitative but not a place where workers learn the most. This result may be organization specific as different e-learning designs and implementations might easily move this result higher or lower.

Frontline clerks didn't get much from company magazines and the like, but managers (not represented in the results above) did find value in these. Store managers also reported that networking with other store managers was on of the "Learn Most" entries for them. For this company, this network was even more important than learning from their district managers (their direct bosses). This makes sense because their network is more accessible throughout the heat of the daily grind.

These results were eye-opening for my client, and they are still wrangling with the implications. For example, district managers and district training staff seemed to produce very little learning benefits. So, should their roles for learning be de-emphasized or re-emphasized?

These types of result have to be understood in the larger data-gathering effort of course. Analyzed alone, they suffer from the problem of de-contextualized self-report data. Combined with multiple other data sources, they paint a really robust picture of an organization's learning environment.

Informal Learning, Social Networks, etc.

Vendors are out and about in our field now selling the benefits of complicated and expensive analysis tools for looking at how people learn through so-called informal on-the-job mechanisms. The example above shows that if you don't have the big bucks, there are simpler ways to get good data as well. 

Elliott Masie's LMS Wish List

Elliott Masie came up with a great and very insightful wish list for LMS's. Click here to access it. He even added a few suggestions in the past few days, probably based on feedback from his loyal audience.

I really like the richness that Elliott's suggestions might create for a typical LMS. Most LMS implementations are just a list of course offerings.

On the other hand, I worry about overly complicating options for users. Most workers just don't have extra time to waste. Maybe the suggestion to let users rate the courses comes into play here.

I also worry about user-generated content. It can be great, could be better than what the training folks can create, could engender more engagement, could be bottom line more effective. But we should all recognize that it is a double-edge sword. User generated content could be incorrect, could be a huge waste of time, could cause the organization to leave itself vulnerable to legal liability.

Doesn't Fix the Biggest Problem with the LMS Mentality

The biggest problem with LMS's can't be fixed with Elliott's suggestions. The biggest problem is that the whole LMS face sends a powerful hidden message that "learning" is about taking courses or accessing other learning events. This "Learning Means Sitting" LMS mentality infiltrates whole organizations.

I've seen this recently with one of my clients, a huge retailer, where their LMS has encouraged store managers and other store leaders to focus learning time on taking courses, in lieu of coaching, learning from each other, trying things out and getting feedback, encouraging store employees to take responsibility for particular areas, etc. It's not that they completely ignore these other learning opportunities; it's that the LMS focuses everyones' time and attention on courses, creating a lot of wasted effort.

To get the most from an LMS, you ought to throw away your LMS and start over. People can learn something—develop competencies/skills—from courses or from other means. A competency-management system that offers multiple means to develop oneself is ideal, where courses/events are just one option. I still haven't seen a commercial system that does this though...Most are course first designs.

Maybe I'm too over-the-top recommending that we get rid of all LMS's. I make the statement to highlight the humongous problems that the LMS mentality is causing.

Neon Elephant Award 2007 to Sharon Shrock and Bill Coscarelli

I'd like to announce the winners of the 2007 Neon Elephant Award, given this year to Sharon Shrock and Bill Coscarelli for advocating against the use of memorization-level questions in learning measurement and for the use of authentic assessment items, including scenario-based questions, simulations, and real-world skills tests.

The Neon Elephant Award is awarded to a person, team, or organization exemplifying enlightenment, integrity, and innovation in the field of workplace learning and performance. Announced on the day of the winter solstice—the day of the year when the northern hemisphere turns away from darkness toward the light and hope of warmer days to come—the Neon Elephant Award honors those who have truly changed the way we think about the practice of learning and performance improvement. Award winners are selected for demonstrated success in pushing the field forward in significant paradigm-altering ways while maintaining the highest standards of ethics and professionalism.

See the full announcement by clicking here...

Learning Styles Challenge 1-Year Update

It has been exactly one year since I offered $1,000 to anyone who could demonstrate that utilizing learning styles improved learning outcomes. Click here for the original challenge.

So far, no one has even come close.

For all the talk about learning styles over the last 15 years, we might expect that I was at risk of quickly losing my money.

Let me be clear, my argument is not that people don't have different learning styles, learning preferences, or learning skills. My argument is that for real-world instructional-development situations, learning styles is an ineffective and inefficient waste of resources that is unlikely to produce meaningful results.

Let me leave you with the original challenge:

"Can an e-learning program that utilizes learning-style information outperform an e-learning program that doesn't utilize such information by 10% or more on a realistic test of learning, even it is allowed to cost up to twice as much to build?"

The challenge is still on.

Human Cognition is More Reactive Than You Think

In today's New York Times there is a great article, Who's Minding the Mind?, by BENEDICT CAREY that sums up a large number of research studies on human cognition that show that human beings are more reactive than we might think. We tend to believe that we, as human beings, are very proactive and consciously in control of our thoughts and actions; but these studies show that much of what we do and think is due to hard-wired, often unconscious processes.

For example, the article cites how sitting near a briefcase (as opposed to a backpack) can make people more competitive. Or as Carey writes:

New studies have found that people tidy up more thoroughly when there’s a faint tang of cleaning liquid in the air; they become more competitive if there’s a briefcase in sight, or more cooperative if they glimpse words like “dependable” and “support” — all without being aware of the change, or what prompted it.

This basic fact about human behavior is relevant to the learning and performance field, of course. One of the things I've talked about for years is the notion of "spontaneous remembering." If we create learning right, we're more likely to help our learners—when they're on the job at a later time—by helping them spontaneously trigger memories of what they've learned. We can do this best by requiring our learners to utilize realistic cues in the learning context in making real-world decisions and taking real-world actions. This is why simulations are so effective (if they are well designed).

When learners process learning objectives or prequestions before encountering learning material, the learners are primed to pay attention to relevant learning material. It's not necessarily a conscious process, but it works.

There are many examples available, but here's another point: The learner-centric movement of the 1990's and 2000's has relied too heavily on the notion that the learners always know best, and that they are in conscious control of their learning and we just need to let them make the best decisions.

When we realize that our learners are more deterministically driven than the we want to believe (its about free will a little, isn't it?), we have more work to do if we really want to drive maximum performance. Even when our clients consciously want to do something, we may be able to help them reach their goals by setting up learning and performance situations that unconsciously trigger the behavior they want to achieve.

Evidence-Based Learning

The concept of evidence-based practice is bubbling up all over. I started Work-Learning Research in 1998 to bridge the gap between research and practice. Ruth Clark has been talking about evidence-based recommendations for years. The medical profession has transformed itself to focus on evidence-based medicine. The No-Child-Left-Behind initiative was based on the concept of evidence-based education. Though No Child Left Behind has been poorly implemented, the core concept is sound. Kevin Kruse, CEO of the custom e-learning company Axiom Health, has trademarked the term, "Evidence-Based Training." Management gurus, Jeffrey Pfeffer and Bob Sutton have recently written a best selling book (Pfeffer and Sutton, 2006. Hard Facts, Dangerous Half-Truths And Total Nonsense: Profiting From Evidence-Based Management). ISPI (the International Society for Performance Improvement) has been promoting evidence-based practices in their CPT certification program since the 1990's.

Evidence-Based Practice is on an upward trajectory, but what does it mean for those of us in the learning-and-performance field? I'm not going to go into depth now, but I want to highlight a few critical points.

1. Evidence-Based Learning (EBL) DOES NOT simply mean that we follow research-based prescriptions.
2. Evidence-Based Learning (EBL) requires us also to measure our own performance. In other words, we ought to be routinely gathering good EVIDENCE about how well our learning interventions are working. Only by having feedback loops can we learn from our performance.
3. Evidence-Based Learning (EBL) requires us also to build continuous cycles of improvement into our practices. After gathering and analyzing the evidence, we need to act on it. Then we need to evaluate and analyze and act again.

I spend an inordinate amount of time every year culling practical learning wisdom from the world's preeminent refereed journals on learning, memory, and instruction. It appears that I am one of the most passionate advocates for learning research living today. Yet still, I believe that following research-based recommendations can provide us with less than half, probably less than one-third, of the power of a full practice of evidence-based learning.

In fact, I've come to believe that, as a field, we have only reached a small measure of our potential because we don't utilize evidence-based practices. We don't have adequate feedback loops. We act too often on superstition, on the ideas inherent in commercial messaging, and on our learner's lowest-common denominator comfort zones.

The bottom line recommendation is this: Only with true evidence-based practices, not warmed over attempts to follow a few research-based prescriptions, can you build a maximally effective learning program.

Sorry I can't provide more specifics in this short blog format. If you want to know more, feel free to get in touch with me.

The Magic Question for Learning and Instructional Design

The most important question that instructional designers can ask is:

“What do learners need to be able to do, and in what situations do they need to do those things?”

While we might discount such a simple question as insignificant, the question brilliantly forces us to focus on our ultimate goals and helps us to align our learning interventions with the human learning system.

Too many of us design with a focus on topics, content, knowledge. This tendency pushes us, almost unconsciously, to create learning that is too boring, filled with too much information, and bereft of practice in realistic situations.

The Magic Question requires us to be relevant. For workplace learning, it focuses our thinking toward learners' future job situations. For education learning, it focuses our thinking toward real-world relevance of our academic topics.

The Magic Question in Practice

In practice, the Magic Question forces us to begin our instructional-design efforts by not only creating a list of instructional objectives, but also by creating a list of performance situations. For example, if we're creating leadership training, we not only need to compile objectives like, "For most decisions, it can be helpful to bring your direct reports into decision-making, so as to increase the likelihood that they will bring energy and passion in implementing decisions." We also need to compile a list of situations were this objective is relevant, for example in weekly staff meetings, project meetings, in one-on-one face-to-face conversations, in phone conversations, etc. Also, for general decision making, but not in situations where time is urgent, where safety is an issue, where legal ramifications are evident, etc.

By framing our instructional-design projects in this way, we get to think about our learning designs in ways that are much more action-oriented, relevant, and practical. The framing makes it more likely that we will align our learning and performance contexts, making it more likely that our learners, in their future situations, will spontaneously remember what we've taught them. The framing makes it more likely that we will focus on practice instead of overloading our learners with information. The framing also makes it more likely that we will utilize relevant scenarios that more fully engage our learners. Finally, using the Magic Question forces our SME's (subject-matter experts) to reformulate their expertise into potent practical packages of relevant material. It's not always easy to bend SME's to this discipline, but after the pain, they'll thank you profusely as together you push their content to a much higher level.

Obviously, there is more to be said about how the Magic Question can be integrated into learning-design efforts. On the other hand, as my clients have reported, the Magic Question has within it a simple power to (1) change the way we think about instructional design, and (2) transform the learning interventions we build.

Training and Carbon Offsets

The Carbon Offset idea works like this. We all pollute, but when we do so we can help limit the damaging effects by either (1) offsetting our damage by doing good in other ways (for example if we have to drive a large car we can replace all our light bulbs with energy-saving flourescents), or (2) we can donate money to projects that help support renewable energy, energy efficiency, and reforestation. For example, check out the not-for-profit organizations CarbonFund.org and The Clean Air Conservancy.

Here's some ideas for those of us in the training and development field:

1. Encourage the use of e-learning, which limits the carbon footprint of travel. And, make sure you build e-learning that is effective and engaging, so more folks will want to use e-learning.
2. When calculating the "cost" of training, calculate carbon footprint costs as well. See for example, The Carbon Fund's calculators or The Clean Air Conservancy's calculators. Make these costs evident.
3. Encourage your company to buy carbon offsets when utilizing training. It's not just a good thing to do, but it may help your company attract business and recruit highly-educated employees.
4. In your e-learning courses, provide an option for learners to calculate how many tons of carbon dioxide they would have utilized had they had to travel from their location to headquarters.

What other ideas can you think of?

Measuring Learning Results: The New Research-to-Practice White Paper

I've just completed a new research-to-practice white paper. As far as I can tell, it is the first work on learning measurement (assessment and evaluation) that actually takes human learning into consideration. I'd like to thank Questionmark for agreeing to support this work.

Words from the paper's introduction:

In writing this report on using fundamental learning research to inform assessment  design, I am combining two of my passions—learning and the measurement of learning. As an experienced learner and learning designer, I have come to the belief that those of us responsible for designing, developing, and delivering learning interventions are often left in the dark about our own successes and failures. The measurement techniques we use simply do not provide us with valid feedback about our own performances.

The traditional model of assessment utilizes end-of-learning assessments provided to learners in the context in which they learned. This model is seriously flawed, especially in failing to give us an idea of how well our learning interventions are doing in preparing our learners to retrieve information in future situations—the ultimate goal of training and education. By failing to measure our performance in this regard, we are missing opportunities to provide ourselves with valid feedback. We are also likely failing our institutions and our learners because we are not able to create a practice of continuous improvement to maximize our learning outcomes.

This report is designed to help you improve your assessments in this regard. I certainly won’t claim to have all the answers, nor do I think it is easy to create the perfect assessment, but I do believe very strongly that all of us can improve our assessments substantially, and by so doing improve the practice of education and training.

How to buy the paper:

• Click to go to my catalog
• Click to buy the paper directly

Wiki Improvements

I have critiqued the wiki revolution (see posts in 2005 and in 2006) because I worried about the garbage-in garbage-out problem. That is, how can consumers of wikized information know whether the information is valid? Previously, the knowledge culture has relied on editors, peer-reviewers, and publishers to vet information prior to publication.

Wikipedia has come to recognize this problem and is taking steps to lessen it. See their WikiProject Fact and Reference Check webpage. As you browse Wikipedia today, you'll often see pages marked with the warning, "This [entry] does not adequately cite its references or sources. Please help improve this article by adding citations to reliable sources."

This is a great first step. Whether it is enough, we will see. It probably depends on the topic area discussed.

And to be balanced, we must recognize that any influence can tilt content toward one truth or another, whether that influence is an editor or an admonition to cite reliable sources. Therefore, my next recommendation is to formalize alternative interpretations within wiki technology and practice. The wiki interface sometimes formalizes and encourages a "one-truth" paradigm, so where one truth is inadequate, the technology needs to encourage a different sort of mental model, one that allows information consumers to feel the heat, sweat, and uncertainty of the truth-building process.