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Note October 2018. This post was written before the LTEM model was developed. It therefore refers to the Four-Level Model’s Levels instead of LTEM’s eight tiers. The same principle still applies and I am leaving the article as written originally. To learn more about LTEM, click here or copy and paste: https://www.worklearning.com/ltem/. To learn why it’s now called the Kirkpatrick-Katzell model, click here.

The Kirkpatrick-Katzell four-level model of evaluation includes Level 1 learner reactions, Level 2 learning, Level 3 behavior, and 4 Level results. Because of the model’s ubiquity and popularity, many learning professionals and organizations are influenced or compelled by the model to measure the two higher levels—Behavior and Results—even when it doesn’t make sense to do so and even if poor methods are used to do the measurement. This pressure has led many of us astray. It has also enabled vendors to lie to us.

Let me get right to the point. When we ask learners whether a learning intervention will improve their job performance, we are getting their Level 1 reactions. We are NOT getting Level 3 data. More specifically, we are not getting information we can trust to tell us whether a person’s on-the-job behavior has improved due to the learning intervention.

Similarly, when we ask learners about the organizational results that might come from a training or elearning program, we are getting learners’ Level 1 reactions. We are NOT getting Level 4 data. More specifically, we are not getting information we can trust to tell us whether organizational results improved due to the learning intervention.

One key question is, “Are we getting information we can trust?” Another is, “Are we sure the learning intervention caused the outcome we’re targeting—or whether, at least, it was significant in helping to create the targeted outcomes?”

Whenever we gather learner answers, we have to remember that people’s subjective opinions are not always accurate. First there are general problems with human subjectivity; including people’s tendencies toward wanting to be nice, to see themselves and their organizations in a positive light, to believing they themselves are more productive, intelligent, and capable than they actually are. In addition, learners don’t always know how different learning methods affect learning outcomes, so asking them to assess learning designs has to be done with great care to avoid bias.

The Foolishness of Measuring Level 3 and 4 with Learner-Input Alone

There are also specific difficulties in having learners rate Level 3 and 4 results.

  • Having learners assess Level 3 is fraught with peril because of all the biases that are entailed. Learners may want to look good to others or to themselves. They may suffer from the Dunning-Kruger effect and rate their performance at a higher level than what is deserved.
  • Assessing Level 4 organizational results is particularly problematic. First, it is very difficult to track all the things that influence organizational performance. Asking learners for Level 4 results is a dubious enterprise because most employees cannot observe or may not fully understand the many influences that impact organizational outcomes.

Many questions we ask learners in measuring Level 3 and 4 are biased in and of themselves. These four questions are highly biasing, and yet sadly they were taken directly from two of our industry’s best-known learning-evaluation vendors:

  • “Estimate the degree to which you improved your performance related to this course?” (Rated on a scale of percentages to 100)
  • “The training has improved my job performance.” (Rated on a numeric scale)
  • “I will be able to apply on the job what I learned during this session.” (rated with a Likert-like scale)
  • “I anticipate that I will eventually see positive results as a result of my efforts.” (rated with a Likert-like scale)

At least two of our top evaluation vendors make the case explicitly that smile sheets can gather Level 3 and 4 data. This is one of the great lies in the learning industry. A smile sheet garners Level 1 results! It does not capture data at any other levels.

What about delayed smile sheets—questions delivered to learners weeks or months after a learning experience? Can these get Level 2, 3, and 4 data? No! Asking learners for their perspectives, regardless of when their answers are collected, still gives us only Level 1 outcomes! Yes, learners answers can provide hints, but the data can only be a proxy for outcomes beyond Level 1.

On top of that, the problems cited above regarding learner perspectives on their job performance and on organizational results still apply even when questions are asked well after a learning event. Remember, the key to measurement is always whether we can trust the data we are collecting! To reiterate, asking learners for their perspectives on behavior and results suffers from the following:

  • Learners’ biases skew the data
  • Learners’ blind spots make their answers suspect
  • Biased questioning spoils the data
  • The complexity in determining the network of causal influences makes assessments of learning impact difficult or impossible

In situations where learner perspectives are so in doubt, asking learners questions may generate some reasonable hypotheses, but then these hypotheses must be tested with other means.

The Ethics of the Practice

It is unfair to call Level 1 data Level 3 data or Level 4 data.

In truth, it is not only unfair, it is deceptive, disingenuous, and harmful to our learning efforts.

How Widespread is this Misconception?

If two of are top vendors are spreading this misconception, we can be pretty sure that our friend-and-neighbor foot soldiers are marching to the beat.

Last week, I posted a Twitter poll asking the following question:

If you ask your learners how the training will impact their job performance, what #Kirkpatrick level is it?

Twitter polls only allow four choices, so I gave people the choice of choosing Level 1 — Reaction, Level 2 –Learning, Level 3 — Behavior, or Level 4 — Results.

Over 250 people responded (253). Here are the results:

  • Level 1 — Reaction (garnered 31% of the votes)
  • Level 2 — Learning (garnered 15% of the votes)
  • Level 3 — Behavior (garnered 38% of the votes)
  • Level 4 — Results (garnered 16% of the votes)

Level 1 is the correct answer! Level 3 is the most common misconception!

And note, given that Twitter is built on a social-media follower-model—and many people who follow me have read my book on Performance-Focused Smile Sheets, where I specifically debunk this misconception—I’m sure this result is NOT representative of the workplace learning field in general. I’m certain that in the field, more people believe that the question represents a Level 3 measure.

Yes, it is true what they say! People like you who read my work are more informed and less subject to the vagaries of vendor promotions. Also better looking, more bold, and more likely to be humble humanitarians!

My tweet offered one randomly-chosen winner a copy of my award-winning book. And the winner is:

Sheri Kendall-DuPont, known on Twitter as:

Thanks to everyone who participated in the poll…

Update January 2018: To see my latest recommendations for smile-sheet question design, go to this web page.

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The Original Post:

The response to the book, Performance-Focused Smile Sheets: A Radical Rethinking of a Dangerous Art Form, has been tremendous! Since February, when it was published, I’ve received hundreds of thank you’s from folks the world over who are thrilled to have a new tool — and to finally have a way to get meaningful data from learner surveys. At the ATD conference where I spoke recently, the book sold out it was so popular! If you want to buy the book, the best place is still SmileSheets.com, the book’s website.

Since publication, I’ve begun a research effort to learn how companies are utilizing the new smile-sheet approach — and to learn what’s working, what the roadblocks are, and what new questions they’ve developed. As I said in the book in the chapter that offers 26 candidate questions, I hope that folks tailor questions, improve them, and develop new questions. This is happening, and I couldn’t be more thrilled. If your company is interested in being part of my research efforts, please contact me by clicking here. Likewise, if you’ve got new questions to offer, let me know as well.

Avoiding Issues of Traditional Smile Sheets

Traditional smile sheets tend to focus on learners’ satisfaction and learners’ assessments of the value of the learning experience. Scientific research shows us that such learner surveys are not likely to be correlated with learning results. Performance-focused smile sheets offer several process improvements:

  1. Avoid Likert-like scales and numerical scales which create a garbage-in garbage-out problem, which don’t offer clear delineations between answer choices, which don’t support respondent decision-making, and which open responding to bias.
  2. Instead, utilize concrete answer choices, giving respondents more granularity, and enabling much more meaningful results.
  3. In addition to, or instead of, focusing on factors related to satisfaction and perceived value; target factors that are related to learning effectiveness.

New Example Questions

As new questions come to my attention, I’ll share them here on my blog and elsewhere. You can sign up for my email newsletter if you want to increase the likelihood that you’ll see new smile-sheet questions (and for other learning-research related information as well).

Please keep in mind that there are no perfect assessment items, no perfect learning metrics, and no perfect smile-sheet questions. I’ve been making improvements to my own workshop smile sheets for years, and every time I update them, I find improvements to make. If you see something you don’t like in the questions below, that’s wonderful! When evaluating an assessment item, it’s useful to ask whether the item (1) is targeting something important and (2) is it better than other items that we could use or that we’ve used in the past.

Question Example — A Question for Learners’ Managers

My first example comes from a world renowned data and media company. They decided to take one of the book’s candidate questions, which was designed for learners to answer, and modify the question to ask learners’ managers to answer. Their reasoning: The training is strategically important to their business and they wanted to go beyond self-report data. Also, they wanted to send “stealth messages” to learners’ managers that they as managers had a role to play in ensuring application of the training to the job.

Here’s the question (aimed at learners’ managers):

In regard to the course topics taught, HOW EFFECTIVELY WAS YOUR DIRECT REPORT ABLE to put what he/she learned into practice in order to PERFORM MORE EFFECTIVELY ON THE JOB?

A. He/she has NOT AT ALL ABLE to put the concepts into practice.

B. He/she has GENERAL AWARENESS of the concepts taught, but WILL NEED MORE TRAINING / GUIDANCE to put the concepts into practice.

C. He/she WILL NEED MORE HANDS-ON EXPERIENCE to be fully competent in using the concepts taught.

D. He/she is at a FULLY COMPETENT LEVEL in using the concepts taught.

E. He/she is at an EXPERT LEVEL in using the concepts taught.

Question Example — Tailoring a Question to the Topic

In writing smile-sheet questions, there’s a tradeoff between generalization and precision. Sometimes we need a question to be relevant to multiple courses. We want to compare courses to one another. Personally, I think we overvalue this type of comparison, even when we might be comparing apples to oranges. For example, do we really want to compare scores on courses that teach such disparate topics as sexual harassment, word processing, leadership, and advanced statistical techniques? Still, there are times when such comparisons make sense.

The downside of generalizability is that we lose precision. Learners are less able to calibrate their answers. Analyzing the results becomes less meaningful. Also, learners see the learner-survey process as less valuable when questions are generic, so they give less energy and thought to answering the questions, and our data become less valuable and more biased.

Here is a question I developed for my own workshop (on how to create better smile sheets, by the way SMILE):

How READY are you TO WRITE QUESTIONS for a Performance-Focused Smile Sheet?

CIRCLE ONE OR MORE ANSWERS

AND/OR WRITE YOUR REASONING BELOW

A. I’m STILL NOT SURE WHERE TO BEGIN.

B. I KNOW ENOUGH TO GET STARTED.

C. I CAN TELL A GOOD QUESTION FROM A BAD ONE.

D. I CAN WRITE MY OWN QUESTIONS, but I’d LIKE to get SOME FEEDBACK before using them.

E. I CAN WRITE MY OWN QUESTIONS, and I’m CONFIDENT they will be reasonably WELL DESIGNED.

More
Thoughts?

 

 

Note several things about this question. First to restate. It is infinitely more tailored than a generic question could be. It encourages more thoughtful responding and creates more meaningful feedback.

Second, you might wonder why all the CAPS! I advocate CAPS because (1) CAPS have been shown in research to slow reading speed. Too often, our learners burn through our smile-sheet questions. Anything we can do to make them attend more fully is worth trying. Also, (2) respondents often read the full question and then skim back over it when determining how to respond. I want them to have an easy way to parse the options. Full disclosure. To my knowledge, all CAPS has not been studied yet for smile sheets. At this point, my advocacy for all CAPS is based on my intuition about how people process smile-sheet questions. If you’d like to work with me to test this in a scientifically rigorous fashion, please contact me.

Third, notice the opportunity for learners to write clarifying comments. Open-ended questions, though not easily quantifiable, can be the most important questions on smile sheets. They can provide intimate granularity — a real sense of the respondents’ perceptions. In these questions, we’re using a hybrid format, a forced choice question followed by an open-ended opportunity for clarification. This not only enables the benefits of open-ended responding, but it also enables us to get clarifying meaning. In addition, in some way it provides a reality-check on our question design. If we notice folks responding in ways that aren’t afforded in the answer choices given, we can improve our question for later versions.

 

Question Example — Simplifying The Wording

In writing smile-sheet questions, there’s another tradeoff to consider. More words add more precision, but fewer words add readability and motivation to engage the question fully. In the book, I talk about what I once called, “The World’s Best Smile Sheet Question.” I liked it partly because the answer choices were more precise than a Likert-like scale. It did have one drawback; it used a lot of words. For some audiences this might be fine, but for others it might be entirely inappropriate.

Recently, in working with a company to improve their smile sheet, a first draft included the so-called World’s Best Smile Sheet Question. But they were thinking of piloting the new smile sheet for a course to teach basic electronics to facilities professionals. Given the topic and audience, I recommended a simpler version:

How able will you be to put what you’ve learned into practice on the job?  Choose one.

A. I am NOT AT ALL ready to use the skills taught.
B. I need MORE GUIDANCE to be GOOD at using these skills
C. I need MORE EXPERIENCE to be GOOD at using these skills.
D. I am FULLY COMPETENT in using these skills.
E. I am CAPABLE at an EXPERT LEVEL in using these skills.

This version nicely balances precision with word count.

 

Question Example — Dealing with the Sticky Problem of “Motivation”

In the book, I advocate a fairly straightforward question asking learners about their motivation to apply what they’ve learned. In many organizations — in many organizational cultures — this will work fine. However in others, our trainers may be put off by this. They’ll say, “Hey, I can’t control people’s motivations.” They’re right, of course. They can’t control learners’ motivations, but they can influence them. Still, it’s critical to realize that motivation is a multidimensional concept. When we speak of motivation, we could be talking simply about a tendency to take action. We could be talking about how inspired learners are, or how much they believe in the value of the concepts, or how much self-efficacy they might have. It’s okay to ask about motivation in general, but you might generate clearer data if you ask about one of the sub-factors that comprise motivation.

Here is a question I developed recently for my Smile-Sheet Workshop:

How motivated are you to IMPLEMENT PERFORMANCE-FOCUSED SMILE SHEETS in your organization?

CIRCLE ONLY ONE ANSWER. ONLY ONE!

A. I’m NOT INTERESTED IN WORKING TOWARD IMPLEMENTING this.

B. I will confer with my colleagues to SEE IF THERE IS INTEREST.

C. I WILL ADVOCATE FOR performance-focused smile sheet questions.

D. I WILL VIGOROUSLY CHAMPION performance-focused smile sheet questions.

E. Because I HAVE AUTHORITY, I WILL MAKE THIS HAPPEN.

More
Thoughts?

In this question, I’m focusing on people’s predilection to act. Here I’ve circumnavigated any issues in asking learners to divulge their internal motivational state, and instead I’ve focused the question on the likelihood that they will utilize their newly-learned knowledge in developing, deploying, and championing performance-focused smile sheets.

 

Final Word

It’s been humbling to work on smile sheet improvements over many years. My earlier mistakes are still visible in the digital files on my hard drive. I take solace in making incremental improvements — and in knowing that the old way of creating smile-sheet questions is simply no good at all, as it provides us with perversely-irrelevant information.

As an industry — and the learning industry is critically important to the world — we really need to work on our learning evaluations. Smile sheets are just one tool in this. Unfortunately, poorly constructed smile sheets have become our go-to tool, and they have led us astray for decades.

I hope you find value in my book (SmileSheets.com). More importantly, I hope you’ll participate along with some of the world’s best-run companies and organizations in developing improved smile sheet questions. Again, please email me with your questions, your question improvements, and alternatively, with examples of poorly-crafted questions as well.