Data collection « Evaluation is an Everyday Activity

Hi everybody–it is time for another TIMELY TOPIC. This week’s topic is about using pretest/posttest evaluation or a post-then-pre evaluation.

There are many considerations for using these designs. You have to look at the end result and decide what is most appropriate for your program. Some of the key considerations include:

the length of your program;
the information you want to measure;
the factors influencing participants response; and
available resources.

Before explaining the above four factors, let me urge you to read on this topic. There are a couple of resources (yes, print…) I want to pass your way.

Campbell, D. T. & Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Houghton Mifflin Company: Boston, MA. (The classic book on research and evaluation designs.)
Rockwell, S. K., & Kohn, H. (1989). Post-then-pre evaluation. Journal of Extension [On-line]. 27(2). Available at: http://www.joe.org/joe/1989summer/a5.htm (A seminal JoE paper explaining post-then-pre test.)
Nimon, K. Zigarami, D. & Allen, J. (2011). Measures of program effectiveness based on retrospective pretest data: Are all created equal? American Journal of Evaluation, 32, 8 – 28. (A 2011 publication with an extensive bibliography.)

Let’s talk about considerations.

Length of program.

For pre/post test, you want a program that is long. More than a day. Otherwise you risk introducing a desired response bias and the threats to internal validity that Campbell and Stanley identify. Specifically the threats called history, maturation, testing, and instrumentation, also a possible regression to the mean threat, though that is on a possible source of concern. These threats to internal validity assume no randomization and a one group design, typical for Extension programs and other educational programs. Post-then-pre works well for short programs, a day or less, and tend to control for response shift and desired response bias. There may still be threats to internal validity.

Information you want to measure.

If you want to know a participants specific knowledge, a post-then-pre cannot provide you with that information because you can not test something you cannot unknow. The traditional pre/post can focus on specific knowledge, e.g., what food is the highest in Vitamin C in a list that includes apricot, tomato, strawberry cantaloupe. (Answer: strawberry) If you are wanting agreement/disagreement with general knowledge (e.g., I know what the key components of strategic planning are), the post-pre works well. Confidence, behaviors, skills, and attitudes can all be easily measured with a post-then-pre.

Factors influencing participants response.

I mentioned threats to internal validity above. These factors all influence participants responses. If there is a long time between the pretest and the post test, participants can be affected by history (a tornado prevents attendance to the program); maturation (especially true with programs with children–they grow up); testing (having taken the pretest, the post test scores will be better); and instrumentation (the person administering the posttest administers it differently than the pretest was administered). Participants desire to please the program leader/evaluator, called desired response bias, also affects participants response.

Available resources.

Extension programs (as well as many other educational programs) are affected by the availability of resources (time, money, personnel, venue, etc.). If you only have a certain amount of time, or a certain number of people who can administer the evaluation, or a set amount of money, you will need to consider which approach to evaluation you will use.

The idea is to get usable, meaningful data that accurately reflects the work that went into the program.

We recently held Professional Development Days for the Division of Outreach and Engagement. This is an annual opportunity for faculty and staff in the Division to build capacity in a variety of topics. The question this training posed was evaluative:

How do we provide meaningful feedback?

Evaluating a conference or a multi-day, multi-session training is no easy task. Gathering meaningful data is a challenge. What can you do? Before you hold the conference (I’m using the word conference to mean any multi-day, multi-session training), decide on the following:

Are you going to evaluate the conference?
What is the focus of the evaluation?
How are you going to use the results?

The answer to the first question is easy: YES. If the conference is an annual event (or a regular event), you will want to have participants’ feedback of their experience, so, yes, you will evaluate the conference. Look at a Penn State Tip Sheet 16 for some suggestions. (If this is a one time event, you may not; though as an evaluator, I wouldn’t recommend ignoring evaluation.)

The second question is more critical. I’ve mentioned in previous blogs the need to prioritize your evaluation. Evaluating a conference can be all consuming and result in useless data UNLESS the evaluation is FOCUSED. Sit down with the planners and ask them what they expect to happen as a result of the conference. Ask them if there is one particular aspect of the conference that is new this year. Ask them if feedback in previous years has given them any ideas about what is important to evaluate this year.

This year, the planners wanted to provide specific feedback to the instructors. The instructors had asked for feedback in previous years. This is problematic if planning evaluative activities for individual sessions is not done before the conference. Nancy Ellen Kiernan, a colleague at Penn State, suggests a qualitative approach called a Listening Post. This approach will elicit feedback from participants at the time of the conference. This method involves volunteers who attended the sessions and may take more persons than a survey. To use the Listening Post, you must plan ahead of time to gather these data. Otherwise, you will need to do a survey after the conference is over and this raises other problems.

The third question is also very important. If the results are just given to the supervisor, the likelihood of them being used by individuals for session improvement or by organizers for overall change is slim. Making the data usable for instructors means summarizing the data in a meaningful way, often visually. There are several way to visually present survey data including graphs, tables, or charts. More on that another time. Words often get lost, especially if words dominate the report.

There is a lot of information in the training and development literature that might also be helpful. Kirkpatrick has done a lot of work in this area. I’ve mentioned their work in previous blogs.

There is no one best way to gather feedback from conference participants. My advice: KISS–keep it simple and straightforward.

I’ve talked about how each phase of a logic model has evaluative activities. I’ve probably even alluded to the fact that needs assessment is the evaluative activity for that phase called situation (see the turquoise area on the left end of the image below.)

What I haven’t done is talk about is the why, what, and how of needs assessment (NA). I also haven’t talked about the utilization of the findings of a needs assessment–what makes meaning of the needs assessment.

OK. So why is a NA conducted? And what is a NA?

Jim Altschuld is my go-to person when it comes to questions about needs assessment. He recently edited a series of books on the topic.

Although Jim is my go-to person, Belle Ruth Witkin (a colleague, friend, and collaborator of Jim Altschuld) says in the preface to the co-authored volume (Witkin and Altschuld, 1995–see below), that the most effective way to decide the best way to divide the (often scarce) resources among the demands (read programs) is to conduct a needs assessment when the planning for the use of those resources begins.

Book 1 of the kit discusses an overview. In that volume, Jim defines what a needs assessment is: “Needs assessment is the process of identifying needs, prioritizing them, making needs-based decisions, allocating resources, and implementing actions in organizations to resolve problems underlying important needs (pg.20).” Altschuld states that there are many models for assessing needs and provides citations for those models. I think the most important aspect of this first volume is the presentation of the phased model developed by Belle Ruth Witkin in 1984 and revised by Altschuld and Witkin in their 1995 and 2000 volumes.Those phases are preassessment, assessment, and postassessment. They divide those three phases into three levels, primary, secondary, and tertiary, each level targeting a different group of stakeholders. This volume also discusses the why and the how. Subsequent volumes go into more detail–volume 2 discusses phase 1 (getting started); volume 3 discusses phase II (collecting data); volume 4 discusses analysis and priorities; and volume 5 discusses phase III (taking action).

Laurie Stevahn and Jean A. King are the authors of this volume. In chapter 3, they discuss strategies for the action plan using facilitation procedures that promote positive relationships, develop shared understanding, prioritize decisions, and assess progress. They warn of interpersonal conflict and caution against roadblocks that impede change efforts. They also promote the development of evaluation activities at the onset of the NA because that helps ensure the use of the findings.

Needs assessment is a political experience. Some one (or ones) will feel disenfranchised, loose resources, have programs ended. These activities create hard feelings and resentments. These considerations need to be identified and discussed at the beginning of the process. It is like the elephant and the blind people–everyone has an image of what the creature is, there may or may not be consensus, yet for the NA to be successful, consensus is important. Without it, the data will sit on someone’s shelf or in someone’s computer. Not useful.

…that there is a difference between a Likert item and a Likert scale?**

Did you know that a Likert item was developed by Rensis Likert, a psychometrician and an educator?

And that the item was developed to have the individual respond to the level of agreement or disagreement with a specific phenomenon?

And did you know that most of the studies on Likert items use a five- or seven-points on the item? (Although sometimes a four- or six-point scale is used and that is called a forced-choice approach–because you really want an opinion, not a middle ground, also called a neutral ground.)

And that the choices in an odd-number choice usually include some variation on the following theme, “Strongly disagree”, “Disagree”, “Neither agree or disagree”, “Agree”, “Strongly Agree”?

And if you did, why do you still write scales, and call them Likert, asking for information using a scale that goes from “Not at all” to “A little extent” to “Some extent” to “Great extent? Responses that are not even remotely equidistant (that is, have equal intervals with respect to the response options) from each other–a key property of a Likert item.

And why aren’t you using a visual analog scale to get at the degree of whatever the phenomenon is being measured instead of an item for which the points on the scale are NOT equidistant? (For more information on a visual analog scale see a brief description here or Dillman’s book.)

I sure hope Rensis Likert isn’t rolling over in his grave (he died in 1981 at the age of 78).

Extension professionals use survey as the primary method for data gathering. The choice of survey is a defensible one. However, the format of the survey, the question content, and the question construction must also be defensible. Even though psychometric properties (including internal consistency, validity, and other statistics) may have been computed, if the basic underlying assumptions are violated, no psychometric properties will compensate for a poorly designed instrument, an instrument that is not defensible.

All Extension professionals who choose to use survey to evaluate their target audiences need to have scale development as a personal competency. So take it upon yourself to learn about guidelines for scale development (yes, there are books written on the subject!).

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**Likert scale is the SUM of of responses on several Likert items. A Likert item is just one 4 -, 5-, 6, or 7-point single statement asking for an opinion.

Reference: Devellis, R. F. (1991). Scale development: Theory and applications. Newbury Park: Sage Publications. Note: there is a newer edition.

Dillman, D. A, Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored design method. (3rd ed.). Hoboken, NJ: John Wiley& Sons, Inc.

Last week, I spoke about how to questions and applying them to program planning, evaluation design, evaluation implementation, data gathering, data analysis, report writing, and dissemination. I only covered the first four of those topics. This week, I’ll give you my favorite resources for data analysis.

This list is more difficult to assemble. This is typically where the knowledge links break down and interest is lost. The thinking goes something like this. I’ve conducted my program, I’ve implemented the evaluation, now what do I do? I know my program is a good program so why do I need to do anything else?

YOU need to understand your findings. YOU need to be able to look at the data and be able to rigorously defend your program to stakeholders. Stakeholders need to get the story of your success in short clear messages. And YOU need to be able to use the findings in ways that will benefit your program in the long run.

Remember the list from last week? The RESOURCES for EVALUATION list? The one that says:

1. Contact your evaluation specialist.

2. Listen to stakeholders–that means including them in the planning.

3. Read

Good. This list still applies, especially the read part. Here are the readings for data analysis.

First, it is important to know that there are two kinds of data–qualitative (words) and quantitative (numbers). (As an aside, many folks think words that describe are quantitative data–they are still words even if you give them numbers for coding purposes, so treat them like words, not numbers).

Qualitative data analysis. When I needed to learn about what to do with qualitative data, I was given Miles and Huberman’s book. (Sadly, both authors are deceased so there will not be a forthcoming revision of their 2nd edition, although the book is still available.)

Citation: Miles, M. B., & Huberman, A. Michael. (1994). Qualitative data analysis: An expanded source book. Thousand Oaks, CA: Sage Publications.

Fortunately, there are newer options, which may be as good. I will confess, I haven’t read them cover to cover at this point (although they are on my to-be-read pile).

Citation: Saldana, J. (2009). The coding manual for qualitative researchers. Los Angeles, CA: Sage.

Bernard, H. R. & Ryan, G. W. (2010). Analyzing qualitative data. Los Angeles, CA: Sage.

If you don’t feel like tackling one of these resources, Ellen Taylor-Powell has written a short piece (12 pages in PDF format) on qualitative data analysis.

There are software programs for qualitative data analysis that may be helpful (Ethnograph, Nud*ist, others). Most people I know prefer to code manually; even if you use a soft ware program, you will need to do a lot of coding manually first.

Quantitative data analysis. Quantitative data analysis is just as complicated as qualitative data analysis. There are numerous statistical books which explain what analyses need to be conducted. My current favorite is a book by Neil Salkind.

Citation: Salkind, N. J. (2004). Statistics for people who (think they) hate statistics. (2nd ed. ). Thousand Oaks, CA: Sage Publications.

NOTE: there is a 4th ed. with a 2011 copyright available. He also has a version of this text that features Excel 2007. I like Chapter 20 (The Ten Commandments of Data Collection) a lot. He doesn’t talk about the methodology, he talks about logistics. Considering the logistics of data collection is really important.

Also, you need to become familiar with a quantitative data analysis software program–like SPSS, SAS, or even Excel. One copy goes a long way–you can share the cost and share the program–as long as only one person is using it at a time. Excel is a program that comes with Microsoft Office. Each of these has tutorials to help you.

A part of my position is to build evaluation capacity. This has many facets–individual, team, institutional.

One way I’ve always seen as building capacity is knowing where to find the answer to the how to questions. Those how to questions apply to program planning, evaluation design, evaluation implementation, data gathering, data analysis, report writing, and dissemination. Today I want to give you resources to build your tool box. These resources build capacity only if you use them.

RESOURCES for EVALUATION

1. Contact your evaluation specialist.

2. Listen to stakeholders–that means including them in the planning.

3. Read.

If you don’t know what to read to give you information about a particular part of your evaluation, see resource Number 1 above. For those of you who do not have the luxury of an evaluation specialist, I’m providing some reading resources below (some of which I’ve mentioned in previous blogs).

1. For program planning (aka program development): Ellen Taylor-Powell’s web site at the University of Wisconsin Extension. Her web site is rich with information about program planning, program development, and logic models.

2. For evaluation design and implementation: Jody Fitzpatrick”s book.

Citation: Fitzpatrick, J. L., Sanders, J. R., & Worthen, B. R. (2004). Program evaluation: Alternative approaches and practical guidelines. (3rd ed.). Boston: Pearson Education, Inc.

3. For evaluation methods, that depends on the method you want to use for data gathering; it doesn’t cover the discussion of evaluation design, though.

For needs assessment, the books by Altschuld and Witkin (there are two).

(Yes, needs assessment is an evaluation activity).

Citation: Witkin, B. R. & Altschuld, J. W. (1995). Planning and conducting needs assessments: A practical guide. Thousand Oaks, CA: Sage Publications.

Citation: Altschuld, J. W. & Witkin B. R. (2000). From needs assessment to action: Transforming needs into solution strategies. Thousand Oaks, CA: Sage Publications, Inc.

For survey design: Don Dillman’s book.

Citation: Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored design method. (3rd. ed.). Hoboken, New Jersey: John Wiley & Son, Inc.

For focus groups: Dick Krueger’s book.

Citation: Krueger, R. A. & Casey, M. A. (2000). Focus groups: A practical guide for applied research. (3rd. ed.). Thousand Oaks, CA: Sage Publications, Inc.

For case study: Robert Yin’s classic OR

Bob Brinkerhoff’s book.

Citation: Yin, R. K. (2009). Case study research: Design and methods. (4th ed.). Thousand Oaks, CA: Sage, Inc.

Citation: Brinkerhoff, R. O. (2003). the success case method: Find out quickly what’s working and what’s not. San Francisco: Berrett-Koehler Publishers, Inc.

For multiple case studies: Bob Stake’s book.

Citation: Stake, R. E. (2006). Multiple case study analysis. New York: The Guilford Press.

Since this post is about capacity building, a resource for evaluation capacity building:

Hallie Preskill and Darlene Russ-Eft’s book .

Citation: Preskill, H. & Russ-Eft, D. (2005). Building Evaluation Capacity: 72 Activities for teaching and training. Thousand Oaks, CA: Sage Publications.

I’ll cover reading resources for data analysis, report writing, and dissemination another time.

There has been a lot of buzz recently about the usefulness of the Kirkpatrick model.

I’ve been talking about it (in two previous posts) and so have others. This model has been around a long time and has continued to be useful in the training field. Extension does a lot of training. Does that mean this model should be used exclusively when training is the focus? I don’t think so. Does this model have merits. I think so. Could it be improved upon? That depends on the objective of your program and your evaluation, so probably.

If you want to know about whether your participants react favorably to the training, then this model is probably useful.

If you want to know about the change in knowledge, skills, attitudes, then this model may be useful. You would need to be careful because knowledge is a slippery concept to measure.

If you want to know about the change in behavior, probably not. Kirkpatrick on the website says that application of learning is what is measured in the behavioral stage. How do you observe behavior change at a training? Observation is the obvious answer here and one does not necessarily observe behavior change at a training. Intention to change is not mentioned in this level.

If you want to know what difference you made in the social, economic, and/or environmental conditions in which your participants live, work, and practice, then the Kirkpatrick model won’t take you there. The 4th level (which is where evaluation starts for this model, according to Kirkpatrick) says: To what degree targeted outcomes occur as a result of the training event and subsequent reinforcement. I do not see this as condition change or what I call impact.

A faculty member asked me for specific help in assessing impact. First, one needs to define what is meant by impact. I use the word to mean change in social, environmental, and/or economic conditions over the long run. This means changes in social institutions like family, school, employment (social conditions). It means changes in the environment which may be clean water or clean air OR it may mean removing the snack food vending machine from the school (environmental conditions). It means changes in some economic indicator, up or down, like return on investment, change in employment status, or increase revenue (economic conditions). This doesn’t necessarily mean targeted outcomes of the training event.

I hope that any training event will move participants to a different place in their thinking and acting that will manifest in the LONG RUN in changes in one of the three conditions mentioned above. To get there, one needs to be specific in what one is asking the participants. Intention to change doesn’t necessarily get to impact. You could anticipate impact if participants follow through with their intention. The only way to know that for sure is to observe it. We approximate that by asking good questions.

What questions are you asking about condition change to get at impacts of your training and educational programs?

Next week: TIMELY TOPIC. Any suggestions?

You’ve developed your program. You think you’ve met a need. You conduct an evaluation. Low and behold! Some of your respondents give you such negative feedback you wonder what program they attended. Could it really have been your program?

This is the phenomena I call “all of the people all of the time”, which occurs regularly in evaluating training programs. And it has to do with use–what you do with the results of this evaluation. And you can’t do it–please all of the people all of the time, that is. There will always be some sour grapes. In fact, you will probably have more negative comments than positive comments. People who are upset want you to know; people are happy are just happy.

Now, I’m sure you are really confused. Good. At least I’ve got your attention and maybe you’ll read to the end of today’s post.

You have seen this scenario: You ask the participants for formative data so that you can begin planning the next event or program. You ask about the venue, the time of year, the length of the conference, the concurrent offerings, the plenary speakers. Although some of these data are satisfaction data (the first level, called Reaction, in Don Kirkpatrick’s training model and the Reaction category in Claude Bennett’s TOPs Hierarchy [see diagram]

they are important part of formative evaluation; an important part of program planning. You are using the evaluation report. That is important. You are not asking if the participants learned something. You are not asking if they intend to change their behavior. You are not asking about what conditions have changed. You only want to know about their experience in the program.

What do you do with the sour grapes? You could make vinegar, only that won’t be very useful and use is what you are after. Instead, sort the data into those topics over which you have some control and those topics over which you have no control. For example–you have control over who is invited to be a plenary speaker, if there will be a plenary speaker, how many concurrent sessions, who will teach those concurrent sessions; you have no control over the air handling at the venue, the chairs at the venue, and probably, the temperature of the venue.

You can CHANGE those topics over which you have control. Comments say the plenary speaker was terrible. Do not invite that person to speak again. Feedback says that the concurrent sessions didn’t provide options for classified staff, only faculty. Decide the focus of your program and be explicit in the program promotional materials–advertise it explicitly to your target audience. You get complaints about the venue–perhaps there is another venue; perhaps not.

You can also let your audience know what you decided based on your feedback. One organization for which I volunteered sent out a white paper with all the concerns and how the organization was addressing them–or not. It helped the grumblers see that the organization takes their feedback seriously.

And if none of this works…ask yourself: Is it a case of all of the people all of the time?

Although I have been learning about and doing evaluation for a long time, this week I’ve been searching for a topic to talk about. A student recently asked me about the politics of evaluation–there is a lot that can be said on that topic, which I will save for another day. Another student asked me about when to do an impact study and how to bound that study. Certainly a good topic, too, though one that can wait for another post. Something I read in another blog got me thinking about today’s post. So, today I want to talk about gathering demographics.

Last week, I mentioned in my TIMELY TOPIC post about the AEA Guiding Principles. Those Principles along with the Program Evaluation Standards make significant contributions in assisting evaluators in making ethical decisions. Evaluators make ethical decisions with every evaluation. They are guided by these professional standards of conduct. There are five Guiding Principles and five Evaluation Standards. And although these are not proscriptive, they go along way to ensuring ethical evaluations. That is a long introduction into gathering demographics.

The guiding principle, Integrity/Honesty states that “Evaluators display honesty and integrity in their own behavior, and attempt to ensure the honesty and integrity of the entire evaluation process.” When we look at the entire evaluation process, as evaluators, we must strive constantly to maintain both personal and professional integrity in our decision making. One decision we must make involves deciding what we need/want to know about our respondents. As I’ve mentioned before, knowing what your sample looks like is important to reviewers, readers, and other stakeholders. Yet, if we gather these data in a manner that is intrusive, are we being ethical?

Joe Heimlich, in a recent AEA365 post, says that asking demographic questions “…all carry with them ethical questions about use, need, confidentiality…” He goes on to say that there are “…two major conditions shaping the decision to include – or to omit intentionally – questions on sexual or gender identity…”:

When such data would further our understanding of the effect or the impact of a program, treatment, or event.
When asking for such data would benefit the individual and/or their engagement in the evaluation process.

The first point relates to gender role issues–for example are gay men more like or more different from other gender categories? And what gender categories did you include in your survey? The second point relates to allowing an individual’s voice to be heard clearly and completely and have categories on our forms reflect their full participation in the evaluation. For example, does marital status ask for domestic partnerships as well as traditional categories and are all those traditional categories necessary to hear your participants?

The next time you develop a questionnaire that includes demographic questions, take a second look at the wording–in an ethical manner.

Hello, readers. This week I’m doing something different with this blog. This week, and the third week in each month from now on, I’ll be posting a column called Timely Topic. This will be a post on a topic that someone (that means you reader) has suggested. A topic that has been buzzing around in conversations. A topic that has relevance to evaluation. This all came about because a colleague from another land grant institution is concerned about the dearth of evaluation skills among Extension colleagues. (Although this comment makes me wonder to whom this colleague is talking, that question is content for another post, another day.) So thinking about how to get core evaluation information out to more folks, I decided to devote one post a month to TIMELY TOPICS. To day’s post is about “THINKING CAREFULLY”.

Recently, I’ve been asked to review a statistics text book for my department. This particular book uses a program that is available on everyone’s computer. The text has some important points to make and today’s post reflects one of those points. The point is thinking carefully about using statistics.

As an evaluator–if only the evaluator of your own programs–you must think critically about the “…context of the data, the source of the data, the method used in data collection, the conclusions reached, and the practical implications” (Triola, 2010, p. 18). The author posits that to understand general methods of using sample data; make inferences about populations; understand sampling and surveys; and important measures of key characteristics of data, as well as the use of valid statistical methods, one must recognize the misuse of statistics.

I’m sure all of you have heard the quote, “Figures don’t lie; liars figure,” which is attributed to Mark Twain. I’ve always heard the quote as “Statistics lie and liars use statistics.” Statistics CAN lie. Liars CAN use statistics. That is where thinking carefully comes in–to determine if the statistical conclusions being presented are seriously flawed.

As evaluators, we have a responsibility (according to the AEA guiding principles) to conduct systematic, data-based inquiry; provide competent performance; display honesty and integrity…of the entire evaluation process; respect the security, dignity, and self-worth of all respondents; and consider the diversity of the general and public interests and values. This demands that we think carefully about the reporting of data. Triola cautions, “Do not use voluntary response sample data for making conclusions about a population.” How often have you used data from individuals who decide themselves (self-selected) whether to participate in your survey or not? THINK CAREFULLY about your sample. These data cannot be generalized to all people like your respondents because of the bias that is introduced by self-selection.

Other examples of misuse of statistics include

using correlation for concluding causation;
reporting data that involves a sponsors product;
identifying respondents inappropriately;
reporting data that is affected with a desired response bias;
using small samples to draw conclusions for large groups;
implying that being precise is being accurate; and
reporting misleading or unclear percentages. (This cartoon was drawn by Ben Shabad.)

When reporting statistics gathered from your evaluation, THINK CAREFULLY.

Evaluation is an Everyday Activity

Program Evaluation Discussions

Tag Archives: Data collection

TIMELY TOPIC: PRE-POST or POST THEN PRE?

Conference evaluation

Needs Assessment

Did you know…

More resources

How do you find the answer?

Impact or not?

All of the people all of the time?

Demographics

TIMELY TOPIC: Thinking carefully

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