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QUESTIONNAIRE DESIGN
Questionnaires are an inexpensive way to gather data from a potentially large number of respondents. Often they are the only feasible way to reach a number of reviewers large enough to allow statistical analysis of the results. A well-designed questionnaire that is used effectively can gather information on both the overall performance of the test system as well as information on specific components of the system. If the questionnaire includes demographic questions on the participants, they can be used to correlate performance and satisfaction with the test system among different groups of users.
It is important to remember that a questionnaire should be viewed as a multi-stage process beginning with definition of the aspects to be examined and ending with interpretation of the results. Every step needs to be designed carefully because the final results are only as good as the weakest link in the questionnaire process. Although questionnaires may be cheap to administer compared to other data collection methods, they are every bit as expensive in terms of design time and interpretation.
The steps required to design and administer a questionnaire include:
This document will concentrate on how to formulate objectives and write the questionnaire. Before these steps are examined in detail, it is good to consider what questionnaires are good at measuring and when it is appropriate to use questionnaires.
What can questionnaires measure?
Questionnaires are quite flexible in what they can measure, however they are not equally suited to measuring all types of data. We can classify data in two ways, Subjective vs. Objective and Quantitative vs. Qualitative.
When a questionnaire is administered, the researchers control over the environment will be somewhat limited. This is why questionnaires are inexpensive to administer. This loss of control means the validity of the results are more reliant on the honesty of the respondent. Consequently, it is more difficult to claim complete objectivity with questionnaire data then with results of a tightly controlled lab test. For example, if a group of participants are asked on a questionnaire how long it took them to learn a particular function on a piece of software, it is likely that they will be biased towards themselves and answer, on average, with a lower than actual time. A more objective usability test of the same function with a similar group of participants may return a significantly higher learning time. More elaborate questionnaire design or administration may provide slightly better objective data, but the cost of such a questionnaire can be much higher and offset their economic advantage. In general, questionnaires are better suited to gathering reliable subjective measures, such as user satisfaction, of the system or interface in question.
Questions may be designed to gather either qualitative or quantitative data. By their very nature, quantitative questions are more exact then qualitative. For example, the word "easy" and "difficult" can mean radically different things to different people. Any question must be carefully crafted, but in particular questions that assess a qualitative measure must be phrased to avoid ambiguity. Qualitative questions may also require more thought on the part of the participant and may cause them to become bored with the questionnaire sooner. In general, we can say that questionnaires can measure both qualitative and quantitative data well, but that qualitative questions require more care in design, administration, and interpretation.
When to use a questionnaire?
There is no all encompassing rule for when to use a questionnaire. The choice will be made based on a variety of factors including the type of information to be gathered and the available resources for the experiment. A questionnaire should be considered in the following circumstances.
I. Defining the Objectives of the Survey
The importance of well-defined objectives cannot be over emphasized. A questionnaire that is written without a clear goal and purpose is inevitably going to overlook important issues and waste participants' time by asking useless questions. The questionnaire may lack a logical flow and thereby cause the participant to lose interest. Consequential, what useful data you may have collected could be further compromised. The problems of a poorly defined questionnaire do not end here, but continue on to the analysis stage. It is difficult to imagine identifying a problem and its cause, let alone its solution, from responses to broad and generalizing questions. In other words, how would it be possible to reach insightful conclusions if one didn't actually know what they had been looking for or planning to observe.
An objective such as "to identify points of user dissatisfaction with the interface and how these negatively affect the software's performance" may sound clear and to the point, but it is not. The questionnaire designer must clarify what is meant by user dissatisfaction. Is this dissatisfaction with the learning of the software, the power of the software, of the ease of learning the software? Is it important for the users to learn the software quickly if they learn it well? What is meant by the software's performance? How accurate must the measurements be? All of these issues must be narrowed and focused before a single question is formulated. A good rule of thumb is that if you are finding it difficult to write the questions, then you haven't spent enough time defining the objectives of the questionnaire. Go back and do this step again. The questions should follow quite naturally from the objectives.
II. Writing the Questionnaire
At this point, we assume that we have already decided what kind of data we are to measure, formulated the objectives of the investigation, and decided on a participant group. Now we must compose our questions.
If the preceding steps have been faithfully executed, most of the questions will be on obvious topics. Most questionnaires, however, also gather demographic data on the participants. This is used to correlate response sets between different groups of people. It is important to see whether responses are consistent across groups. For example, if one group of participants is noticeably less satisfied with the test interface, it is likely that the interface was designed without fair consideration of this group's specific needs. This may signify the need for fundamental redesign of the interface. In addition, certain questions simply may only be applicable to certain kinds of users. For example, if one is asking the participants whether they find the new tutorial helpful, we do not want to include in our final tally the responses of experienced users who learned the system with an older tutorial. There is no accurate way to filter out these responses without simply asking the users when they learned the interface.
Typically, demographic data is collected at the beginning of the questionnaire, but such questions could be located anywhere or even scattered throughout the questionnaire. One obvious argument in favor of the beginning of the questionnaire is that normally background questions are easier to answer and can ease the respondent into the questionnaire. One does not want to put off the participant by jumping in to the most difficult questions. We are all familiar with such kinds of questions.
It is important to ask only those background questions that are necessary. Do not ask income of the respondent unless there is at least some rational for suspecting a variance across income levels. There is often only a fine line between background and personal information. You do not want to cross over in to the personal realm unless absolutely necessary. If you need to solicit personal information, phrase your questions as unobtrusively as possible to avoid ruffling your participants and causing them to answer less than truthfully.
What kind of questions do we ask?
In general, there are two types of questions one will ask, open format or closed format.
Open format questions are those that ask for unprompted opinions. In other words, there are no predetermined set of responses, and the participant is free to answer however he chooses. Open format questions are good for soliciting subjective data or when the range of responses is not tightly defined. An obvious advantage is that the variety of responses should be wider and more truly reflect the opinions of the respondents. This increases the likelihood of you receiving unexpected and insightful suggestions, for it is impossible to predict the full range of opinion. It is common for a questionnaire to end with and open format question asking the respondent for her unabashed ideas for changes or improvements.
Open format questions have several disadvantages. First, their very nature requires them to be read individually. There is no way to automatically tabulate or perform statistical analysis on them. This is obviously more costly in both time and money, and may not be practical for lower budget or time sensitive evaluations. They are also open to the influence of the reader, for no two people will interpret an answer in precisely the same way. This conflict can be eliminated by using a single reader, but a large number of responses can make this impossible. Finally, open format questions require more thought and time on the part of the respondent. Whenever more is asked of the respondent, the chance of tiring or boring the respondent increases.
Closed format questions usually take the form of a multiple-choice question. They are easy for the respondent, give
There is no clear consensus on the number of options that should be given in an closed format question. Obviously, there needs to be sufficient choices to fully cover the range of answers but not so many that the distinction between them becomes blurred. Usually this translates into five to ten possible answers per questions. For questions that measure a single variable or opinion, such as ease of use or liability, over a complete range (easy to difficult, like to dislike), conventional wisdom says that there should be an odd number of alternatives. This allows a neutral or no opinion response. Other schools of thought contend that an even number of choices is best because it forces the respondent to get off the fence. This may induce the some inaccuracies for often the respondent may actually have no opinion. However, it is equally arguable that the neutral answer is over utilized, especially by bored questionnaire takers. For larger questionnaires that test opinions on a very large number of items, such as a music test, it may be best to use an even number of choices to prevent large numbers of no-thought neutral answers.
Closed format questions offer many advantages in time and money. By restricting the answer set, it is easy to calculate percentages and other hard statistical data over the whole group or over any subgroup of participants. Modern scanners and computers make it possible to administer, tabulate, and perform preliminary analysis in a matter of days. Closed format questions also make it easier to track opinion over time by administering the same questionnaire to different but similar participant groups at regular intervals. Finally closed format questions allow the researcher to filter out useless or extreme answers that might occur in an open format question.
Whether your questions are open or closed format, there are several points that must by considered when writing and interpreting questionnaires:
To this end, it is best to phrase your questions empirically if possible and to avoid the use of necessary adjectives. For example, it asking a question about frequency, rather than supplying choices that are open to interpretation such as:
It is better to quantify the choices, such as:
There are other more subtle aspects to consider such as language and culture. Avoid the use of colloquial or ethnic expressions that might not be equally used by all participants. Technical terms that assume a certain background should also be avoided.
A less blatant example would be a Yes/No question that asked:
* Is this the best CAD interface you have ever used?
In this case, even if the participant loved the interface, but had a favorite that was preferred, she would be forced to answer No. Clearly, the negative response covers too wide a range of opinions. A better way would be to ask the same question but supply the following choices:
This example is also poor in the way it asks the question. Its choice of words makes it a leading question and a good example for the next section on phrasing.
In the above example of "Is this the best CAD interface you have ever used?" clearly "best" has strong overtones that deny the participant an objective environment to consider the interface. The signal sent the reader is that the designers surely think it is the best interface, and so should everyone else. Though this may seem like an extreme example, this kind of superlative question is common practice.
A more subtle, but no less troublesome, example can be made with verbs that have neither strong negative or positive overtones. Consider the following two questions:
They both ask the same thing, but will likely produce different data. One asks in a positive way, and the other in a negative. It is impossible to predict how the outcomes will vary, so one method to counter this is to be aware of different ways to word questions and provide a mix in your questionnaire. If the participant pool is very large, several versions may be prepared and distributed to cancel out these effects.
This forces the respondent to give thought to something he may have never considered. This does not produce clear and consistent data representing real opinion. Do not ask hypothetical questions.
There is little that can be done to prevent prestige bias. Sometimes there just is no way to phrase a question so that all the answers are noble. The best means to deal with prestige bias is to make the questionnaire as private as possible. Telephone interviews are better than person-to-person interviews, and written questionnaires mailed to participants are even better still. The farther away the critical eye of the researcher is, the more honest the answers.
Now What?
Now that you've completed you questionnaire, you are still not ready to send it out. Just like any manufactured product, your questionnaire needs to go through quality testing. The major hurdle in questionnaire design is making it clear and understandable to all. Though you have taken great care to be clear and concise, it is still unreasonable to think that any one person can anticipate all the potential problems. Just as a usability test observes a test user with the actual interface, you must observe a few test questionnaire takers. You will then review the questionnaire with the test takers and discuss all points that were in any way confusing and work together to solve the problems. You will then produce a new questionnaire. It is possible that this step may need to be repeated more than once depending on resources and the need for accuracy.
Conclusions
Questionnaire design is a long process that demands careful attention. A questionnaire is a powerful evaluation tool and should not be taken lightly. Design begins with an understanding of the capabilities of a questionnaire and how they can help your research. If it is determined that a questionnaire is to be used, the greatest care goes into the planning of the objectives. Questionnaires are like any scientific experiment. One does not collect data and then see if they found something interesting. One forms a hypothesis and an experiment that will help prove or disprove the hypothesis.
Questionnaires are versatile, allowing the collection of both subjective and objective data through the use of open or closed format questions. Modern computers have only made the task of collecting and extracting valuable material more efficient. However, a questionnaire is only as good as the questions it contains. There are many guidelines that must be met before you questionnaire can be considered a sound research tool. The majority deal with making the questionnaire understandable and free of bias. Mindful review and testing is necessary to weed out minor mistakes that can cause great changes in meaning and interpretation. When these guidelines are followed, the questionnaire becomes a powerful and economic evaluation tool.