One of the most effective tools to get to know the level of customer satisfaction, employee engagement, or academic research results is survey. Central to most good surveys is the Likert scale, a mere-but-effective way to gauge opinions, attitudes and perceptions. Properly applied, Likert scales can give useful information that enables making data-based organizational decisions.
Nevertheless, the best you can get is what you design your questionnaire, in terms of quality of data you collect. Weakly formed Likert scale questionnaires scales may mislead respondents, breed bias and render the results inauthentic. On one hand, by adopting a well-thought-out questionnaire, consistency, reliability and meaningful analysis of responses are guaranteed.
This blog will examine best practices in design as well as in administration of Likert scale questionnaires, including writing clear questions, putting wording on the response choices, the use of response categories, typical pitfalls to avoid, and the evaluation of results. You will finish with a useful guide to how to construct a survey so that it is user friendly and at the same time statistically sound.
Likert Scale Survey Design
How to Write Likert Scale Questions
One of the most crucial things in terms of Likert scale questionnaires survey design is the wording of your questions. An excellent question must have one concept, must sound neutral and must be free of ambiguity. As an example, instead of asking how satisfied one is with our product and customer service, split them into two; question one relates to the quality of products and the other question is about customer service. This makes the responses valid since results are not mixed in the answers.
Effective Survey Questionnaire Tips
The other best practice is to maintain a brief Likert scale questionnaires. The Likert scales can be easily filled out but the length of the survey can normally result to the risk of respondent fatigue and may cause low completion rates and careless responses. Question formulation should be limited to the most essential questions. Repetition of words is also important-words must be kept short, recognized, and easily comprehended by your audience. To a novice or a general reader, jargon use does not help in making the survey understandable and the chances of responsive answers also get reduced.
Likert Scale Formatting Guide
Response Scale Consistency
Consistency is one of the golden rules in formatting Likert scale questionnaires. It would be better to use the same scale throughout the total questionnaire in case you decide that 5-points is the most convenient one. Using both five-point and seven-point scales in such a one survey will be confusing and analysis of data will be a challenge. The consistency enables the respondents to have a rhythm when answering in it and can have any results compared among items.
Neutral Option in Likert Scales
A debate on survey design is whether neutral option is to include or not. A middle option, like neither agree nor disagree, may give the respondent an honest option in case he is indifferent. But, forced-choice (with or without neutral option) may work better when the desired outcome is to push respondents to take a stance. The choice will have to be made depending upon what your survey is to be used. Academic researchers tend to include a neutral point as an indication of all possible attitude shades whereas business tends to leave this point out in order to obtain more practical feedback.
Balanced Likert Scale Examples
A good Likert scale should be balanced one, with the same number of negative and positive answers. As an illustration, in a scale of 5, strongly disagree, disagree, neutral, agree, and strongly agree, there are two positive, two negative and one neutral. An unbalanced scale e.g. three positive and only one negative options slants the responses and lowers reliability. Moderate constructions add faith to the mix and make data interpretation more accurate.
Best Likert Scale Layout Practices
Questionnaire Development Process
All the process of compiling your likert scale questionnaires must begin with an objective definition of your research. Ask yourself: what do you want to measure: satisfaction, agreement, or frequency? When you have worked out your constructs, then create items that represent them specifically. Each of them is supposed to represent a single dimension that can be measured. When a draft is ready, organize a pilot test of the material on a small group to locate obvious language gaps, scales that can be misunderstood, or technical problems. Pilot testing is time-saving since it eliminates the errors before implementing it in full.
Best Likert Scale Layout Practices
Layout is also relevant for the quality of data. Organize the questions in groups to form a flow such that it begins with the easier ones before proceeding to the sensitive ones. Do not make the design cluttered make sure to space the questions evenly. Where possible, it must use digital means such as progress tracking to allow respondents know how far they are in the survey. Good design of user interface decreases the amount of cognitive load on the user and increases the completion rate..
5-Point vs 7-Point Scales in Practice
The first is the number of response points when Likert surveys are designed. The most commonly employed is the 5-point scale since it is easy to understand and use and prevents fatigue. It can be used with significant effect when approaching mass consumers or performing mass consumer studies.
The 7-point scale is more subtle and accurate though. It is also desirable when you need to record minor variations in opinions or attitudes, especially those conducted by academicians or psychologists. Each of the two can be advantageous, and the decision is based on what you are looking to achieve using the survey. Less complicated surveys will have an advantage of five points whereas more complicated ones will have to include seven.
How to Analyze Likert Scale Data
Your analysis of Likert responses relies on whether you code them as ordinal or interval data. When analyzed as ordinal, emphasize on medians, modes and the non-parametric tests like the Mann-Whitney U and Kruskal-Wallis test. Such a strategy does not presuppose the same distances between categories.
When you treat Likert data as interval data, it is possible to compute means and standard deviations, and even correlate and regress such data. This methodology is typical of social research, particularly in the case where several Likert items are used together as a score. Irrespective of approach, data coding consistency and constancy in scale structure is prerequisite to proper outcomes.
Common Errors in Likert Scale Surveys
The process of designing a likert scale questionnaires can be fairly straightforward, but it may be undermined by some of the errors. The most typical errors are the following:
- Double-barreled questions: This is where the asking of two ideas in one question occurs (e.g., “How satisfied are you with our product and service to the customers?”). This distorts the answers and makes it unreliable.
- Leading or biased wording: Leading questions encourage and corner the respondent to give a particular answer by the use of words like “Would you not agree that our service is excellent?”
- Unclear instructions: Confusing instructions such as unfamiliar terms may lead the respondents to give inappropriate answers.
- Inconsistent scale lengths: Combining five or seven-point scales in a questionnaire makes comparisons difficult and confusing to the respondents.
- Unbalanced scales: It is important not to provide a more positive than a negative alternative because it skews the results and lowers validity.
- Overly long surveys: Both lengthy and repetitive surveys contribute to response fatigue, where the person filling in the survey may be in a hurry and will therefore give haphazard responses.
The best way to avoid the pitfalls of Likert surveys is to pilot test them before the full deployment and thus make sure your Likert surveys will provide you with accurate, reliable, and actionable data.
Conclusion
Creating an efficient Likert scale questionnaires must be considerate of the detail. Asking clear questions and selecting the suitable response scale are steps that can be of a high time-consuming nature, but consistency and avoidance of bias are also crucial and can affect the quality of the results. Neutral choices, non-complicated design, and format will enable the respondents to give sincere responses, whereas the pilot test guarantees that any problems will be eliminated beforehand.
These are the best practices of Likert scale survey design, with the adherence to which you can create credible surveys. No matter what customer satisfaction, employee, academic or any other variable you are surveying, a properly designed Likert survey will improve the quality of data, make the respondent experience more positive, and lead to better decision making.
FAQ
1: How many Likert points are ideal?
Both 5- and 7-point scales can be used. Five versus seven point scales are less straining and more fatiguing respectively. Your purpose and audience on the survey determine the best choice.
2: Does a Likert scale need a neutral?
A neutral response such as Neither agree nor disagree is handy when you would like to capture an authentic neutrality. A forced-choice scale, however, with no midpoint can be adopted with the idea of promoting a more conclusive answer.
3: What are the pitfalls of Likert scales surveys?
The most common mistakes are the case of a double-barreled question, leading phrase, lack of consistency in response formats, and being too long, which makes fatigue. These errors will detract reliability and may be lessened through pilot testing.
4: How do you analyse Likert scale data?
When treated as ordinal, then emphasis on medians and non-parametric testing. When treated as interval, you can apply averages, correlations, regressions. Many researchers treat cumulatively aggregated Likert scales as interval numbers to allow more sophisticated analysis.
