LESSON 39 - QUESTIONNAIRES: TYPES OF INFORMATION & DESIGNS OF CONSTRUCTING A QUESTIONNAIRE

A well-designed questionnaire depends less on clever wording and more on getting usable data: enough questionnaires come back, respondents finish them fully, and the answers are honest and accurate. That practical focus—response rate, completion rate, and response validity—drives every design choice, because weak returns or incomplete/invalid responses can’t produce credible findings for the research problem.

A questionnaire itself is defined as a set of standardized questions (items) meant to collect information from respondents. It can be self-administered, with respondents completing it independently, or administered by reading the questions aloud—when that happens, the instrument functions more like an interview schedule. The lesson also draws a clear line between “questions of research” (the questionnaire items and other instrument questions) and “research questions” (the investigative questions meant to solve the research problem). Confusing the two leads to misaligned instruments.

The questionnaire must target specific types of information tied to the study’s variables and conceptual framework. First are demographic information items—background details such as gender, marital status, education, and age—only when those details are relevant to the research problem. Second are knowledge questions that measure what respondents know about an issue; for example, assessing consumer awareness of counterfeit drugs. Third are attitude items, which capture liking or disliking toward a concept and are typically measured using a Likert scale. Fourth are self-perception questions that ask respondents to evaluate their own behavior or ability relative to others, such as rating their ability to identify counterfeit drugs; that’s not knowledge, but perceived competence.

Designing the questionnaire involves choosing between closed-ended and open-ended formats. Closed-ended questions provide prepared lists of concrete questions and response options, making analysis easier but risking bias because respondents must select from researcher-provided alternatives. Adding an “other” option can reduce forced-choice problems. Open-ended questions let respondents express thoughts freely, such as asking for recommendations to improve online learning.

To keep questionnaires effective, the lesson sets out do’s and don’ts for question construction. General rules include aligning every item with the research questions and conceptual framework, ensuring the question clearly states what information is needed, and testing clarity by asking what the respondent would understand before fielding it. Specific rules emphasize plain language, avoiding double-barreled items (questions that demand two answers at once), using neutral and non-offensive wording, and minimizing negative wording that can confuse interpretation. The lesson also warns against response-set pitfalls, where respondents detect patterns and answer consistently in the same direction; staggering items can help. Rating scales should be used consistently across the instrument, questionnaires should be brief and avoid duplication (often refined through piloting), and vague frequency terms like “often” or “regularly” should be replaced with actual frequency measures. Finally, questions should be specific rather than overly general, and items should not combine two assumptions or two questions in one prompt.

Overall, the lesson frames questionnaire construction as a chain: define the needed information types, choose question designs, and apply strict wording rules so the resulting instrument produces returned, completed, and valid data for answering the research problem. Next steps point toward demonstrating how to develop questionnaire items.