Suppose you are creating a questionnaire to conduct an investigation. How does one decide which response format to use? Many questionnaires use rating scales such as the Likert scale, where one has to indicate how much they agree with a statement (e.g., ‘I make new friends easily’) or on a scale of 1 (strongly disagree) to 5 (strongly agree). One example of how questionnaires measure responses are via semantic differential rating scales.
Millions of flashcards designed to help you ace your studies
Sign up for freeWhat dimension of attitudes do opposite adjectives ‘good–bad’ represent?
What dimension of attitudes do opposite adjectives ‘strong–weak’ represent?
What dimension of attitudes do the two opposite adjectives active-passive represent?
Unlike questionnaires, social desirability is not an issue in semantic differential rating scales. True or false?
Semantic differential rating scales measure views.
In semantic differential rating scales opposing adjectives are used to see how respondents feel about something, true or false.
Are semantic differential rating scales considered a reliable and valid tool?
What type of data do semantic differential rating scales collect?
The semantic differential scale is a rating scale used in questionnaires to assess respondents’ attitudes by examining their associations with concepts.
Rate your feelings about social media between ‘good’ and ‘bad’. Is this an example of a semantic differential rating scale?
What dimension of attitudes do opposite adjectives ‘good–bad’ represent?
What dimension of attitudes do opposite adjectives ‘strong–weak’ represent?
What dimension of attitudes do the two opposite adjectives active-passive represent?
Unlike questionnaires, social desirability is not an issue in semantic differential rating scales. True or false?
Semantic differential rating scales measure views.
In semantic differential rating scales opposing adjectives are used to see how respondents feel about something, true or false.
Are semantic differential rating scales considered a reliable and valid tool?
What type of data do semantic differential rating scales collect?
The semantic differential scale is a rating scale used in questionnaires to assess respondents’ attitudes by examining their associations with concepts.
Rate your feelings about social media between ‘good’ and ‘bad’. Is this an example of a semantic differential rating scale?
Achieve better grades quicker with Premium
Geld-zurück-Garantie, wenn du durch die Prüfung fällst
Review generated flashcards
Start learning or create your own AI flashcards
Team Semantic Differential Rating Scale Teachers
Semantic differential scales are also a type of rating scale. So let us examine what makes semantic differential scales different from other scales and when they are best used.
What do we mean by a semantic differential scale?
A semantic differential scale is a rating scale used in surveys or questionnaires that allows you to indicate how your feelings lie between opposing adjectives on a continuum.
Semantic differential scales do not measure attitudes directly like Likert scales but indirectly by asking you to rate the importance of a concept (such as a product or event) on a continuum.
Likert scales measure attitudes directly by asking a person to indicate the degree of agreement with a particular statement.
Semantic differential scales are based on connotative meanings; they measure what feelings you associate with a concept.
For example, the word school refers to a building or institution, but depending on your experiences and attitudes, the connotations may include feelings of comfort, frustration, support, or isolation.
Figure 1. Connotative meanings reflect our attitudes.
The inventor of the semantic differential scale, Charles Egerton Osgood, distinguished three dimensions of attitudes:
1. Evaluation
2. Potency
3. Activity
Evaluation determines a person’s attitude, usually noting whether they view the subject positively or negatively.
An example response showing how the semantic differential scale evaluates social media includes adding five response options between opposite adjectives (positive-negative).
Fig. 1. Evaluation is used to measure the connotations of attitudes.
Measuring potency indicates how strong the issue we are dealing with is for that person. The highest and lowest points on the scales can indicate potency in terms of excitable to calm, for instance.
Fig. 2. Potency determines how strongly someone feels about something.
Activity indicates how ‘active’ the subject is; one example is one side of the scale indicating active and the opposite end indicating passive.
Fig. 3. measuring activity using semantic differential rating scales can be used to determine how often a consumer exercises after receiving a fitness product.
Semantic difference scales can assess people’s attitudes towards a product.
For example, a new app that helps students learn. Researchers can measure how users evaluate the app (e.g., ‘Useful’–‘Useless’) and rate its potency (‘What impact did the app have on your revision?’, ‘Strong–Weak’).
Semantic differential scales can assess customer satisfaction.
For example, you can ask customers about their feelings about customer service (e.g., ‘How was the staff?’, ‘Helpful–Unhelpful) or the accuracy of the product they purchased (e.g., ‘Accurate–Inaccurate’).
They can also be used to rate your personality traits.
For example, extraversion could be rated based on responses to the statement’ Spending time with large groups of people is:’ on a scale from ‘Exhausting’ to ‘Energising’.
The semantic differential scale advantages are:
Designing appropriate semantic differential scales can be challenging because deciding which adjectives are most appropriate for assessing the concept and which concepts are important to the study is tedious.
The researcher must also decide how many options to include between the two opposing adjectives. Too many options can reduce accuracy, but too few options can reduce the sensitivity of the measurement.
Another problem with semantic differential scales is that participants sometimes find it difficult to rank their views on the continuum and tend to tick only the extreme values.
This is known as extreme response bias.
Semantic differential scales measure subjective attitudes; ticking the same point on a continuum between adjectives may mean different things to different people.
Social desirability bias may influence participants’ responses when measuring socially sensitive concepts such as undesirable behaviour (cheating or stealing) or undesirable views (prejudice).
Social desirability refers to the tendency to respond according to what is desirable rather than our actual attitudes.
Sign up for free to gain access to all our flashcards.
What is the semantic differential scale?
The meaning of semantic differential scale is a rating scale used in questionnaires to indirectly assess respondents’ attitudes by examining their associations with concepts.
What are the advantages of semantic differential scale?
The semantic differential scales advantages are that they are valid and reliable, easy to understand, and accurately reflect respondents’ subjective feelings.
What are the disadvantages of semantic differential scale?
The semantic differential scale disadvantages are a good design of semantic differential scales can be challenging, and they can be prone to response bias like extreme responding or social desirability bias.
What is semantic differential scale examples?
Semantic differential scales require you to rate a concept between two opposite adjectives on a scale. For example, rate your feelings about social media between ‘good’ and ‘bad’ or ‘harmful’ and ‘beneficial’.
What is the difference between Likert scales and semantic differential?
Likert scales and semantic differential scales can both be used to measure attitudes. However, Likert scales measure attitudes directly by measuring your degree of agreement with a statement, while semantic differential scales measure attitudes indirectly by assessing the connotations of a concept.
At StudySmarter, we have created a learning platform that serves millions of students. Meet the people who work hard to deliver fact based content as well as making sure it is verified.
Lily Hulatt is a Digital Content Specialist with over three years of experience in content strategy and curriculum design. She gained her PhD in English Literature from Durham University in 2022, taught in Durham University’s English Studies Department, and has contributed to a number of publications. Lily specialises in English Literature, English Language, History, and Philosophy.
Get to know Lily
Gabriel Freitas is an AI Engineer with a solid experience in software development, machine learning algorithms, and generative AI, including large language models’ (LLMs) applications. Graduated in Electrical Engineering at the University of São Paulo, he is currently pursuing an MSc in Computer Engineering at the University of Campinas, specializing in machine learning topics. Gabriel has a strong background in software engineering and has worked on projects involving computer vision, embedded AI, and LLM applications.
Get to know Gabriel