TL;DR: The Self-Assessment Manikin (SAM) is a valid and reliable picture-based measurement of perceived emotion. Emotion is measured in three dimensions (Pleasure, Arousal, Dominance), but the Dominance dimension is not usually needed.

But how do we measure emotion? That’s the question the Self-Assessment Manikin (SAM) is answering. More specifically, SAM measures perceived emotion. Emotion measurement dates considerably before Human-Computer Interaction’s existence; naturally, SAM has its roots in psychology and emotion measurement in a psychological context. It was introduced in 1980 by Peter J. Lang. As a matter of fact, a large dataset of studies utilising SAM to measure perceived emotion has used pictures, audio, and nouns (words). However, in measuring aspects of Interaction Experience (IX), we find it useful to also measure perceived emotion (for example).

Setting up the SAM

The questions of SAM

The Self-Assessment Manikin is different from the questionnaires we normally use in IX measurement in that it consists of pictures. Five pictures and a blank space in between them that represents the in-the-middle values are organised in a 3-row format; each line is one dimension: Pleasure, Arousal and Dominance. There is also a variant (the original version) that includes only 5 pictures per line, without the in-the-middle boxes.

• The first line measures pleasure (valence): from (left) feeling very happy, to (right) feeling very unhappy. (This is the initial ordering of items, although some publications use the reverse order)
• The second line measures arousal (how strong the feeling is): from (left) a very tense feeling to (right) a very calm feeling. (Once again, this is the initial ordering of items, although some publications use the reverse order)
• The third line measures dominance: from (left) submissiveness to (right) dominance

The responses of SAM

Participants can rate their affective state (emotion) by placing an X in one box per line.

In analysis, the leftmost manikin is coded with the number -8 and moving to the box on its right adds 2. So the equivalent numerical values for each dimension (with in-the-middle values) are: -8, -6, -4, -2, 0, 2, 4, 6, and 8.

• For the first line, pleasure, -8 represents a very happy feeling, 0 represents feeling neither happy nor unhappy, and 8 represents a very unhappy feeling
• For the second line, arousal, -8 represents a very tense feeling, 0 represents a feeling neither tense nor calm, and 8 represents a very calm feeling
• For the third line, dominance, -8 represents a very submissive feeling, 0 represents neither a dominant nor a submissive feeling, and 8 represents a very dominant feeling

The participants don’t see the numbers; we only use them to code the responses for analysis. 

Calculating the SAM score

Given that there is no single SAM score, we interpret the three replies of each participant as a triple that describes the perceived affective state in a three-dimensional plane. 

So, calculating the score for the emotional response that an interaction with a system, product, or service elicits is a matter of averaging all replies for each of the dimensions, not forgetting to also state standard errors. We can also use statistical analysis tools to automate the process (for example, IX Calculator offers both the original three-dimensional, and the current two-dimensional version). Then we interpret the results using the equivalence between the numbers and the affective state for each dimension (above).

For example, if we have the replies of 50 participants after an interaction with a product, and we calculate the averages as: average(Pleasure) = -6.4, average(Arousal) =  -4.5 and average(Dominance) = 1.0, we can interpret it as that the product, on average, was very pleasurable to use, arousing, and that participants felt dominant during their use.

The Dominance dimension is not needed

Since 1980, there has been substantial development in how emotion, or more accurately, core affect, can be represented. Although SAM was based on Russell’s and Mehrabian’s theory of Pleasure, Arousal, Dominance (PAD), later Russell clarified that core affect can be represented fully by just two dimensions (Pleasure and Arousal), which is also the case in frontier emotion construction theories.

So, the SAM can be administered and analysed by just the first two lines measuring Pleasure and Arousal, dropping completely the Dominance dimension.

Reliability, validity, and properties of SAM

In the last almost half a century, SAM has shown good psychometric properties. Test-retest reliability was very high (r = .96–.98). At the same time, Pleasure and Arousal dimensions showed high correlations with the Semantic Differential Scale and demonstrated high agreement between participants. 

The distribution of emotions in a two-dimensional space

Even though all numerical combinations of Pleasure–Arousal are theoretically possible, in practice, measured emotion appears as a U-curve when plotted on a Pleasure-Arousal space and can be modelled with a quadratic function. That highlights the difficulty of the appearance of emotions that are felt as either very happy and very calm, or very unhappy and very calm. At the same time, emotions that are considered very calm tend to be neutral in terms of pleasure.

TL;DR: The UMUX-Lite is a short 2-items questionnaire that incorporates the TAM. It has good psychometric properties and can be correlated with the System Usability Scale.

The UMUX-Lite is really a direct descendant of UMUX, it assumes that user acceptance of a new technology is based on its perceived usefulness (Item 2 of the UMUX) and perceived ease of use (Item 3 of the UMUX). Similar to the Technology Acceptance Model.

The Questions: Assessing Usability for User Experience Lite

In order to gauge user acceptance effectively, the UMUX-Lite questionnaire utilises the two positively worded questions of the UMUX. Each question is rated on a 7-point Likert scale, ranging from strongly disagree to strongly agree. The questions used in UMUX-Lite are as follows:

• Usefulness: This system’s capabilities meet my requirements
• Ease of Use: This system is easy to use

The subsequent calculation of the UMUX-Lite score allows for a quantitative evaluation of user experience.

Calculating the UMUX-Lite Score

The UMUX-Lite score serves as a quantitative measure to assess the usability of a system based on user feedback. To calculate the UMUX-Lite score for each user, the following steps are followed:

• Add the scores of the two questions provided by the user.
• Subtract 2 from the total obtained in step 1.
• Multiply the result by 100/12 or 8.33 to normalise the score (bring it on a scale from 0 to 100).

To obtain the UMUX-Lite score for the entire system, the average of all user UMUX scores is calculated. Alternatively, you can use this free tool to automatically calculate the UMUX score.

This system score offers a comprehensive overview of the overall usability from the collective user perspective.

Correlation to SUS: Linking UMUX-Lite and SUS

The UMUX-Lite metric has demonstrated a notable correlation with the widely used System Usability Scale (SUS). Multiple studies have consistently reported correlation coefficients between UMUX-Lite and SUS ranging from 0.74 to 0.83, indicating a strong association between the two metrics.  This is quite useful since the SUS, being one of the most thoroughly researched usability questionnaires, comes with a wide variety of benchmarks.

The initial regression formula

Initially, a regression formula was introduced as it seemed to exhibit a stronger correlation with the SUS. The regression formula is calculated as: 

UMUX-Liter = 0.65 * (Item1 – Item2 – 2) * (100 / 12) + 22.9. 

However, subsequent evidence emerged contradicting the initial claim that the regression formula correlates better with the SUS compared to the original UMUX-Lite calculation.

Multiple studies (for example, Lah et al. and Schrepp et al.) have argued against the predictive quality of this formula; thus, the initial regression formula shouldn’t be preferred over the original UMUX-Lite calculation.

Which formula to use to correlate UMUX-Lite with the SUS

Correlating to SUS using just the Ease question

In this approach, the SUS score is obtained through the equation: (Item2 – 1) * (100 / 6). The idea behind just using the ease-of-use item comes from the initial research of UMUX, where this question was a rephrasing of the SUS’s third question.

Correlating to SUS using the regression equation of the Ease question

The other alternative is to use a regression equation specifically derived from the Ease question. The UMUX-Lite score can be obtained using the equation: 19.2 * ((Item2 – 1) * (4 / 6) + 1) – 2.279. This approach has the highest predictive quality.

Evaluating the Approaches

Both the simple correlation equation and the regression equation exhibit improved results in correlating with the SUS. This is supported by MeasuringU’s unpublished studies, encompassing a diverse range of systems and involving nearly 500 combined participants, and later research by Schrepp et al. Nonetheless, just using the overall UMUX-Lite score as a proxy for the SUS is a straightforward alternative that gives good results.

Alternatives to the first question of UMUX-Lite

In a separate investigation conducted by Lewis and Sauro, alternative formulations were explored to simplify the first question of UMUX-Lite, “This system’s capabilities meet my requirements.” The following alternative statements can be considered as viable alternatives to the original question:

• “{Product}’s functionality meets my needs.”
• “{Product}’s features meet my needs.”
• “{Product}’s functions meet my needs.”
• “{Product} does what I need it to do.”

These alternative statements aim to provide flexibility for picking the question to suit specific research contexts and user populations.

Presenting the UMUX-Lite: Communicating the Metric Effectively

The UMUX-Lite metric can be effectively presented using two distinct approaches: a graphical representation and a grading system.

Graphical Way: Visualising the UMUX-Lite

Not to state the obvious, as with all one-score questionnaires, the system’s overall UMIX-Lite score can be presented using a graph. However, UMUX-Lite offers a unique visualisation opportunity compared to other usability questionnaires. Since it is built to follow the TAM, each question can be presented in its axis to mark the overall usability of the system in the two-dimensional world —quite handy for comparison of different systems.

While nicely presented, there is no evidence that each question is reliably capturing one aspect of usability, so use with caution.

Grading System: Categorising the UMUX-Lite Scores

Since we can approximate an application’s SUS score from the UMUX-Lite, we can use the two grading scales for SUS scores, and all other known benchmarks of SUS scores (e.g., the average SUS score of approximately 500 products in the wild is 68). 

A visualisation idea is to calculate the SUS score corresponding to the measured UMUX-Lite score based on one of the correlation formulas on top (or just by using the UMUX-Lite score directly). Then plot the system’s grade based on a grading scale.

TL;DR: The UMUX is a short, 4 items questionnaire that correlates to the System Usability Scale. It is a valid and reliable way of measuring perceived usability. Its short form makes it a good asset in a researcher’s toolbox of UX Metrics that can be administered in-the-wild or on user testings.

There are a lot of definitions of usability; the ISO 9241-11 defines usability as a combination of effectiveness, efficiency, and satisfaction. There are also a lot of ways to measure usability, in regards to quantitative usability measurement questionnaires are frontrunners, with the System Usability Scale being the most commonly used and researched. However, the SUS consists of 10 questions and can be difficult to administer in large, in-the-wild, studies. Kraig Finstad understood that and in 2010 introduced the Usability Metric for User Experience (UMUX) with 4 questions.

Setting up the UMUX

The questions of the UMUX

The UMUX consists of 4 questions, these questions measure the perceived usability as described in the relevant ISO. As in the SUS the tone of the questions changes between positive and negative.

1. [This system’s] capabilities meet my requirements.
2. Using [this system] is a frustrating experience.
3. [This system] is easy to use
4. I have to spend too much time correcting things with [this system].

Example of questions with changed system’s wording

The design of the questionnaire allows for changing the content of the brackets ([This system’s]) to the actual name of the system, or a more suitable word for the application.

• This application’s capabilities meet my requirements.
• Using Google Forms is a frustrating experience.

etc.

The responses of the UMUX

The UMUX can be administered either verbally or through some written format (including digital questionnaires). Each question is scored on a Likert scale, from 1 (strongly disagree) to 7 (strongly agree).

Calculating the UMUX score

The rules:

• Positively worded questions are 1 and 3
• Negatively worded questions are 2 and 4

Scoring each question:

1. For positively worded questions, take the number of the reply and subtract 1 (e.g. if the answer to the question 1 is Slight Agreement—5, then the question is scored: 5 – 1 = 4)
2. For negatively worded questions, take the number of the reply and subtract it from 7 (e.g. if the answer to the question 2 is Slight Agreement—5, then the question is scored: 7 – 5 = 2)

Find the participant score:

We have the score of each question, to calculate the UMUX score for each participant:

1. Add all the questions’ score
2. Multiply by 4.1667 (or 100 / 24)
3. You will get a score between 0 and 100, this is the UMUX score

To sum up, the formula for calculating the participant’s UMUX score is:

UMUX = ((Item_1 − 1) + (Item_3 − 1) + (7 − Item_2) + (7 − Item_4)) * (100/24)

The overall score of the UMUX (the system’s score)

Often one would use the UMUX to “put a number” to the usability of the whole system / application in question. In that case, the System’s score (or overall UMUX score) is the average of all the participant’s scores.

Presenting the UMUX results

Except for presenting the mean UMUX score of the system, usually the Standard Deviation and participants volume (sample size) are presented as well.

How many participants should someone include to get significant results?

To the point of the writing (will update if new research is published), unlike in the SUS, there are no general guidelines of the minimum number of participants required to achieve accurate results. Finstad created the questionnaire in a study with 42 participants, while Berkman and Karahoca validated it with 3 studies of 363, 42, and 151 participants — to give some general numbers. When working with relatively low numbers of participants, Laplace’s rule of succession is your friend.

Is the UMUX a good metric for measuring User Experience?

UMUX is a reliable metric. It is a great metric of usability, which can be seen as a part of User Experience. It has been validated numerous times. Berkman and Karahoca investigated deeply the structure, validity, and reliability of the UMUX, they also found that the UMUX scores correlate with the scores of the System Usability Scale (SUS) and the Computer System Usability Questionnaire (CSUQ).

Nonetheless UMUX is a usability questionnaire. If one wants to evaluate a system they can use UMUX and obtain similar results to other validated questionnaires. The age and genre of the participants shouldn’t affect the UMUX scores.

Is the UMUX affected by participant’s characteristics?

As with other usability questionnaires, the previous experience of the participant with the system affects the resulting score. Participants that have used the system in the past would tend to rate the system higher, than participants who haven’t. Berkman and Karahoca also reported that non-native English speakers gave slightly different UMUX scores than native English speakers.

Translations of the UMUX

UMUX has been translated and validated in a couple of languages:

The Arabic UMUX

The adaptation can be found in the original paper by Khalid S. Al-Tahat.

The Chinese UMUX

1. 该系统的功能能够满足我的要求.
2. 使用该系统是令人沮丧的经历.
3. 该系统易于使用.
4. 我必须花大量时间去适应该系统.

Adapted by Yuhui Wang, Jing Chai & Tian Lei.

The Greek UMUX

1. Οι δυνατότητες [αυτού του συστήματος] ανταποκρίνονται στις απαιτήσεις μου.
2. Η χρήση [αυτού του συστήματος] είναι μία απογοητευτική εμπειρία.
3. [Αυτό το σύστημα] είναι εύκολο στη χρήση.
4. Πρέπει να αφιερώσω πολύ χρόνο για να διορθώσω πράγματα με [αυτό το σύστημα].

Adapted by Christos Katsanos, Georgios Melissourgos, Nikolaos Tselios.

The Slovene UMUX

1. Zmogljivosti [] izpolnjujejo moje zahteve.
2. Uporaba [] me frustrira.
3. [] je enostaven za uporabo.
4. Preveč časa porabim za popravljanje napak ob uporabi [].

Adapted by Urška Laha, James R. Lewis, and Boštjan Šumak.

The Turkish UMUX

The adaptation can be found in the original paper by Mİ Berkman, Ş Şahin.

TL;DR: The positive SUS, designed by Sauro and Lewis in 2011, is as good at measuring perceived usability as the original System Usability Scale designed by Brooke in 1996. The positive SUS could help in studies in which cognitive load is a concern, while the original SUS ability to detect acquiescence bias could be used in more error-prone studies.

The System Usability Scale is arguably one of the most used perceived usability questionnaires. However, since its original publication by Brooke in 1996 there have been several criticisms, one of the most common being the alternation between negatively and positively worded items. In the SUS questionnaire, all even questions are negatively worded, and all odd are positively worded; this design tries to mitigate acquiescence bias. Nonetheless, there are four main lines of reasoning against that wording alternation:

1. Negatively worded questions increase the cognitive load
2. They reduce the psychometric qualities of the questionnaire, as measured by Cronbach’s coefficient
3. They increase the likelihood of replies miscoding
4. They do not help that much in addressing the acquiescence bias

The positive SUS

In 2011 Jeff Sauro and James R. Lewis introduced the positive System Usability Scale (positive SUS), which is a modified version of the original SUS with even items having positive wording. They read as follows:

1. I think that I would like to use the website frequently.
2. I found the website to be simple.
3. I thought the website was easy to use.
4. I think that I could use the website without the support of a technical person.
5. I found the various functions in the website were well integrated.
6. I thought there was a lot of consistency in the website.
7. I would imagine that most people would learn to use the website very quickly.
8. I found the website very intuitive.
9. I felt very confident using the website.
10. I could use the website without having to learn anything new.

Calculation of the positive SUS

Calculation of the positive System Usability Scale is more straightforward than the original SUS, that’s part of the reason it was created after all. In short:

Scoring each question:

• Take the number of the answer and subtract 1 (e.g. if the answer was disagree, the score is 2 – 1 = 1)

Calculating the participant’s score

1. Add all 10 questions’ scores
2. Multiply that number by 2.5
3. You will get a number between 0 and 100, which is the SUS score

Calculating the mean (total) score

Most of the time, when stating the SUS score the total usability of a system is the mean of all the participants’ scores.

Mean SUS = (score of participant 1 + score of participant 2 + … + score of participant n) / n

There are free utilities that will perform this calculation just by adding the raw score, for example our (free) positive SUS calculator.

The same interpretation of the score applies using the scale developed by A. Bangor, P.T. Kortum, and J.T. Miller

Is the positive SUS equivalent to the original SUS?

The positive SUS was introduced alongside two studies that justified its validity and correspondence to the original System Usability Scale. Philip Kortum et al. in 2020 compared the two questionnaires by surveying retrospectively a short of 1000 participants, they found that both questionnaires are measuring perceived usability similarly. In general, they can be considered equivalent and the same principles should apply when examining SUS scores.

The positive SUS is as valid as the original SUS

In the same study, when measuring internal reliability the positive SUS showed constantly higher measures of validity compared to SUS. However, the reasoning behind that is not understood. The higher internal reliability coefficient could be due to participants being less careful in their replies —tending to agree with all the questions. At last, we can say that both questionnaires show the same validity.

Should we all switch to using the positive SUS?

For the time being, the answer is no. Both questionnaires are equivalent and usability practitioners can use them independently based on the specific study attributes and personal experience. The positive SUS could help in studies in which cognitive load is a concern, while the original SUS ability to detect acquiescence bias could be used in more error-prone studies.

TL;DR: SUS is a very reliable measurement of a system’s perceived usability. It uses 10 questions, graded from strongly disagree to strongly agree, to measure perceived usability.

A large amount of effort is attributed to uncovering usability issues of a system. The System Usability Scale is a quantitative measure of the usability of the system. Although it doesn’t pinpoint specific attributes that affect usability, it is shown to be one of the most powerful ways to put a number on the system’s perceived usability.

The purpose of this document is to provide an extensive insight into the current state of the System Usability Scale, with the most recent information. Updated regularly.

Setting up the System Usability Scale (SUS)

The SUS is a questionnaire that can be administered either verbally in a moderated environment or written in an unmoderated environment. It was initially introduced in 1986 by John Brooke as an undimensional, quick-and-dirty way of measuring usability and was validated numerous times.

The questions of the SUS

The SUS consists of 10 questions, interchanging positive and negative wordings. See below the original questions with the number 8 modified by Finstad for non-native English speakers

1. I think that I would like to use this system frequently.
2. I found the system unnecessarily complex.
3. I thought the system was easy to use.
4. I think that I would need the support of a technical person to be able to use this system.
5. I found the various functions in this system were well integrated.
6. I thought there was too much inconsistency in this system.
7. I would imagine that most people would learn to use this system very quickly.
8. I found the system very cumbersome/awkward to use.
9. I felt very confident using the system.
10. I needed to learn a lot of things before I could get going with this system.

The responses of the SUS

Each question is supposed to be answered on a scale from 1 (Strongly Disagree) to 5 (Strongly Agree). Participants shouldn’t dwell on any specific questions, but instead respond with their first thoughts. If the test is administered verbally and the participant doesn’t answer a specific question, it is scored as a 3.

Calculating the score of SUS

The rules:

• Each question’s score ranges between 0 and 4
• Positively worded questions are 1, 3, 5, 7 and 9
• Negatively worded questions are 2, 4, 6, 8 and 10

Scoring each question:

1. For positively worded questions, take the number of the answer and subtract 1 (e.g. if the answer to the first question was neutral (3), then the score of the question is 3 – 1 = 2)
2. For negatively worded questions, take the number of the answer and subtract it from 5 (e.g. if the answer to the second question was agree (4), then the score of that question is 5 – 4 = 1)

After that, the overall score of the SUS is calculated as follows:

1. Add all 10 questions’ scores
2. Multiply the number by 2.5
3. You will get a number between 0 and 100, which is the SUS score

If you want to save the manual work, you can just enter the scores of each question and get all relevant results in our free SUS calculator.

Extracting learnability measurements

Although there was some evidence by James R. Lewis and Jeff Sauro that SUS measures two dimensions of one’s system: Learnability and Usability, this is not considered the case in most studies. Instead, Lewis and Sauro reviewed 9000 questionnaires to find a factor structure of negatively vs positively worded questions, rather than Usability and Learnability. However, there is still some connection between questions 4 and 10 that, in some cases, may be strong enough to form a separate factor.

If in the specific field of the study, learnability is a strong factor (most of the time not the case), questions 4 and 10 form a separate factor (specifically measure learnability), the SUS’s learnability score can be extracted as follows:

1. Add the scores of questions 4 and 10
2. Multiply the result by 12.5
3. You will get a number between 0 and 100, which corresponds to the learnability of the system

Understanding the score of SUS

A score of 0 translates to “it is impossible to perform the required task”, whereas a score of 100 means that the required task is performed easily. However, most systems are evaluated by testing a flow with numerous tasks; thus, realistically, it is very difficult for a score to be close to 0. In general, it is suggested to use the System Usability Score as a relative measurement of the system tested. A system with a higher SUS than another means that it is more usable, although how much more usable is not up to the SUS to show.

One way to understand the score of the SUS is to compare the evaluated application’s SUS score with a pool of other SUS scores. Two common ways of qualifying the SUS scores are the grading scales below.

Adjective Rating Scale

Aaron Bangor, Philip Kortum, and James Miller have correlated the numerical score of the SUS with a perceived adjective meaning. By asking users to both rate an application with the SUS and replying to the question “Overall, I would rate the user-friendliness of this product as: Worst Imaginable -> Best imaginable” they created a qualitative meaning of each score range (for example, a SUS score larger than 50.9 and less than 71.4 means that users perceive the usability of the application as “Good”). They then created a grading scale from F (SUS score < 60) to A (SUS Score >90) with all grades in the middle spanning 10 points. Presenting the grade instead (or alongside) a SUS score gives a qualitative understanding and comes in handy for setting KPIs.

Curved Grading Scale

Sauro and Lewis analysed 446 SUS studies (including the data from Bangor et al. above) and noted that the average of the SUS score from approximately 500 products is 68. They then created a curved grading scale that has 68 as the centre and provided with percentiles for each grade to enable comparison of a SUS score with that dataset of studies (for example, a SUS score of 79 is considered an A- which is assigned to a percentile range of 85-89. That means that the evaluated application with SUS score 79 has a better usability than at least 85% of the studies in the dataset; see also Quantifying the User Experience: Practical Statistics for User Research, Sauro and Lewis: 204).

How many participants should be included in a SUS test

The power of SUS is also shown in the sample size needed to achieve statistical significance. Thomas S. Tullis and Jacqueline N. Stetson showed that for 12 participants or more, the SUS result remains the same.

Can you change the word “system” in the SUS questions?

SUS is quite resilient to changes in the name of the “system”. Bangor et al. changed the word “system” to “product” and didn’t see a significant change in the results. This suggests that probably other, more specific, synonyms of “system” could be used safely.

Internationalised SUS vs non-native English speakers

The SUS is tested with non-native English speakers, and its reliability stays the same. However, several researchers have translated and validated SUS into local languages. If the participants are native speakers of a language other than English, it is worth considering using the local version of the SUS.

Does perceived Usability affect loyalty?

There exists initial data to support a link between the perceived usability of a system and users’ loyalty. Users who are promoters, measured with NPS, rate the system with substantially higher usability than passives and detractors. That could potentially indicate that improving usability could increase the likelihood of a user becoming a promoter.

What about the positive SUS?

Sauro and Lewis developed an all-positively worded version of the System Usability Scale. It performs as well and is as reliable as the original SUS.

Validated translations of the System Usability Scale

The Chinese System Usability Scale

1. 我愿意经常使用这个系统.
2. 我发现这个系统太复杂.
3. 我认为这个系统使用起来很容易.
4. 我认为我需要技术人员的帮助才能使用这个系统.
5. 我发现这个系统很好地集成了各种功能.
6. 在使用该系统的过程中, 我发现很多操作结果和预想功能不一致.
7. 我想大多数用户能很快学会使用该系统.
8. 我发现这个系统使用起来很别扭.
9. 我对熟练掌握这个系统很有信心.
10. 在使用这个系统之前, 我需要学习很多知识.

Adaption by Yuhui Wang, Tian Lei & Xinxiong Liu

The Danish System Usability Scale

1. Jeg tror godt, at jeg kunne tænke mig at bruge systemet ofte.
2. Jeg synes, at systemet var unødigt kompliceret at bruge.
3. Jeg synes, at systemet var nemt at bruge.
4. Jeg tror, at jeg ville få brug for support fra en tekniker for at kunne bruge systemet.
5. Jeg synes, at mange af systemets funktioner var godt integreret med hinanden.
6. Jeg synes, at systemet var usammenhængende.
7. Jeg tror, at de fleste hurtigt kan lære at bruge dette system.
8. Jeg synes, at systemet var meget besværligt at bruge.
9. Jeg følte mig sikker på, at jeg kunne bruge systemet.
10. Jeg var nødt til at lære en masse ting, for at komme i gang med at bruge systemet.

Adaption by

Julie Christine S. Hvidt, Lone Fisker Christensen, Christian Sibbersen, Stig Helweg-Jørgensen, Jens Peter Hansen & Mia Beck Lichtenstein

The French System Usability Scale

1. Je voudrais utiliser ce système fréquemment.
2. Ce système est inutilement complexe.
3. Ce système est facile à utiliser.
4. J’aurais besoin du soutien d’un technicien pour être capable d’utiliser ce système.
5. Les différentes fonctionnalités de ce système sont bien intégrées.
6. Il y a trop d’incohérences dans ce système.
7. La plupart des gens apprendront à utiliser ce système très rapidement.
8. Ce système est très lourd à utiliser.
9. Je me suis senti·e très en confiance en utilisant ce système.
10. J’ai eu besoin d’apprendre beaucoup de choses avant de pouvoir utiliser ce système.

Adaptation by Guillaume Gronier & Alexandre Baudet

The German System Usability Scale

1. Ich denke, dass ich das System gerne häufig benutzen würde.
2. Ich fand das System unnötig komplex.
3. Ich fand das System einfach zu benutzen.
4. Ich glaube, ich würde die Hilfe einer technisch versierten Person benötigen, um das System benutzen zu können.
5. Ich fand, die verschiedenen Funktionen in diesem System waren gut integriert.
6. Ich denke, das System enthielt zu viele Inkonsistenzen.
7. Ich kann mir vorstellen, dass die meisten Menschen den Umgang mit diesem System sehr schnell lernen.
8. Ich fand das System sehr umständlich zu nutzen.
9. Ich fühlte mich bei der Benutzung des Systems sehr sicher.
10. Ich musste eine Menge lernen, bevor ich anfangen konnte das System zu verwenden.

Translation by Rummet et al. picked by Tobias J. Brix, Alice Janssen, Michael Storck, Julian Varghese

The Greek System Usability Scale

1. Νομίζω οτι θα ήθελα να χρησιμοποιώ αυτό το σύστημα συχνά.
2. Βρήκα αυτό το σύστημα αδικαιολόγητα περίπλοκο.
3. Σκέφτηκα ότι αυτό το σύστημα ήταν έυκολο στη χρήση.
4. Νομίζω οτι θα χρειαστώ βοήθεια από κάποιον τεχνικό για να είμαι σε θέση να χρησιμοποιήσω αυτό το σύστημα.
5. Βρήκα τις διάφορες λειτουργίες σε αυτό το σύστημα καλά ολοκληρωμένες.
6. Σκέφτηκα οτι υπήρχε μεγάλη ασυνέπεια σε αυτό το σύστημα.
7. Φαντάζομαι οτι οι περισσότεροι άνθρωποι θα μάθουν να χρησιμοποιούν αυτό το σύστημα πολύ γρήγορα.
8. Βρήκα αυτό το σύστημα πολύ περίπλοκο/δύσκολο στη χρήση.
9. Ένιωσα πολύ σίγουρος/η χρησιμοποιώντας αυτό το σύστημα.
10. Χρειάστηκε να μάθω πολλά πράγματα πριν μπορέσω να ξεκινήσω με αυτό το σύστημα.

Adaptation by Christos Katsanos, Nikolaos Tselios, Michalis Xenos

The Indonesian System Usability Scale

1. Saya berpikir akan menggunakan sistem ini lagi.
2. Saya merasa sistem ini rumit untuk digunakan.
3. Saya merasa sistem ini mudah untuk digunakan.
4. Saya membutuhkan bantuan dari orang lain atau teknisi dalam menggunakan sistem ini.
5. Saya merasa fitur-fitur sistem ini berjalan dengan semestinya.
6. Saya merasa ada banyak hal yang tidak konsisten (tidak serasi) pada sistem ini.
7. Saya merasa orang lain akan memahami cara menggunakan sistem ini dengan cepat.
8. Saya merasa sistem ini membingungkan.
9. Saya merasa tidak ada hambatan dalam menggunakan sistem ini.
10. Saya perlu membiasakan diri terlebih dahulu sebelum menggunakan sistem ini.

Adaptation by Zahra Sharfina, Harry Budi Santoso

The Malay (Mobile) System Usability Scale

1. Saya rasa saya ingin kerap menggunakan aplikasi mudah alih ini.
2. Saya rasa aplikasi mudah alih ini sesuatu yang rumit.
3. Saya rasa aplikasi mudah alih ini mudah untuk digunakan.
4. Saya memerlukan bantuan daripada orang lain untuk menggunakan aplikasi mudah alih ini.
5. Saya mendapati fungsi-fungsi dalam aplikasi mudah alih ini saling bersepadu (berhubungkait) dengan baik.
6. Saya rasa terdapat banyak kandungan di dalam aplikasi mudah alih ini yang tidak konsisten antara satu sama lain.
7. Saya membayangkan bahawa kebanyakan orang akan cepat belajar menggunakan aplikasi mudah alih ini.
8. Saya mendapati aplikasi mudah alih ini leceh untuk digunakan.
9. Saya berasa yakin menggunakan aplikasi mudah alih ini.
10. Saya perlu belajar terlalu banyak perkara sebelum boleh menggunakan aplikasi mudah alih ini.

Adaptation by Muhamad Fadhil Mohamad Marzuki, Nor Azwany Yaacob, Najib Majdi Yaacob

The Polish System Usability Scale

1. Myślę, że często używałbym/używałabym tego systemu.
2. Odbieram ten system jako niepotrzebnie skomplikowany.
3. Myślę, że system jest łatwy w użyciu.
4. Myślę, że potrzebowałbym/potrzebowałabym wsparcia asystenta, aby używać tego systemu.
5. Uważam, że różne funkcje tego system są dobrze zintegrowane.
6. Myślę, że w tym systemie jest za dużo niespójności.
7. Wydaje mi się, że większość ludzi nauczyłaby się bardzo szybko używać tego systemu.
8. Odbieram ten system jako bardzo niewygodny w użyciu.
9. Czułem/czułam się bardzo pewnie używając tego systemu.
10. Musiałem/musiałam nauczyć się wielu rzeczy, zanim zacząłem/zaczęłam właściwie posługiwać się tym systemem.

Adaptation by Anna Borkowska and Katarzyna Jach

The European Portuguese System Usability Scale

1. Acho que gostaria de utilizar este produto com frequência.
2. Considerei o produto mais complexo do que necessário.
3. Achei o produto fácil de utilizar.
4. Acho que necessitaria de ajuda de um técnico para conseguir utilizar este produto.
5. Considerei que as várias funcionalidades deste produto estavam bem integradas.
6. Achei que este produto tinha muitas inconsistências.
7. Suponho que a maioria das pessoas aprenderia a utilizar rapidamente este produto.
8. Considerei o produto muito complicado de utilizar.
9. Senti-me muito confiante a utilizar este produto.
10. Tive que aprender muito antes de conseguir lidar com este produto.

Adaptation by Ana Isabel Martins,*, Ana Filipa Rosa, Alexandra Queirós, Anabela Silva, Nelson Pacheco Rocha

The Spanish System Usability Scale

1. Me gustaría usar esta herramienta frecuentemente.
2. Considero que esta herramienta es innecesariamente compleja.
3. Considero que la herramienta es fácil de usar.
4. Considero necesario el apoyo de personal experto para poder utilizar esta herramienta.
5. Considero que las funciones de la herramienta están bien integradas.
6. Considero que la herramienta presenta muchas contradicciones.
7. Imagino que la mayoría de las personas aprenderían a usar esta herramienta rápidamente.
8. Considero que el uso de esta herramienta es tedioso.
9. Me sentí muy confiado al usar la herramienta.
10. Necesité saber bastantes cosas antes de poder empezar a usar esta herramienta.

Adaptation by Magdalena Del Rocio Sevilla-Gonzalez, Lizbeth Moreno Loaeza, Laura Sofia Lazaro-Carrera, Brigette Bourguet Ramirez, Anabel Vázquez Rodríguez, María Luisa Peralta-Pedrero, Paloma Almeda-Valdes

The Slovene System Usability Scale

1. Menim, da bi ta sistem rad pogosto uporabljal.
2. Sistem se mi je zdel po nepotrebnem zapleten.
3. Sistem se mi je zdel enostaven za uporabo.
4. Menim, da bi za uporabo tega sistema potreboval pomoč tehnika.
5. Različne funkcije tega sistema so se mi zdele dobro povezane v smiselno celoto.
6. Sistem se mi je zdel preveč nekonsistenten.
7. Menim, da bi se večina uporabnikov zelo hitro naučila uporabljati ta sistem.
8. Sistem se mi je zdel neroden za uporabo.
9. Pri uporabi sistema sem bil zelo suveren.
10. Preden sem osvojil uporabo tega sistema, sem se moral naučiti veliko stvari.

Adaptation by Bojan Blažica and James R. Lewis