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Hello all UX researchers, In my recent UX study, I used a single ease of use question at the start and end of the each task on the scale of 1 to 7 ( where 1= strongly disagree, 7= strongly agree).

Pre-task question: The participants were asked to rate how easy/difficult they thought the task was going to be.
Post task question: The participants were asked to rate how easy/difficult the task actually was.

I am interested in learning about your process of analyzing such data.

Q1. Do you perform descriptive statistics on all scores or select only the ratings of the participants who completed the task successfully.

Q2. I normally plot pre/post data and perform paired t-test. What is your process?

Thank you for response.

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    Doesn't asking the user before the task to rate how difficult he thinks the task will be creates some sort of expectation and corrupts the second answer (if the task was really that hard)? I mean, either influencing it towards being more like the first answer by the principle of commitment, or influencing it by creating a false expectation that is later broken, thus generating a distorted impression of ease/difficulty?
    – JotaRMonteiro
    Aug 18, 2015 at 20:25

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In a Idle situation, it is always a good practice to go non descriptive as the objective of the capture is mere an assessment of an acceptance level. Just go with the complete submissions against each line Items to conclude on your decision.

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