UX - Deep Dive on Task Experience and its success by Pranavjeet Mishra

Everyday in world , we encounter tasks . It ranges all scenarios where watching TV or accessing a website or it could be playing a game .

I will today write about Performance and enhancing the efficiency of task with mathematically proven UX scope .

Considering a website which constitute a form " Railway reservation form " and task could be considered as Filling the form and successfully submit it. Taking the above task as scenario I will consider 5 things to measure my UX .

1. Task Success
2. Time of Task
3. Errors
4. Efficiency and Learnability.

To measure task success, each task that participants are asked to perform must have a clear end-state or Non clear end state . A clear end means which could be clearly and without help could be completed . So filling the first name or last name is something which User can fill , Hence Non clear end state is something which hold back User in task completion for example A foreign tourist filling a form "From destination " to " To destination " , would be bit nasty experience if he/she doesn't know exactly Location spelling correctly .

How we could find Clear state and non end clear state.

We could do this by rule called "Binary Success" . Binary success is the simplest and most common way of measuring task success. Either participants complete a task successfully or they don’t. In simple terms , it is coin's head and tail , either user can complete the task or cannot .

How to measure Binary success?

Before measuring the Binary success , we should have few things in consideration . first we need to provide many tasks to many users to measure their confidence intervals . here I mean many Tasks as : iterated versions of your form design. and many users could be group of many different users so that their time complexity , confidence , failure chances could be measured based on their handling experience .

Supply the task to all users of different community and check whether they faced success or failed . measure success with 1 and fail with 0 ,iterate with different TASK ( iterated with different versions of UI ) , calculate the average as shown in below diagram .

Confidence interval could be measured by Binomial distribution.

Highest average points the most beautiful experience most of users have faced .

Now lets calculate the probability of Binary success .

Based on four checklist we will run one more feasible process.

1. Frequency of use (infrequent users versus frequent users)
2. Previous experience using the product
3. Domain expertise (low-domain knowledge versus high-domain knowledge)
4. Age group

Conduct A small validation check on community and categorise them in groups based on above factors . Provide Task ** again and calculate its success and failed rate . UX could be finalised with below Graph .

With this Categorise the Task performance and iterate with Few UX design principles and check with User for their success rate .

Task 1: A simple form where user filling From Destination and To Destination .

Task 2: Modified form providing a modal pop up upon clicking the from destination with all cities name.

Task 3:

Selecting the From destination " with Mega menu " and indication of map of country in sidebar with Hover effect of train or flight Number " . Selected train will show green track " from " to "destination " unselected train will become " Fade".

Thanks for Reading :)

Next article will be on Learnability of UX .