Packt
Eye Tracking the User Experience: From Design to Analysis

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Packt

Eye Tracking the User Experience: From Design to Analysis

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Design stimuli and tasks that generate meaningful gaze data

  • Integrate eye tracking with verbal and behavioral protocols

  • Analyze visual attention using qualitative and quantitative methods

Details to know

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Recently updated!

November 2025

Assessments

13 assignments

Taught in English

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There are 13 modules in this course

In this section, we clarify eye tracking for UX, detailing fixations, saccades, and usage motives, then assess when disciplined gaze analysis meaningfully enhances research outcomes and design decisions.

What's included

2 videos3 readings1 assignment

In this section, we assess when eye-tracking meaningfully augments UX research, contrast qualitative insight versus quantitative metrics, and prioritize the simplest evidence-based method for convincing stakeholders.

What's included

1 video5 readings1 assignment

In this section, we compare remote and wearable eye trackers, translate specs like sampling rate and accuracy into actionable UX insights, and plan cost-effective equipment or outsourcing supporting multi-location studies.

What's included

1 video3 readings1 assignment

In this section, we transform curiosity into testable eye-tracking research questions, align stimulus fidelity with task goals, and implement balanced within- or between-subjects designs that control sequence and sampling effects.

What's included

1 video6 readings1 assignment

In this section, we will combine eye tracking with behavioural analytics and interviews, using fixation duration to verify usability scores and turning gaze patterns into insights on comprehension, memory and clicks.

What's included

1 video1 reading1 assignment

In this section, we contrast CVP and RVP for UX eye-tracking, evaluate gaze-cued memory aids, and demonstrate targeted probing to balance reliable gaze metrics with rich qualitative user insights.

What's included

1 video1 reading1 assignment

In this section, we will learn to select eye-tracking metrics, separate attraction and performance measures, and organise area-of-interest data into user-experience insights for evidence-based design.

What's included

1 video4 readings1 assignment

In this section, we identify trackability constraints like corrective eyewear, screen participants, and apply probability and inferential statistics to determine efficient sample sizes for formative and summative eye-tracking studies.

What's included

1 video4 readings1 assignment

In this section, we will design distraction-free eye-tracking labs, pilot tasks, calibrate cameras, monitor sessions live, and log anomalies to secure reliable gaze data that drives sound user experience decisions.

What's included

1 video5 readings1 assignment

In this section, we prepare eye-tracking datasets by setting robust fixation criteria, crafting optimal AOIs, exporting measures, and cleansing anomalies, laying groundwork for trustworthy quantitative or qualitative analysis.

What's included

1 video5 readings1 assignment

In this section, we will explore gaze plots, heatmaps, and dynamic heatmaps while mastering customization, spotting usability issues, and conveying user experience research insights with persuasive eye tracking imagery.

What's included

1 video2 readings1 assignment

In this section, we will interpret fixation maps and scanpaths to classify search outcomes, pinpoint perception or comprehension failures, and generate clear, actionable user-experience recommendations.

What's included

1 video8 readings1 assignment

In this section, we will learn to choose eye tracking metrics, apply inferential statistics, and design clear graphs with confidence intervals for compelling quantitative user experience reports.

What's included

1 video3 readings1 assignment

Instructor

Packt - Course Instructors
Packt
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