Thinking about UX research: User, system, and context

A helpful way to approach UX research is by considering three key areas: User, System, and Context. These elements interact to shape how people experience technology.

Best for: Examining the relationship between human factors, computing systems, and external conditions.

User: Focus on cognitive psychology, behavior, and user needs.

Example search terms:

• "cognitive biases in decision-making"
• "user perception of algorithmic recommendations"
• "mental workload in human-computer interaction"
• "affordances and signifiers in UX design"

System: Analyze architecture, security, algorithms, or usability of computing systems.

Example search terms:

• "algorithmic bias in recommendation systems"
• "usability heuristics for AI-driven interfaces"
• "error tolerance in automated decision-making"
• "human factors in cybersecurity authentication"

Context: Investigate the impact of culture, accessibility, ethics, and security on computing technologies.

Example search terms:

• "cultural differences in UX design"
• "ethical implications of AI in decision-making"
• "digital accessibility standards and compliance"
• "privacy concerns in wearable technology"

Combining concepts for a strong search query:

Bringing these three perspectives together can strengthen research and design decisions. For example, combining search terms like "cognitive biases" AND "algorithmic bias" AND "ethical implications of AI" can reveal insights into how human psychology interacts with system biases in an ethical context.

Example search:

"cognitive biases" AND "algorithmic bias" AND "ethical implications of AI"

This search investigates how human psychology (User) interacts with biased systems (System) in an ethical context (Context).

This isn’t a formal research model but rather a way to organize key factors in UX research. It can be a useful lens for thinking about interdisciplinary connections and structuring search strategies

The five Es of usability framework

Best for: Evaluating system performance, user satisfaction, and computing efficiency.

Efficiency: How quickly tasks can be completed.

Example search terms:

• "task completion time in user testing"
• "response time optimization in cloud computing"
• "latency impact on user experience"

Effectiveness: Accuracy of system outputs.

Example search terms:

• "error rates in speech recognition software"
• "data visualization accuracy in decision-making"
• "AI model performance in real-world scenarios"

Engagement: User satisfaction and motivation.

Example search terms:

• "gamification in cybersecurity training"
• "user engagement in digital health apps"
• "interactive design principles for e-learning"

Error tolerance: How systems handle mistakes.

Example search terms:

• "fault tolerance in distributed computing"
• "error handling in natural language processing"
• "adaptive interfaces for error prevention"

Ease of learning: How quickly users adapt.

Example search terms:

• "learnability of low-code development platforms"
• "usability testing of onboarding experiences"
• "novice vs. expert interaction patterns in software"

Combining concepts for a strong search query

Example search:

"response time optimization" AND "error handling in NLP" AND "user engagement in digital tools"

This search investigates efficiency (speed), error tolerance (handling mistakes), and engagement (user motivation).

Why use research frameworks to structure your keyword searching?

Finding relevant research can be overwhelming, especially in computing fields where topics overlap. A research framework helps you focus your search, refine your keywords, and structure your research more effectively.

How research frameworks help:

• Clarify your topic: Break broad ideas into clear research questions.
• Improve search results: Use targeted keywords instead of trial-and-error searching.
• Make connections: Identify relationships between user behavior, system design, and real-world applications.
• Save time: Find high-quality, relevant sources faster by using a structured approach.

Whether you're researching user experience, artificial intelligence, cybersecurity, or software usability, frameworks can help you structure your approach to get more relevant and focused results.

Using a framework helps focus you so you can spend less time searching—and more time understanding and applying your research.