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Sensors and Artificial Intelligence Methods and Algorithms for Human-Computer Intelligent Interaction: A Systematic Mapping Study.

Sensors (Basel, Switzerland)·2022

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Intelligent User Interfaces and Their Evaluation: A Systematic Mapping Study.

Saša Brdnik¹, Tjaša Heričko¹, Boštjan Šumak¹

¹Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia.

Sensors (Basel, Switzerland)

|August 12, 2022

Summary

Intelligent user interfaces (IUI) enhance human-computer interaction (HCI) by integrating artificial intelligence. While most studies show usability and user experience (UX) improvements, tailored evaluation methods for IUI are lacking.

Keywords:

IUI evaluation intelligent user interfaces usability user experience

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Area of Science:

Computer Science
Human-Computer Interaction (HCI)
Artificial Intelligence (AI)

Background:

Intelligent user interfaces (IUI) aim to improve user experience (UX) and usability in human-computer interaction (HCI) through AI.
A review of 211 studies from 2012-2022 highlights the prevalence of IUI research within HCI and Software Engineering (SE) domains.

Purpose of the Study:

To identify, assess, and synthesize the state-of-the-art in Intelligent User Interfaces (IUI).
To specifically focus on the evaluation methodologies and outcomes within the IUI field.

Main Methods:

Systematic analysis of 211 research papers published between 2012 and 2022.
Examination of IUI definitions, characteristics, and evaluation approaches, including data collection methods like experiments and questionnaires.

Main Results:

Key IUI characteristics include adaptation, representation, and intelligence, with common descriptive verbs being adaptation, reasoning, and representation.
81% of evaluated studies reported improvements in usability or UX, primarily using experiments and questionnaires.
A notable gap exists in specialized evaluation tools, methods, and metrics for IUI.

Conclusions:

While IUIs show promise in enhancing usability and UX, current evaluation practices are inconsistent.
There is a critical need for the development of dedicated evaluation frameworks and metrics to better assess IUI effectiveness.