Human-computer Interaction Overview

Principles

Definition

Human-computer interaction is the academic field concerned with the design, evaluation, and implementation of interactive computing systems for human use, and with the study of major phenomena surrounding them. This multidisciplinary domain investigates the complex interplay between people and technology, focusing on optimizing usability, accessibility, efficiency, effectiveness, and overall user experience in the interaction process.

Ontological type

Research Methods

Core Theories

Application Domains

Key developments

Key Figures

User-Centered HCI era

Yvonne Rogers [1] is a leading figure in user-centered HCI during this era, with affiliations at the University of Bristol [3] and the University of Sussex [4]. Her work, including The psychology of human-computer interaction [7], helped establish how psychological theory informs interface design and usability assessment, key for turning user testing and task analysis into routine practice. Blake Ives [2] contributed to the era's measurement focus, with affiliations at Dartmouth College [5] and Binghamton University [6]. His work on The measurement of user information satisfaction [8] provided formal metrics for evaluating user experience, a foundation for usability engineering and iterative testing that defined the period.

Context-Sensitive Multimodality era

Jonathan R. Wolpaw [1], affiliated with Baylor College of Medicine [3] and Vanderbilt University [4], stands as a pivotal figure in the context-sensitive multimodality era of 1995–2008. His work on BCI2000 [7], together with noninvasive control of a two-dimensional movement signal [8], and a brain–computer interface using electrocorticographic signals in humans [9], established common research pipelines and demonstrated viable pathways for both noninvasive and invasive brain–computer interfaces in 2004. Viswanath Venkatesh [2], affiliated with the University of Minnesota [5] and University of Maryland, College Park [6], contributed a foundational perspective on user interaction by integrating control, intrinsic motivation, and emotion into technology acceptance. His 2000 paper Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model [10] clarified how these factors shape ease of use, informing evaluation frameworks for context-aware multimodal interfaces and telepresence-enabled applications in this era.

Integrated Embodied Interaction era

Michel Galley [1] is associated with Stanford University [3] and the University of Washington [4] during the Integrated Embodied Interaction era. His work on A Diversity-Promoting Objective Function for Neural Conversation Models [6] and A Persona-Based Neural Conversation Model [7] advanced neural dialogue by fostering diverse and persona-consistent responses, a crucial step for end-to-end, context-aware interactive agents in this era. Bill Dolan [2] is associated with Massachusetts Institute of Technology [5] and the University of Washington [4] during this era. With the works A Diversity-Promoting Objective Function for Neural Conversation Models [6] and A Persona-Based Neural Conversation Model [7], his contributions helped promote diversity and persona in neural dialogue models, advancing end-to-end, embodied dialogue systems.