Human–computer interaction

(Redirected from Human-Computer Interface)

Human–computer interaction (HCI) is research in the design and the use of computer technology, which focuses on the interfaces between people (users) and computers. HCI researchers observe the ways humans interact with computers and design technologies that allow humans to interact with computers in novel ways. A device that allows interaction between human being and a computer is known as a "Human-computer Interface (HCI)".

A close-up photograph of a computer monitor.
A computer monitor provides a visual interface between the machine and the user.

As a field of research, human–computer interaction is situated at the intersection of computer science, behavioral sciences, design, media studies, and several other fields of study. The term was popularized by Stuart K. Card, Allen Newell, and Thomas P. Moran in their 1983 book, The Psychology of Human–Computer Interaction. The first known use was in 1975 by Carlisle.[1] The term is intended to convey that, unlike other tools with specific and limited uses, computers have many uses which often involve an open-ended dialogue between the user and the computer. The notion of dialogue likens human–computer interaction to human-to-human interaction: an analogy that is crucial to theoretical considerations in the field.[2][3]

Introduction

edit

Humans interact with computers in many ways, and the interface between the two is crucial to facilitating this interaction. HCI is also sometimes termed human–machine interaction (HMI), man-machine interaction (MMI) or computer-human interaction (CHI). Desktop applications, internet browsers, handheld computers, and computer kiosks make use of the prevalent graphical user interfaces (GUI) of today.[4] Voice user interfaces (VUI) are used for speech recognition and synthesizing systems, and the emerging multi-modal and Graphical user interfaces (GUI) allow humans to engage with embodied character agents in a way that cannot be achieved with other interface paradigms. The growth in human–computer interaction field has led to an increase in the quality of interaction, and resulted in many new areas of research beyond. Instead of designing regular interfaces, the different research branches focus on the concepts of multimodality[citation needed] over unimodality, intelligent adaptive interfaces over command/action based ones, and active interfaces over passive interfaces.[5]

The Association for Computing Machinery (ACM) defines human–computer interaction as "a discipline that is concerned with the design, evaluation, and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them".[4] A key aspect of HCI is user satisfaction, also referred to as End-User Computing Satisfaction. It goes on to say:

"Because human–computer interaction studies a human and a machine in communication, it draws from supporting knowledge on both the machine and the human side. On the machine side, techniques in computer graphics, operating systems, programming languages, and development environments are relevant. On the human side, communication theory, graphic and industrial design disciplines, linguistics, social sciences, cognitive psychology, social psychology, and human factors such as computer user satisfaction are relevant. And, of course, engineering and design methods are relevant."[4]

Due to the multidisciplinary nature of HCI, people with different backgrounds contribute to its success.

Poorly designed human-machine interfaces can lead to many unexpected problems. A classic example is the Three Mile Island accident, a nuclear meltdown accident, where investigations concluded that the design of the human-machine interface was at least partly responsible for the disaster.[6][7][8] Similarly, accidents in aviation have resulted from manufacturers' decisions to use non-standard flight instruments or throttle quadrant layouts: even though the new designs were proposed to be superior in basic human-machine interaction, pilots had already ingrained the "standard" layout. Thus, the conceptually good idea had unintended results.

Human–computer interface

edit

The human–computer interface can be described as the point of communication between the human user and the computer. The flow of information between the human and computer is defined as the loop of interaction. The loop of interaction has several aspects to it, including:

  • Visual Based: The visual-based human–computer interaction is probably the most widespread human–computer interaction (HCI) research area.
  • Audio-Based: The audio-based interaction between a computer and a human is another important area of HCI systems. This area deals with information acquired by different audio signals.
  • Task environment: The conditions and goals set upon the user.
  • Machine environment: The computer's environment is connected to, e.g., a laptop in a college student's dorm room.
  • Areas of the interface: Non-overlapping areas involve the processes related to humans and computers themselves, while the overlapping areas only involve the processes related to their interaction.
  • Input flow: The flow of information begins in the task environment when the user has some tasks requiring using their computer.
  • Output: The flow of information that originates in the machine environment.
  • Feedback: Loops through the interface that evaluate, moderate, and confirm processes as they pass from the human through the interface to the computer and back.
  • Fit: This matches the computer design, the user, and the task to optimize the human resources needed to accomplish the task.
    • Visual- Based HCI ----
      1. Facial Expression Analysis: This area focuses on visually recognizing and analyzing emotions through facial expressions.
      2. Body Movement Tracking (Large-scale): Researchers in this area concentrate on tracking and analyzing large-scale body movements.
      3. Gesture Recognition: Gesture recognition involves identifying and interpreting gestures made by users, often used for direct interaction with computers in command and action scenarios.
      4. Gaze Detection (Eyes Movement Tracking): Gaze detection involves tracking the movement of a user's eyes and is primarily used to better understand the user's attention, intent, or focus in context-sensitive situations.
        While the specific goals of each area vary based on applications, they collectively contribute to enhancing human-computer interaction. Notably, visual approaches have been explored as alternatives or aids to other types of interactions, such as audio- and sensor-based methods. For example, lip reading or lip movement tracking has proven influential in correcting speech recognition errors.
    • Audio - Based HCI ----Audio-based interaction in human-computer interaction (HCI) is a crucial field focused on processing information acquired through various audio signals. While the nature of audio signals may be less diverse compared to visual signals, the information they provide can be highly reliable, valuable, and sometimes uniquely informative. The research areas within this domain include:
      1. Speech Recognition: This area centers on the recognition and interpretation of spoken language.
      2. Speaker Recognition: Researchers in this area concentrate on identifying and distinguishing different speakers.
      3. Auditory Emotion Analysis: Efforts have been made to incorporate human emotions into intelligent human-computer interaction by analyzing emotional cues in audio signals.
      4. Human-Made Noise/Sign Detections: This involves recognizing typical human auditory signs like sighs, gasps, laughs, cries, etc., which contribute to emotion analysis and the design of more intelligent HCI systems.
      5. Musical Interaction: A relatively new area in HCI, it involves generating and interacting with music, with applications in the art industry. This field is studied in both audio- and visual-based HCI systems.
    • Sensor-Based HCI ----This section encompasses a diverse range of areas with broad applications, all of which involve the use of physical sensors to facilitate interaction between users and machines. These sensors can range from basic to highly sophisticated. The specific areas include:
      1. Pen-Based Interaction: Particularly relevant in mobile devices, focusing on pen gestures and handwriting recognition.
      2. Mouse & Keyboard: Well-established input devices discussed in Section 3.1, commonly used in computing.
      3. Joysticks: Another established input device for interactive control, commonly used in gaming and simulations.
      4. Motion Tracking Sensors and Digitizers: Cutting-edge technology that has revolutionized industries like film, animation, art, and gaming. These sensors, in forms like wearable cloth or joint sensors, enable more immersive interactions between computers and reality.
      5. Haptic Sensors: Particularly significant in applications related to robotics and virtual reality, providing feedback based on touch. They play a crucial role in enhancing sensitivity and awareness in humanoid robots, as well as in medical surgery applications.
      6. Pressure Sensors: Also important in robotics, virtual reality, and medical applications, providing information based on pressure exerted on a surface.
      7. Taste/Smell Sensors: Although less popular compared to other areas, research has been conducted in the field of sensors for taste and smell. These sensors vary in their level of maturity, with some being well-established and others representing cutting-edge technologies.

Goals for computers

edit

Human–computer interaction studies the ways in which humans make—or do not make—use of computational artifacts, systems, and infrastructures. Much of the research in this field seeks to improve the human–computer interaction by improving the usability of computer interfaces.[9] How usability is to be precisely understood, how it relates to other social and cultural values, and when it is, and when it may not be a desirable property of computer interfaces is increasingly debated.[10][11]

Much of the research in the field of human–computer interaction takes an interest in:

  • Methods for designing new computer interfaces, thereby optimizing a design for a desired property such as learnability, findability, the efficiency of use.
  • Methods for implementing interfaces, e.g., by means of software libraries.
  • Methods for evaluating and comparing interfaces with respect to their usability and other desirable properties.
  • Methods for studying human–computer use and its sociocultural implications more broadly.
  • Methods for determining whether or not the user is human or computer.
  • Models and theories of human–computer use as well as conceptual frameworks for the design of computer interfaces, such as cognitivist user models, Activity Theory, or ethnomethodological accounts of human–computer use.[12]
  • Perspectives that critically reflect upon the values that underlie computational design, computer use, and HCI research practice.[13]

Visions of what researchers in the field seek to achieve might vary. When pursuing a cognitivist perspective, researchers of HCI may seek to align computer interfaces with the mental model that humans have of their activities. When pursuing a post-cognitivist perspective, researchers of HCI may seek to align computer interfaces with existing social practices or existing sociocultural values.

Researchers in HCI are interested in developing design methodologies, experimenting with devices, prototyping software, and hardware systems, exploring interaction paradigms, and developing models and theories of interaction.

Design

edit

Principles

edit
 
The user interacts directly with hardware for the human input and output such as displays, e.g. through a graphical user interface. The user interacts with the computer over this software interface using the given input and output (I/O) hardware.
Software and hardware are matched so that the processing of the user input is fast enough, and the latency of the computer output is not disruptive to the workflow.

The following experimental design principles are considered, when evaluating a current user interface, or designing a new user interface:

  • Early focus is placed on the user(s) and task(s): How many users are needed to perform the task(s) is established and who the appropriate users should be is determined (someone who has never used the interface, and will not use the interface in the future, is most likely not a valid user). In addition, the task(s) the users will be performing and how often the task(s) need to be performed is defined.
  • Empirical measurement: the interface is tested with real users who come in contact with the interface daily. The results can vary with the performance level of the user and the typical human–computer interaction may not always be represented. Quantitative usability specifics, such as the number of users performing the task(s), the time to complete the task(s), and the number of errors made during the task(s) are determined.
  • Iterative design: After determining what users, tasks, and empirical measurements to include, the following iterative design steps are performed:
    1. Design the user interface
    2. Test
    3. Analyze results
    4. Repeat

The iterative design process is repeated until a sensible, user-friendly interface is created.[14]

Methodologies

edit

Various strategies delineating methods for human–PC interaction design have developed since the conception of the field during the 1980s. Most plan philosophies come from a model for how clients, originators, and specialized frameworks interface. Early techniques treated clients' psychological procedures as unsurprising and quantifiable and urged plan specialists to look at subjective science to establish zones, (for example, memory and consideration) when structuring UIs. Present-day models, in general, center around a steady input and discussion between clients, creators, and specialists and push for specialized frameworks to be folded with the sorts of encounters clients need to have, as opposed to wrapping user experience around a finished framework.

  • Activity theory: utilized in HCI to characterize and consider the setting where human cooperations with PCs occur. Action hypothesis gives a structure for reasoning about activities in these specific circumstances and illuminates the design of interactions from an action-driven perspective.[15]
  • User-centered design (UCD): a cutting-edge, broadly-rehearsed plan theory established on the possibility that clients must become the overwhelming focus in the plan of any PC framework. Clients, architects, and specialized experts cooperate to determine the requirements and restrictions of the client and make a framework to support these components. Frequently, client-focused plans are informed by ethnographic investigations of situations in which clients will associate with the framework. This training is like participatory design, which underscores the likelihood for end-clients to contribute effectively through shared plan sessions and workshops.
  • Principles of UI design: these standards may be considered during the design of a client interface: resistance, effortlessness, permeability, affordance, consistency, structure, and feedback.[16]
  • Value sensitive design (VSD): a technique for building innovation that accounts for the individuals who utilize the design straightforwardly, and just as well for those who the design influences, either directly or indirectly. VSD utilizes an iterative planning process that includes three kinds of examinations: theoretical, exact, and specialized. Applied examinations target the understanding and articulation of the different parts of the design, and its qualities or any clashes that may emerge for the users of the design. Exact examinations are subjective or quantitative plans to explore things used to advise the creators' understanding regarding the clients' qualities, needs, and practices. Specialized examinations can include either investigation of how individuals use related advances or the framework plans.[17]

Display designs

edit

Displays are human-made artifacts designed to support the perception of relevant system variables and facilitate further processing of that information. Before a display is designed, the task that the display is intended to support must be defined (e.g., navigating, controlling, decision making, learning, entertaining, etc.). A user or operator must be able to process whatever information a system generates and displays; therefore, the information must be displayed according to principles to support perception, situation awareness, and understanding.

Thirteen principles of display design

edit

Christopher Wickens et al. defined 13 principles of display design in their book An Introduction to Human Factors Engineering.[18]

These human perception and information processing principles can be utilized to create an effective display design. A reduction in errors, a reduction in required training time, an increase in efficiency, and an increase in user satisfaction are a few of the many potential benefits that can be achieved by utilizing these principles.

Certain principles may not apply to different displays or situations. Some principles may also appear to be conflicting, and there is no simple solution to say that one principle is more important than another. The principles may be tailored to a specific design or situation. Striking a functional balance among the principles is critical for an effective design.[19]

Perceptual principles

edit

1.Make displays legible (or audible). A display's legibility is critical and necessary for designing a usable display. If the characters or objects being displayed cannot be discernible, the operator cannot effectively use them.

2.Avoid absolute judgment limits. Do not ask the user to determine the level of a variable based on a single sensory variable (e.g., color, size, loudness). These sensory variables can contain many possible levels.

3.Top-down processing. Signals are likely perceived and interpreted by what is expected based on a user's experience. If a signal is presented contrary to the user's expectation, more physical evidence of that signal may need to be presented to assure that it is understood correctly.

4.Redundancy gain. If a signal is presented more than once, it is more likely to be understood correctly. This can be done by presenting the signal in alternative physical forms (e.g., color and shape, voice and print, etc.), as redundancy does not imply repetition. A traffic light is a good example of redundancy, as color and position are redundant.

5.Similarity causes confusion: Use distinguishable elements. Signals that appear to be similar will likely be confused. The ratio of similar features to different features causes signals to be similar. For example, A423B9 is more similar to A423B8 than 92 is to 93. Unnecessarily similar features should be removed, and dissimilar features should be highlighted.

Mental model principles

edit

6. Principle of pictorial realism. A display should look like the variable that it represents (e.g., the high temperature on a thermometer shown as a higher vertical level). If there are multiple elements, they can be configured in a manner that looks like they would in the represented environment.

7. Principle of the moving part. Moving elements should move in a pattern and direction compatible with the user's mental model of how it actually moves in the system. For example, the moving element on an altimeter should move upward with increasing altitude.

Principles based on attention

edit

8. Minimizing information access cost or interaction cost. When the user's attention is diverted from one location to another to access necessary information, there is an associated cost in time or effort. A display design should minimize this cost by allowing frequently accessed sources to be located at the nearest possible position. However, adequate legibility should not be sacrificed to reduce this cost.

9. Proximity compatibility principle. Divided attention between two information sources may be necessary for the completion of one task. These sources must be mentally integrated and are defined to have close mental proximity. Information access costs should be low, which can be achieved in many ways (e.g., proximity, linkage by common colors, patterns, shapes, etc.). However, close display proximity can be harmful by causing too much clutter.

10. Principle of multiple resources. A user can more easily process information across different resources. For example, visual and auditory information can be presented simultaneously rather than presenting all visual or all auditory information.

Memory principles

edit

11. Replace memory with visual information: knowledge in the world. A user should not need to retain important information solely in working memory or retrieve it from long-term memory. A menu, checklist, or another display can aid the user by easing the use of their memory. However, memory use may sometimes benefit the user by eliminating the need to reference some knowledge globally (e.g., an expert computer operator would rather use direct commands from memory than refer to a manual). The use of knowledge in a user's head and knowledge in the world must be balanced for an effective design.

12. Principle of predictive aiding. Proactive actions are usually more effective than reactive actions. A display should eliminate resource-demanding cognitive tasks and replace them with simpler perceptual tasks to reduce the user's mental resources. This will allow the user to focus on current conditions and to consider possible future conditions. An example of a predictive aid is a road sign displaying the distance to a certain destination.

13. Principle of consistency. Old habits from other displays will easily transfer to support the processing of new displays if they are designed consistently. A user's long-term memory will trigger actions that are expected to be appropriate. A design must accept this fact and utilize consistency among different displays.

Current research

edit

Topics in human–computer interaction include the following:

Social computing

edit

Social computing is an interactive and collaborative behavior considered between technology and people. In recent years, there has been an explosion of social science research focusing on interactions as the unit of analysis, as there are a lot of social computing technologies that include blogs, emails, social networking, quick messaging, and various others. Much of this research draws from psychology, social psychology, and sociology. For example, one study found out that people expected a computer with a man's name to cost more than a machine with a woman's name.[20] Other research finds that individuals perceive their interactions with computers more negatively than humans, despite behaving the same way towards these machines.[21]

Knowledge-driven human–computer interaction

edit

In human and computer interactions, a semantic gap usually exists between human and computer's understandings towards mutual behaviors. Ontology, as a formal representation of domain-specific knowledge, can be used to address this problem by solving the semantic ambiguities between the two parties.[22]

Emotions and human–computer interaction

edit

In the interaction of humans and computers, research has studied how computers can detect, process, and react to human emotions to develop emotionally intelligent information systems. Researchers have suggested several 'affect-detection channels'. The potential of telling human emotions in an automated and digital fashion lies in improvements to the effectiveness of human–computer interaction. The influence of emotions in human–computer interaction has been studied in fields such as financial decision-making using ECG and organizational knowledge sharing using eye-tracking and face readers as affect-detection channels. In these fields, it has been shown that affect-detection channels have the potential to detect human emotions and those information systems can incorporate the data obtained from affect-detection channels to improve decision models.

Brain–computer interfaces

edit

A brain–computer interface (BCI), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.[23]

Security interactions

edit

Security interactions are the study of interaction between humans and computers specifically as it pertains to information security. Its aim, in plain terms, is to improve the usability of security features in end user applications.

Unlike HCI, which has roots in the early days of Xerox PARC during the 1970s, HCISec is a nascent field of study by comparison. Interest in this topic tracks with that of Internet security, which has become an area of broad public concern only in very recent years.

When security features exhibit poor usability, the following are common reasons:

  • they were added in casual afterthought
  • they were hastily patched in to address newly discovered security bugs
  • they address very complex use cases without the benefit of a software wizard
  • their interface designers lacked understanding of related security concepts
  • their interface designers were not usability experts (often meaning they were the application developers themselves)

Factors of change

edit

Traditionally, computer use was modeled as a human–computer dyad in which the two were connected by a narrow explicit communication channel, such as text-based terminals. Much work has been done to make the interaction between a computing system and a human more reflective of the multidimensional nature of everyday communication. Because of potential issues, human–computer interaction shifted focus beyond the interface to respond to observations as articulated by D. Engelbart: "If ease of use were the only valid criterion, people would stick to tricycles and never try bicycles."[24]

How humans interact with computers continues to evolve rapidly. Human–computer interaction is affected by developments in computing. These forces include:

  • Decreasing hardware costs leading to larger memory and faster systems
  • Miniaturization of hardware leading to portability
  • Reduction in power requirements leading to portability
  • New display technologies leading to the packaging of computational devices in new forms
  • Specialized hardware leading to new functions
  • Increased development of network communication and distributed computing
  • Increasingly widespread use of computers, especially by people who are outside of the computing profession
  • Increasing innovation in input techniques (e.g., voice, gesture, pen), combined with lowering cost, leading to rapid computerization by people formerly left out of the computer revolution.
  • Wider social concerns leading to improved access to computers by currently disadvantaged groups

As of 2010 the future for HCI is expected[25] to include the following characteristics:

  • Ubiquitous computing and communication. Computers are expected to communicate through high-speed local networks, nationally over wide-area networks, and portably via infrared, ultrasonic, cellular, and other technologies. Data and computational services will be portably accessible from many if not most locations to which a user travels.
  • High-functionality systems. Systems can have large numbers of functions associated with them. There are so many systems that most users, technical or non-technical, do not have time to learn about traditionally (e.g., through thick user manuals).
  • The mass availability of computer graphics. Computer graphics capabilities such as image processing, graphics transformations, rendering, and interactive animation become widespread as inexpensive chips become available for inclusion in general workstations and mobile devices.
  • Mixed media. Commercial systems can handle images, voice, sounds, video, text, formatted data. These are exchangeable over communication links among users. The separate consumer electronics fields (e.g., stereo sets, DVD players, televisions) and computers are beginning to merge. Computer and print fields are expected to cross-assimilate.
  • High-bandwidth interaction. The rate at which humans and machines interact is expected to increase substantially due to the changes in speed, computer graphics, new media, and new input/output devices. This can lead to qualitatively different interfaces, such as virtual reality or computational video.
  • Large and thin displays. New display technologies are maturing, enabling huge displays and displays that are thin, lightweight, and low in power use. This has large effects on portability and will likely enable developing paper-like, pen-based computer interaction systems very different in feel from present desktop workstations.
  • Information utilities. Public information utilities (such as home banking and shopping) and specialized industry services (e.g., weather for pilots) are expected to proliferate. The proliferation rate can accelerate with the introduction of high-bandwidth interaction and the improvement in the quality of interfaces.

Scientific conferences

edit

One of the main conferences for new research in human–computer interaction is the annually held Association for Computing Machinery's (ACM) Conference on Human Factors in Computing Systems, usually referred to by its short name CHI (pronounced kai, or Khai). CHI is organized by ACM Special Interest Group on Computer-Human Interaction (SIGCHI). CHI is a large conference, with thousands of attendants, and is quite broad in scope. It is attended by academics, practitioners, and industry people, with company sponsors such as Google, Microsoft, and PayPal.

There are also dozens of other smaller, regional, or specialized HCI-related conferences held around the world each year, including:[26]

See also

edit

Footnotes

edit
  1. ^ Carlisle, James H. (June 1976). "Evaluating the impact of office automation on top management communication". Proceedings of the June 7-10, 1976, national computer conference and exposition on - AFIPS '76. Proceedings of the June 7–10, 1976, National Computer Conference and Exposition. pp. 611–616. doi:10.1145/1499799.1499885. S2CID 18471644. Use of 'human–computer interaction' appears in references
  2. ^ Suchman, Lucy (1987). Plans and Situated Action. The Problem of Human-Machine Communication. New York, Cambridge: Cambridge University Press. ISBN 9780521337397. Retrieved 7 March 2015.
  3. ^ Dourish, Paul (2001). Where the Action Is: The Foundations of Embodied Interaction. Cambridge, MA: MIT Press. ISBN 9780262541787.
  4. ^ a b c Hewett; Baecker; Card; Carey; Gasen; Mantei; Perlman; Strong; Verplank. "ACM SIGCHI Curricula for Human–Computer Interaction". ACM SIGCHI. Archived from the original on 17 August 2014. Retrieved 15 July 2014.
  5. ^ Gurcan, Fatih; Cagiltay, Nergiz Ercil; Cagiltay, Kursat (2021-02-07). "Mapping Human–Computer Interaction Research Themes and Trends from Its Existence to Today: A Topic Modeling-Based Review of past 60 Years". International Journal of Human–Computer Interaction. 37 (3): 267–280. doi:10.1080/10447318.2020.1819668. ISSN 1044-7318. S2CID 224998668.
  6. ^ Ergoweb. "What is Cognitive Ergonomics?". Ergoweb.com. Archived from the original on September 28, 2011. Retrieved August 29, 2011.
  7. ^ "NRC: Backgrounder on the Three Mile Island Accident". Nrc.gov. Archived from the original on August 24, 2019. Retrieved August 29, 2011.
  8. ^ "Report of the President's Commission on the Accident at Three Miles Island" (PDF). 2019-03-14. Archived from the original on 2011-04-09. Retrieved 2011-08-17.{{cite web}}: CS1 maint: unfit URL (link)
  9. ^ Grudin, Jonathan (1992). "Utility and usability: research issues and development contexts". Interacting with Computers. 4 (2): 209–217. doi:10.1016/0953-5438(92)90005-z.
  10. ^ Chalmers, Matthew; Galani, Areti (2004). "Seamful interweaving". Proceedings of the 5th conference on Designing interactive systems: Processes, practices, methods, and techniques (PDF). pp. 243–252. doi:10.1145/1013115.1013149. ISBN 978-1581137873. S2CID 12500442. Archived (PDF) from the original on 2020-08-01. Retrieved 2019-10-04.
  11. ^ Barkhuus, Louise; Polichar, Valerie E. (2011). "Empowerment through seamfulness: smart phones in everyday life". Personal and Ubiquitous Computing. 15 (6): 629–639. doi:10.1007/s00779-010-0342-4.
  12. ^ Rogers, Yvonne (2012). "HCI Theory: Classical, Modern, and Contemporary". Synthesis Lectures on Human-Centered Informatics. 5 (2): 1–129. doi:10.2200/S00418ED1V01Y201205HCI014.
  13. ^ Sengers, Phoebe; Boehner, Kirsten; David, Shay; Joseph, Kaye (2005). "Reflective design". Proceedings of the 4th decennial conference on Critical computing: Between sense and sensibility. Vol. 5. pp. 49–58. doi:10.1145/1094562.1094569. ISBN 978-1595932037. S2CID 9029682.
  14. ^ Green, Paul (2008). Iterative Design. Lecture presented in Industrial and Operations Engineering 436 (Human Factors in Computer Systems, University of Michigan, Ann Arbor, MI, February 4, 2008.
  15. ^ Kaptelinin, Victor (2012): Activity Theory. In: Soegaard, Mads and Dam, Rikke Friis (eds.). "Encyclopedia of Human–Computer Interaction". The Interaction-Design.org Foundation. Available online at http://www.interaction-design.org/encyclopedia/activity_theory.html Archived 2012-03-23 at the Wayback Machine
  16. ^ "The Case for HCI Design Patterns". Archived from the original on 2019-09-28. Retrieved 2019-08-26.
  17. ^ Friedman, B., Kahn Jr, P. H., Borning, A., & Kahn, P. H. (2006). Value Sensitive Design and information systems. Human–Computer Interaction and Management Information Systems: Foundations. ME Sharpe, New York, 348–372.
  18. ^ Wickens, Christopher D., John D. Lee, Yili Liu, and Sallie E. Gordon Becker. An Introduction to Human Factors Engineering. Second ed. Upper Saddle River, NJ: Pearson Prentice Hall, 2004. 185–193.
  19. ^ Brown, C. Marlin. Human–Computer Interface Design Guidelines. Intellect Books, 1998. 2–3.
  20. ^ Posard, Marek (2014). "Status processes in human–computer interactions: Does gender matter?". Computers in Human Behavior. 37 (37): 189–195. doi:10.1016/j.chb.2014.04.025.
  21. ^ Posard, Marek; Rinderknecht, R. Gordon (2015). "Do people like working with computers more than human beings?". Computers in Human Behavior. 51: 232–238. doi:10.1016/j.chb.2015.04.057.
  22. ^ Dong, Hai; Hussain, Farookh; Elizabeth, Chang (2010). "A human-centered semantic service platform for the digital ecosystems environment". World Wide Web. 13 (1–2): 75–103. doi:10.1007/s11280-009-0081-5. hdl:20.500.11937/29660. S2CID 10746264.
  23. ^ Krucoff, Max O.; Rahimpour, Shervin; Slutzky, Marc W.; Edgerton, V. Reggie; Turner, Dennis A. (2016-01-01). "Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation". Frontiers in Neuroscience. 10: 584. doi:10.3389/fnins.2016.00584. PMC 5186786. PMID 28082858.
  24. ^ Fischer, Gerhard (1 May 2000). "User Modeling in Human–Computer Interaction". User Modeling and User-Adapted Interaction. 11 (1–2): 65–86. doi:10.1023/A:1011145532042.
  25. ^ SINHA, Gaurav; SHAHI, Rahul; SHANKAR, Mani. Human–Computer Interaction. In: Emerging Trends in Engineering and Technology (ICETET), 2010 3rd International Conference on. IEEE, 2010. p. 1–4.
  26. ^ "Conference Search: hci". www.confsearch.org. Archived from the original on 2009-08-20. Retrieved 2009-05-15.

Further reading

edit
Academic overviews of the field
  • Julie A. Jacko (Ed.). (2012). Human–Computer Interaction Handbook (3rd Edition). CRC Press. ISBN 1-4398-2943-8
  • Andrew Sears and Julie A. Jacko (Eds.). (2007). Human–Computer Interaction Handbook (2nd Edition). CRC Press. ISBN 0-8058-5870-9
  • Julie A. Jacko and Andrew Sears (Eds.). (2003). Human–Computer Interaction Handbook. Mahwah: Lawrence Erlbaum & Associates. ISBN 0-8058-4468-6
  • Dix, A. (2004). Human–computer interaction (3rd ed.). Pearson Education. ISBN 0-1304-6109-1
Historically important classic[citation needed]
Overviews of history of the field


Social science and HCI
Academic journals
Collection of papers
  • Ronald M. Baecker, Jonathan Grudin, William A. S. Buxton, Saul Greenberg (Eds.) (1995): Readings in human–computer interaction. Toward the Year 2000. 2. ed. Morgan Kaufmann, San Francisco 1995 ISBN 1-55860-246-1
  • Mithun Ahamed, Developing a Message Interface Architecture for Android Operating Systems, (2015). [4]
Treatments by one or few authors, often aimed at a more general audience
Textbooks
edit