The mapping requires the user to figure out how to accomplish a goal with an interface. It implies that "The user must translate the psychological goals and intentions into the desired system state, then determine what settings of the control mechanisms will yield that state, and then determine what physical manipulations of the mechanism are required" [600, p. 37].

In direct manipulation interfaces (Chapter 28), the visual presentation of an object resembles its physical correspondent and can be directly acted on. For example, text in a text editor can be highlighted, deleted, or changed by point-and-click-style interactions [416].

the seven-stage model of interaction proposed by Norman [600] applies to all modalities of interaction

They also aid design and engineering by highlighting desirable properties of a dialogue system [5].

This AAC system was designed to use context to facilitate the creation of personal narratives [75].

The cognitive scientist Kirsh presented a criticism of Norman's view of dialogue and developed an alternative based on the theory of embodied cognition [416].

Horvitz [360] summarized the principles of mixed-initiative interfaces as follows:

A research group at the University of Washington [60] recruited 10 families and recorded their communications with Amazon Echo Dot (Alexa) for four weeks.

Communication repair refers to the "work of restoring shared understanding" when conversational partners misunderstand each other [60].

Section 18.3 outlines a view of dialogue developed by Suchman [804] that emphasizes the situated nature of dialogue.

A cornerstone of this research is the book Plans and Situated Action: The Problem of Human–Machine Communication by Suchman [804].

According to Scholtz [745], the two gulfs manifest differently in the different roles a user may have when interacting with a robot:

Norman's model stresses the need for users' acts to be understood by the computer and for users to understand the computer. Successful interfaces should also "provide a strong sense of understanding and control" [600, p. 49].

Affordance, which we discussed in Chapter 3, refers to how well users can interpret what actions are possible with a widget. Visibility is a handy related concept in design that underlies direct manipulation interfaces [416].

Norman suggested that the ease of mapping is related to its directness, "where directness can be measured by the complexity of the relationship between representation and value, measured by the length of the description of the mapping" [600, pp. 28–29].

Norman offered two central concepts to help us understand these cognitive efforts: the gulf of execution and the gulf of evaluation (Figure 18.2).

A significant early theory of dialogue interaction is the seven-stage model of Norman [600]. It considers interaction as goal-directed, turn-based dialogue.

Liu and Chilton [488] studied prompt engineering for text-to-image generation; see the figure in this paper example box, which shows examples of answers to the prompt "SUBJECT in the style of STYLE."

Liu and Chilton [488] noted that interaction with such models faces a dilemma. While it is possible to input anything as a prompt to such models, users must "engage in bruteforce trial and error with the text prompt when the result quality is poor."

The cognitive scientist Kirsh presented a criticism of Norman's view of dialogue and developed an alternative based on the theory of embodied cognition [416].

The How was School today. . .? concept was developed iteratively with two children with CP and the help of school staff. This AAC system was designed to use context to facilitate the creation of personal narratives [75].

According to Scholtz [745], the two gulfs manifest differently in the different roles a user may have when interacting with a robot:

Horvitz [360] summarized the principles of mixed-initiative interfaces as follows:

A research group at the University of Washington [60] recruited 10 families and recorded their communications with Amazon Echo Dot (Alexa) for four weeks.

According to Suchman, robustness is a key consideration in the design of dialogue.

A cornerstone of this research is the book Plans and Situated Action: The Problem of Human–Machine Communication by Suchman [804].

Liu and Chilton [488] studied prompt engineering for text-to-image generation

Liu and Chilton [488] noted that interaction with such models faces a dilemma. While it is possible to input anything as a prompt to such models, users must

The How was School today. . .? concept was developed iteratively with two children with CP and the help of school staff. This AAC system was designed to use context to facilitate the creation of personal narratives [75].

The cognitive scientist Kirsh presented a criticism of Norman's view of dialogue and developed an alternative based on the theory of embodied cognition [416].

Horvitz [360] summarized the principles of mixed-initiative interfaces as follows:

A research group at the University of Washington [60] recruited 10 families and recorded their communications with Amazon Echo Dot (Alexa) for four weeks.

According to Scholtz [745], the two gulfs manifest differently in the different roles a user may have when interacting with a robot.

Liu and Chilton [488] studied prompt engineering for text-to-image generation.

Liu and Chilton [488] noted that interaction with such models faces a dilemma.

Section 18.3 outlines a view of dialogue developed by Suchman [804] that emphasizes the situated nature of dialogue.

A cornerstone of this research is the book Plans and Situated Action: The Problem of Human–Machine Communication by Suchman [804].

Norman offered two central concepts to help us understand these cognitive efforts: the gulf of execution and the gulf of evaluation (Figure 18.2).

A significant early theory of dialogue interaction is the seven-stage model of Norman [600].

A good design allows users to try out options without penalizing trials.

Kirsh argued that we are not just passively reacting to computer-generated options.

Kirsh argued that users need to actively explore interfaces to become aware of the available functions and how they work.

Kirsh points out that Norman's model makes an unrealistic assumption: The user is assumed to know the environment and its options and is merely picking an option.

Generally, it is beneficial when mixed-initiative interfaces learn and adapt to individual users.

A mixed-initiative interface needs to infer the user's goals so that it can act upon them.

Mixed-initiative interaction is the idea of organizing interaction in dialogue where both the computer and the human can take initiative.

Code-switching refers to a switch in language to match the capabilities of the communication partner.

According to Suchman, robustness is a key consideration in the design of dialogue.

Human–machine interaction, according to Suchman, is similar to but different from human–human dialogue.

Communication between humans and computers is a long-standing topic of HCI research.

FSMs are an effective way to describe how dialogue is structured; however, they are limited to memory-free dialogue.

An FSM can be graphically presented as a graph where nodes represent states and edges represent transitions.

An FSM is a model of discrete computation applicable to dialogues.

A mode refers to the variation in the interpretation of a user's input according to an internal state.

Dialogue can be described using models of computation from computer science.

Affordance, which we discussed in Chapter 3, refers to how well users can interpret what actions are possible with a widget.

Mapping and feedback are crucial concepts for understanding a computer's turn.

Norman offered two central concepts to help us understand these cognitive efforts: the gulf of execution and the gulf of evaluation.

A significant early theory of dialogue interaction is the seven-stage model of Norman [600].

Fourth, both the computer and the user may have initiative.

Third, in dialogue, both the computer and the human participate in establishing a shared context.

Second, both dialogues in Figure 18.1 evolve in a turn-based manner.

Both are forms of dialogue.

This broad definition has several immediate and important consequences for HCI.

In one turn, an appropriate communication act is made by one partner based on the communication context.

The key idea in the dialogue view of interaction is the organization of communication as a series of turns.

The dialogue view of interaction evolved early in the history of computing.

In human–computer interaction (HCI), the communication partners are an interactive system and the user of such a system.

Interaction may be viewed as a dialogue, that is, a conversation that occurs between two partners in a context for some purpose.

Fourth, both the computer and the user may have initiative. For example, a pop-up window can be presented to confirm a risky selection.

Therefore, the design of feedback, affordances, and cues is central to dialogue-based interaction.

Third, in dialogue, both the computer and the human participate in establishing a shared context. The computer does not simply receive a message; it also communicates the effects of that message.

Context, as we will see, can be understood through the concept of a state: The feasible communication acts and their effects are conditioned by the state of the partner.

In other words, in dialogue, acts of communication are conditional: The meaning of a turn depends on the communication context.

Siri's reply and the selection of "compose" would make no sense without the context provided by the preceding exchange.

Second, both dialogues in Figure 18.1 evolve in a turn-based manner. Each turn redefines the communication context.

For instance, the seven-stage model of interaction proposed by Norman [600] applies to all modalities of interaction; Section 18.1 explains this model in detail.

In Figure 18.1, two nominally different types of interaction are shown: speech-based and graphical. Both are forms of dialogue. This means that the concepts of dialogue are applicable across modalities.

This broad definition has several immediate and important consequences for HCI. First, dialogue, as a form of interaction, is not limited to speech and language even though this is often our first interpretation of the term "dialogue."

Initially, text consoles were used to provide access to programs running on mainframe computers.

This made it possible to structure interaction in the form of a dialogue, freeing the user from having to memorize commands, as required in command-based interfaces.

From the 1960s to the 1980s, rapid advances in computer displays made it possible to present much richer information to users.

The dialogue view of interaction evolved early in the history of computing.

These theories also have implications for how we design interaction.

These theories explain what happens in dialogue and how it shapes the relationship between the partners.

HCI researchers have developed a rich palette of theories to understand such dialogues.

In human–computer interaction (HCI), the communication partners are an interactive system and the user of such a system.

This view draws on what we know about human–human communication and, in particular, how conversations are structured; see Chapter 9 for a summary.

Interaction may be viewed as a dialogue, that is, a conversation that occurs between two partners in a context for some purpose.

Dialogue can be understood as computation, goal-directed action, communication, or embodied action.

Dialogue interaction includes speech-based and graphical interactions.

The core elements of dialogue are communication turns, the communication context, and turn interpretation.

Dialogue is about the organization of communication as a series of turns between communication partners.

A mode refers to the variation in the interpretation of a user's input according to an internal state.

Code-switching refers to a switch in language to match the capabilities of the communication partner.

Communication repair refers to the "work of restoring shared understanding" when conversational partners misunderstand each other.

Robustness refers to the communication partners' ability to achieve shared understanding even in light of misunderstandings and other unanticipated troubles.

Mixed-initiative interaction is the idea of organizing interaction in dialogue where both the computer and the human can take initiative.

An FSM is a model of discrete computation applicable to dialogues.

Dialogue can be described using models of computation from computer science.

Mapping and feedback are crucial concepts for understanding a computer's turn.

Norman offered two central concepts to help us understand these cognitive efforts: the gulf of execution and the gulf of evaluation.

A significant early theory of dialogue interaction is the seven-stage model of Norman.

This understanding then forms the context within which the other partner takes their turn.

The act aims to get the other partner to do or understand something.

In one turn, an appropriate communication act is made by one partner based on the communication context.

Dialogue evolves through communication turns between two or more partners.

The key idea in the dialogue view of interaction is the organization of communication as a series of turns.

Interaction may be viewed as a dialogue, that is, a conversation that occurs between two partners in a context for some purpose.

Robustness refers to the communication partners' ability to achieve shared understanding even in light of misunderstandings and other unanticipated troubles.

Communication repair refers to the "work of restoring shared understanding" when conversational partners misunderstand each other.

Mixed-initiative interaction is the idea of organizing interaction in dialogue where both the computer and the human can take initiative.

Gulf of evaluation: This gulf refers to knowing how a perceived change in the computer has moved it closer to the intended goal state.

Gulf of execution: This gulf is about knowing what to do to bring about a desired state change in the computer.

Code-switching refers to a switch in language to match the capabilities of the communication partner.

An FSM is a model of discrete computation applicable to dialogues. In computer science, an FSM is a special case of a Turing machine that reads but does not write on the tape.

A mode refers to the variation in the interpretation of a user's input according to an internal state. In a modeless dialogue, all inputs are possible in all states and their interpretation is always the same.

The key idea in the dialogue view of interaction is the organization of communication as a series of turns. Dialogue evolves through communication turns between two or more partners. In one turn, an appropriate communication act is made by one partner based on the communication context. The act aims to get the other partner to do or understand something. This understanding then forms the context within which the other partner takes their turn.

Interaction may be viewed as a dialogue, that is, a conversation that occurs between two partners in a context for some purpose.