%!TEX root = ../hdrmain.tex
-\chapter{Engineering of interactive systems}
+\chapter{A model of interactive systems}
\epigraph{\lorem}{Auteur}
\begin{Abstract}
We discuss the similarities and differences of the two models, how they combine, as well as implications for the design of interactive systems.
\end{Abstract}
-\section{7 stages model}
+%\section{7 stages model}
Studying interactive system is a complex task because it requires knowledge on a wide range of areas.
It spans from human sciences such as psychology, biology or sociology, to technical sciences such as computer science, electronics, mechanics, automatics or mathematics.
All these experts need a common ground for studying interactive systems together.
+In particular, despite the fact that computers are intended for interacting with humans, they are still not designed for this use.
+They are still designed for computation in mind.
+There is certainly an historical reason for this, exacerbated by inertia and resistance to change.
+However we argue here that the theoretical background computers are built upon is the main reason why today computers are designed for computation rather than for interaction.
-\begin{idee}
-In the paper we mentioned the usefulness of this model for several audiences. We will elaborate more on the objectives for HCI researchers and practitioners.
-Our model provides a framework for describing the software and hardware parts of an interactive system. We will describe it along three dimensions Beaudouin Lafon proposed to evaluate interaction models~\cite{mbl04} descriptive, evaluative and generative.
+In this chapter we first present existing models of computation, software and users.
+Then we describe our own model.
+Finally, we describe two case studies, to demonstrate the descriptive and evaluative powers of our model.
-\begin{itemize}
-\item Descriptive power. Many research papers do not describe critical information such as transfer functions, input\&output mappings, actuator response, …. Our model is a systematic structure for describing interactive systems. Such a description enables highlighting useful implementation details. Benefits include replicability, and highlighting potential undesired side effects in psychophysical experiments for instance.
-\item Evaluative power. Implementing hardware+software interactive systems is a particular difficult task. Many of these, including published research prototypes, have implementation issues that could be avoided with using a systematic approach. For example input systems have jitter because they do not use filtering. Many vibrotactile systems give poor feedback because they have a high inertia. Describing interactive systems with this common framework would make it easier to compare their implementation, and identify implementation issues.
-\item Generative power. The description of interactive systems with a common framework also has the advantage of inspiring alternative designs, new combination of designs and transgressive uses of technology.
-\end{itemize}
+\begin{idee}
+None of the computational and software models consider the hardware part
\end{idee}
+\section{Modelling interactive systems}
+
\begin{idee}
-Reviewers questioned the similarity with past research due to insufficient positioning in the paper. Past research they mention on toolkits and tasks models essentially focus on the application, input phrase or encoding stages of our model. However, in the HCI community we observe a notable rise of custom hardware for the design of interactive systems in the past decade. Our model covers both the software and hardware parts of interactive systems, as a whole.
+Reviewers questioned the similarity with past research due to insufficient positioning in the paper. Past research they mention on toolkits and tasks models essentially focus on the application, input phrase or encoding stages of our model. However, in the HCI community we observe a notable rise of custom hardware for the design of interactive systems in the past decade. Our model covers both the software and hardware parts of interactive systems, as{} a whole.
\end{idee}
+\cite{hornbaek17}
+
+\subsection{Computational models}
+
Computing models such as $\lambda$-calculus~\cite{church32} or Turing machines~\cite{turing38} focus on solving numerical problem, and overlook the interaction machines have with their environment.
While people daily interact with a world full of interactive devices, machines constantly interact with the world full of humans.
Because of that, Goldin and Wegner showed that interaction is a more general model of computing that Turing-complete models~\cite{goldin08}.
+They argue that the universality of the computing models above is due to the fact they all rely on induction~\cite{wegner99}.
+Interaction is rather a co-inductive phenomenon.
+
+The induction mechanism converges to base cases, which ensures computation always terminates.
+At the opposite, co-induction is a process that applies to streams as input are received.
+The question whether the co-inductive process terminates is not relevant.
+It potentially runs forever on an infinite input stream.
+This is a necessary mechanism to model and implement interaction with external agents.
+
+\begin{algorithm}[htb]
+\SetAlgoLined
+\caption{Typical main function of an interactive application}
+\While{true}{
+ get inputs\;
+ update internal model\;
+ generate outputs\;
+}
+\end{algorithm}
+
+\subsection{Software models}
+
+PAC \cite{coutaz87}
+Arch \cite{arch92}
+MVC \cite{reenskaug79a}
+Seeheim \cite{green85}
+
+\subsection{User models}
Many human behavior models are used in HCI, and there is an active community working on this.
With GOMS~\cite{card83} and Keystroke~\cite{card80} we can predict the time it takes for a person to use a keyboard or a pointer for example, including mental activities.
After describing the model, we discuss its combination with Norman's model, and its implications to the design of interactive systems.
-\subsection{Seven stages of reaction}
+\section{Seven stages of reaction}
Interactive systems globally work in a similar way than humans.
They sense the world, and they act on it.
\label{fig:mysevenstages}
\end{figure}
-\subsubsection{Input chain}
+\subsection{Input chain}
The input stage is the mirror of the evaluation part of the seven stages of action.
It comprises three stages that explain how interactive systems get informations from the environment.
%Multimodality is the combination of several modalities.
%\cite{oviatt99}.
-\subsubsection{Application}
+\subsection{Application}
The \emph{application} layer is specialized for assisting users in their tasks.
It executes actions as a result of input phrases, and produce outputs to give users feedback, and the result of their actions.
%Software architecture models such as further detail this stage.
-\subsubsection{Output chain}
+\subsection{Output chain}
The output chain mirrors the action part on the seven stages of action.
It describes the way interactive systems act on the world.
Last the physical effect can be inconsistent for the same command.
Some haptic devices can behave differently depending on ambient temperature, finger moisture, cleanliness, etc.
-\subsection{Interaction between users and systems}
+
+\begin{idee}
+In the paper we mentioned the usefulness of this model for several audiences. We will elaborate more on the objectives for HCI researchers and practitioners.
+Our model provides a framework for describing the software and hardware parts of an interactive system. We will describe it along three dimensions Beaudouin Lafon proposed to evaluate interaction models~\cite{mbl04} descriptive, evaluative and generative.
+
+\begin{itemize}
+\item Descriptive power. Many research papers do not describe critical information such as transfer functions, input\&output mappings, actuator response, …. Our model is a systematic structure for describing interactive systems. Such a description enables highlighting useful implementation details. Benefits include replicability, and highlighting potential undesired side effects in psychophysical experiments for instance.
+\item Evaluative power. Implementing hardware+software interactive systems is a particular difficult task. Many of these, including published research prototypes, have implementation issues that could be avoided with using a systematic approach. For example input systems have jitter because they do not use filtering. Many vibrotactile systems give poor feedback because they have a high inertia. Describing interactive systems with this common framework would make it easier to compare their implementation, and identify implementation issues.
+\item Generative power. The description of interactive systems with a common framework also has the advantage of inspiring alternative designs, new combination of designs and transgressive uses of technology.
+\end{itemize}
+\end{idee}
+
+\section{Interaction between users and systems}
The purpose of interactive systems is to assist users in their activities.
We can model the interaction of a user with a system by simply plugging the seven stages of action to the seven stages of reaction.
\label{fig:loops}
\end{figure}
-\subsubsection{Initiative}
+\subsection{Initiative}
In Norman's model, the first stage is the user's goal.
This means in this extended model that the user has the initiative, and the system reacts to her actions.
Designing interactive systems consists in combining users and machines strengths to compensate their weaknesses in order to empower users.
\begin{idee}
-Regarding related work on AI, while the paper does mention these topics, it is not the focus on this submission. There is certainly more to say on this, but it would require a proper paper. The Intervention UI paradigm is relevant to our model though, and will be discussed in the Initiative paragraph, where we already discuss Horvitz's mixed initiatives. It is a form of Beaudouin Lafon's partner paradigm, and integrates well in our model (Figure 4b).
+Regarding related work on AI, while the paper does mention these topics, it is not the focus on this submission. There is certainly more to say on this, but it would require a proper paper. The Intervention UI paradigm\cite{schmidt17} is relevant to our model though, and will be discussed in the Initiative paragraph, where we already discuss Horvitz's mixed initiatives. It is a form of Beaudouin Lafon's partner paradigm, and integrates well in our model (Figure 4b).
\end{idee}
\begin{figure}[htb]
%The interaction between a user and an interactive system is represented Figure~\ref{fig:extendedaction}.
%The user's actions are connected to the system sensors of the input devices, and the physical effects produced by the output devices are connected to the user's sensory organs.
-\subsubsection{Computing affordance}
+\subsection{Computing affordance}
The seven stages of actions are closely related to the notion of \emph{affordance}~\cite{gibson77}.
An affordance is a property between a person an an object that enables this person to perform a set of physical actions on this object.
%However the behavior of the system can be different, because of something unpredicted in the environment, or just because of a software or hardware malfunction.
-\subsubsection{Evolution}
+\subsection{Evolution}
The discrepancy between the the system behavior and the design model is complementary to the discrepancy between the user's model and the designer's model revealed by Norman's model.
They both contribute to the evolution of the interactive system.
Proving the behavior with rational methods of neural networks is a current challenge in machine learning.
Similarly to interactive systems, they seem to be more suited for empirical evaluations.
-\subsection{Conclusion}
+\section{Conclusion}
Designing and implementing an interactive system is hard because it connects sensory, cognitive, software and hardware components.
Mismatches between intended and actual behaviors can happen at any stage of the process.
\end{idee}
\cite{frisson17}
-\section{analytic? Case study (Latency)}
+\section{Evaluative Case study (Latency)}
\cite{casiez17}
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