revisions of the revisions

thesis/chapters/02_background.tex

@@ -61,13 +61,11 @@ This expanding landscape reveals a persistent fundamental gap in the design spac
     \node[desc] at (8.25, 1.7) {Requires specialized\\training\\No methodological rigor};
 
 \end{tikzpicture}
-\caption{The design space of WoZ tools categorized by technical barrier and methodological rigor. A fundamental gap exists for a platform that is both accessible and rigorous.}
+\caption{WoZ tool design space by technical barrier and methodological rigor.}
 \label{fig:tool-matrix}
 \end{figure}
 
-By methodological rigor, I refer to systematic features that guide experimenters toward best practices: consistently following experimental protocols, maintaining comprehensive logging, and producing reproducible experimental designs.
-
-Moreover, few platforms directly address the methodological concerns raised by systematic reviews of WoZ research. Riek's influential analysis \cite{Riek2012} of 54 HRI studies uncovered widespread inconsistencies in how wizard behaviors were controlled and reported. Very few studies documented standardized wizard training procedures or measured wizard error rates, raising questions about internal validity---that is, whether observed outcomes can be attributed to the intended experimental manipulation rather than to uncontrolled variation in wizard behavior. The tools themselves often exacerbate this problem: poorly designed interfaces increase cognitive load on wizards, leading to timing errors and behavioral inconsistencies that can confound experimental results. Recent work by Strazdas et al. \cite{Strazdas2020} further demonstrates the importance of careful interface design in WoZ systems, showing that intuitive wizard interfaces directly improve both the quality of robot behavior and the reliability of collected data.
+The missing quadrant in Figure~\ref{fig:tool-matrix} matters because methodological rigor requires systematic features that guide experimenters toward best practices: consistently following experimental protocols, maintaining comprehensive logging, and producing reproducible experimental designs. Few platforms directly address the methodological concerns raised by systematic reviews of WoZ research. Riek's influential analysis \cite{Riek2012} of 54 HRI studies uncovered widespread inconsistencies in how wizard behaviors were controlled and reported. Very few studies documented standardized wizard training procedures or measured wizard error rates, raising questions about internal validity---that is, whether observed outcomes can be attributed to the intended experimental manipulation rather than to uncontrolled variation in wizard behavior. The tools themselves often exacerbate this problem: poorly designed interfaces increase cognitive load on wizards, leading to timing errors and behavioral inconsistencies that can confound experimental results. Recent work by Strazdas et al. \cite{Strazdas2020} further demonstrates the importance of careful interface design in WoZ systems, showing that intuitive wizard interfaces directly improve both the quality of robot behavior and the reliability of collected data.
 
 \section{Requirements for Modern WoZ Infrastructure}