update: discussion wpm + ter done

chap4/methodology.tex

@@ -20,8 +20,7 @@ hand was able to apply to distinct keys in different locations. We then created
 the design for the adjusted keyboard based on those measurements. Lastly, an
 experiment with twenty-four participants was conducted, where we compared the
 performance and user satisfaction while using four different keyboards,
-including our adjusted keyboard, to values obtained with the participant's own
+including our adjusted keyboard.
-keyboards.
 
 \subsection{Preliminary Telephone Interview}
 \label{sec:telephone_interview}

chap6/discussion.tex

@@ -1,2 +1,99 @@
 \section{Discussion}
-\label{sec:label}
+\label{sec:discussion}
+In the following sections, we reiterate on our findings presented in the last
+section and try to derive answers regarding our seven hypotheses and research
+question \textit{``Does an adjusted actuation force per key have a positive
+  impact on efficiency and overall satisfaction while using a mechanical
+  keyboard?''}.
+
+\subsection{Impact of Actuation Force on Typing Speed}
+\label{sec:dis_speed}
+
+Our main experiment yielded, that there are differences in typing speed for both
+metrics related to transcribed text we measured―namely \glsfirst{WPM} and
+\glsfirst{AdjWPM}. Especially the keyboard with the lowest uniform actuation
+force of 35 g―\textit{Nyx}―performed worse than all other keyboards. In terms of
+\gls{WPM}, \textit{Nyx (35 g)} was on average 4.1\% slower than \textit{Athena
+  (80 g)} and \textit{Aphrodite (50 g)} and 4.8\% slower than the adjusted
+keyboard \textit{Hera (35 - 60 g)}. Similarly, for \gls{AdjWPM}, \textit{Nyx}
+was 4.3\% slower than \textit{Athena} and \textit{Aphrodite} and 4.9\% slower
+than \textit{Hera}. The 4\% to 5\% difference in \gls{WPM} and \gls{AdjWPM} in
+our sample account for approximately 2 words per minute. When extrapolated with
+the mean daily keyboard usage of 6.69 hours reported by our participants, this
+difference would be as big as 803 words, which when put into perspective, is
+equivalent to roughly two full pages of only written content (11pt font
+size). Although, this specific example would assume constant typing for 6.69
+hours, it is still a useful estimate of the loss in productivity under normal
+working conditions over the course of several days. These differences in
+\gls{WPM} and \gls{AdjWPM} could be explained by the higher error rates and
+thereby the loss of ``typing flow'' we discuss in the next section. \gls{KSPS}
+reflects the raw input speed by including backspaces and previously deleted
+characters. The reason we included \gls{KSPS} in our analysis was to reveal
+possible differences in the physical speed participants type on a keyboard and
+not to further asses speed in the sense of productivity. We could not find any
+statistically significant differences in \gls{KSPS} but saw a trend, indicating
+that subjects typed a bit slower (< 3\%) on \textit{Athena (80 g)} compared to
+\textit{Aphrodite (50 g)} and \textit{Hera (35 - 60 g)}. With the differences in
+metrics that are commonly used to measure typing speed more closely related to
+productivity (\gls{WPM}, \gls{AdjWPM}) and the trends that indicate a slight
+difference in operating speed, we can accept our hypothesis that solely a
+difference in actuation force has an impact on typing speed.
+
+\begin{phga_hyp}[\checkmark]
+  Actuation force has an impact on typing speed (efficiency - speed).
+\end{phga_hyp}
+
+% During our telephone interviews 76\% of respondents would have preferred a
+% keyboard with lighter actuation force.
+
+% Our study tried to present the participant with a typing scenario that is as
+% close to a typical text input situation as possible, by allowing but not
+% enforcing the correction of erroneous input.
+
+\subsection{Impact of Actuation Force on Error Rate}
+\label{sec:dis_error}
+
+As already briefly mentioned in Section \ref{sec:dis_speed}, measured error
+rates like \glsfirst{UER}, \glsfirst{CER} and \glsfirst{TER} differed especially
+between \textit{Nyx (35 g)} and the other test keyboards. The statistical
+analyses further revealed, that \textit{Athena}, the keyboard with the highest
+actuation force of 80 g, produced on average 1\% less \gls{TER} than
+\textit{Hera (35 - 60 g)} and \textit{Aphrodite (50 g)} and 3\% less than
+\textit{Nyx (35g)}. Furthermore, \textit{Hera} and \textit{Aphrodite} both had a
+2\% lower \gls{TER} than \textit{Nyx}. Additionally to the quantitative results,
+fourteen of the twenty-four participants also reported, that \textit{Nyx's}
+light actuation force was the reason for many accidental key presses. It further
+stood out, that as shown in Figure \ref{fig:max_opc_ter}, \textit{Athena} was
+the most accurate keyboard for 58\% of participants and also more accurate than
+keyboard \textit{Own} for eleven of the subjects. This concludes, that a higher
+actuation force has a positive impact on error rate.
+
+\begin{phga_hyp}[\checkmark]
+  Higher key actuation force decreases typing errors compared to lower key
+  actuation force (efficiency - error rate).
+\end{phga_hyp}
+
+\textbf{Impact of \gls{TER} on \gls{WPM}}
+
+The higher error rates and the possibility to correct erroneous input could have
+also been a factor that led to lower \textit{WPM}. To evaluate the likelihood of
+this additional relation, we conducted a \gls{LRT} of fixed effects for our
+linear mixed-effects model with two random effects (participant and first/second
+typing test), fixed effect \gls{TER} and response variable \gls{WPM}. The
+results of the \gls{LRT} ($\chi^2(1)$ = 110.44, p = 0.00000000000000022)
+suggest, that the \gls{TER} indeed had an impact on \gls{WPM}. This could have
+been, because every time an error was made, almost all participants decided to
+correct it right away. With a higher error rate, this obviously leads to many
+short interruptions and an increased number of characters that are not taken
+into account when computing the \gls{WPM} metric.
+
+
+\subsection{Impact of Actuation Force on Satisfaction}
+\label{sec:dis_sati}
+
+\subsection{Impact of Actuation Force on Muscle Activity}
+\label{sec:dis_emg}
+
+\subsection{Impact of an Adjusted Keyboard on Typing Speed, Error Rate and
+  Satisfaction}
+\label{sec:dis_hera}

glossary.tex

@@ -43,6 +43,7 @@
 \newacronym{OPC}{OPC}{percentage of keyboard ``Own''}
 \newacronym{SP}{SP}{starting point}
 \newacronym{EP}{EP}{end point}
+\newacronym{LRT}{LRT}{Likelihood Ratio Test}
 
 
 

thesis.tex

@@ -22,6 +22,7 @@ openright]{scrartcl}
 \usepackage[font=footnotesize]{caption}
 \usepackage[outputdir=auto]{minted}
 \usepackage[framemethod=tikz]{mdframed}
+\usepackage{amssymb}
 
 \BeforeBeginEnvironment{minted}{\begin{mdframed}}
   \AfterEndEnvironment{minted}{\end{mdframed}}
@@ -115,12 +116,26 @@ citecolor=red,
   skipbelow = 20pt,
   linecolor=thi_blue,
   frametitlebackgroundcolor=thi_blue!8,
+  backgroundcolor=thi_blue!8,
   linewidth=1.9pt,
   leftline=false,
   rightline=false,
   bottomline=false,
 }
 \mdtheorem[style=phga_sum]{phga_sum}{Relevance for this Thesis}
+\mdfdefinestyle{phga_hyp}{
+  skipabove = 20pt,
+  skipbelow = 20pt,
+  linecolor=thi_blue,
+  frametitlebackgroundcolor=thi_blue!8,
+  backgroundcolor=thi_blue!8,
+  backgroud=thi_blue!8,
+  linewidth=1.9pt,
+  leftline=false,
+  rightline=false,
+  bottomline=false,
+}
+\mdtheorem[style=phga_hyp]{phga_hyp}{Hypothesis}
 
 % ----Glossar-------------------------------------------------------------------------
 \usepackage[toc,acronym,nonumberlist,nogroupskip]{glossaries}