@phdthesis{Schad2012,
  author    = {Schad, Daniel},
  title     = {Mindless reading and eye movements : theory, experiments and computational modeling},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-70822},
  school      = {Universit{\"a}t Potsdam},
  year      = {2012},
  abstract  = {It sometimes happens that we finish reading a passage of text just to realize that we have no idea what we just read. During these episodes of mindless reading our mind is elsewhere yet the eyes still move across the text. The phenomenon of mindless reading is common and seems to be widely recognized in lay psychology. However, the scientific investigation of mindless reading has long been underdeveloped. Recent progress in research on mindless reading has been based on self-report measures and on treating it as an all-or-none phenomenon (dichotomy-hypothesis). Here, we introduce the levels-of-inattention hypothesis proposing that mindless reading is graded and occurs at different levels of cognitive processing. Moreover, we introduce two new behavioral paradigms to study mindless reading at different levels in the eye-tracking laboratory. First (Chapter 2), we introduce shuffled text reading as a paradigm to approximate states of weak mindless reading experimentally and compare it to reading of normal text. Results from statistical analyses of eye movements that subjects perform in this task qualitatively support the 'mindless' hypothesis that cognitive influences on eye movements are reduced and the 'foveal load' hypothesis that the response of the zoom lens of attention to local text difficulty is enhanced when reading shuffled text. We introduce and validate an advanced version of the SWIFT model (SWIFT 3) incorporating the zoom lens of attention (Chapter 3) and use it to explain eye movements during shuffled text reading. Simulations of the SWIFT 3 model provide fully quantitative support for the 'mindless' and the 'foveal load' hypothesis. They moreover demonstrate that the zoom lens is an important concept to explain eye movements across reading and mindless reading tasks. Second (Chapter 4), we introduce the sustained attention to stimulus task (SAST) to catch episodes when external attention spontaneously lapses (i.e., attentional decoupling or mind wandering) via the overlooking of errors in the text and via signal detection analyses of error detection. Analyses of eye movements in the SAST revealed reduced influences from cognitive text processing during mindless reading. Based on these findings, we demonstrate that it is possible to predict states of mindless reading from eye movement recordings online. That cognition is not always needed to move the eyes supports autonomous mechanisms for saccade initiation. Results from analyses of error detection and eye movements provide support to our levels-of-inattention hypothesis that errors at different levels of the text assess different levels of decoupling. Analyses of pupil size in the SAST (Chapter 5) provide further support to the levels of inattention hypothesis and to the decoupling hypothesis that off-line thought is a distinct mode of cognitive functioning that demands cognitive resources and is associated with deep levels of decoupling. The present work demonstrates that the elusive phenomenon of mindless reading can be vigorously investigated in the cognitive laboratory and further incorporated in the theoretical framework of cognitive science.},
  language  = {en}
}
@misc{Schad2007,
  author    = {Schad, Daniel},
  title     = {How do implicit and explicit motives differ? The role of non-verbal versus verbal stimulus and non-declarative versus declarative response formats},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-71390},
  year      = {2007},
  abstract  = {How distinct implicit and explicit motive systems differ has long been unclear. Schultheiss' (2001) information processing account of implicit motive arousal hypothesized that implicit motives respond to nonverbal stimuli to influence non-declarative measures of motivation and that explicit motives respond to verbal stimuli to influence declarative measures of motivation. Moreover, in individuals high in referential competence, i.e., with the ability to quickly translate non-verbal stimuli into a verbal representation, implicit motives are thought to respond to verbal stimuli and influence declarative measures of motivation and explicit motives are thought to respond to nonverbal stimuli and to influence non-declarative measures of motivation. The present study tested these hypotheses by assessing liking ratings as a declarative response format and an affective stroop task as a non-declarative response format using emotion words as verbal and emotional facial expressions as non-verbal stimuli. Individual power, affiliation, and achievement motive dispositions were assessed via the Picture Story Excercise for implicit motives and via questionnaires for explicit motives. Referential competence was assessed via a colour-naming/-reading task. I found that as expected explicit and implicit motives overall were not correlated across subjects. Moreover, implicit and explicit motives affected declarative and non-declarative responses for verbal and non-verbal stimuli. As predicted, however, implicit motives responded to verbal stimuli and influenced declarative responses more strongly for individuals high compared to those low in referential competence. Likewise, explicit motive effects were moderated by referential competence in some - but not all - of the predicted conditions. These results show that implicit and explicit motives can influence declarative and non-declarative responses to verbal and non-verbal stimuli. They support the hypothesis that referential processing is needed for implicit motives to respond to verbal stimuli and influence declarative response formats, and they partly support the hypothesis that referential processing plays a role for the influence of explicit motives. Results for explicit motives may suggest that new measures are needed to assess the referential competence to translate verbal stimuli into non-verbal representations. Overall, the findings provide support to the information processing account of implicit motive arousal by Schultheiss' (2001), suggesting that a non-verbal and non-declarative implicit motive system and a distinct verbal and declarative explicit motive system interact via referential processing, i.e., by translating information between representational formats.},
  language  = {en}
}