Merge-Konflikte gelöst: Dateien gelöscht wie im Remote-Branch

.gitignore

@@ -4,4 +4,7 @@
 *.aux
 *.toc
 *.out
+*.synctex.gz
+*-concordance.tex
+
 

manuscript-concordance.tex

@@ -1,2 +0,0 @@
-\Sconcordance{concordance:manuscript.tex:manuscript.Rnw:1 177 1 1 2 1 0 1 1 7 0 1 2 1 %
-1}

manuscript.Rnw

@@ -30,6 +30,31 @@ This dataset allows for future research on psychological and behavioral dynamics
 
 \section{Background and Summary}
 
+% Taken from LEK application
+This project is a joint project from the human-computer interaction group at
+IWM. There will be several preregistrations from group members focusing on their
+subquestions. However, the overall aim is to examine how people change their
+use, perception, and attitudes towards AI-tools like ChatGPT, Siri, or Alexa.
+
+We target an US-American sample and plan a longitudinal study starting at the
+end of August 2024 (six waves, roughly one year). We use a longitudinal design
+to track changes over time and to get some hints on causality. We target an
+American sample because Apple announced to release its new AI platform Apple
+Intelligence in autumn 24 (in the US due to the stricter regulations in the EU)
+and we expect that many people will be exposed to this AI on their Apple
+devices. Longitudinal studies are more likely to find changes if there is a
+potential change trigger (Zhao et al., 2024)
+
+Central questions are whether predictors of technology acceptance as well as
+technology use change over time, whether the perception of AI-Tools as tools vs.
+agents (if so: what type of role/relationship) changes over time, whether this
+perception is related to concepts like credibility, trustworthiness, or task
+delegation, and whether factors such as social presence of perceive
+anthropomorphism mediate such processes. We’ll also explore the long-term
+effects of delegating tasks to AI Tools on outcomes like perceived
+self-efficacy (writing skills), loneliness, or cognitive self-esteem and explore
+the moderating role of personality.
+
 ...
 Longitudinal studies like this are needed to capture the evolving perceptions of opportunities and risks associated with AI, perceived capabilities of AI systems, attitudes toward AI, trust in AI, willingness to delegate tasks to AI, areas of application, and the interrelationships among these constructs over time (to be continued). To examine those changes and relationships, an American sample mainly consisting of AI users (specify) was invited to participate in this survey at two-month intervals between September 2024 and July 2025.
 % Overview of Dataset
@@ -44,6 +69,27 @@ Longitudinal studies like this are needed to capture the evolving perceptions of
 * outlook on potential developments in other countries
 * connection of actual use and stable psychological variables
 
+% WP1 Teresa/Nico/Vanessa/Angelica
+%
+% WP2 Teresa
+%
+% WP3 Sonja https://aspredicted.org/4g3d-rqkt.pdf
+%
+% WP4 Büsra https://aspredicted.org/m6zv9.pdf
+%
+% WP5 Büsra/Teresa https://aspredicted.org/kx5r-4pxq.pdf
+%
+% WP6 Angelica/Gerrit
+%
+% WP7 Mike ???
+%
+% WP8 Steffi/Sonja https://osf.io/f3jyc?view_only=d8d009e575c64dc2bd453f969c3cb7b1
+%
+% WP9 Steffi https://osf.io/h5fwe?view_only=8c5bc9e62074469ebdb3d72b38f4716d
+%
+% --> Are these all WPs? Are there any missing?
+
+
 % Previous Publications
 %
 % * Cite any previous publications that utilized these data, in whole or in part

manuscript.tex

@@ -30,6 +30,31 @@ This dataset allows for future research on psychological and behavioral dynamics
 
 \section{Background and Summary}
 
+% Taken from LEK application
+This project is a joint project from the human-computer interaction group at
+IWM. There will be several preregistrations from group members focusing on their
+subquestions. However, the overall aim is to examine how people change their
+use, perception, and attitudes towards AI-tools like ChatGPT, Siri, or Alexa.
+
+We target an US-American sample and plan a longitudinal study starting at the
+end of August 2024 (six waves, roughly one year). We use a longitudinal design
+to track changes over time and to get some hints on causality. We target an
+American sample because Apple announced to release its new AI platform Apple
+Intelligence in autumn 24 (in the US due to the stricter regulations in the EU)
+and we expect that many people will be exposed to this AI on their Apple
+devices. Longitudinal studies are more likely to find changes if there is a
+potential change trigger (Zhao et al., 2024)
+
+Central questions are whether predictors of technology acceptance as well as
+technology use change over time, whether the perception of AI-Tools as tools vs.
+agents (if so: what type of role/relationship) changes over time, whether this
+perception is related to concepts like credibility, trustworthiness, or task
+delegation, and whether factors such as social presence of perceive
+anthropomorphism mediate such processes. We’ll also explore the long-term
+effects of delegating tasks to AI Tools on outcomes like perceived
+self-efficacy (writing skills), loneliness, or cognitive self-esteem and explore
+the moderating role of personality.
+
 ...
 Longitudinal studies like this are needed to capture the evolving perceptions of opportunities and risks associated with AI, perceived capabilities of AI systems, attitudes toward AI, trust in AI, willingness to delegate tasks to AI, areas of application, and the interrelationships among these constructs over time (to be continued). To examine those changes and relationships, an American sample mainly consisting of AI users (specify) was invited to participate in this survey at two-month intervals between September 2024 and July 2025.
 % Overview of Dataset
@@ -44,6 +69,27 @@ Longitudinal studies like this are needed to capture the evolving perceptions of
 * outlook on potential developments in other countries
 * connection of actual use and stable psychological variables
 
+% WP1 Teresa/Nico/Vanessa/Angelica
+%
+% WP2 Teresa
+%
+% WP3 Sonja https://aspredicted.org/4g3d-rqkt.pdf
+%
+% WP4 Büsra https://aspredicted.org/m6zv9.pdf
+%
+% WP5 Büsra/Teresa https://aspredicted.org/kx5r-4pxq.pdf
+%
+% WP6 Angelica/Gerrit
+%
+% WP7 Mike ???
+%
+% WP8 Steffi/Sonja https://osf.io/f3jyc?view_only=d8d009e575c64dc2bd453f969c3cb7b1
+%
+% WP9 Steffi https://osf.io/h5fwe?view_only=8c5bc9e62074469ebdb3d72b38f4716d
+%
+% --> Are these all WPs? Are there any missing?
+
+
 % Previous Publications
 %
 % * Cite any previous publications that utilized these data, in whole or in part
@@ -119,7 +165,11 @@ We collected sociodemographic information, including, age, gender, educational l
 
 \section{Data Records}
 
+<<<<<<< HEAD
 Data records for each of the six waves are available in csv format at (tbd) together with the R/python scripts for data anonymization, data cleaning, and data preprocessing. 
+=======
+Data records for each of the six waves are available in csv format at (tbd) together with the R/python scripts for data anonymization, data cleaning, and data preprocessing.
+>>>>>>> 81a7f066fe930d67e466e742b1dfe7944e6b1db7
 That is, firstly the data was anonymized by removing participants' Prolific IDs and unused variables, empty variables resulting from faulty questionnaire programming, and xy were removed. Thus (filename) represents the cleaned and anonymized raw data, including the single items of each measurement. Second, variable names were harmonized and scales were calculated, resulting an the preprocessed data set xy, ready for analyses across scales.
 Moreover, a codebook explaining variable abbreviations and containing information about the waves in which the variable was collected (what else?) is available at (tbd).
 
@@ -183,7 +233,11 @@ Hier ist ein R-Chunk:
 \end{Sinput}
 \begin{Soutput}
     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
+<<<<<<< HEAD
 -2.22278 -0.52719  0.10680  0.07778  0.82073  2.77297 
+=======
+-2.79361 -0.91601  0.03741 -0.13932  0.64710  2.73127 
+>>>>>>> 81a7f066fe930d67e466e742b1dfe7944e6b1db7
 \end{Soutput}
 \end{Schunk}