Search in publications
25 results
Zeitschriftenartikel
(2023):
Predicting question difficulty in web surveys: A machine learning approach based on mouse movement features
:
Social Science Computer Review,
41,
1,
pp. 141-162.
more
(2022):
lab.js: A free, open, online study builder
:
Behavior Research Methods,
54,
2,
pp. 556–573.
more
(2018):
Lead Us (Not) into Temptation: Testing the Motivational Mechanisms Linking Honesty–Humility to Cooperation
:
European Journal of Personality,
32,
2,
pp. 116-127.
more
Konferenzpräsentationen
(2020):
Mousetrap-web: An open, flexible survey paradata collection tool
:
[
BigSurv20,
(virtual conference),
]
more
(2020):
Detecting difficulty in computer-assisted surveys through mouse movement trajectories: A new model for functional data classification
:
[
BigSurv20,
(virtual conference),
]
more
(2020):
Easy Online Experimentation with lab.js
:
[
Annual Meeting of the Psychonomic Society,
(virtual conference),
]
more
(2020):
An ensemble method for multivariate functional data classification, with application to mouse movement trajectories
:
[
CMStatistics 2020,
(virtual conference),
]
more
(2019):
Uncovering judgement and decision‐making processes using mouse‐tracking: Software, analysis, and application
:
[
Subjective Probability, Utility & Decision Making Conference 2019,
Amsterdam,
]
more
(2019):
Mousetrap-Web: Mouse-Tracking in the Browser
:
[
60th Annual Meeting of the Psychonomic Society,
Montréal,
]
more
(2019):
Mousetrap-Web: Mouse-Tracking in the Browser
:
[
49th Annual Meeting of the Society for Computers in Psychology,
Montréal,
]
more
(2019):
Beyond the lab: Collecting mouse-tracking data in online studies
:
[
61st Conference of Experimental Psychologists,
London,
]
more
(2019):
Mousetrap: Open-source tools for advanced analyses of mouse-tracking data
:
[
61st Conference of Experimental Psychologists,
London,
]
more
(2018):
Mousetrap: Open-source and cross-platform software for mouse-tracking data collection and analysis
:
[
51st Congress of the German Psychological Society,
Frankfurt am Main,
]
more
(2018):
Mousetrap: Open-source tools for advanced analyses of hand- and mouse-tracking data
:
[
48th Annual Meeting of the Society for Computers in Psychology,
New Orleans, LA,
]
more
(2018):
Precision Timing in the Browser With lab.js: A Free, Open, Online Study Builder
:
[
59th Annual Meeting of the Psychonomic Society,
New Orleans, LA,
]
more
(2018):
Who said browser-based experiments can't have proper timing? Implementing accurate presentation and response timing in the browser
:
[
Annual Meeting of the Society for Computers in Psychology,
New Orleans, LA,
]
more
(2018):
lab.js: A free, open, online study builder
:
[
51. Kongress der Deutschen Gesellschaft für Psychologie,
Frankfurt am Main,
]
more
(2017):
Learning from Mouse Movements: Improving Questionnaire and Respondents' User Experience through Passive Data Collection
:
[
19th General Online Research Conference,
Berlin,
]
more
(2016):
Learning from Mouse Movements: Improving Questionnaires and Respondents’ User Experience Through Passive Data Collection
:
[
International Conference on Questionnaire Design, Development, Evaluation, and Testing (QDET2),
Miami,
]
more
Beiträge in Büchern
Beatty Paul C.,
Debbie Collins,
Lyn Kaye,
Jose-Luis Padilla,
Gordon B. Willis,
Amanda Wilmot
(Eds.)
(2020):
Learning from Mouse Movements: Improving Questionnaire and Respondents’ User Experience through Passive Data Collection
:
pp. 403-425.
Hoboken, NJ,
Wiley
more
Kühberger Anton,
Joseph G. Johnson
(Eds.)
(2019):
Mouse-tracking: Detecting types in movement trajectories
:
2,
pp. 131-145.
New York, NY,
Routledge
more
Kühberger Anton,
Joseph G. Johnson
(Eds.)
(2019):
Mouse-tracking: A practical guide to implementation and analysis
:
2,
pp. 111-130.
New York, NY,
Routledge
more
Berichte
(2020):
Predicting respondent difficulty in web surveys: A machine-learning approach based on mouse movement features
:
pp. 40.
Ithaca, NY,
Cornell University
more
(2017):
Learning from mouse movements: Improving questionnaire and respondents' user experience through passive data collection
:
2017,
pp. 26.
Nürnberg,
Institut for Employment Research
more
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