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Jheronimus Academy of Data Science (JADS), a collaboration between Eindhoven University of Technology (TU/e) and Tilburg University, invites you to take part in this research project. This study is conducted as part of a Research-in-Action course at JADS and may inform a future MSc thesis project. The aim is to investigate how people interact with and experience personalised news recommendation systems. The study takes approximately 10 to 15 minutes. To participate you must be 18 years of age or older and comfortable reading news in English.
Your participation is completely voluntary and does not pose any physical, legal, or economic risks. You are not obliged to answer questions you are uncomfortable with and you can withdraw at any time before submitting your final consent decision without explaining why. Declining or withdrawing will not have any negative consequences for you.
| Data controller | Eindhoven University of Technology (TU/e), De Groene Loper 3, 5612 AE Eindhoven |
| Researcher | Fehmican Aydemir — f.aydemir@student.tue.nl |
| Supervisors | Dr. Martijn Willemsen (TU/e / JADS) — m.c.willemsen@tue.nl Jasmin Kareem (JADS) — j.kareem@tue.nl |
| Privacy | privacy@tue.nl |
| Data Protection Officer | dataprotectionofficer@tue.nl |
| Demographic data | Age, gender, education level — used to describe the study sample |
| News habits | Reading frequency and preferences — used as control variables |
| Behavioural logs | Article clicks and reading time during the session — used to test research hypotheses |
| Survey responses | Your ratings and opinions about the experience — primary outcome measures |
| Session identifier | A random code with no link to your identity — links behavioural data to survey responses |
We do not collect your name, email address, or IP address. All data is pseudonymous from the moment of collection. During the study, data is stored on a GDPR-compliant EU server hosted by Hetzner Cloud in Germany. After data collection is complete, data will be transferred to TU/e OneDrive for secure institutional storage. Data is retained for 10 years after the research is complete, after which it will be deleted or fully anonymised.
You have the right to request access to, rectification of, objection to, or erasure of your personal data. For questions or complaints contact the researcher at f.aydemir@student.tue.nl or the TU/e Data Protection Officer at dataprotectionofficer@tue.nl. You may also file a complaint with the Dutch Data Protection Authority: Autoriteit Persoonsgegevens (www.autoriteitpersoonsgegevens.nl).
TU/e processes your personal data to conduct scientific research, which is the university's public task as stated in Article 1.3 of the Dutch Wet Hoger onderwijs en Wetenschappelijk onderzoek.
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Please indicate how much you agree with the statements below. There are no right or wrong answers. We are interested in your honest experience.
This study investigated how explanations and user control in news recommendation systems affect perceived transparency, perceived agency, trust, and satisfaction.
The study used a 2x2 between-subjects design crossing two features: counterfactual explanations (showing why articles were recommended) and reading history control (allowing you to remove articles from your history to change recommendations). Participants were randomly assigned to one of four conditions: no features (baseline), explanations only, control only, or both features combined. We could not tell you this beforehand because knowing the purpose might have influenced your responses.
Your participation helps us understand how to design more transparent and trustworthy AI-powered news systems. This research is conducted as part of a Research-in-Action course at JADS, a collaboration between Eindhoven University of Technology and Tilburg University, and may inform a future MSc thesis project.
Please note that the articles you read come from a real archive of UK news coverage (the Guardian, BBC, Sky News, Evening Standard, the Independent, and i), originally published in November and December 2023. Most articles show the real, original text as published by these outlets. For a small number of articles where the original text could not be retrieved, the full text was instead generated using an AI language model (Claude Haiku 4.5 by Anthropic), based on the article's real title and lead. In all cases the titles, leads, and underlying stories are genuine.
Now that you know the full purpose of this study, we ask for your consent to use your responses in our research. You are free to withdraw your data at this point.
Please note: if you choose to withdraw here, your submission will be returned on Prolific and you will not receive a completion code or the standard payment for this session, in line with Prolific's policy for withdrawn-consent submissions. If you consent, you will receive your completion code on the next screen to submit for payment.
Please save this code as proof of participation.
Continue to Prolific →You have already made your consent decision on the previous screen, and your completion code above is yours to keep and submit to Prolific for payment regardless of any later request.
If you have any questions or complaints about this study, you are welcome to contact f.aydemir@student.tue.nl at any time.
Your data has been deleted and will not be used in this research. Thank you for your time.
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