12.6.2020 Why Privacy should matter more (Hoel)

Big data is seen as helpful to solve a number of pressing societal challenges, most lately to the Covid-19 crisis. While activities like teaching and learning (and also the defense of this doctoral dissertation) are forced online, governments expect citizens to share personal information in an unprecedented extent to fight the pandemic. And people seem to be willing to do so with few reservations concerning privacy. Why are people so willing to share the most personal information when the situation feels right? And what does this mean for the possibility to design privacy protection solutions that give the users more control over their personal data?
Julkaistu
12.6.2020

This study is situated in the emerging field of learning analytics, which uses learning activity data to understand and improve learning and the context in which learning occurs. In this new research field, ethics and privacy were a major concern for the community and potentially a showstopper for adoption of new learning technologies and practices. However, in schools and universities, students seem willing to share their data. This study contributes to the understanding of privacy as a phenomenon very much dependent upon context and how the users feel their integrity is handled in different contexts. The study designs conceptual tools to enable a discussion of privacy in contexts, in particular related to learning analytics.

Throughout the ten papers that make up this dissertation by publication the exploration of conditions for design of privacy solutions are carried out both from philosophical, cultural, social and technical perspectives. Only when we have a solid understanding of what privacy means for online users can we come up with suggestions for technical solutions. This study offers a direction for design that makes negotiations of contexts that maintain integrity for the individual a starting point, and utilises technologies that empowers the individual management of one’s online data trails.

Mag.Phil. Tore Hoelin tietojärjestelmätieteen väitöskirjan "Privacy for Learning Analytics in the Age of Big Data – exploring Conditions for Design of Privacy Solutions" tarkastustilaisuus järjestetään perjantaina 12.6.2020 klo 12 alkaen verkkovälitteisesti. Vastaväittäjänä apulaisprofessori Mikko-Jussi Laakso (Turun yliopisto) ja kustoksena professori Jan Pawlowski (Jyväskylän yliopisto). Väitöstilaisuuden kieli on englanti.

Yleisö voi seurata väitöstilaisuutta verkkovälitteisesti

  • Linkki Zoom-webinaariin (suositellaan Zoom-sovellusta tai Google Chrome selainta):
  • Webinaarin salasana: 829478

Julkaisutiedot

Väitöskirja on julkaistu verkkojulkaisusarjassa JYU Dissertations numerona 239, Jyväskylä 2020. Pysyvä osoite on .