1. Gizem Can, Master thesis on profiling
The aim of the project is to create personas of adults by exploring how they use AI tools in informal learning and work contexts. These personas help understand different user needs and behaviors. Our project is grounded in the sense-making framework, in which we analyze how individuals interpret and give meaning to information provided by AI. Sense-making is crucial for ensuring that AI outputs are not only accurate but also contextually relevant and actionable. We aim to help users make informed decisions.
2. Vere Dugolli, Master thesis on a systematic literature review about measuring social processes on digital learning environments
From 2057 research papers, we systematically selected 164 empirical papers to further analyse. This project examines how different existing constructs that explain socio-emotional properties of interpersonal interactions are measured at various time scales (individual, dyad, group, community) and levels (short-term process outcome, long-term outcome). This study also compiles existing evidence on the antecedents of constructs that explain the socio-emotional properties of interpersonal interactions.
3. Zhenzhong Wang, Master thesis on socio-emotional properties of interpersonal interactions in digital learning environments
This project aims to synthesise and explore the similarities and differences between items in various questionnaires that measure these socio-emotional attributes. Using advanced natural language processing (NLP) techniques, specifically LLM embedding models, we analyse the differences and similarities from 69 different self-reports, resulting in 733 individual items related to 43 different socio-emotional properties. Our findings aim to highlight the need for standardised measurement tools, which can improve the reliability and validity of socio-emotional assessments, ultimately enhancing the quality of online education by creating more engaging and supportive learning environments.
4. Deisy Briceno, Master thesis on understanding the role of group discussions on consent
Research on how individuals make decisions regarding their data often neglects the social implications of consent (Solove, 2013). To address this gap, we examine the interrelationship between privacy and ethics within their social contexts (Luger & Rodden, 2013). Our intervention consists of four phases, during which participants are presented with a set of vignettes to rate both individually and in groups. This approach allows us to investigate the impact of social deliberation on consent.