0000000000459988
AUTHOR
Sofia Papavlasopoulou
Identifying the combinations of motivations and emotions for creating satisfied users in SNSs: An fsQCA approach
Social Networking Sites (SNSs) play an important role in our daily lives and the number of their users increases regularly. To understand how users can be satisfied in the complex digital environment of SNSs, this study examines how motivations and emotions combine with each other to explain high satisfaction. Users’ motivations comprise four attributes, entertainment, information, social-psychological, and convenience. Emotions are divided into their two main categories, that is positive and negative emotions. We draw on complexity and configuration theories, present a conceptual model along with propositions and perform a fuzzy-set qualitative comparative analysis (fsQCA). Through an empi…
Fitbit for learning: Towards capturing the learning experience using wearable sensing
The assessment of learning during class activities mostly relies on standardized questionnaires to evaluate the efficacy of the learning design elements. However, standardized questionnaires pose additional strain on students, do not provide “temporal” information during the learning experience, require considerable effort and language competence, and sometimes are not appropriate. To overcome these challenges, we propose using wearable devices, which allow for continuous and unobtrusive monitoring of physiological parameters during learning. In this paper we set out to quantify how well we can infer students’ learning experience from wrist-worn devices capturing physiological data. We coll…
Wearable Sensing and Quantified-self to explain Learning Experience
Author's accepted manuscript © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The confluence of wearable technologies for sensing learners and the quantified-self provides a unique opportunity to understand learners’ experience in diverse learning contexts. We use data from learners using Empatica Wristbands and self-reported questionnaire. We compute stress, ar…