Rafa Absar

Exploring social context in mobile information behavior

This paper reports on the social context of mobile information behavior based on an interview and diary study (n=19). We examine different types of mobile information behavior and how these are affected by social variables. In addition, we compare social and non-social mobile information behavior in terms of where it occurs, applications utilized, expressed information needs of users, and levels of satisfaction. We promote a broader view of how social context shapes and is shaped by mobile information behavior.

Exploring the complexities of information practices through arts-based research

Within and beyond Library and Information Science (LIS), researchers are employing participatory, arts-based research as one way of extending traditional research methods. The use of creative methods can enrich our understanding of complex information practices, particularly in multimedia information environments. This panel will provide an overview of arts-involved practices of data collection, data analysis and knowledge exchange, including examples of specific applications within LIS research projects. We will discuss the ways creative arts may function socially and psychologically among researchers and research participants, as well as topics and populations with which arts-involved methods may be especially enriching.

Toward a Model of Mobile User Engagement

In this paper we propose User Engagement (UE) as a conceptual framework for studying mobile information interaction. We redefine the six attributes of UE: focused attention, felt involvement, perceived usability, novelty, aesthetic appeal, and endurability for the mobile environment. We argue that mobile information interaction is an emerging area and situating it in UE can further research in this area.

Linking Online Identities and Content in Connectivist MOOCs across Multiple Social Media Platforms

In this paper, we examine how multiple social media platforms are being used for formal and informal learning by examining data from two connectivist MOOCs (or cMOOCs). Our overarching goal is to develop and evaluate methods for learning analytics to detect and study collaborative learning processes. For this paper, we focus on how to link multiple online identities of learners and their contributions across several social media platforms in order to study their learning behaviours in open online environments. Many challenges were found in collection, processing, and analyzing the data; results are presented here to provide others with insight into such issues for examining data across multiple open media platforms.

Media multiplexity in connectivist MOOCs

In this poster, we present work on exploring use of multiple social media platforms for learning in two connectivist MOOCs (or cMOOCs) to develop and evaluate methods for learning analytics to detect and study collaborative learning processes.

A Task-based Approach to Mobile Information Interactions

In this paper we examine current representations and classifications of mobile information interactions. We propose a task-based approach to unify and guide future work of mobile information retrieval.