Characterizing Digging Deeper in Online Information Behavior

• In Event: Virtual Poster Session
  In Virtual iPresentation Only: SIG-Learning Sciences Virtual Poster Session

Abstract

This mixed-methods study examined when and how adults engage in deep online information behavior for personal purposes. We surveyed 201 adults using the Online Information Searching Strategy Inventory (OISSI) and conducted semi-structured interviews with 13 participants who reported recent extended investigations. Binary logistic regression revealed that metacognitive regulation skills and specific source evaluation criteria—including cross-referencing sources, seeking multiple dispassionate opinions, and considering source popularity—significantly predicted deep inquiry, independent of demographics. Qualitative analysis identified four patterns combining inquiry drivers (ongoing versus spontaneous interest) with investigation trajectories (deep versus surface). The same individuals exhibited both deep and surface behaviors depending on contextual factors such as time constraints and perceived stakes, highlighting the situational nature of information behavior strategies.

Authors

• Sky Galili, Ben-Gurion University of the Negev

• Iris Tabak, Ben-Gurion University of the Negev