SlideSpace: Heuristic design of a hybrid presentation medium

The Slide and Canvas metaphors are two ways of helping people create visual aids for oral presentations. Although such physical metaphors help both authors and audiences make sense of material, they also constrain authoring in ways that can negatively impact presentation delivery. In this article, we derive heuristics for the design of presentation media that are independent of any underlying physical metaphors. We use these heuristics to craft a new kind of presentation medium called SlideSpace-one that combines hierarchical outlines, content collections, and design rules to automate the real-time, outline-driven synthesis of hybrid Slide-Canvas visuals. Through a qualitative study of SlideSpace use, we validate our heuristics and demonstrate that such a hybrid presentation medium can combine the advantages of existing systems while mitigating their drawbacks. Overall, we show how a heuristic design approach helped us challenge entrenched physical metaphors to create a fundamentally digital presentation medium with the potential to transform the activities of authoring, delivering, and viewing presentations

HirePeer: Impartial Peer-Assessed Hiring at Scale in Expert Crowdsourcing Markets

Expert crowdsourcing (e.g., Upwork.com) provides promising benefits such as productivity improvements for employers, and flexible working arrangements for workers. Yet to realize these benefits, a key persistent challenge is effective hiring at scale. Current approaches, such as reputation systems and standardized competency tests, develop weaknesses such as score inflation over time, thus degrading market quality. This paper presents HirePeer, a novel alternative approach to hiring at scale that leverages peer assessment to elicit honest assessments of fellow workers' job application materials, which it then aggregates using an impartial ranking algorithm. This paper reports on three studies that investigate both the costs and the benefits to workers and employers of impartial peer-assessed hiring. We find, to solicit honest assessments, algorithms must be communicated in terms of their impartial effects. Second, in practice, peer assessment is highly accurate, and impartial rank aggregation algorithms incur a small accuracy cost for their impartiality guarantee. Third, workers report finding peer-assessed hiring useful for receiving targeted feedback on their job materials

A Qualitative Investigation of Unmet Information-Seeking Needs of Online Workers

This qualitative study investigates socialization to online labor platforms using the information-seeking framework introduced by Miller and Jablin’s (1991). As workers adapt to this new work arrangement, they experience ambiguity and uncertainty that triggers seeking out information. Interviews with 29 online workers reveals the unmet information-seeking needs experienced by these workers. The findings extend the theoretical framework of information-seeking to account for the affordances and limitations present in OLPs. Furthermore, our findings suggest practical implications for the design of online labor platforms