Applying Hierarchical Task Analysis Method to Discovery Layer Evaluation

While usability tests have been helpful in evaluating the success or failure of implementing discovery layers in the library context, the focus of usability tests has remained on the search interface rather than the discovery process for users. The informal site-­‐ and context specific usability tests have offered little to test the rigor of the discovery layers against the user goals, motivations and workflow they have been designed to support. This study proposes hierarchical task analysis (HTA) as an important complementary evaluation method to usability testing of discovery layers. Relevant literature is reviewed for the discovery layers and the HTA method. As no previous application of HTA to the evaluation of discovery layers was found, this paper presents the application of HTA as an expert based and workflow centered (e.g., retrieving a relevant book or a journal article) method to evaluating discovery layers. Purdue University’s Primo by Ex Libris was used to map eleven use cases as HTA charts. Nielsen’s Goal Composition theory was used as an analytical framework to evaluate the goal charts from two perspectives: a) users’ physical interactions (i.e., clicks), and b) user’s cognitive steps (i.e., decision points for what to do next). A brief comparison of HTA and usability test findings is offered as a way of conclusion

Understanding Library Users’ Preferences and Expectations of Online Help

Purpose Online help and tutorials are an important part of library services, yet they are often studied in specific contexts and disciplines like subject-specific research guides. The objective of this study was to examine users’ common preferences and expectations of library help channels in general and online help in particular. Design/methodology/approach The authors conducted a qualitative survey with 45 library users. The survey asked users how they seek library help, their preferences and expectations of online help, content format and general help channels and later, a content analysis of survey responses was performed. Findings Results showed that survey participants have different prioritizations of library help channels. Half of the respondents preferred conceptual help that emphasizes concepts and underlying principles, while the other half preferred procedural (step-by-step) help or mixed. The survey also indicated reliance by participants on expert help, even when online help was available. Originality/value Based on the results, the authors identified users’ behavioral preferences, attitudes and expectations toward library help channels and online help content. They also discussed the unique challenge of creating online help for libraries, as users have a dynamic range of help-seeking preferences and mixed expectations of help content depending on the context

Building Better Help: User Characteristics’ Effect on Library Help Design

The goal of this study is to examine the effect of user help seeking characteristics on their perception of library help design principles, formats and tools. Structural equation modeling (SEM) of a questionnaire survey results showed a number of significant regression relationships. Analysis of open-ended survey questions revealed existing user behaviors such as preferred help formats and gave insights into the likelihood of using a help system

Affordances Of Eco-Feedback Design in Home Energy Context

Along with environmental awareness, the interdisciplinary field of eco-feedback has become an active research interest in Human Computer Interaction (HCI), Computing, and Sustainable Design. While designers face the challenge of designing complex socio-technical systems (Norman and Stappers 2015), eco-feedback lacks comprehensive theoretical contributions to guide such efforts. This paper followed the PRISMA-P structured review method and reports on mostly empirical papers (N=36) on eco-feedback design from the past decade (2006-2016). The aim was to systematize the emerging field by classifying feedback types according to their impact on end users and identify theoretical grounding. Through our deep inductive engagement with the studies, we present four eco-feedback affordances: (1) Inform for awareness change; (2) Incentivize for motivation change; (3) Educate for behavioral change; and (4) Control for convenience. Current research is corroborating empirical evidence in support of eco-feedback, but their lack of theoretical grounding has resulted in incomparable constructs and inconsistent results