Researchers have been studying personal information management (PIM) for many years, but little exists by way of practical advice for how individuals should manage their own information. We employed the Delphi Method to engage PIM researchers with expertise in a variety of relevant areas in a five-round extended dialog about PIM practices. Participants identified key everyday choices of PIM, suggested alternatives, and identified pros and cons of each alternative. Our contributions include: 1) a set of 36 PIM practices, along with pros, cons, and recommendations for or against each practice, 2) directions of future research and development including "near-future" improvements in tool support and 3) a detailed description of how we applied the Delphi Method to study PIM and how it might be used more widely in HCI research as a complement to more established methods of inquiry.

Primary and secondary (K–12) teachers form the essential core of children's formal learning before adulthood. Even though teaching is a mainstream, information‐rich profession, teachers are understudied as information users. More specifically, not much is known about teacher personal information management (PIM). Teacher PIM is critically important, as teachers navigate a complex information space complicated by the duality of digital and physical information streams and changing demands on instruction. Our research study increases understanding of teacher PIM and informs the development of tools to support educators. Some important unknowns exist about teachers as information users: What are teachers' PIM practices? What are the perceived consequences of these practices for teaching and learning? How can PIM practices be facilitated to benefit teaching and learning? This study employed a qualitative research design, with interviews from 24 primary and secondary teachers. We observed various systems for information organization, and teachers report their systems to be effective. Important sources for teachers' information in order of importance are personal collections, close colleagues, and the Internet. Key findings reveal that inheriting and sharing information play an important part in information acquisition for teachers and that information technology supporting education creates unintentional demands on information management. The findings on the nature of teacher information, teacher information finding, keeping, and organizational practices have important implications for teachers themselves, school principals, digital library developers, school librarians, curriculum developers, educational technology developers, and educational policy makers.

Educational standards are a central focus of the current educational system in the United States, underpinning educational practice, curriculum design, teacher professional development, and high-stakes testing and assessment. Digital library users have requested that this information be accessible in association with digital learning resources to support teaching and learning as well as accountability requirements. Providing this information is complex because of the variability and number of standards documents in use at the national, state, and local level. This article describes a cataloging tool that aids catalogers in the assignment of standards metadata to digital library resources, using natural language processing techniques. The research explores whether the standards suggestor service would suggest the same standards as a human, whether relevant standards are ranked appropriately in the result set, and whether the relevance of the suggested assignments improve when, in addition to resource content, metadata is included in the query to the cataloging tool. The article also discusses how this service might streamline the cataloging workflow.

Rapid growth in the availability of digital libraries of K-12 curriculum, coupled with an increased emphasis on standard-based teaching has led to the development of automated standard assignment tools. To assess the performance of one of those tools and to gain insight into the differences between how human catalogers and automated tools conduct these standard assignments, we explore the use of network modeling and visualization techniques for comparing and contrasting the two. The results show significant differences between the human-based and machine-based network maps. Unlike the machine-based maps, the human-based assignment maps elegantly reflect the rationales and principles of the assignments; i.e., clusters of standards separate along lines of content and pedagogical principles. In addition, humans seem significantly more apt at assigning so-called `methodological' standards.

In this poster, we will present the results of efforts we have undertaken to conduct evaluations of a QA system in a real world environment and to understand the nature of the dimensions on which users evaluate QA systems when given full reign to comment on whatever dimensions they deem important.

The poster reports on a project in which we are investigating methods for breaking the human metadata-generation bottleneck that plagues Digital Libraries. The research question is whether metadata elements and values can be automatically generated from the content of educational resources, and correctly assigned to mathematics and science educational materials. Natural Language Processing and Machine Learning techniques were implemented to automatically assign values of the GEMgenerate metadata element set tofor learning resources provided by the Gateway for Education (GEM), a service that offers web access to a wide range of educational materials. In a user study, education professionals evaluated the metadata assigned to learning resources by either automatic tagging or manual assignment. Results show minimal difference in the eyes of the evaluators between automatically generated metadata and manually assigned metadata.