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The purpose of this paper is to report the results of a case study on virtual reality (VR) learning environments, focused on the development and integration of multi-user reference support.

This paper used a case study methodology to understand applied software development incorporating textual browsing experiences within the HTC Vive virtual reality headset. An open corpus of text from the HathiTrust Digital Library accessed via the API was used as a data source.

In collaboration with students from a senior undergraduate Computer Science project course, the project team developed software to pilot a multi-user VR experience, with functionality for users to search, discover and select e-books and other digitized content from the HathiTrust digital library.

Overall, the system has been developed as a prototype e-book experiment to model several VR affordances for browsing, user support and educational endeavors within libraries. Within the VR reading room pilot, users are able collaboratively explore digital collections. Aspects of reference librarian user support were modeled in the VR system including communication in real-time using chat features and text highlighting and manipulation tools that are unique to learning in VR environments.

More than 100 macros have been written and made available on the Web since the debut of PFW in 1996. Evidently, OML has benefited many OCLC system users in automating their jobs. Nevertheless, finding the desired macros takes considerable time and effort because Web sites that provide macros present them in widely varied formats. This article presents the Web sites that currently provide macros for sharing, initiates the discussion on Web macro presentation guidelines, evaluates the presented Web sites based on these guidelines, and provides a source list of useful macros specifically for OCLC subsystem applications.

The purpose of this paper is to undertake a formative evaluation of growth over time that would demonstrate diverse library users’ development as they interact with mobile digital library services.

This paper incorporated a server log analysis to evaluate first, the location of users. To study the nature of diverse user development, users from unique locations were identified and tracked over several years. The type of growth that this paper analyzes is the development of a library user from the beginning stages of use into one who is more experienced. For the purposes of this paper, the authors define library experts as experienced library users. These are users who have come back to the library over multiple sessions of learning and branched out into multiple areas of library functionality and services.

The findings of modular mobile use over time suggest that, while over half of users only utilized one module, 39 per cent of all users accessed more than one module. This formative approach to assessing student library engagement suggests alternative metrics for assessing outreach and distance learning.

The underlying departure point for this study is that formative models may introduce descriptive data valuable to the learning analytics toolkit. The library research literature on learning analytics, and perhaps library service offerings that support learning, may gain additional value by attending to students’ formative development as they interact with library resources. Describing the way in which mobile app users develop can yield insights about learning over time, both on campus and at a distance.

This paper aims to introduce a machine learning-based “My Account” recommender for implementation in open discovery environments such as VuFind among others.

The approach to implementing machine learning-based personalized recommenders is undertaken as applied research leveraging data streams of transactional checkout data from discovery systems.

The authors discuss the need for large data sets from which to build an algorithm and introduce a prototype recommender service, describing the prototype’s data flow pipeline and machine learning processes.

The browse paradigm of discovery has neglected to leverage discovery system data to inform the development of personalized recommendations; with this paper, the authors show novel approaches to providing enhanced browse functionality by way of a user account.

In the age of big data and machine learning, advances in deep learning technology and data stream processing make it possible to leverage discovery system data to inform the development of personalized recommendations.

The purpose of this paper is to introduce mobile augmented reality applications for library uses and next generation library services.

Examples are drawn from museum and archives informatics, computer science applied research, and computer vision research as well as original research and development work from the Undergraduate Library at the University of Illinois.

Mobile augmented reality uses include augmenting physical book stacks browsing, library navigation, optical character recognition, facial recognition, and building identification mobile software for compelling library experiences.

The paper suggests uses of mobile augmented reality applications in library settings and models a demonstration prototype interface.

The purpose of this paper is to present the results of a usability study which inquired into undergraduate student information seeking with Wikipedia on the iPod touch.

Data are drawn from iPod search logs and student survey responses. Search log data are coded with FRBR subject entities (group 3 entity sets) for analysis.

Students characterize the overall nature of information searched for with the Wikipedia app to be for recreational and for short factual information. Recreational searching as a way in which undergraduate students utilize mobile technology is an earlier finding of Wikipedia iPod usage, and is verified as a trend of undergraduate student search using the iPod. All undergraduate student participants of the Wikipedia app on a mobile interface report this tool as helping to become more efficient in their research. Students viewed Wikipedia articles about people and concepts more so than other article types.

Undergraduate student mobile search log analysis over a specific type of information resource on the iPod Touch is an original usability project. Previous mobile search log analysis analyzes thousands of unknown users and millions of anonymous queries, where the devices used for searching are not always identifiable and trends about touch screens cannot be ascertained.

Passport for Windows (PFW) and OCLC Macro Language (OML) are a library software combination that is hard to beat in terms of power and flexibility. PFW provides a desktop where multiple telecommunications (usually telnet) sessions can exist simultaneously, and the OML permits programmatic control and automation of tasks in any individual session as well as data sharing between different sessions. The fact that an entire programming language is available to the OML macro writer is what gives PFW the ability to seemingly work "magic" literally at the touch of a key, especially through the use of conditional logic for automated decision‐making. Not only is OML available in OCLC’s PFW product, but slight variants are available in OCLC’s Cataloging MicroEnhancer and ILL MicroEnhancer products as well. Although the pros of OML far outnumber the cons, there exist some downside issues (documentation, networkability, differences between products) which sometimes make macro writing and use by staff more difficult than it needs to be. In the end, though, all the efforts are worth it, because, by using PFW/OML macros, automation can do what it is good at, thereby giving staff the time and opportunity to do what they are good at.

Two studies were undertaken with the aim of determining the nature and prevalence of exposure to alcohol sponsorship communications associated with sport. Study 1 reports a content analysis of alcohol sponsors' leveraging across popular sporting events. Study 2 examines alcohol sponsors' activation in social media. A high proportion of alcohol sponsorship messages containing content appealing to young adult drinkers are revealed across multiple media. Events and policy implications are addressed.

The purpose of this paper is to report results of a formative usability study that investigated first-year student use of an optical character recognition (OCR) mobile application (app) designed to help students find resources for course assignments. The app uses textual content from the assignment sheet to suggest relevant library resources of which students may not be aware.

Formative evaluation data are collected to inform the production level version of the mobile application and to understand student use models and requirements for OCR software in mobile applications.

Mobile OCR apps are helpful for undergraduate students searching known titles of books, general subject areas or searching for help guide content developed by the library. The results section details how student feedback shaped the next iteration of the app for integration as a Minrva module.

This usability paper is not a large-scale quantitative study, but seeks to provide deep qualitative research data for the specific mobile interface studied, the Text-shot prototype.

The OCR application is designed to help students learn about availability of library resources based on scanning (e.g. taking a picture, or “Text-shot”) of an assignment sheet, a course syllabus or other course-related handouts.

This study contributes a new area of application development for libraries, with research methods that are useful for other mobile development studies.