Information and Library Science

Lifewide learning has grown in importance amongst UK universities, with many now offering award programmes to both encourage students to take part in extra- and co-curricular activities and to recognise their efforts in these areas. However, the typical requirement to align these awards with the existing academic year means that the submission and assessment of the awards occur at one of the most demanding times of the year for both students and staff. This paper suggests that a model for lifewide learning awards where the assessment activities are devolved to trusted third-parties would help to reduce the burden on students and staff. The idea of Open Badges, a standard for creating and sharing secure, verifiable digital credentials and evidence, is proposed and discussed using a case study as a means to support a devolved approach to lifewide learning awards.

The delight of this collaboration has been each author's firm belief that the others made the essential contributions. Accordingly, the order currently shown does not represent an equilibrium. We are grateful for the contributions of many colleagues to the ideas presented here, and especially to Markus Becker, Phanish Puranam, and Jason Owen-Smith for comments on an earlier draft. 1 We do not wish to enter here the controversy on similarity measures originating with Tversky (1977). For a critical appraisal and a defense of geometric measures of similarity, see Gärdenfors (2000).

SFX is a tool provided by the University Library that creates shortcuts to the full-text of online articles, as well as links to other Library services. When searching in many of the University Library databases, there will be an SFX button or link that connects to a menu of options.

Open Research Contributor ID (ORCID) is an open, non-profit, community-based effort to create and maintain a registry of researcher identifiers, and to solve the name ambiguity problems that have hindered the development of interoperable scholarly tools and networks. By creating a registry of unique identifiers for individual researchers, it allows a transparent and reliable method of linking research activities and outputs to these identifiers, thereby enabling not only more accurate attribution in traditional research articles, but also attribution in the new forms of scholarly communication that are arising. In December, 2012, MLibrary signed a (Basic) Member License Agreement with ORCID which allows us to, among other things, create ORCID records, update existing ORCID records, and use various APIs and the data those APIs can access to perform tasks associated with ORCID iDs. ORCID is not currently a mature, commercial product. Commercial publisher buy-in is strong -Elsevier Scopus, Nature Publishing Group, and Thomson Reuters are among the launch partners, and Cambridge University Press, Springer, and Wiley are among the sponsors -but right now ORCID is a nascent, open source project. Regardless, we recommend that U-M, and specifically MLibrary, facilitate and encourage the use of ORCID iDs. Doing so will position us as an early adopter, and we will likely have to commit resources to make things work for us (and by extension, others

To plan safe trajectories in urban environments, autonomous vehicles must be able to quickly assess the future intentions of dynamic agents. Pedestrians are particularly challenging to model, as their motion patterns are often uncertain and/or unknown a priori. This paper presents a novel changepoint detection and clustering algorithm that, when coupled with offline unsupervised learning of a Gaussian process mixture model (DPGP), enables quick detection of changes in intent and online learning of motion patterns not seen in prior training data. The resulting long-term movement predictions demonstrate improved accuracy relative to offline learning alone, in terms of both intent and trajectory prediction. By embedding these predictions within a chanceconstrained motion planner, trajectories which are probabilistically safe to pedestrian motions can be identified in real-time. Hardware experiments demonstrate that this approach can accurately predict pedestrian motion patterns from onboard sensor/perception data and facilitate robust navigation within a dynamic environment.

ing the work that PPPs can do to foster global development. Arguably, the United States was a particularly fitting jurisdiction for the HathiTrust project, given the solid foundation of the fair use exception to copyright as an established part of the US Copyright Act, 2 and its robust interpretation in US case law. US copyright law specifically limits the copyright holder's rights by authorizing special uses for libraries and archives in Section 108 of the 1976 Copyright Act. 3 In addition to special reproduction rights for libraries under prescribed circumstances, US copyright law additionally features fair use as stated in Section 107 of the 1976 Act. 4 Indeed, Section 108 (which addresses exceptions and limitations to copyright, for libraries and archives) explicitly refers to the section 107 fair use as a right: "Nothing in this section in any way affects the right of fair use as provided by section 107 . . ." 5 Despite these clearly available exceptions, the legal complexity of the Google scanning project and scale of resulting litigation against Google and UML and other libraries by authors and publishers over the better part of a decade was groundbreaking. That Google and HathiTrust prevailed in this costly litigation raises questions about lessons learned, specifically, whether this arguably unique approach is replicable in other jurisdictionsor whether instead the multilateral copyright framework requires recalibration in order to promote and support similar PPP collaborations elsewhere. This chapter begins in Part I with a brief history of HathiTrust, including the motivations on the part of UML as well as Google to form this PPP. In Part II, it describes the background of general concerns, including those of research librarians with book preservation as well as those of librarians in general regarding access to information by persons with visual disabilities. The chapter then turns in Part III to the importance of copyright exceptions and limitations as a prerequisite for the partnership formed as a result of the mutual interests of UML and Google. Part IV then details the partnership itself, by discussing some key provisions in the partnership contract that allow the project to be of both private and public benefit. This section also touches upon significant social relationships that allowed the partnership to move forward constructively, as well as the benefits expected and realized by participating partners. The chapter concludes in Part V with an exploration of the role of IP as a distinct challenge to the partnership goals, 2 U.S. Copyright Act, 17 U.S.C § § 101-1332 (2012). Fair use is a unique feature of US copyright law, although Israel, Poland, and South Korea have similar provisions. Fair use and the related (but distinct) concept of fair dealing find their origins in England and have been translated in former UK spheres of influence.

Yahoo Answers (YA) is a large and diverse question-answer forum, acting not only as a medium for sharing technical knowledge, but as a place where one can seek advice, gather opinions, and satisfy one's curiosity about a countless number of things. In this paper, we seek to understand YA's knowledge sharing activity. We analyze the forum categories and cluster them according to content characteristics and patterns of interaction among the users. While interactions in some categories resemble expertise sharing forums, others incorporate discussion, everyday advice, and support. With such a diversity of categories in which one can participate, we find that some users focus narrowly on specific topics, while others participate across categories. This not only allows us to map related categories, but to characterize the entropy of the users' interests. We find that lower entropy correlates with receiving higher answer ratings, but only for categories where factual expertise is primarily sought after. We combine both user attributes and answer characteristics to predict, within a given category, whether a particular answer will be chosen as the best answer by the asker.

Communication between automated vehicles (AVs) and vulnerable road users (VRUs) is highly relevant in coordinating traffic maneuvers and therefore ensuring road safety. Especially in shared spaces such as parking areas, communication is highly important. As automated driving changes the driver's role, communication between different traffic participants will also change. External human-machine interfaces (eHMIs) may enhance safety and effective communication between VRUs and AVs by providing relevant information to other traffic participants if informal communication is insufficient. Hence, a variety of information (e.g., about AVs' driving mode or future maneuvers) is recommended to be communicated to VRUs. Therefore, we investigated the effects of three different light signals, presented by a light bar placed on the test vehicle's roof, as a form of an eHMI: automation mode, starting mode and crossing mode. Moreover, two different driving conditions (i.e., a manual and a simulated automated driving condition) were implemented to investigate the effects between these conditions. Either the driver was visible in the manual condition or the vehicle appeared driverless as a seat suit covered the driver in the simulated automated condition (Wizard-of-Oz design). A total of N = 173 random pedestrians passing by were interviewed and behavioral data were collected from over 1500 pedestrians. Results indicate that participants felt significantly safer during the interaction with the vehicle when a driver was visible. Although VRUs evaluated the general approach of applying light signals as eHMIs for AVs as useful, they assessed the presented light signals as only partially trustworthy and rather unintuitive. Moreover, many participants were unsure of whether the light signals were directed towards them, thus the directedness of light signals should be considered when implementing a light-based eHMI in AVs. Further, moving light signals attracted more attention (i.e., increased pedestrians' head movements towards the vehicle) than a steady or no light signal did. Interestingly, no difference existed between the investigated steady light signal and the baseline condition (i.e., no light signal) regarding head movements towards the vehicle. The results underline the importance of implementing an appropriate eHMI design in AVs.

This chapter focuses on the application to the authors' lived experiences of a model originating in the field of education that has to date been minimally referenced: omnidirectional mentoring. It briefly introduces the concepts of omnidirectional mentoring and critical mass, as well as presenting the author's personal narratives and discussions of how they have built critical mass, served as mentors, and been mentored by omnidirectional mentoring communities in different aspects of their careers and personal lives. It ends with recommendations for individuals and institutions interested in exploring and encouraging omnidirectional mentorship in their own contexts.

The current paradigm for advancing autonomous driving functionalities on public roads predominantly operates within the tangible realm. Autonomous vehicles (AVs) are equipped with an array of sensors, including Lidar, cameras, radar, GPS, and on-boardunit (OBU) modems, each actively collecting data about the surrounding environment. This data is then processed through sophisticated algorithms, enhancing the vehicle's situational awareness. In our pursuit of refining autonomous driving capabilities, we leverage the AVTSC Simulator as our chosen Autonomous Vehicle (AV) simulation environment. Notably, this simulator stands out for its ability to replicate realistic urban settings and seamlessly integrate with widely used platforms such as Apollo and ROS. By harnessing the capabilities of this simulation environment, we aim to bridge the gap between real-world testing and simulated scenarios. This abstract encapsulates the essence of our strategy, emphasizing the integration of advanced sensor technologies and simulation environments for the development of autonomous driving features. Preliminary results indicate a promising 94% success rate for the proposed methodology, showcasing the efficacy of our approach in enhancing the robustness and reliability of autonomous systems.

SUMMARYSolving wireless packet retransmission problem (WPRTP) using network coding (NC) is increasingly attracting research efforts. However, existing NC‐based schemes for WPRTP are with high computational complexity resulting from computation on larger Galois field (GF(2q)), or the solutions on GF(2) found by the schemes are less efficient. In this paper, combining the basic ideas in two existing schemes, denoted as ColorNC and CliqueNC, respectively, we present a new scheme named as ColorCliqueNC. The advantages of ColorCliqueNC include the following: (i) it is suitable for all kinds of WPRTP instances; (ii) it works on GF(2); thus, it is computationally efficient than the schemes working on larger Galois fields; and (iii) the solutions found by ColorCliqueNC usually have fewer packet retransmissions than those by ColorNC and CliqueNC despite that they all work on GF(2). Theoretical analysis indicates that ColorCliqueNC is superior to ColorNC and CliqueNC. Simulation results show ...

The TeraGrid Planning Process was funded by the National Science Foundation's (NSF) Office of Cyberinfrastructure through a grant to the University of Michigan's School of Information (UM-SI). Ann Zimmerman and Thomas A. Finholt served as Principal Investigator (PI) and Co-PI, respectively. The role of the UM-SI was to support and facilitate a planning process to be led by a steering committee representative of key stakeholder communities and with diverse expertise.

Scholarly communication is often thought of as the preservation of knowledge. In fact, it also influences the creation, transformation, and dissemination of knowledge. The new norms of scholarly communication are multiple authorships, inter-institutional and international collaboration, and use of social media. The evolving norms for the librarians and consortial groups are supporting research data management, aiding discovery of collaborators, and dissemination and preservation of results, especially in digital formats. Librarians are viewed as experts in scholarly communication on many campuses but their leadership is not always recognized. First, Christine Stamison characterized new norms and evolving tools to aid the creation and transformation of scholarly knowledge. Next, Anne McKee discussed the dissemination and preservation of knowledge and what libraries and consortia are doing to support it.

Scholarly communication is often thought of as the preservation of knowledge. In fact, it also influences the creation, transformation, and dissemination of knowledge. The new norms of scholarly communication are multiple authorships, inter-institutional and international collaboration, and use of social media. The evolving norms for the librarians and consortial groups are supporting research data management, aiding discovery of collaborators, and dissemination and preservation of results, especially in digital formats. Librarians are viewed as experts in scholarly communication on many campuses but their leadership is not always recognized. First, Christine Stamison characterized new norms and evolving tools to aid the creation and transformation of scholarly knowledge. Next, Anne McKee discussed the dissemination and preservation of knowledge and what libraries and consortia are doing to support it.

In this paper, a cooperative decision-making is presented, which is suitable for intention-aware automated vehicle functions. With an increasing number of highly automated and autonomous vehicles on public roads, trust is a very important issue regarding their acceptance in our society. The most challenging scenarios arise at low driving speeds of these highly automated and autonomous vehicles, where interactions with vulnerable road users likely occur. Such interactions must be addressed by the automation of the vehicle. The novelties of this paper are the adaptation of a general cooperative and shared control framework to this novel use case and the application of an explicit prediction model of the pedestrian. An extensive comparison with state-of-the-art algorithms is provided in a simplified test environment. The proposed approach is also implemented on the experimental vehicle. The results show the superiority of the proposed model-based algorithm and its suitability for real-world applications.

We seek to motivate drivers who regularly use webbased local and mapping services and have access to viable alternative transit methods -such as public transportation, carpooling, walking or bicycling -to use these alternatives instead of driving alone. altVerto works with users' existing habits to intervene during trip planning, and then sustains long-term positive behavior through progress tracking and communitybuilding around alternatives to driving. Our study investigates how computer-mediated intervention at decision making moments and online transit-related community motivates and sustains the use of alternative transit methods.

Given the rapidly changing economics of scholarly communication in the digital age, the importance of accurate, specific data on the resource flows within this realm has become increasingly important. Both the producers and the collectors of scholarly information require accurate information in order to nimbly navigate their changing roles in advancing the progress of knowledge. Two key actors in this area are university presses and academic libraries, which both hold keystone roles in scholarly communications, as disseminators and conservators of scholarship, respectively. This paper describes an exploratory study examining one contentious aspect of the relationship between these two actors: trends in purchases of university press books by academic libraries. It does so in order to provide an empirical basis for evaluating frequent claims by publishers that declines in libraries' monographic purchasing over the past three decades can be held primarily responsible for the declining economic fortunes of university presses over the same period. The results of this analysis indicate that this relationship is not clear-cut, for at least two reasons: first, to the extent that purchasing reductions have occurred, they have occurred much more recently than prior accounts have suggested, and second, purchasing trends vary significantly between different libraries and between different sizes of university press.

Table of Participants and their Survey Responses 22 Appendix C -Setup Documents and Interview Protocol 24 Setup Instructions 24 Consent Form 26 Interview Protocol 27 Experienced User Interviews -MLibrary Usability Group Summer 2012 Methods Research Methods Recruitment Subject specialist librarians distributed a screening survey created by members of the Usability Group. The screening survey asked respondents for their status, affiliation, area of research, and a self-report of how comfortable they were with the library website and what they used it for (see Appendix A for full screening survey). The screening survey was initially opened on January 9th, 2012, and closed on February 20th, 2012. Usability Group members selected ten Experienced User Interviews -MLibrary Usability Group Summer 2012

Digital libraries have been defined in the literature as being collections of electronic resources, serving a community of users, and services offered to those users. In this, the definition of digital libraries is little different from a definition of a physical library. Most actual digital libraries, however, are primarily collections, with little attention given to services that may be offered to increase the value of those collections. Indeed, in the Institute of Museum and Library Services'

Computer support helpdesks often engage in sensemaking while working on atypical problems. Handoffs are common in these sensemaking situations due to shift changes, because a different skill or perspective is needed or simply because the current sensemaker may be exhausted. Though handoff may be needed, it may not always be successful. This could be true because sensemaking involves non-routine activities for which no structural support for handoff may exist, or because sensemakers may not be sure what to handoff if sensemaking is not complete. This study examined the issues related to sensemaking handoff in computer support helpdesks. Existing theories of sensemaking (Russell et al, 1993 and Weick, 1996) were used as a framework. Semi-structured interviews were conducted with two different computer helpdesk personnel groups at a large mid-western university. Successful handoffs occurred either very early or very late in the sensemaking process. This choice of handoff time as well as other aspects of handoffs are discussed using the principles of least collaborative effort [13] and mindfulness [18].

A number of studies have demonstrated strong links between students' language features (as found in spoken and written production) and their math performance. However, no studies have examined links between the students’ language features and measures of their Math Identity. This project extends prior studies that use natural language processing (NLP) features to examine student language features and math performance, replicating their analyses. The study then uses NLP features to model students’ Math Identity. Specifically, the study compares performance on basic math skills within an online math tutoring system to both student language (as captured in emails to a virtual pedagogical agent) and to survey measures of Math Identity (math self concept, interest, and value). Language features were analyzed by a number of NLP tools that extracted information related to text cohesion, lexical sophistication, and sentiment. The findings indicate weak to medium relationships between ma...

This paper reports on an effort to develop a digital badging and e-portfolio environment that will illuminate and assess curricular, co-curricular, and extracurricular learning in cybersecurity. This effort includes Cal Poly Pomona and Coastline College, which are both designated as Centers of Academic Excellence in Cyber Defense (CAE/CD) along with a collection of academic and industry partners in creating learning pathways that move interested beginners all the way through an exciting career in the field of cybersecurity. The pathways are designed to incorporate curricular, co-curricular, and extracurricular learning in a student-managed process in which students consume the learning modules they desire/need and which move them toward the learning goals they have chosen. Students will be able to see how formal curricular programs align with their learning journey and plan curricular, cocurricular, and extracurricular learning tasks that fit their plan and allow them to achieve the...

Large-scale digitization is generating extraordinary collections of visual and textual surrogates, potentially endowed with transcendent long-term cultural and research values. Understanding the nature of digital surrogacy is a substantial intellectual opportunity for archival science and the digital humanities, because of the increasing independence of surrogate collections from their archival sources. The paper presents an argument that one of the most significant requirements for the long-term access to collections of digital surrogates is to treat digital surrogates as archival records that embody traces of their fluid lifecycles and therefore are worthy of management and preservation as archives. It advances a theory of the archival nature of surrogacy founded on longstanding notions of archival quality, the traces of their source and the conditions of their creation, and the functional ''work of the archive.'' The paper presents evidence supporting a ''secondary provenance'' derived from re-digitization, re-ingestion of multiple versions, and de facto replacement of the original sources. The design of the underlying research that motivates the paper and summary findings are reported separately. The research has been supported generously by the US Institute of Museum and Library Services.

Diversity can have positive and negative effects on team decision making. Text communication has been put forth as one solution to addressing this duality of team diversity. Unfortunately, the empirical results have been far from conclusive. We believe that resolving such inconsistencies is crucial to developing a more complete understanding of the use of communication technologies. To accomplish this, we developed a research model based on media synchronicity theory. We empirically tested this model by conducting a laboratory experiment with 46 teams, consisting primarily of men and women self-identified as Caucasians and Asians, performing a decision-making task. The results show that the type of diversity matters. Text communication improved knowledge sharing (i.e., conveyance) and knowledge integration (i.e., convergence) in racially diverse teams but impaired both in gender diverse teams. Knowledge integration was more important to decision quality when racial and gender divers...

In this poster abstract, we motivate and describe the design rationale for an approach to making audiences of creative content more visible and salient to producers contributing to user generated content and social media systems. Set in the specific context of digital photography, we discuss how this approach is appropriate for visualizing multiple audience types, thus supporting heterogeneous use models, relationship types and motivations. We also discuss the research questions and future assessment work through which this UI intervention will be evaluated.

Autonomous vehicles (AVs) have the potential to improve road safety. Trust in AVs, especially among pedestrians, is vital to alleviate public skepticism. Yet much of the research has focused on trust between the AV and its driver/passengers. To address this shortcoming, we examined the interactions between AVs and pedestrians using uncertainty reduction theory (URT). We empirically verified this model with a user study in an immersive virtual reality environment (IVE). The study manipulated two factors: AV driving behavior (defensive, normal and aggressive) and the traffic situation (signalized and unsignalized). Results suggest that the impact of aggressive driving on trust in AVs depends on the type of crosswalk. At signalized crosswalks the AV's driving behavior had little impact on trust, but at unsignalized crosswalks the AV's driving behavior was a major determinant of trust. Our findings shed new insights on trust between AVs and pedestrians.

For automated vehicles (AVs) to reliably navigate through crosswalks, they need to understand pedestrians' crossing behaviors. Simple and reliable pedestrian behavior models aid in real-time AV control by allowing the AVs to predict future pedestrian behaviors. In this paper, we present a Behavioraware Model Predictive Controller (B-MPC) for AVs that incorporates long-term predictions of pedestrian crossing behavior using a previously developed pedestrian crossing model. The model incorporates pedestrians' gap acceptance behavior and utilizes minimal pedestrian information, namely their position and speed, to predict pedestrians' crossing behaviors. The B-MPC controller is validated through simulations and compared to a rule-based controller. By incorporating predictions of pedestrian behavior, the B-MPC controller is able to efficiently plan for longer horizons and handle a wider range of pedestrian interaction scenarios than the rule-based controller. Results demonstrate the applicability of the controller for safe and efficient navigation at crossing scenarios. Index Terms-autonomous urban driving, behavior-aware control, autonomous control, social human-robot interaction.

In conditionally automated driving, drivers decoupled from operational control of the vehicle have difficulty taking over control when requested. To address this challenge, we conducted a human-in-the-loop experiment wherein the drivers needed to take over control from an automated vehicle. We collected drivers' physiological data and data from the driving environment, and based on which developed random forest models for predicting drivers' takeover performance in real time. Drivers' subjective ratings of their takeover performance were treated as the ground truth. The best random forest model had an accuracy of 70.2% and an F1-score of 70.1%. We also discussed the implications on the design of an adaptive in-vehicle alert system.

For safe navigation around pedestrians, automated vehicles (AVs) need to plan their motion by accurately predicting pedestrians' trajectories over long time horizons. Current approaches to AV motion planning around crosswalks predict only for short time horizons (1-2 s) and are based on data from pedestrian interactions with human-driven vehicles (HDVs). In this paper, we develop a hybrid systems model that uses pedestrians' gap acceptance behavior and constant velocity dynamics for long-term pedestrian trajectory prediction when interacting with AVs. Results demonstrate the applicability of the model for long-term (> 5 s) pedestrian trajectory prediction at crosswalks. Further, we compared measures of pedestrian crossing behaviors in the immersive virtual environment (when interacting with AVs) to that in the real world (results of published studies of pedestrians interacting with HDVs), and found similarities between the two. These similarities demonstrate the applicability of the hybrid model of AV interactions developed from an immersive virtual environment (IVE) for real-world scenarios for both AVs and HDVs.

Autonomous vehicles (AVs) have the potential to improve road safety. Trust in AVs, especially among pedestrians, is vital to alleviate public skepticism. Yet much of the research has focused on trust between the AV and its driver/passengers. To address this shortcoming, we examined the interactions between AVs and pedestrians using uncertainty reduction theory (URT). We empirically verified this model with a user study in an immersive virtual reality environment (IVE). The study manipulated two factors: AV driving behavior (defensive, normal and aggressive) and the traffic situation (signalized and unsignalized). Results suggest that the impact of aggressive driving on trust in AVs depends on the type of crosswalk. At signalized crosswalks the AV's driving behavior had little impact on trust, but at unsignalized crosswalks the AV's driving behavior was a major determinant of trust. Our findings shed new insights on trust between AVs and pedestrians.

Trust is a vital determinant of acceptance of automated vehicles (AVs) and expectations and explanations are often at the heart of any trusting relationship. Once expectations have been violated, explanations are needed to mitigate the damage. This study introduces the importance of timing of explanations in promoting trust in AVs. We present the preliminary results of a within-subjects experimental study involving eight participants exposed to four AV driving conditions (i.e. 32 data points). Preliminary results show a pattern that suggests that explanations provided before the AV takes actions promote more trust than explanations provided afterward.

In conditionally automated driving, drivers engaged in non-driving related tasks (NDRTs) have difficulty taking over control of the vehicle when requested. This study aimed to examine the relationships between takeover performance and drivers' cognitive load, takeover request (TOR) lead time, and traffic density. We conducted a driving simulation experiment with 80 participants, where they experienced 8 takeover events. For each takeover event, drivers' subjective ratings of takeover readiness, objective measures of takeover timing and quality, and NDRT performance were collected. Results showed that drivers had lower takeover readiness and worse performance when they were in high cognitive load, short TOR lead time, and heavy oncoming traffic density conditions. Interestingly, if drivers had low cognitive load, they paid more attention to driving environments and responded more quickly to takeover requests in high oncoming traffic conditions. The results have implications for the design of in-vehicle alert systems to help improve takeover performance. CCS Concepts: • Human-centered computing → Empirical studies in HCI.

Pedestrians' acceptance of automated vehicles (AVs) depends on their trust in the AVs. We developed a model of pedestrians' trust in AVs based on AV driving behavior and traffic signal presence. To empirically verify this model, we conducted a human-subject study with 30 participants in a virtual reality environment. The study manipulated two factors: AV driving behavior (defensive, normal, and aggressive) and the crosswalk type (signalized and unsignalized crossing). Results indicate that pedestrians' trust in AVs was influenced by AV driving behavior as well as the presence of a signal light. In addition, the impact of the AV's driving behavior on trust in the AV depended on the presence of a signal light. There were also strong correlations between trust in AVs and certain observable trusting behaviors such as pedestrian gaze at certain areas/objects, pedestrian distance to collision, and pedestrian jaywalking time. We also present implications for design and future research.

Explanations given by automation are often used to promote automation adoption. However, it remains unclear whether explanations promote acceptance of automated vehicles (AVs). In this study, we conducted a within-subject experiment in a driving simulator with 32 participants, using four different conditions. The four conditions included: (1) no explanation, (2) explanation given before or (3) after the AV acted and (4) the option for the driver to approve or disapprove the AV's action after hearing the explanation. We examined four AV outcomes: trust, preference for AV, anxiety and mental workload. Results suggest that explanations provided before an AV acted were associated with higher trust in and preference for the AV, but there was no difference in anxiety and workload. These results have important implications for the adoption of AVs.

Two generalizations of Bacon's theory of loop-free decomposition of probabilistic finite-state systems are proposed. The first of these consists of a modification of the structure of the decomposition which then allows for the decomposition of a larger class of systems. The second generalization subsumes the first: sufficient conditions for a stochastic finite-state system to be decomposable for a single initial distribution on its set of states are given.

Recent studies suggest that users often retrieve incomplete healthcare information because of the complex and skewed distribution of facts across relevant webpages. To understand the causes for such skewed distributions , this paper presents the results of two analyses: (1) A distribution analysis discusses how facts related to healthcare topics are scattered across high-quality healthcare pages. (2) A cluster analysis of the same data suggests that the skewed distribution can be explained by the existence of three page profiles that vary in information density, each of which play in important role in providing comprehensive information of a topic. The above analyses provide clues towards a model of information scatter which describes how the design decisions by individual webpage authors could collectively lead to the scatter of information as observed in the data. The analyses also suggest implications for the design of websites, search algorithms, and search interfaces to help users find comprehensive information about a topic.

Sensemaking tasks are challenging and typically involve collecting, organizing and understanding information. Sensemaking often involves a handoff where a subsequent recipient picks up work done by a provider. Sensemaking handoffs are very challenging because handoffs introduce discontinuity in sensemaking. This dissertation attempts to explore various factors involved in sensemaking handoffs. This work drew on existing literature on sensemaking to propose five sensemaking task attributes: representation novelty required, encoding difficulty, broader applicability, representation search space and subtask interdependence. These attributes capture what makes sensemaking difficult and also help in choosing tasks to study sensemaking as well as modifying laboratory tasks so that they involve more sensemaking. Synthesizing existing literature on collaboration, the dissertation identified important elements in a sensemaking handoff: intent to collaborate, common ground, shared space, awar...

This work is an attempt to reconcile three separate but influential threads in study of sensemaking. The first two of these are theories from different domains, human computer interaction (HCI) and social/organizational psychology. The last thread is that of design, of sensemaking support tools. Integrated, these three threads form a strong foundation for researchers, tool-designers and ultimately sensemakers themselves. Understanding and supporting the special role of people-people interaction can help us tie these separate threads together. This synthesis also suggests further research that can expand our understanding of sensemaking.

The complexities of sensemaking suggest that collaboration should be difficult, requiring a rich ecology of collaboration support. This can be a problem for handoff sensemaking, where one person must continue where another has left off, sometimes with only material artifacts as the basis of the handoff. A detailed analysis of essential attributes of sensemaking tasks, and elements identified in the computer supported collaborative work literature were combined to yield insight into handoff sensemaking and guide empirical work. A lab‐study showed that handoffs relying only on artifacts from previous sensemaking could be successful. The lab studies also indicated timing and quality affects on the sensemaking handoffs, with different quality materials used differently, and early efforts possibly being particularly difficult to hand off. Design of support for sensemaking handoffs will have to take such effects into account.

Web 2.0 has allowed online shoppers to become not just information seekers but also information providers. Many e-commerce venues allow users to share their experiences in the form of textual product reviews. While textual product reviews represent a wealth of information for candidate buyers, finding pertinent information becomes difficult, as the number of reviews for a particular product becomes large, or if the buyer is interested in particular features of an item. We present ChatterCrop, a tool that uses text summarization. ChatterCrop condenses the information from a large set of reviews into a few sentences, and allows users to customize these summaries for feature-focused search. In a user study, subjects used ChatterCrop and a sortable list of reviews, to answer questions about two camcorder models. When looking for information about particular features, ChatterCrop outperformed the list, in terms user confidence and perceived ease in finding pertinent information. ChatterCrop's summaries also provided users with starting points to guide further research, and were particularly helpful in the early stages of sensemaking.