Using Scenarios to Validate Requirements through the use of Eye-Tracking in Prototyping

Research has shown that eliciting and capturing the correct behavior of systems reduces the number of defects that a system contains. A requirements engineer will model the functions of the system to gain a comprehensive understanding of the system in question. Engineers must verify the model for correctness by either having another engineer review it or build a prototype and validate with a stakeholder. However, research has shown that this form of verification can be ineffective because looking at an existing model can be suggestive and stump the development of new ideas. This paper provides an automated technique that can be used as an unbiased review of use case scenarios. Using the prototype and a scenario, a stakeholder can be guided through the use case scenario demonstrating where they expect to find the next step while their eye movements are tracked. Analysis of the eye tracking data can be used to identify missing requirements such as interaction steps that should have alternative sequences or determining problems with the flow of actions

Multimodality with Eye tracking and Haptics: A New Horizon for Serious Games?

The goal of this review is to illustrate the emerging use of multimodal virtual reality that can benefit learning-based games. The review begins with an introduction to multimodal virtual reality in serious games and we provide a brief discussion of why cognitive processes involved in learning and training are enhanced under immersive virtual environments. We initially outline studies that have used eye tracking and haptic feedback independently in serious games, and then review some innovative applications that have already combined eye tracking and haptic devices in order to provide applicable multimodal frameworks for learning-based games. Finally, some general conclusions are identified and clarified in order to advance current understanding in multimodal serious game production as well as exploring possible areas for new applications

Analysing online user activity to implicitly infer the mental workload of web-based tasks using defeasible reasoning

Mental workload can be considered the amount of cognitive load or effort used over time to complete a task in a complex system. Determining the limits of mental workload can assist in optimising designs and identify if user performance is affected by that design. Mental workload has also been presented as a defeasible concept, where one reason can defeat another and a 5-layer schema to represent domain knowledge to infer mental workload using defeasible reasoning has compared favourably to state-of-the-art inference techniques. Other previous work investigated using records of user activity for measuring mental workload at scale using web-based tasks For this research, a solution design and experiment were put together to analyse user activity from a web-based task to determine if mental workload can be inferred implicitly using defeasible reasoning. While there was one promising result, only weak correlation between inferred values and reference workload profile values was found

Towards searching as a learning process: A review of current perspectives and future directions

We critically review literature on the association between searching and learning and contribute to the formulation of a research agenda for searching as learning. The paper begins by reviewing current literature that tends to characterize search systems as tools for learning. We then present a perspective on searching as learning that focuses on the learning that occurs during the search pro-cess, as well as search outputs and learning outcomes. The concept of ‘comprehensive search’ is proposed to describe iterative, reflec-tive and integrative search sessions that facilitate critical and creative learning beyond receptive learning. We also discuss how search interaction data can provide a rich source of implicit and explicit features through which to assess search-related learning. In conclu-sion, we summarize opportunities and challenges for future research with respect to four agendas: developing a search system that supports sense-making and enhances learning; supporting effective user interaction for searching as learning; providing an inquiry-based literacy tool within a search system; and assessing learning from online searching behaviour.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145734/1/Rieh et al Towards searching as a learning process JIS2016.pd

Perceptions on Hurricane Information and Tracking Maps

Tropical storms and hurricanes have caused extensive casualties and damage in past decades. Recent data indicate that the annual losses from hurricanes are increasing, partly because the U.S. coastal population has increased significantly in the past 20 years. Moreover, the housing values in these areas have increased as well. Thus, population and economic growth in the vulnerable coastal areas have made hurricanes a serious problem and created the potential for a catastrophic loss of life. The existing research literature lacks a sufficient scientific understanding of hurricane information searching and dynamic protective action decision making during events in which additional information becomes available over time. The hurricane evacuation decision context is well understood; the National Hurricane Center (NHC) issues hurricane forecast advisories every 6 hours until a hurricane turns into a tropical depression. Emergency managers and residents in the risk area are most likely to make decisions on their protective actions based on these hurricane forecast advisories. Therefore, this study uses the DynaSearch program to conduct a computer-based experiment that examines hurricane information search pattern by students playing the roles of county emergency managers, their understanding of hurricane strike probabilities and their choices of protective action recommendations during four different hurricane scenarios. This study simulates the approach of a hurricane by providing experiment participants a sequence of hurricane forecast advisories and examining how they search for information, change their threat perceptions and implement protective actions over time. The results show that (1) People prefer graphic information (especially the forecast track and uncertainty cone) over numeric and text information about hurricanes; (2) hurricane intensity was the parameter that was most commonly viewed and hurricane wind radius was the parameter that was least commonly viewed; (3)forecast track had a large number of clicks and long click durations, whereas uncertainty cone had fewer clicks but longer click durations; (4) participants’ judgments of the extent to which they used each of the parameters were not entirely consistent with their search patterns; (5) participants found a hurricane’s current location and day-5 forecast were the most informative time periods; (6) there was no evidence that participants’ personal concern (whether a hurricane will head toward to their county or not) affected their information search pattern in this study; (7) participants failed to evacuate appropriate risk areas in timely manner; and (8) participants had difficulty interpreting strike probabilities. These results suggest the problem of misinterpretation of the uncertainty cone is less severe than some might have concluded from the evidence provided by Broad et al. (2007). Moreover, the results suggest that participants were able to utilize the available information in the tables and tracking maps to make reasonable judgments about each city’s relative strike probability. However, their failure to take appropriate actions suggests a need for more comprehensive training on what actions to take in response to the hurricane information displays

Towards an Effective Organization-Wide Bulk Email System

Bulk email is widely used in organizations to communicate messages to employees. It is an important tool in making employees aware of policies, events, leadership updates, etc. However, in large organizations, the problem of overwhelming communication is widespread. Ineffective organizational bulk emails waste employees' time and organizations' money, and cause a lack of awareness or compliance with organizations' missions and priorities. This thesis focuses on improving organizational bulk email systems by 1) conducting qualitative research to understand different stakeholders; 2) conducting field studies to evaluate personalization's effects on getting employees to read bulk messages; 3) designing tools to support communicators in evaluating bulk emails. We performed these studies at the University of Minnesota, interviewing 25 employees (both senders and recipients), and including 317 participants in total. We found that the university's current bulk email system is ineffective as only 22% of the information communicated was retained by employees. To encourage employees to read high-level information, we implemented a multi-stakeholder personalization framework that mixed important-to-organization messages with employee-preferred messages and improved the studied bulk email's recognition rate by 20%. On the sender side, we iteratively designed a prototype of a bulk email evaluation platform. In field evaluation, we found bulk emails' message-level performance helped communicators in designing bulk emails. We collected eye-tracking data and developed a neural network technique to estimate how much time each message is being read using recipients' interactions with browsers only, which improved the estimation accuracy to 73%. In summary, this work sheds light on how to design organizational bulk email systems that communicate effectively and respect different stakeholders' value.Comment: PhD Thesi

Human-Computer Interaction

In this book the reader will find a collection of 31 papers presenting different facets of Human Computer Interaction, the result of research projects and experiments as well as new approaches to design user interfaces. The book is organized according to the following main topics in a sequential order: new interaction paradigms, multimodality, usability studies on several interaction mechanisms, human factors, universal design and development methodologies and tools

LOAN ME THE MONEY: HOW COGNITIVE ABILITIES AND FINANCIAL KNOWLEDGE INFLUENCE CONSUMERS’ INFORMATION BEHAVIORS

For most people, financial well-being depends on the ability to make sound decisions about many aspects of personal finance. This is especially true in the United States (U.S.), when it comes to consumer loan products such as mortgages and student loans. Consumers who lack strong financial knowledge can unwittingly expose themselves to bad information when searching online. Without understanding people’s searching behaviors, information professionals cannot know whether personal finance-related information systems adequately meet the needs of the people using them. Interactive Information Retrieval (IIR) is well-suited to study this, yet there has been little research in this area. One approach that makes sense for studying debt-related information searching is to investigate the role individual differences play in people’s searching. This is because individual differences are testable constructs that can be associated with differences in search performance outcomes. The purpose of this dissertation research is to understand influences that cognitive abilities and financial knowledge have on outcomes related to search, assessment, and mental workload of adults searching online for debt-related personal finance information. A theoretical model is proposed in which financial knowledge acts as a moderating variable on the effect that cognitive abilities have on search and evaluation behaviors as well as mental workload. The results of the study were mixed. The testing of hypotheses on the model were unsuccessful and provide information for informing future model designs and hypothesis development. The qualitative portion of the study provided numerous insights, including that the topic of personal finance, specifically in the realm of financial loans such as mortgages, student loans, and payday loans, is more challenging for people than they realize. Participants reported low prior knowledge of all task topics and used simple search strategies such as avoiding advertisements on search engine results pages (SERPs), relying heavily on the first SERP result, and reformulating queries rather than investigating SERPs at deeper levels. Participants rated most webpages they found as relevant or very relevant but expert assessors rated most of those same pages as only somewhat relevant or not relevant. The findings have numerous implications and point to key areas for further research.Doctor of Philosoph