A new integrated model for multitasking during web searching

Investigating multitasking information behaviour, particularly while using the web, has become an increasingly important research area. People s reliance on the web to seek and find information has encouraged a number of researchers to investigate the characteristics of information seeking behaviour and the web seeking strategies used. The current research set out to explore multitasking information behaviour while using the web in relation to people s personal characteristics, working memory, and flow (a state where people feel in control and immersed in the task). Also investigated were the effects of pre-determined knowledge about search tasks and the artefact characteristics. In addition, the study also investigated cognitive states (interactions between the user and the system) and cognitive coordination shifts (the way people change their actions to search effectively) while multitasking on the web. The research was exploratory using a mixed method approach. Thirty University students participated; 10 psychologists, 10 accountants and 10 mechanical engineers. The data collection tools used were: pre and post questionnaires, pre-interviews, a working memory test, a flow state scale test, audio-visual data, web search logs, think aloud data, observation, and the critical decision method. Based on the working memory test, the participants were divided into two groups, those with high scores and those with lower scores. Similarly, participants were divided into two groups based on their flow state scale tests. All participants searched information on the web for four topics: two for which they had prior knowledge and two more without prior knowledge. The results revealed that working memory capacity affects multitasking information behaviour during web searching. For example, the participants in the high working memory group and high flow group had a significantly greater number of cognitive coordination and state shifts than the low working memory group and low flow group. Further, the perception of task complexity was related to working memory capacity; those with low memory capacity thought task complexity increased towards the end of tasks for which they had no prior knowledge compared to tasks for which they had prior knowledge. The results also showed that all participants, regardless of their working memory capacity and flow level, had the same the first frequent cognitive coordination and cognitive state sequences: from strategy to topic. In respect of disciplinary differences, accountants rated task complexity at the end of the web seeking procedure to be statistically less significant for information tasks with prior knowledge compared to the participants from the other disciplines. Moreover, multitasking information behaviour characteristics such as the number of queries, web search sessions and opened tabs/windows during searches has been affected by the disciplines. The findings of the research enabled an exploratory integrated model to be created, which illustrates the nature of multitasking information behaviour when using the web. One other contribution of this research was to develop new more specific and closely grounded definitions of task complexity and artefact characteristics). This new research may influence the creation of more effective web search systems by placing more emphasis on our understanding of the complex cognitive mechanisms of multitasking information behaviour when using the web

An investigation of multitasking on the web: key findings

Introduction. This paper presents key findings from a study exploring how multitasking information behaviour is affected by people’s working memory capacity and the flow they experience during the searching process. Method. The research is exploratory using a pragmatic, mixed method approach. 30 study participants, 10 psychologists, 10 accountants and 10 mechanical engineers, conducted Web searches on four information topics. The data collection tools used were: pre and post questionnaires, pre interviews, working memory test, the flow state scale of Jackson and Marsh (1996), audio-visual data, web search logs, think aloud data, observation, and the critical decision method. Results. The results suggested that people with high working memory, high flow and mechanical engineers generated more cognitive coordination and cognitive state shifts than people with low working memory, low flow, accountants and psychologists. The most frequent cognitive state and coordination shift for all groups was from strategy to information topic. Low working memory participants rated task complexity at the end of the procedure more highly for tasks without prior knowledge compared to tasks with prior knowledge. Participants with high flow levels experienced a greater change of knowledge for information tasks without prior knowledge compared to participants with low flow. The degree of change of knowledge for participants with high flow was higher for tasks without prior knowledge rather than for tasks with prior knowledge

Testing the stability of “wisdom of crowds” judgments of search results over time and their similarity with the search engine rankings

PURPOSE: One of the under-explored aspects in the process of user information seeking behaviour is influence of time on relevance evaluation. It has been shown in previous studies that individual users might change their assessment of search results over time. It is also known that aggregated judgments of multiple individual users can lead to correct and reliable decisions; this phenomenon is known as the “wisdom of crowds”. The aim of this study is to examine whether aggregated judgments will be more stable and thus more reliable over time than individual user judgments. DESIGN/METHODS: In this study two simple measures are proposed to calculate the aggregated judgments of search results and compare their reliability and stability to individual user judgments. In addition, the aggregated “wisdom of crowds” judgments were used as a means to compare the differences between human assessments of search results and search engine’s rankings. A large-scale user study was conducted with 87 participants who evaluated two different queries and four diverse result sets twice, with an interval of two months. Two types of judgments were considered in this study: 1) relevance on a 4-point scale, and 2) ranking on a 10-point scale without ties. FINDINGS: It was found that aggregated judgments are much more stable than individual user judgments, yet they are quite different from search engine rankings. Practical implications: The proposed “wisdom of crowds” based approach provides a reliable reference point for the evaluation of search engines. This is also important for exploring the need of personalization and adapting search engine’s ranking over time to changes in users preferences. ORIGINALITY/VALUE: This is a first study that applies the notion of “wisdom of crowds” to examine the under-explored phenomenon in the literature of “change in time” in user evaluation of relevance

Flow in multitasking : the effects of motivation, artifact, and task factors

textThe aims of this dissertation study are 1) to examine how the interplay of motivation, artifacts, and task interconnectedness affect users' flow experience, 2) to understand users' multitasking patterns by analyzing approaches and strategies in multitasking environments through a participatory design session, and 3) to come up with design insights and implications for desired multitasking environments based on findings from the quantitative and qualitative data analysis and synthesis. This dissertation employed the PAT (Person-Artifact-Task) model to examine factors that affect users' flow experience in computer-mediated multitasking environments. Particularly, this study focused on users' flow experience - sense of control, focused attention, curiosity, intrinsic interest and interactivity - in the context of multitasking. The dissertation begins with perspectives on human multitasking research from various disciplines. Emphasis is placed on how researchers have defined the term multitasking and the scope of previous multitasking research. In addition, this study provides definitions of the term task switching, which also has been used to describe human multitasking. The second section of this dissertation focuses on the literature, which characterizes factors and theoretical frameworks of human multitasking research. In this section, human multitasking factors were classified into internal and external factors to analyze factors from the micro to the macro perspective. More detailed definitions and comparisons are also addressed. To summarize and conclude the literature review, this study provides a synthesis framework of internal and external factors of human multitasking contexts. In section III, this dissertation introduces theoretical frameworks that include the constructs of the PAT (Person-Artifact-Task) model and flow model. The next three sections present the research design and two research methods - the experiment and participatory design. The results and discussion section includes the implications of interpreting people's flow experience with motivation, artifact (technology affordance type), and task interconnectedness through the PAT model. The study findings and implications should extend our understanding of multitasking behaviors and contexts and how the interplay of person, artifact, and task factors affects humans' flow experience. A concluding chapter explores future work and design implications on how researchers and designers can take contextual factors into consideration to identify the most effective multitasking in computer-mediated environments.Informatio

Redefining Attention (and Revamping the Legal Profession?) for the Digital Generation

With computers, text messages, Facebook, cell phones, smartphones, tablets, iPods, and other information and communication technologies (“ICTs”) constantly competing for our attention, we live in an age of perpetual distraction. Educators have long speculated that constant exposure to ICTs is eroding our ability to stay focused, and recent research supports these speculations. This raises particularly troubling implications for the practice of law, in which being able to pay sustained attention to the task at hand is crucial. Research also indicates that the brains of today’s young people, the “Digital Generation,” may function differently than the brains of their elders because the Digital Generation have grown up immersed in digital technology. This suggests that the techniques today’s legal professionals might use to cultivate attention in the face of technological distraction could prove to be inappropriate for future generations of lawyers. When the Digital Generation are both the attorneys and the clients, it may be the practice of law — rather than the lawyers — that needs to change. This paper explores the science of attention and explains why attention is important. Next, it introduces the Digital Generation and their relationship with digital technology. It then examines the connection between ICT exposure and attention and reviews several suggestions that others have made about how legal professionals should respond to the challenges ICTs pose to focused attention. This paper then takes the conversation in a new direction: It predicts ways in which the legal profession, rather than the legal professionals, will necessarily have to adapt to technology in the future. Finally, it offers thoughts about how the legal profession should view its relationship with technology going forward

Attention Allocation for Human Multi-Robot Control: Cognitive Analysis based on Behavior Data and Hidden States

Human multi-robot interaction exploits both the human operator’s high-level decision-making skills and the robotic agents’ vigorous computing and motion abilities. While controlling multi-robot teams, an operator’s attention must constantly shift between individual robots to maintain sufficient situation awareness. To conserve an operator’s attentional resources, a robot with self reflect capability on its abnormal status can help an operator focus her attention on emergent tasks rather than unneeded routine checks. With the proposing self-reflect aids, the human-robot interaction becomes a queuing framework, where the robots act as the clients to request for interaction and an operator acts as the server to respond these job requests. This paper examined two types of queuing schemes, the self-paced Open-queue identifying all robots’ normal/abnormal conditions, whereas the forced-paced shortest-job-first (SJF) queue showing a single robot’s request at one time by following the SJF approach. As a robot may miscarry its experienced failures in various situations, the effects of imperfect automation were also investigated in this paper. The results suggest that the SJF attentional scheduling approach can provide stable performance in both primary (locate potential targets) and secondary (resolve robots’ failures) tasks, regardless of the system’s reliability levels. However, the conventional results (e.g., number of targets marked) only present little information about users’ underlying cognitive strategies and may fail to reflect the user’s true intent. As understanding users’ intentions is critical to providing appropriate cognitive aids to enhance task performance, a Hidden Markov Model (HMM) is used to examine operators’ underlying cognitive intent and identify the unobservable cognitive states. The HMM results demonstrate fundamental differences among the queuing mechanisms and reliability conditions. The findings suggest that HMM can be helpful in investigating the use of human cognitive resources under multitasking environments

A Multi-Experimental Examination of Analyzing Mouse Cursor Trajectories to Gauge Subject Uncertainty

Providing information online is pervasive in human-computer interactions. While providing information, people may deliberate their responses. However, organizations only receive the end-result of this deliberation and therefore have no contextual information surrounding the response. One type of contextual information includes knowing people’s response uncertainty while providing information. Knowing uncertainty allows organizations to weigh responses, ask follow-up questions, provide assistance, or identify problematic instructions or responses. This paper explores how mouse cursor movements may indicate uncertainty in a human-computer interaction context. Specifically, it hypothesizes how uncertainty on multiple-choice questions influences a mouse-movement statistic called area-under-the-curve (AUC). We report the result of two studies that suggest that AUC is higher when people have moderate uncertainty about an answer than if people have high or low uncertainty. The results suggest a methodology for measuring uncertainty to facilitate multi-method research and to assess data in a pragmatic setting

The Future of the Internet: Millennials Will Benefit and Suffer Due to Their Hyperconnected Lives

Presents technology stakeholders' survey responses about whether the Millennial generation's always-on connection to people and information through social media, mobile Web, and multi-tasking will be a net positive or negative by 2020. Excerpts comments

Categorical relevance judgment

In this study we aim to explore users' behaviour when assessing search results relevance based on the hypothesis of categorical thinking. In order to investigate how users categorise search engine results, we perform several experiments where users are asked to group a list of 20 search results into a number of categories, while attaching a relevance judgment to each formed category. Moreover, to determine how users change their minds over time, each experiment was repeated three times under the same conditions, with a gap of one month between rounds. The results show that on average users form 4-5 categories. Within each round the size of a category decreases with the relevance of a category. To measure the agreement between the search engine’s ranking and the users’ relevance judgments, we defined two novel similarity measures, the average concordance and the MinMax swap ratio. Similarity is shown to be the highest for the third round as the users' opinion stabilises. Qualitative analysis uncovered some interesting points, in particular, that users tended to categorise results by type and reliability of their source, and particularly, found commercial sites less trustworthy, and attached high relevance to Wikipedia when their prior domain knowledge was limited