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1. Investigating the Influence of Subgoals on Learning during Search

   Urgo, Kelsey (January 2023, Dissertation)

   Search-as-learning research has emphasized the need to better support searchers when learning about complex topics online. Prior work in the learning sciences has shown that effective self-regulated learning (SRL), in which goals are a central function, is critical to improving learning outcomes. This dissertation investigates the influence of subgoals on learning during search. Two conditions were investigated: \textsc{Subgoals} and \textsc{NoSubgoals}. In the \textsc{Subgoals} condition, a tool called the Subgoal Manager was used to help searchers to develop specific subgoals associated with an overall learning-oriented search task. The influence of subgoals is explored along four dimensions: (1) learning outcomes; (2) searcher perceptions; (3) search behaviors; and (4) SRL processes. Learning outcomes were measured with two assessments, an established multiple-choice conceptual knowledge test and an open-ended summary of learning. Learning assessments were administered immediately after search and one week after search to capture learning retention. A qualitative analysis was conducted to identify the percentage of true statements on open-ended learning assessments. A think-aloud protocol was used to capture SRL processes. A second qualitative analysis was conducted to categorize SRL processes from think-aloud comments and behaviors during the search session. Findings from the dissertation suggest that subgoals improved learning during search. Additionally, it seems that subgoals helped participants to better retain what was learned one week later. Findings also suggest that SRL processes of participants in the \textsc{Subgoals} condition were more frequent and more diverse. SRL processes that were explicitly supported by the Subgoal Manager seemed to be more frequent in the \textsc{Subgoals} condition as well as SRL processes that were not explicitly supported. 

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2. The Effects of Learning Objectives on Searchers' Perceptions and Behaviors

   https://doi.org/10.1145/3409256.3409815  

   Urgo, Kelsey; Arguello, Jaime; Capra, Robert (September 2020, Proceedings of the 2020 ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR ’20))

   In recent years, the “search as learning” community has argued that search systems should be designed to support learning. We report on a lab study in which we manipulated the learning objectives associated with search tasks assigned to participants. We manipulated learning objectives by leveraging Anderson and Krathwohl’s taxonomy of learning (A&K’s taxonomy) [2], which situates learning objectives at the intersection of two orthogonal dimensions: the cognitive process and the knowledge type dimension. Participants in our study completed tasks with learning objectives that varied across three cognitive processes (apply, evaluate, and create) and three knowledge types (factual, conceptual, and procedural knowledge). We focus on the effects of the task’s cognitive process and knowledge type on participants’ pre-/post-task perceptions and search behaviors. Our results found that the three knowledge types considered in our study had a greater effect than the three cognitive processes. Specifically, conceptual knowledge tasks were perceived to be more difficult and required more search activity. We discuss implications for designing search systems that support learning. 

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3. Sector search strategies for odor trail tracking

   https://doi.org/10.1073/pnas.2107431118  

   Reddy, Gautam; Shraiman, Boris I.; Vergassola, Massimo (January 2022, Proceedings of the National Academy of Sciences)

   Ants, mice, and dogs often use surface-bound scent trails to establish navigation routes or to find food and mates, yet their tracking strategies remain poorly understood. Chemotaxis-based strategies cannot explain casting, a characteristic sequence of wide oscillations with increasing amplitude performed upon sustained loss of contact with the trail. We propose that tracking animals have an intrinsic, geometric notion of continuity, allowing them to exploit past contacts with the trail to form an estimate of where it is headed. This estimate and its uncertainty form an angular sector, and the emergent search patterns resemble a “sector search.” Reinforcement learning agents trained to execute a sector search recapitulate the various phases of experimentally observed tracking behavior. We use ideas from polymer physics to formulate a statistical description of trails and show that search geometry imposes basic limits on how quickly animals can track trails. By formulating trail tracking as a Bellman-type sequential optimization problem, we quantify the geometric elements of optimal sector search strategy, effectively explaining why and when casting is necessary. We propose a set of experiments to infer how tracking animals acquire, integrate, and respond to past information on the tracked trail. More generally, we define navigational strategies relevant for animals and biomimetic robots and formulate trail tracking as a behavioral paradigm for learning, memory, and planning. 

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4. Sounds of Health: Using Personalized Sonification Models to Communicate Health Information

   https://doi.org/10.1145/3570346  

   Clark, Matthew; Doryab, Afsaneh (December 2022, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies)

   This paper explores the feasibility of using sonification in delivering and communicating health and wellness status on personal devices. Ambient displays have proven to inform users of their health and wellness and help them to make healthier decisions, yet, little technology provides health assessments through sounds, which can be even more pervasive than visual displays. We developed a method to generate music from user preferences and evaluated it in a two-step user study. In the first step, we acquired general healthiness impressions from each user. In the second step, we generated customized melodies from music preferences in the first step to capture participants' perceived healthiness of those melodies. We deployed our surveys for 55 participants to complete on their own over 31 days. We analyzed the data to understand commonalities and differences in users' perceptions of music as an expression of health. Our findings show the existence of clear associations between perceived healthiness and different music features. We provide useful insights into how different musical features impact the perceived healthiness of music, how perceptions of healthiness vary between users, what trends exist between users' impressions, and what influences (or does not influence) a user's perception of healthiness in a melody. Overall, our results indicate validity in presenting health data through personalized music models. The findings can inform the design of behavior management applications on personal and ubiquitous devices. 

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5. Can Real-Time Gaze Sharing Help Team Collaboration? A Preliminary Examination of its Effectiveness with Pairs

   https://doi.org/10.1177/21695067231193659  

   Atweh, Jad A; Hazimeh, Rana; Riggs, Sara L (September 2023, Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Complex and dynamic domains rely on operators to collaborate on multiple tasks and cope with changes in task demands. Gaze sharing is a means of communication used to exchange visual information by allowing teammates to view each other’s gaze points on their displays. Existing work on gaze sharing focuses on relatively simple task-specific domains and no work-to-date addresses how to use gaze sharing in data-rich environments. For this study, nine pairs of participants completed a UAV search and rescue command-and-control task with three visualization techniques: no gaze sharing, gaze sharing using the real-time dot, and gaze sharing using the real-time fixation trail. Our preliminary results show that performance scores using the real-time fixation trail were statistically significantly higher than when no gaze sharing was present. This suggests that the real-time fixation trail is a promising tool to better understand operators’ strategies and could form the basis of an adaptive display. 

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