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Browsing by Author "Cleary, Anne M., committee member"

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    A work-life balance training intervention: motivating training transfer
    (Colorado State University. Libraries, 2019) Cave, Kelly A., author; Fisher, Gwenith G., advisor; Cleary, Anne M., committee member; Kraiger, Kurt, committee member; Rosecrance, John C., committee member
    Organizations are becoming increasingly aware of the consequences poor work-life balance can have on employees, thus encouraging many to seek solutions to reduce its negative effects. Current initiatives mainly focus on offering alternative work arrangements or improving family-supportive supervisor behaviors. Surprisingly, no studies to date have investigated the effectiveness of individual-level training programs that aim to improve employees' work-life balance skills. Using a two-between one-within design, the present study evaluates the effectiveness of a goal-setting manipulation on training transfer. Results show a significant increase in reported work-life balance between 30 days and 60 days post training. Although no significant effects for self-efficacy and goal-setting are seen, it is worth noting the effect sizes are large. Additionally, post hoc analyses indicate a significant effect of self-efficacy and goal-setting on transfer after controlling for number of children. Finally, post-training attitudes (i.e. intentions to improve work-life balance, motivation to transfer, and affective reactions towards the training) were found to predict transfer. This study contributes to practice by investigating the effectiveness of a work-life balance goal-setting manipulation on training transfer. It also makes an academic contribution by further investigating the mechanisms underlying why training is effective.
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    An investigation of the basis of judgments of remembering and knowing (JORKs)
    (Colorado State University. Libraries, 2012) Soderstrom, Nicholas C., author; Rhodes, Matthew G., advisor; Cleary, Anne M., committee member; Davalos, Deana B., committee member; Rickey, Dawn, committee member
    Previous research indicates that prospective metamemory accuracy can be improved if participants are asked to monitor whether contextual details will be remembered or not (i.e., judgments of remembering and knowing; JORKs), as opposed to monitoring confidence (i.e., judgments of learning; JOLs), an important finding given that accurate memory monitoring has been linked to effective learning. Three experiments investigated whether the advantage for JORK is due to these judgments being based more on retrieval processes than JOLs. Experiment 1 showed that JORKs resemble retrospective confidence judgments (RCJs)--judgments known to be based on retrieval processes--in some ways but not in others. Experiment 2 demonstrated that JORKs benefit less from a delay than JOLs when judgments are made under some circumstances but not others, and Experiment 3 showed that JORKs are less susceptible to a manipulation of encoding fluency than JOLs. Thus, overall, the results provide mixed support for the idea that JORKs are more reliant on retrieval processes than JOLs, reinforcing the need for future research on this topic.
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    Process estimates of recollection and familiarity in working memory and episodic memory
    (Colorado State University. Libraries, 2012) Loaiza-Kois, Vanessa Maria, author; Rhodes, Matthew G., advisor; Cleary, Anne M., committee member; Kraiger, Kurt, committee member; Diehl, Manfred, committee member
    Working memory is consistently shown to be related to episodic memory, but the underlying processes that contribute to this relationship are poorly understood. The following dissertation outlines a study which investigated the relationship between working memory and episodic memory, with particular regard to the contribution of familiarity and recollection processes to both constructs. Updating measures were also included to examine the potential mediating effects of updating on the relationship between working memory and episodic memory. Measurement models of both task performance and process estimates indicated a three-factor solution, with separate working memory, updating, and episodic memory factors. Such findings suggest that working memory, updating, and episodic memory are related but distinguishable constructs at the latent level of both task and process estimate.
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    Robust gesture detection for multimodal problem solving
    (Colorado State University. Libraries, 2024) VanderHoeven, Hannah G., author; Blanchard, Nathaniel, advisor; Krishnaswamy, Nikhil, advisor; Cleary, Anne M., committee member
    Throughout various collaborative problem solving (CPS) tasks, multiple different communicative modalities may be used by participants as they communicate with each other to work towards some goal. The ability to recognize and act on these modalities is vital for a multimodal AI agent to effectively interact with humans in a meaningful way. Potential modalities of interest might include, speech, gesture, action, pose, facial expression, and object positions in three dimensional space. As AI becomes move commonplace in various collaborative environments, there is a lot of potential to use an agent to help support learning, training and understanding of how small groups work together to complete CPS tasks. Designing a well rounded system to best understand small group interactions, multiple different modalities need to be supported. Gesture is one of many important features to consider in multimodal design. Robust gesture recognition is a key component of multimodal language understanding in addition to human-computer interaction. Most vision based approaches for gesture recognition focus on static standalone gestures that are identifiable in a single video frame. In CPS tasks, more complex gestures made up of multiple "phases" are more likely to exist. For instance deixis, or pointing, as it is used to indicate objects and referents in a scene. In this thesis, I present a novel method for robust gesture detection based on gesture phase semantics. This method is competitive with many state of the art computer vision approaches while being faster to train on annotated data. I also present various applications of this method to utilize pointing detection in a real-world collaborative task, and I discuss the importance of robust gesture detection as an important feature in multimodal agent design in further depth.
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    Three types of sensory gating: exploring interrelationships, individual differences, and implications
    (Colorado State University. Libraries, 2010) Yadon, Carly Ann, author; Davies, Patricia L., advisor; Nerger, Janice L., advisor; Anderson, Charles W., committee member; Cleary, Anne M., committee member
    The primary purpose of this dissertation was to determine how information is selectively processed in the brain through sensory gating mechanisms. Filtering, habituation, and orienting are three types of sensory gating that have never been investigated together in the same study. Although it has been well established that sensory gating is abnormal in many clinical groups, there remains a fundamental lack of understanding regarding the mechanisms of gating. For example, the functional significance of sensory gating, as well as how different types of sensory gating are related to basic brain processes and to each other, is poorly understood. Using an event-related potential (ERP) paradigm, I measured P50, N100, and P200 filtering, habituation, and orienting and administered a sequence of neuropsychological measures of attention to forty-two healthy adults. I found that filtering, orienting, and habituation and the three ERP components had different patterns of results, suggesting that the three paradigms measured distinct types of sensory gating and that gating is a multistage process. For all three types of sensory gating, higher-level attention tasks tended to predict gating responses better than lower-level attention tasks. This dissertation demonstrated that sensory gating has functional importance and these three gating paradigms seem to reflect different types of gating that should be explored in their own right.
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    Using eye gaze to automatically identify familiarity
    (Colorado State University. Libraries, 2024) Castillon, Iliana, author; Blanchard, Nathaniel, advisor; Sreedharan, Sarath, committee member; Cleary, Anne M., committee member
    Understanding internal cognitive states, such as the sensation of familiarity, is crucial not only in the realm of human perception but also in enhancing interactions with artificial intelligence. One such state is the experience of familiarity, a fundamental aspect of human perception that often manifests as an intuitive recognition of faces or places. Automatically identifying cognitive experiences could pave the way for more nuance in human-AI interaction. While other works have shown the feasibility of automatically identifying other internal cognitive states like mind wandering using eye gaze features, the automatic detection of familiarity remains largely unexplored. In this work, we employed a paradigm from cognitive psychology to induce feelings of familiarity. Then, we trained machine learning models to automatically detect familiarity using eye gaze measurements, both in experiments with traditional computer use (e.g., eye tracker attached to monitor) and in virtual reality settings, in a participant independent manner. Familiarity was detected with a Cohen's kappa value, a measurement of accuracy corrected for random guessing, of 0.22 and 0.21, respectively. This work showcases the feasibility of automatically identifying feelings of familiarity and opens the door to exploring automated familiarity detection in other contexts, such as students engaged with a learning task while interacting with an intelligent tutoring system.