The Experts below are selected from a list of 24291 Experts worldwide ranked by ideXlab platform
Sharon Oviatt - One of the best experts on this subject based on the ideXlab platform.
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ICMI - Dynamic Adaptive Gesturing Predicts Domain Expertise in Mathematics
2019 International Conference on Multimodal Interaction, 2019Co-Authors: Abishek Sriramulu, Jionghao Lin, Sharon OviattAbstract:Embodied Cognition theorists believe that mathematics thinking is embodied in physical activity, like gesturing while explaining math solutions. This research asks the question whether Expertise in mathematics can be detected by analyzing students’ rate and type of manual gestures. The results reveal several unique findings, including that math experts reduced their total rate of gesturing by 50%, compared with non-experts. They also dynamically increased their rate of gesturing on harder problems. Although experts reduced their rate of gesturing overall, they selectively produced 62% more iconic gestures. Iconic gestures are strategic because they assist with retaining spatial information in working memory, so that inferences can be extracted to support correct problem solving. The present results on representation-level gesture patterns are convergent with recent findings on signal-level handwriting, while also contributing a causal understanding of how and why experts adapt their manual activity during problem solving.
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dynamic adaptive gesturing predicts Domain Expertise in mathematics
International Conference on Multimodal Interfaces, 2019Co-Authors: Abishek Sriramulu, Jionghao Lin, Sharon OviattAbstract:Embodied Cognition theorists believe that mathematics thinking is embodied in physical activity, like gesturing while explaining math solutions. This research asks the question whether Expertise in mathematics can be detected by analyzing students’ rate and type of manual gestures. The results reveal several unique findings, including that math experts reduced their total rate of gesturing by 50%, compared with non-experts. They also dynamically increased their rate of gesturing on harder problems. Although experts reduced their rate of gesturing overall, they selectively produced 62% more iconic gestures. Iconic gestures are strategic because they assist with retaining spatial information in working memory, so that inferences can be extracted to support correct problem solving. The present results on representation-level gesture patterns are convergent with recent findings on signal-level handwriting, while also contributing a causal understanding of how and why experts adapt their manual activity during problem solving.
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Dynamic Handwriting Signal Features Predict Domain Expertise
ACM Transactions on Interactive Intelligent Systems, 2018Co-Authors: Sharon Oviatt, K. Hang, Jianlong Zhou, Fang ChenAbstract:As commercial pen-centric systems proliferate, they create a parallel need for analytic techniques based on dynamic writing. Within educational applications, recent empirical research has shown that signal-level features of students’ writing, such as stroke distance, pressure and duration, are adapted to conserve total energy expenditure as they consolidate Expertise in a Domain. The present research examined how accurately three different machine-learning algorithms could automatically classify users’ Domain Expertise based on signal features of their writing, without any content analysis. Compared with an unguided machine-learning classification accuracy of 71%, hybrid methods using empirical-statistical guidance correctly classified 79–92% of students by their Domain Expertise level. In addition to improved accuracy, the hybrid approach contributed a causal understanding of prediction success and generalization to new data. These novel findings open up opportunities to design new automated learning analytic systems and student-adaptive educational technologies for the rapidly expanding sector of commercial pen systems.
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spoken interruptions signal productive problem solving and Domain Expertise in mathematics
International Conference on Multimodal Interfaces, 2015Co-Authors: Sharon Oviatt, Jianlong Zhou, Kevin Hang, Fang ChenAbstract:Prevailing social norms prohibit interrupting another person when they are speaking. In this research, simultaneous speech was investigated in groups of students as they jointly solved math problems and peer tutored one another. Analyses were based on the Math Data Corpus, which includes ground-truth performance coding and speech transcriptions. Simultaneous speech was elevated 120-143% during the most productive phase of problem solving, compared with matched intervals. It also was elevated 18-37% in students who were Domain experts, compared with non-experts. Qualitative analyses revealed that experts differed from non-experts in the function of their interruptions. Analysis of these functional asymmetries produced nine key behaviors that were used to identify the dominant math expert in a group with 95-100% accuracy in three minutes. This research demonstrates that overlapped speech is a marker of group problem-solving progress and Domain Expertise. It provides valuable information for the emerging field of learning analytics.
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ICMI - Spoken Interruptions Signal Productive Problem Solving and Domain Expertise in Mathematics
Proceedings of the 2015 ACM on International Conference on Multimodal Interaction - ICMI '15, 2015Co-Authors: Sharon Oviatt, Jianlong Zhou, Kevin Hang, Fang ChenAbstract:Prevailing social norms prohibit interrupting another person when they are speaking. In this research, simultaneous speech was investigated in groups of students as they jointly solved math problems and peer tutored one another. Analyses were based on the Math Data Corpus, which includes ground-truth performance coding and speech transcriptions. Simultaneous speech was elevated 120-143% during the most productive phase of problem solving, compared with matched intervals. It also was elevated 18-37% in students who were Domain experts, compared with non-experts. Qualitative analyses revealed that experts differed from non-experts in the function of their interruptions. Analysis of these functional asymmetries produced nine key behaviors that were used to identify the dominant math expert in a group with 95-100% accuracy in three minutes. This research demonstrates that overlapped speech is a marker of group problem-solving progress and Domain Expertise. It provides valuable information for the emerging field of learning analytics.
R. Manaszewicz - One of the best experts on this subject based on the ideXlab platform.
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The Role of Domain Expertise in Smart, User-Sensitive, Health Information Portals
2009 42nd Hawaii International Conference on System Sciences, 2009Co-Authors: J. Evans, R. ManaszewiczAbstract:The provision of consumer health information portals acting as gateways to online resources is one strategy for enabling patients to be better informed and engaged in healthcare decision making and support. These portals need to be both smart and user sensitive, able to identify and select resources of relevance to a user community, describe them in ways that facilitate user assessments of quality and relevance, and provide efficient and effective search functionality that can be tailored to individual information needs. The Domain Expertise required to select and describe resources in this manner is a key to the efficacy of such portals, with their viability dependent on the sustainability and scalability of their resource identification, selection and description processes. This paper reports on a study of the Domain Expertise involved with the provision of an information portal for a breast cancer community undertaken as part of the Smart Information Portal Project.
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HICSS - The Role of Domain Expertise in Smart, User-Sensitive, Health Information Portals
2009 42nd Hawaii International Conference on System Sciences, 2009Co-Authors: J. Evans, R. Manaszewicz, Jue XieAbstract:The provision of consumer health information portals acting as gateways to online resources is one strategy for enabling patients to be better informed and engaged in healthcare decision making and support. These portals need to be both smart and user sensitive, able to identify and select resources of relevance to a user community, describe them in ways that facilitate user assessments of quality and relevance, and provide efficient and effective search functionality that can be tailored to individual information needs. The Domain Expertise required to select and describe resources in this manner is a key to the efficacy of such portals, with their viability dependent on the sustainability and scalability of their resource identification, selection and description processes. This paper reports on a study of the Domain Expertise involved with the provision of an information portal for a breast cancer community undertaken as part of the Smart Information Portal Project.
J. Evans - One of the best experts on this subject based on the ideXlab platform.
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The Role of Domain Expertise in Smart, User-Sensitive, Health Information Portals
2009 42nd Hawaii International Conference on System Sciences, 2009Co-Authors: J. Evans, R. ManaszewiczAbstract:The provision of consumer health information portals acting as gateways to online resources is one strategy for enabling patients to be better informed and engaged in healthcare decision making and support. These portals need to be both smart and user sensitive, able to identify and select resources of relevance to a user community, describe them in ways that facilitate user assessments of quality and relevance, and provide efficient and effective search functionality that can be tailored to individual information needs. The Domain Expertise required to select and describe resources in this manner is a key to the efficacy of such portals, with their viability dependent on the sustainability and scalability of their resource identification, selection and description processes. This paper reports on a study of the Domain Expertise involved with the provision of an information portal for a breast cancer community undertaken as part of the Smart Information Portal Project.
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HICSS - The Role of Domain Expertise in Smart, User-Sensitive, Health Information Portals
2009 42nd Hawaii International Conference on System Sciences, 2009Co-Authors: J. Evans, R. Manaszewicz, Jue XieAbstract:The provision of consumer health information portals acting as gateways to online resources is one strategy for enabling patients to be better informed and engaged in healthcare decision making and support. These portals need to be both smart and user sensitive, able to identify and select resources of relevance to a user community, describe them in ways that facilitate user assessments of quality and relevance, and provide efficient and effective search functionality that can be tailored to individual information needs. The Domain Expertise required to select and describe resources in this manner is a key to the efficacy of such portals, with their viability dependent on the sustainability and scalability of their resource identification, selection and description processes. This paper reports on a study of the Domain Expertise involved with the provision of an information portal for a breast cancer community undertaken as part of the Smart Information Portal Project.
Jue Xie - One of the best experts on this subject based on the ideXlab platform.
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HICSS - The Role of Domain Expertise in Smart, User-Sensitive, Health Information Portals
2009 42nd Hawaii International Conference on System Sciences, 2009Co-Authors: J. Evans, R. Manaszewicz, Jue XieAbstract:The provision of consumer health information portals acting as gateways to online resources is one strategy for enabling patients to be better informed and engaged in healthcare decision making and support. These portals need to be both smart and user sensitive, able to identify and select resources of relevance to a user community, describe them in ways that facilitate user assessments of quality and relevance, and provide efficient and effective search functionality that can be tailored to individual information needs. The Domain Expertise required to select and describe resources in this manner is a key to the efficacy of such portals, with their viability dependent on the sustainability and scalability of their resource identification, selection and description processes. This paper reports on a study of the Domain Expertise involved with the provision of an information portal for a breast cancer community undertaken as part of the Smart Information Portal Project.
Thomas G Kannampallil - One of the best experts on this subject based on the ideXlab platform.
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exploiting knowledge in the head and knowledge in the social web effects of Domain Expertise on exploratory search in individual and social search environments
Human Factors in Computing Systems, 2010Co-Authors: Ruogu Kang, Thomas G KannampallilAbstract:Our study compared how experts and novices performed exploratory search using a traditional search engine and a social tagging system. As expected, results showed that social tagging systems could facilitate exploratory search for both experts and novices. We, however, also found that experts were better at interpreting the social tags and generating search keywords, which made them better at finding information in both interfaces. Specifically, experts found more general information than novices by better interpretation of social tags in the tagging system; and experts also found more Domain-specific information by generating more of their own keywords. We found a dynamic interaction between knowledge-in-the-head and knowledge-in-the-social-web that although information seekers are more and more reliant on information from the social Web, Domain Expertise is still important in guiding them to find and evaluate the information. Implications on the design of social search systems that facilitate exploratory search are also discussed.
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CHI - Exploiting knowledge-in-the-head and knowledge-in-the-social-web: effects of Domain Expertise on exploratory search in individual and social search environments
Proceedings of the 28th international conference on Human factors in computing systems - CHI '10, 2010Co-Authors: Ruogu Kang, Thomas G KannampallilAbstract:Our study compared how experts and novices performed exploratory search using a traditional search engine and a social tagging system. As expected, results showed that social tagging systems could facilitate exploratory search for both experts and novices. We, however, also found that experts were better at interpreting the social tags and generating search keywords, which made them better at finding information in both interfaces. Specifically, experts found more general information than novices by better interpretation of social tags in the tagging system; and experts also found more Domain-specific information by generating more of their own keywords. We found a dynamic interaction between knowledge-in-the-head and knowledge-in-the-social-web that although information seekers are more and more reliant on information from the social Web, Domain Expertise is still important in guiding them to find and evaluate the information. Implications on the design of social search systems that facilitate exploratory search are also discussed.