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Enhancing Conversational Interactions for Positive Learning Outcomes through Technology

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This research explores the development of technology designed to enhance conversation and support effective participation. By focusing on human learning and wellbeing, the study shows that when students receive interactive support, they achieve up to 1.25 standard deviations more in their learning outcomes—equivalent to a full letter grade increase. Over seven years, positive results have informed the design of dialogue agents that foster collaboration and personalized support among students while enhancing their conversational skills.

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Enhancing Conversational Interactions for Positive Learning Outcomes through Technology

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Presentation Transcript

  1. Discourse Analytics Carolyn PensteinRosé Language Technologies Institute and Human-Computer Interaction Institute

  2. Developing technology capable of shaping conversation and supporting effective participation in conversation to achieve positive impact on… Human learning Health Wellbeing

  3. Automatic Analysis Of Conversation Positive Learning Outcomes Conversational Interventions

  4. Computer Supported Collaborative Learning ** Students learn up to 1.25 standard deviations more when interactive support is provided in the environment. (more than a full letter grade!)

  5. 7 Years of Positive Results • Foundational study: students work with a partner and dialogue agent for support Learn 1.24 s.d.more than individuals without support (Kumar et al., 2007a) • Selected results inform iterative design of agent behavior • Personalized agents increase supportiveness and help exchange between students (Kumar et al., 2007b) • Agents are more effective when students have control over timing of the interaction (Chaudhuri et al., 2008; Chaudhuri et al., 2009) • Agents that employ Balesian social strategies are more effective than those that do not (Kumar et al., 2010; Ai et al., 2010) • Students are sensitive to agent rhetorical strategies such as displayed bias (Ai et al., 2010), displayed openness to alternative perspectives (Kumar et al., 2011), and targeted elicitation (Howley et al., 2012) • Bazaar architecture enables efficient, principle based agent development (Kumar & Rosé, 2011; Adamson & Rosé, 2012)

  6. Sociolinguistics Language Use Computational Models Of Discourse Analysis Discourse Analysis Machine Learning Language And Identity Applied Statistics Multi- Level Modeling

  7. SouFLé Framework (Howley et al., 2013) Authority Transactive Knowledge Integration Person Person Engagement Engagement Authority

  8. Easy UI for: • Feature Extraction • Model Building • Error Analysis • Data Structuring • Free/open-source for easy integration with existing code • Modular for fast prototyping and plugin writing in Java www.lightsidelabs.com

  9. Thanks!

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