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Dive into the research topics where Doris B. Chin is active.

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Featured researches published by Doris B. Chin.


artificial intelligence in education | 2017

Assessing Whether Students Seek Constructive Criticism: The Design of an Automated Feedback System for a Graphic Design Task

Maria Cutumisu; Kristen Pilner Blair; Doris B. Chin; Daniel L. Schwartz

We introduce a choice-based assessment strategy that measures students’ choices to seek constructive feedback and to revise their work. We present the feedback system of a game we designed to assess whether students choose positive or negative feedback and choose to revise their posters in the context of a poster design task, where they learn graphic design principles from feedback. We then describe an empirical study that sampled one hundred and six students from a US middle school to evaluate the feedback system. We make the following contributions: (1) describe the design and implementation of a novel feedback system embedded in an assessment game, Posterlet, (2) outline an approach to analyze graphic design principles automatically to provide contextual feedback in a novel poster design domain, (3) show that choices to seek negative feedback and to revise correlate with in-game performance, and most importantly, (4) show that choices correlate with in-school achievement: the choice to revise correlated with both in-school performance measures (Science and Mathematics grades), while the choice to seek negative feedback correlated with students’ prior standardized scores in Mathematics.


2012 PHYSICS EDUCATION RESEARCH CONFERENCE | 2013

Applying cognitive developmental psychology to middle school physics learning: The rule assessment method

Nicole R. Hallinen; Min Chi; Doris B. Chin; Joe Prempeh; Kristen Pilner Blair; Daniel L. Schwartz

Cognitive developmental psychology often describes children’s growing qualitative understanding of the physical world. Physics educators may be able to use the relevant methods to advantage for characterizing changes in students’ qualitative reasoning. Siegler developed the “rule assessment” method for characterizing levels of qualitative understanding for two factor situations (e.g., volume and mass for density). The method assigns children to rule levels that correspond to the degree they notice and coordinate the two factors. Here, we provide a brief tutorial plus a demonstration of how we have used this method to evaluate instructional outcomes with middle-school students who learned about torque, projectile motion, and collisions using different instructional methods with simulations.


Journal of Educational Psychology | 2011

Practicing versus inventing with contrasting cases: The effects of telling first on learning and transfer.

Daniel L. Schwartz; Catherine C. Chase; Marily A. Oppezzo; Doris B. Chin


Journal of Science Education and Technology | 2009

Teachable Agents and the Protege Effect: Increasing the Effort towards Learning.

Catherine C. Chase; Doris B. Chin; Marily A. Oppezzo; Daniel L. Schwartz


Educational Technology Research and Development | 2010

Preparing students for future learning with Teachable Agents

Doris B. Chin; Ilsa M. Dohmen; Britte H. Cheng; Marily A. Oppezzo; Catherine C. Chase; Daniel L. Schwartz


Archive | 2008

Interactive Metacognition: Monitoring and Regulating a Teachable Agent

Daniel L. Schwartz; Catherine C. Chase; Doris B. Chin; Marily A. Oppezzo; Henry Kwong; Sandra Y. Okita; Rod D. Roscoe; Hoyeong Jeong; John Wagster; Gautam Biswas


IEEE Transactions on Learning Technologies | 2013

Young Children Can Learn Scientific Reasoning with Teachable Agents

Doris B. Chin; Ilsa M. Dohmen; Daniel L. Schwartz


Journal of learning Analytics | 2015

Posterlet: A Game-Based Assessment of Children's Choices to Seek Feedback and to Revise.

Maria Cutumisu; Kristen Pilner Blair; Doris B. Chin; Daniel L. Schwartz


2015 ASEE Annual Conference & Exposition | 2015

Guardian Angels of Our Better Nature: Finding Evidence of the Benefits of Design Thinking

Luke David Conlin; Doris B. Chin; Kristen Pilner Blair; Maria Cutumisu; Daniel L. Schwartz


Technology, Knowledge, and Learning | 2016

Got Game? A Choice-Based Learning Assessment of Data Literacy and Visualization Skills

Doris B. Chin; Kristen Pilner Blair; Daniel L. Schwartz

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Min Chi

North Carolina State University

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