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Instructional Stance as Indicated by Words: A Lexicometrical Analysis of Teacher Usage of an Inquiry-Based Technological Tool in High School Classrooms

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2013 ASEE International Forum


Atlanta, Georgia

Publication Date

June 22, 2013

Start Date

June 22, 2013

End Date

June 22, 2013

Conference Session

Track 3 - Session II - Faculty Development

Tagged Topic

Faculty Development

Page Count


Page Numbers

21.34.1 - 21.34.15



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Paper Authors


Danielle Marie Dowling Tufts Center for Engineering Education and Outreach

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After nearly 20 years as a journalist, Danielle Dowling decided to return to school to earn a second bachelor's degree in physics, which she received in 2011 from Hunter College in New York City. Soon after, she started her master's degree in science education at Tufts University. While pursuing her master's, she became involved with the Center for Engineering Education and Outreach, where she is currently working on the InterLACE Project, which has been developing a Web-based platform that helps facilitate physics instruction in high school classrooms. In the future, Danielle would like to continue exploring ways that technology can enhance physics education.

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Morgan M Hynes Arizona State University

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Instructional Stance as Indicated by Words: A Lexicometrical Analysis of Teacher Usage of an Inquiry-Based Technological Tool in High School Classrooms  During the first year of the Interactive Learning and Collaboration Environment (InterLACE)Project, we designed a Web-based technological tool with high school physics and engineeringteachers for use in their classrooms and engaged them in professional development activities thatcentered on inquiry instruction to help them maximize the success of that tool when it debuted inthe spring of 2012. Called the Thought Cloud, the tool allows teachers to upload questions thatstudents can view and answer through any Internet-connected device (desktop, laptop, tablet,etc.); the students’ posts are then displayed on a centrally located screen to promote discussionand collective sense-making and to serve as a virtual public work space. Since words constitute alarge share of the data that the Thought Cloud collects, we felt that lexicometry, a relatively newform of statistical textual analysis, would be a good way to examine just how our teachers usedthe tool. Through lexicometry, we conducted an exploration of the respective vocabularies, orlexica, that each of our teachers employed to construct their questions in order to see whatpatterns emerged within the aggregate of these lexica, or corpus, and to determine what factorsmight have shaped these patterns and if they indicate a teacher’s particular instructional stance—be it a traditional lecture style, an inquiry-based approach, or something in between. In doing so,we have defined three lexical categories—content-centric, process-oriented, and student-centric—and found that the teachers who used the tool the most tended to employ words thatwere student-centric, or focused on evoking student reasoning, and those who used the tool leastfavored words that were content-centric, or intended to merely transmit information. A closerexamination of the corpus revealed that this link between lack of use and content-centric lexicadoes not necessarily indicate an aversion to inquiry instruction but rather the pedagogical goalsthe teachers had set when using the Thought Cloud in their classrooms. These results haveprovided us with valuable insight into the instructional stances teachers take when using our tool;therefore, we believe that incorporating lexicometry into future analyses can serve as a sort ofdiagnostic metric that we can use to inform our professional development activities in thecoming years.

Dowling, D. M., & Hynes, M. M. (2013, June), Instructional Stance as Indicated by Words: A Lexicometrical Analysis of Teacher Usage of an Inquiry-Based Technological Tool in High School Classrooms Paper presented at 2013 ASEE International Forum, Atlanta, Georgia. 10.18260/1-2--17239

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