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Are French Fries And Grades Bad For You? Conflicting Evidence On How K 12 Teachers Search In A K 12 Digital Library
Author(s) -
René Reitsma,
Paul Klenk,
Malinda Zarske,
Jacquelyn Sullivan
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--16838
Subject(s) - digital library , relevance (law) , order (exchange) , computer science , world wide web , interface (matter) , library science , mathematics education , information retrieval , psychology , political science , art , business , literature , poetry , finance , bubble , maximum bubble pressure method , law , parallel computing
The TeachEngineering digital library provides teacher-tested, standards-based engineering content for K-12 teachers to use in science and math classrooms. Since its release in 2005, TeachEngineering has experienced significant growth in users and contributors; data on this growth is presented. The TeachEngineering team─researchers at the University of Colorado at Boulder, Oregon State University, Duke University, Colorado School of Mines, and Worcester Polytechnic Institute─continues to research its search functions and user interface in order to ensure that it meets the needs of its intended users, K-12 teachers. Empirical evidence from an experimental study on the dimensions of alignment between digital K-12 lesson materials and education standards, however, contradicts that of the observed search behavior of patrons of TeachEngineering. Whereas the experiment convincingly shows that grade band information does not add to the teaching materials’ relevance for an educational standard, observed patrons’ searching patterns show ample evidence of grade band-based searches. In this paper, we offer that although grade band-based searches should perhaps be avoided because they improperly bias search results, they are such a prominent feature in the actual use of digital libraries that as designers we must support them while mitigating the risk of unfortunate search bias. As a possible solution, we suggest supporting grade-based searches as well as offering query expansion by widening the grade band.

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