Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/40618

Using The Mobile Application Evernote for Diagnostic Assessment to Enhance Foreign Language Proficiency

Item Summary

Title: Using The Mobile Application Evernote for Diagnostic Assessment to Enhance Foreign Language Proficiency
Authors: Ka, Jay
Instructor: Fulford, Catherine
Keywords: diagnostic language assessment
language proficiency test
collecting data
data analysis
Issue Date: 05 May 2016
Abstract: The diagnostic language assessment (DLA) is an important tool for instructors and, military linguists to enhance their language proficiency. The ultimate goal of this research project is to help military instructors use a twenty-first-century tool to assess students' proficiency and provide recommendations to enhance students' language proficiency in order to meet mission requirements. However, the lack of technology used for DLA in the classroom settings is prevalent. Currently, all military instructors use the traditional tools of paper, sticky notes, memory notes and tape recorders for DLA. The purpose of this study is to develop and evaluate the effectiveness of a web-based instructional module that teaches military language instructors on Oahu to use the Evernote web applications to collect student’s language proficiency data and securely input and transfer the data to individual student folder for DLA. Sixteen participants took part in the two-hour web-based module. Comparing the pre and post surveys, after completing the learning module, 94% of participants preferred to use Evernote web 2.0 applications for DLA in the classroom and the attitude and comfort level on using technology improved. Increased skill and confidence, improved attitude, and positive participant responses showed that the chosen theories were applicable to development. The author discussed the effeteness of the module, areas for refinement, and suggested future implementation and contribution to the field of DLA.
Description: Instructional design model
Pages/Duration: 16
URI/DOI: http://hdl.handle.net/10125/40618
Appears in Collections:LTEC 690, Spring 2016



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