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Early Adopters of OER: Instructor Ad...
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Sorenson, Lars.
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Early Adopters of OER: Instructor Adoption Patterns for an Open Source Data Analytics Curriculum.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Early Adopters of OER: Instructor Adoption Patterns for an Open Source Data Analytics Curriculum./
Author:
Sorenson, Lars.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:
160 p.
Notes:
Source: Dissertation Abstracts International, Volume: 80-08(E), Section: A.
Contained By:
Dissertation Abstracts International80-08A(E).
Subject:
Educational technology. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13811913
ISBN:
9781392052990
Early Adopters of OER: Instructor Adoption Patterns for an Open Source Data Analytics Curriculum.
Sorenson, Lars.
Early Adopters of OER: Instructor Adoption Patterns for an Open Source Data Analytics Curriculum.
- Ann Arbor : ProQuest Dissertations & Theses, 2019 - 160 p.
Source: Dissertation Abstracts International, Volume: 80-08(E), Section: A.
Thesis (Ed.D.)--Northeastern University, 2019.
This study examined an initiative at the researcher's institution to provide an online, open source data analytics curriculum for courses at the university level. Semistructured interviews were conducted with seven professors of accounting at universities in the US and Canada to explore their experiences while adopting this open educational resource to teach data analytics skills and tools. Transcripts were analyzed using Interpretive Phenomenological Analysis (IPA) to identify themes. Three major themes emerged from the analysis: instructor responses to a changing professional field for which they were preparing students; adapting approaches to instruction to meet changing demand; and navigating the university's institutional environment and the marketplace of data analytics tool providers to promote diffusion of new teaching practices. These findings were considered within the context of existing literature on education technology and Diffusion of Innovations Theory (IDT) to identify opportunities for next practices and to support adoption across departments and institutions. Findings of this study suggested formalizing market research to better understand workplace demands, identifying early adopters of next practices and elevating their work, tying academic innovation to education research, and deploying existing administrative personnel to support technology adoption.
ISBN: 9781392052990Subjects--Topical Terms:
517670
Educational technology.
Early Adopters of OER: Instructor Adoption Patterns for an Open Source Data Analytics Curriculum.
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This study examined an initiative at the researcher's institution to provide an online, open source data analytics curriculum for courses at the university level. Semistructured interviews were conducted with seven professors of accounting at universities in the US and Canada to explore their experiences while adopting this open educational resource to teach data analytics skills and tools. Transcripts were analyzed using Interpretive Phenomenological Analysis (IPA) to identify themes. Three major themes emerged from the analysis: instructor responses to a changing professional field for which they were preparing students; adapting approaches to instruction to meet changing demand; and navigating the university's institutional environment and the marketplace of data analytics tool providers to promote diffusion of new teaching practices. These findings were considered within the context of existing literature on education technology and Diffusion of Innovations Theory (IDT) to identify opportunities for next practices and to support adoption across departments and institutions. Findings of this study suggested formalizing market research to better understand workplace demands, identifying early adopters of next practices and elevating their work, tying academic innovation to education research, and deploying existing administrative personnel to support technology adoption.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13811913
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