Modeling the Instructional Effectiveness of Responsible Conduct of Research Education: A Meta-Analytic Path-Analysis

Logan L. Watts; Tyler J. Mulhearn; Kelsey E. Medeiros; Logan M. Steele; Shane Connelly; Michael D. Mumford

doi:10.1080/10508422.2016.1247354

Modeling the Instructional Effectiveness of Responsible Conduct of Research Education: A Meta-Analytic Path-Analysis

Logan L. Watts
, Tyler J. Mulhearn
, Kelsey E. Medeiros
, Logan M. Steele
, Shane Connelly
, Michael D. Mumford

Management Department

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

Predictive modeling in education draws on data from past courses to forecast the effectiveness of future courses. The present effort sought to identify such a model of instructional effectiveness in scientific ethics. Drawing on data from 235 courses in the responsible conduct of research (RCR), structural equation modeling techniques were used to test a predictive model of RCR course effectiveness. Fit statistics indicated the model fit the data well, with the instructional characteristics included in the model explaining approximately 85% of the variance in RCR instructional effectiveness. Implications for using the model to develop and improve future RCR courses are discussed.

Original language	English
Pages (from-to)	632-650
Number of pages	19
Journal	Ethics and Behavior
Volume	27
Issue number	8
DOIs	https://doi.org/10.1080/10508422.2016.1247354
State	Published - 17 Nov 2017

Keywords

ethics training
instructional effectiveness
predictive modeling
responsible conduct of research

Access to Document

10.1080/10508422.2016.1247354

Cite this

@article{2bc0acebc5a544f49093ab422fa9846a,

title = "Modeling the Instructional Effectiveness of Responsible Conduct of Research Education: A Meta-Analytic Path-Analysis",

abstract = "Predictive modeling in education draws on data from past courses to forecast the effectiveness of future courses. The present effort sought to identify such a model of instructional effectiveness in scientific ethics. Drawing on data from 235 courses in the responsible conduct of research (RCR), structural equation modeling techniques were used to test a predictive model of RCR course effectiveness. Fit statistics indicated the model fit the data well, with the instructional characteristics included in the model explaining approximately 85\% of the variance in RCR instructional effectiveness. Implications for using the model to develop and improve future RCR courses are discussed.",

keywords = "ethics training, instructional effectiveness, predictive modeling, responsible conduct of research",

author = "Watts, \{Logan L.\} and Mulhearn, \{Tyler J.\} and Medeiros, \{Kelsey E.\} and Steele, \{Logan M.\} and Shane Connelly and Mumford, \{Michael D.\}",

note = "Publisher Copyright: Copyright {\textcopyright} 2017 Taylor \& Francis Group, LLC.",

year = "2017",

month = nov,

day = "17",

doi = "10.1080/10508422.2016.1247354",

language = "English",

volume = "27",

pages = "632--650",

number = "8",

}

TY - JOUR

T1 - Modeling the Instructional Effectiveness of Responsible Conduct of Research Education

T2 - A Meta-Analytic Path-Analysis

AU - Watts, Logan L.

AU - Mulhearn, Tyler J.

AU - Medeiros, Kelsey E.

AU - Steele, Logan M.

AU - Connelly, Shane

AU - Mumford, Michael D.

PY - 2017/11/17

Y1 - 2017/11/17

N2 - Predictive modeling in education draws on data from past courses to forecast the effectiveness of future courses. The present effort sought to identify such a model of instructional effectiveness in scientific ethics. Drawing on data from 235 courses in the responsible conduct of research (RCR), structural equation modeling techniques were used to test a predictive model of RCR course effectiveness. Fit statistics indicated the model fit the data well, with the instructional characteristics included in the model explaining approximately 85% of the variance in RCR instructional effectiveness. Implications for using the model to develop and improve future RCR courses are discussed.

AB - Predictive modeling in education draws on data from past courses to forecast the effectiveness of future courses. The present effort sought to identify such a model of instructional effectiveness in scientific ethics. Drawing on data from 235 courses in the responsible conduct of research (RCR), structural equation modeling techniques were used to test a predictive model of RCR course effectiveness. Fit statistics indicated the model fit the data well, with the instructional characteristics included in the model explaining approximately 85% of the variance in RCR instructional effectiveness. Implications for using the model to develop and improve future RCR courses are discussed.

KW - ethics training

KW - instructional effectiveness

KW - predictive modeling

KW - responsible conduct of research

UR - https://www.scopus.com/pages/publications/84994588724

U2 - 10.1080/10508422.2016.1247354

DO - 10.1080/10508422.2016.1247354

M3 - Article

AN - SCOPUS:84994588724

SN - 1050-8422

VL - 27

SP - 632

EP - 650

JO - Ethics and Behavior

JF - Ethics and Behavior

IS - 8

ER -

Modeling the Instructional Effectiveness of Responsible Conduct of Research Education: A Meta-Analytic Path-Analysis

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this