Predicting Faculty Integration of Faith and Learning. Issue 3 (27th May 2017)
- Record Type:
- Journal Article
- Title:
- Predicting Faculty Integration of Faith and Learning. Issue 3 (27th May 2017)
- Main Title:
- Predicting Faculty Integration of Faith and Learning
- Authors:
- Kaul, Corina R.
Hardin, Kimberly A.
Beaujean, A. Alexander - Abstract:
- ABSTRACT: Concern regarding the secularization of Christian higher education has prompted researchers to investigate the extent that faith and learning is integrated at a faculty level and what factors might predict faculty integration (Lyon, Beaty, Parker, & Mencken, 2005 ). This research attempted to replicate Lyon et al.'s (2005 ) logistic regression model predicting faculty integration of faith using survey responses gathered as part of Phase II of the Council for Christian Colleges & Universities (CCCU) Denominational Study (Rine, Glanzer, & Davignon, 2013 ). Respondents included 2, 074 faculty from 55 institutions. The first model used in this study suggested that the most powerful predictors of faculty integration are full-time employment status, earning a degree from an institution that shares the same denominational affiliation, and a match between the faculty member's religious denominational affiliation and the institutional affiliation. A second logistic regression model added faculty academic specialization as a predictor of integration to investigate if that model was a better fit. Results suggested that religion and philosophy instructors are the most likely to integrate faith into their teaching, and professors specializing in computer science, math, and engineering were the least likely. As faculty are considered the primary influence on the integration of faith and learning, existing faculty and institutional administrators concerned with maintaining faithABSTRACT: Concern regarding the secularization of Christian higher education has prompted researchers to investigate the extent that faith and learning is integrated at a faculty level and what factors might predict faculty integration (Lyon, Beaty, Parker, & Mencken, 2005 ). This research attempted to replicate Lyon et al.'s (2005 ) logistic regression model predicting faculty integration of faith using survey responses gathered as part of Phase II of the Council for Christian Colleges & Universities (CCCU) Denominational Study (Rine, Glanzer, & Davignon, 2013 ). Respondents included 2, 074 faculty from 55 institutions. The first model used in this study suggested that the most powerful predictors of faculty integration are full-time employment status, earning a degree from an institution that shares the same denominational affiliation, and a match between the faculty member's religious denominational affiliation and the institutional affiliation. A second logistic regression model added faculty academic specialization as a predictor of integration to investigate if that model was a better fit. Results suggested that religion and philosophy instructors are the most likely to integrate faith into their teaching, and professors specializing in computer science, math, and engineering were the least likely. As faculty are considered the primary influence on the integration of faith and learning, existing faculty and institutional administrators concerned with maintaining faith in the classroom may want to consider the contributing factors discussed. … (more)
- Is Part Of:
- Christian higher education. Volume 16:Issue 3(2017)
- Journal:
- Christian higher education
- Issue:
- Volume 16:Issue 3(2017)
- Issue Display:
- Volume 16, Issue 3 (2017)
- Year:
- 2017
- Volume:
- 16
- Issue:
- 3
- Issue Sort Value:
- 2017-0016-0003-0000
- Page Start:
- 172
- Page End:
- 187
- Publication Date:
- 2017-05-27
- Subjects:
- Christian universities and colleges -- Periodicals
378.07105 - Journal URLs:
- http://www.tandfonline.com/toc/uche20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/15363759.2016.1250684 ↗
- Languages:
- English
- ISSNs:
- 1536-3759
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3181.824000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2095.xml