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Exploration of Predictors for Korean Teacher Job Satisfaction via a Machine Learning Technique, Group Mnet.

ABSTRACT: Despite the high academic achievements of Korean students in international comparison studies, their teachers' job satisfaction remains below the Organization for Economic Co-operation and Development (OECD) average. As job satisfaction is one of the major factors affecting student achievement as well as student and teacher retention, the identification of the most important satisfaction predictors is crucial. The current study analyzed data from the OECD 2013 Teaching and Learning International Survey (TALIS) via machine learning. In particular, group Mnet (a penalized regression method) was employed in order to consider hundreds of TALIS predictors in one statistical model. Specifically, this study repeated 100 times of variable selection after random data-splitting as well as cross-validation, and presented predictors selected 50% of the time or more. As a result, 18 predictors were identified out of 558, including variables relating to collaborative school climates and teacher self-efficacy, which was consistent with previous research. Newly found variables to teacher job satisfaction included items about teacher feedback, participatory school climates, and perceived barriers to professional development. Suggestions and future research topics are discussed.

SUBMITTER: Yoo JE

PROVIDER: S-EPMC7088446 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Exploration of Predictors for Korean Teacher Job Satisfaction via a Machine Learning Technique, Group Mnet.

Yoo Jin Eun JE Rho Minjeong M

Frontiers in psychology 20200313

Despite the high academic achievements of Korean students in international comparison studies, their teachers' job satisfaction remains below the Organization for Economic Co-operation and Development (OECD) average. As job satisfaction is one of the major factors affecting student achievement as well as student and teacher retention, the identification of the most important satisfaction predictors is crucial. The current study analyzed data from the OECD 2013 Teaching and Learning International ...[more]

PMID: 32231629

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Project description:A shortage of competent health-care providers is a major contributor to poor quality health care in sub-Saharan Africa. To increase the retention of skilled health-care providers, we need to understand which factors make them feel satisfied with their work and want to stay in their job. This study investigates the relative contribution of provider, facility and contextual factors to job satisfaction and intention to stay on the job among health-care providers who performed obstetric care in Uganda and Zambia. This study was a secondary analysis of data from a maternal and newborn health program implementation evaluation in Uganda and Zambia. Using a Likert scale, providers rated their job satisfaction and intention to stay in their job. Predictors included gender, cadre, satisfaction with various facility resources and country. We used the Shapley and Owen decomposition of R2 method to estimate the variance explained by individual factors and groups of factors, adjusting for covariates at the facility and provider levels. Of the 1134 providers included in the study, 68.3% were female, 32.4% were nurses and 77.1% worked in the public sector. Slightly more than half (52.3%) of providers were strongly satisfied with their job and 42.8% strongly agreed that they would continue to work at their facility for some time. A group of variables related to facility management explained most of the variance in both job satisfaction (37.6%) and intention to stay (43.1%). Among these, the most important individual variables were satisfaction with pay (20.57%) for job satisfaction and opinions being respected in the workplace (17.52%) for intention to stay. Doctors reported lower intention to stay than nurses. Provider demographics and facility level and ownership (public/private) were not associated with either outcome. There were also differences in job satisfaction and intention to stay between Ugandan and Zambian health-care providers. Our study suggests that managers play a crucial role in retaining a sufficient number of satisfied health-care providers providing obstetric care in two sub-Saharan African countries, Uganda and Zambia. Prioritizing and investing in health management systems and health managers are essential foundations for high-quality health systems.

Project description:BackgroundJob satisfaction is a predictor of intention to stay and turnover among allied healthcare providers. However, there is limited research examining job satisfaction among allied health professionals, specifically in residential long-term care (LTC) settings. The purpose of this study was to identify factors (demographic, individual, and organizational) that predict job satisfaction among allied healthcare providers in residential LTC.MethodsWe conducted a secondary analysis of data from Phase 2 of the Translating Research in Elder Care program. A total of 334 allied healthcare providers from 77 residential LTC in three Western Canadian provinces were included in the analysis. Generalized estimating equation modeling was used to assess demographics, individual, and organizational context predictors of allied healthcare providers' job satisfaction. We measured job satisfaction using the Michigan Organizational Assessment Questionnaire Job Satisfaction Subscale.ResultsBoth individual and organizational context variables predicted job satisfaction among allied healthcare providers employed in LTC. Demographic variables did not predict job satisfaction. At the individual level, burnout (cynicism) (β = -.113, p = .001) and the competence subscale of psychological empowerment (β = -.224, p = < .001), were predictive of lower job satisfaction levels while higher scores on the meaning (β = .232, p = .001), self-determination (β = .128, p = .005), and impact (β = .10, p = .014) subscales of psychological empowerment predicted higher job satisfaction. Organizational context variables that predicted job satisfaction included: social capital (β = .158, p = .012), organizational slack-time (β = .096, p = .029), and adequate orientation (β = .088, p = .005).ConclusionsThis study suggests that individual allied healthcare provider and organizational context features are both predictive of allied healthcare provider job satisfaction in residential LTC settings. Unlike demographics and structural characteristics of LTC facilities, all variables identified as important to allied healthcare providers' job satisfaction in this study are potentially modifiable, and therefore amenable to intervention.

Dataset Information

Exploration of Predictors for Korean Teacher Job Satisfaction via a Machine Learning Technique, Group Mnet.

Publications

Exploration of Predictors for Korean Teacher Job Satisfaction via a Machine Learning Technique, Group Mnet.

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