Teachers emotional intelligence to predictive work performance using linear and non-linear models
Journal Title: Journal of Advanced Research in Social Sciences and Humanities - Year 2021, Vol 6, Issue 2
Abstract
Aim: Teachers’ job performance has been impacted by rapid changes and reforms in educational systems around the world. Despite these advancements, the debate about how to forecast teacher success remains complicated and difficult to assess. The role of emotional intelligence in teacher success is investigated in this research, which fills a void/gap in the literature. The relationship between Emotional Intelligence (EI), which has four dimensions: self-regulations, self awareness, self-motivation, and social ability (relationship management), and job performance is examined in this research. Methodology: 160 teachers from six technical colleges in Nigeria’s north-east were polled. The data was gathered through a questionnaire survey, and analyse using artificial intelligence model (FFNN, LSSVM, NF and MLR). Findings: The models were assessed using determination coefficient (R2), root mean square error (RMSE) and correlation coefficient (R). the result obtained from the simple models showed that neuro fuzzy sub clustering hybrid (NF-SCH) shows (R2 = 0.8814502 and 0.8375132) both training and testing, the correctness of models has been improved which increase accuracy of the single models up to 17%, 18%, and 20% FFNN, MLR and LSSVM for calibration and up to 40%, 73% and 70% FFNN, MLR and LSSVM for verification respectively the results show a strong connection between emotional intelligence and work satisfaction. Implications/Novel Contribution: Overall, this study adds to the body of knowledge on emotional intelligence by having practical management implications for school administrators and the Nigerian higher education system.
Authors and Affiliations
IDRIS A SEZER K TAHIRU ZANNA HASSAN SALEH ADAMU GAMBO
Keywords
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