Student Academic Achievement Forecast Based on Emotional Intelligence, Personality, Demographic Characteristics and Attitude Towards Education and Future Career - Hajar Tarverdizadeh; Mohammad Taghipour (International Journal of Education Sciences, 2024)
This study was aimed at predicting students' academic achievement based on emotional intelligence of personality traits, attitudes to education and future career. The present study was a correlational-analytical study. The statistical population of Zanjan University students in the academic year of 1395-1395 was the sample of 489 people selected by cluster random sampling method. Academic Resilience Scale (ARI) and Schotte Emotional Intelligence Questionnaire and Researcher Attitude Questionnaire were used to evaluate the suggested pattern through the pattern of structural equation using AMOS-7 software. The results indicated that demographic variables negatively predict academic achievement. Among the personality factors, emotional intelligence and education in education and career future are positively predicted academic achievement. By resilience, emotional intelligence also predicts academic success. Academic resilience does not mediate the relationship between attitude to education and career future, gender, age, and academic achievement, and academic resilience only mediates the relationship between personality conscience and academic achievement. These findings show the significance of personality traits and emotional intelligence in academic achievement, emphasizing the intricate interactions between these variables and how they affect students' resilience and academic results. This research adds to our knowledge of the ways in which psychological and demographic factors interact to influence academic accomplishment, offering insightful information for instructional strategies and interventions meant to improve student performance.
Keywords: Academic Achievement; Academic resilience; Emotional intelligence; Future career; Structural Equation Modeling; demographic variables