青年教育分流、學用相符、工作滿意及快樂感之縱向關係

Longitudinal Relationships among Educational Tracking, Job-Education Match, Job Satisfaction, and Happiness of Taiwan Youth

本研究以縱貫方法，探討青年在25歲、30歲、33歲三個時間點的生涯發展過程中，學用相符、工作滿意及快樂感的關聯，並將高中職階段的教育分流（普通類、技職類）及相關預測變項納入模型。分析資料來自臺灣教育長期追蹤資料庫（TEPS）及其後續調查資料庫（TEPS-B）的SH樣本，共1,637人，以隨機截距交叉滯後模型（RI-CLPM）為分析方法。結果顯示，臺灣青年的學用相符、工作滿意度及快樂感三者成正相關。在滯後效果方面，三波次間的學用相符及快樂感有自回歸效果，工作滿意度則僅在後二波有自回歸效果；而除了30歲的快樂感能正向預測33歲的工作滿意度，其餘交叉滯後效果皆未顯著。在預測變項方面，學歷對三個主要變項皆有正向預測力；高三時後悔所選組科別對後來生涯的工作滿意度及快樂感有負向預測力。整體而言，教育分流的調節作並不明顯，僅25歲到30歲間的少數路徑有差異；在二種教育分流各別樣本模型中，發現高三時後悔所選科別對技職分流者的工作滿意度及快樂感有負向預測力，而生涯嘗試對普通分流者的學用相符有正向預測力。最後，提供未來研究與實務建議。

This study uses longitudinal analysis of the Taiwan Education Panel Survey to explore background factors of educational tracking experiences among Taiwanese youth and their dynamic associations with job-education match, job satisfaction, and happiness. The sustainable careers concept (De Vos et al., 2020) views individuals as core actors, emphasizing personal, situational, and temporal dimensions’influence on career sustainability, expanding school-to-work transition research (Blokker et al., 2023). However, existing studies often focus on adults and are cross-sectional, missing key youth changes and early educational experiences’impact on careers. While educational tracking’s role in occupational choice has been explored, understanding of how job-education match affects job satisfaction and happiness, especially under different educational backgrounds, remains limited. This study’s longitudinal analysis aims to provide a comprehensive perspective for sustainable career theory and practice.
Research shows job-education match, job satisfaction, and happiness are interrelated. Job-education match includes educational level, field of study, and skills/abilities matching, positively correlating with job satisfaction (Badillo-Amador & Vila, 2013; Santis et al., 2021). From strengths-use perspective, knowledge and abilities need an environment for application, with full utilization increasing work engagement, satisfaction, and happiness (Miglianico et al., 2020). Job satisfaction and happiness’s positive association is often explained by the spillover hypothesis, including top-down and bottom-up effects. Longitudinal meta-analyses show life satisfaction and happiness have cross-sectional associations and cross-lagged effects (Bowling et al., 2010; Karabati et al., 2019; Steel et al., 2019). This study analyzes these relationships using data from Taiwan.
The impact of early educational experiences on later career development is worth investigating. Existing research on Taiwanese youth indicates that high school students’post-graduation development is influenced by learning experiences and employment considerations. Key moments for youth to consider career development are during the educational tracking at high school levels and when facing graduation from university (Kuo et al., 2021; Wu et al., 2018). In Taiwan’s education system, the educational tracking at the high school level is a crucial stage in youth career development. Vocational high school students mostly choose their major subjects upon graduating from junior high school, while students in academic high school choose their stream (liberal arts or science) after completing their first year, and decide on their specific university major when applying for higher education. This study employs longitudinal tracking to investigate how regret over high school track/major choices in the third year influences subsequent career development, addressing limitations of retrospective methods in existing research. It also focuses on youth with different educational tracking experiences, exploring how their subsequent career development trajectories differ. While previous studies have explored how educational tracking affects various work outcomes over time (Birkelund et al., 2022; Delaruelle et al., 2020; Verhaest et al., 2018), there remains a gap in research specific to Taiwan's unique educational and sociocultural context.
Career exploration during university, especially actions to change or expand learning specialties (changing majors, minors, double majors, taking programs), is a crucial experience for future career development. Educational level is also an important factor. Although literature shows mixed results regarding the match between educational level and work, studies focusing on Taiwanese workers mostly indicate that higher education levels help improve job satisfaction and happiness (Chen et al., 2020). Therefore, this study uses longitudinal analysis to enhance understanding.
The statistical analysis adopts the random intercept cross-lagged panel model (RI-CLPM) (Mulder & Hamaker, 2021), using data from the Taiwan Education Panel Survey (TEPS) and its follow-up database (TEPS-B) SH sample, with 1,637 participants. It examines the associations between job-education match, job satisfaction, and happiness at three time points: ages 25 (T1), 30 (T2), and 33 (T3), incorporating relevant factors from the educational period into the model. In the model, job-education match, job satisfaction, and happiness are time-varying factors, divided into random intercepts at the between-person level to explore correlations, and within-person level to explore autoregression and cross-lagged effects. Educational tracking type, regret over chosen major in the third year of high school (data from high school period), educational level, and career exploration are time-invariant predictors of random intercepts, with gender included as a control variable. Additionally, the study examines whether different educational tracks in high schools (vocational vs. academic) show different effects on various paths and further observes by inputting two group samples into the model.
The main findings are as follows:
First, the random intercepts of job-education match, job satisfaction, and happiness are positively correlated among Taiwanese youth, similar to previous research findings. Those with higher job-education match have higher job satisfaction and happiness due to work content meeting expectations and knowledge and skills matching job requirements (Ilies et al., 2019; Kristof-Brown et al., 2005; Unanue et al., 2017).
Second, job-education match and happiness show autoregressive effects across the three waves, while job satisfaction only shows autoregressive effects in the latter two waves. The autoregressive effect of job-education match reflects the profound impact of the educational stage on career paths. The autoregressive effect of happiness may indicate that increasing age and stable living environments can increase the stability of happiness. Job satisfaction shows no autoregressive effect from 25-30 but does from 30-33, reflecting more career transitions and exploration before 30, with less obvious job satisfaction stability. After 30, higher chances of finding ideal jobs and clearer career positioning lead to more significant job satisfaction stability (Wille et al., 2012).
Third, except for happiness at age 30 positively predicting job satisfaction at age 33, other cross-lagged effects are not significant. This positive effect aligns with the top-down effect of the spillover hypothesis, i.e., overall life satisfaction extends to the work domain (Steel et al., 2019). However, the cross-lagged effects between job-education match and job satisfaction are not obvious, possibly because after entering the workforce, job content and responsibilities may increase, and expectations for working conditions become more complex.
Fourth, overall, the moderating effect of educational tracking is not obvious, with only a few paths differing between ages 25 and 30. The autoregression of happiness T1 to happiness T2 is higher for those in vocational tracks than those in academic track; the influence of job satisfaction T1 on happiness T2 and job satisfaction T1 on job-education match T2 is higher for those in academic track than those in vocational track. This suggests that in the early career stage, the two educational track have their own characteristics. However, the overall total path effect difference is not significant, indicating that regardless of the educational track, the within-person career process experiences similar changes.
Fifth, regarding predictor variables, factors such as educational level, third-year high school major regret, and career exploration during university have different effects depending on the type of educational track. Educational level has a significant positive predictive effect on job-education match in both tracks; however, while educational level positively predicts happiness in the academic track, it has no significant effect in the vocational track. Career exploration has a positive effect on job-education match for those in the academic track, but no effect for those in the vocational track. This study particularly notes that regretting the chosen track/major in the third year of high school negatively predicts job satisfaction and happiness, but only for vocational track participants. These students may lack occupational knowledge or career exploration when transitioning from junior high, yet must make choices determining their professional field at age 15. If they regret their choice, changing fields or retraining may be difficult, affecting job choices and satisfaction. Academic track participants who regret their chosen track (liberal arts or science) in high school can still select their desired major when entering university at age 18, impacting career satisfaction differently. This paper suggests these findings may reflect issues related to early tracking, warranting further investigation.
Regarding research limitations, this study spans many years, and youth may experience job changes, socioeconomic conditions, and family status changes that affect their careers. However, for model simplicity, this study did not include these time-varying factors in the analysis, which future research could further incorporate. Although this is a longitudinal study, inferring causal relationships still requires more exploration, such as mediating effects of other variables or qualitative data support. The three waves in this study have unequal time intervals, limiting effect comparisons and making it inappropriate to constrain the model, leading to insufficiencies in inference and model simplification, so it is recommended that future studies use longitudinal data with equal intervals. The three main variables in this study all use single-item measures as observation sources, which cannot reflect complex constructs; future research should consider multi-item studies. This study treats educational level, career exploration, and educational tracking as time-invariant factors, unable to rule out potential changes for a small number of people between different waves. Understanding of the types of changes in different variables at different time points for participants is limited; future research could explore this through latent heterogeneity analysis to benefit practical work.