影响职前技术教师学业成绩的因素:横断面研究

Sukit Chiranorawanit, Vitsanu Nittayathammakul
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摘要

本研究旨在确定在技术教师培训背景下预测职前技术教师学业成绩的因素。本研究采用了预测性相关设计。我们结合以往的研究建立了概念框架,然后制作了一份调查问卷来收集数据。2022 年 8 月 1 日至 8 月 30 日期间,拉贾曼加拉理工大学(RMUTK)技术教育学院的 109 名本科生收到了一份在线自填问卷。统计分析采用了皮尔逊相关系数和多元回归法。研究结果表明,性别、学习动机和态度、学习习惯、家庭支持、课程质量和教学质量等因素与职前技术教师的学业成绩呈正相关,相关系数在 0.230 至 0.292 之间,均有统计学意义(P < 0.05)。多重相关系数(R)为 0.474,表明自变量和因变量之间在 0.05 的水平上存在显著关系。R 平方值为 0.225,表明这六个变量加在一起可以解释 22.5%的学业成绩变异。然而,这也表明我们的模型未能解释约 77.5%的变异。本研究得出的某些结论预计将有助于制定数字化干预措施,以更好地跟踪学生的学业成绩,从而在未来提供公平的教育体验,最大限度地提高每个性别群体的学业成绩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Influencing Pre-Service Technical Teachers' Academic Performance: Cross-Sectional Study
This research aims to identify factors predicting pre-service technical teachers’ academic performance in a technical teacher training context. This study employed a predictive correlational design. We developed the conceptual framework by combining previous research, and then created a survey to gather data. Between August 1 and August 30, 2022, 109 undergraduates from the Faculty of Technical Education at Rajamangala University of Technology Krungthep (RMUTK) received an online self-administered questionnaire. The statistical analysis employed the Pearson correlation coefficient and multiple regression. The findings of the research showed that there was a positive correlation between various factors such as gender, motivation and attitude towards learning, study habits, family support, curriculum quality, and teaching quality with pre-service technical teachers' academic performance, with the correlation coefficients ranged from .230 to .292 and were all statistically significant (p < 0.05). The multiple correlation coefficient (R) was .474 showed a significant relationship between the independent and dependent variables at the .05 level. The R-squared value was .225, indicating that these six variables combined explain 22.5% of the variation in academic performance. However, this also suggests that our model fails to explain around 77.5% of the variance. Some aspects of the findings derived from this study are expected to result in the creation of digital interventions to better track students' academic performance, aiming to provide equitable educational experiences that maximize the academic performance of each gender group in the future.
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