Althewini Abdulaziz
King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center and Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.
Front Med (Lausanne). 2025 Jul 8;12:1595079. doi: 10.3389/fmed.2025.1595079. eCollection 2025.
Accurate prediction of academic performance is essential for selecting students into competitive medical and health science programs. In Saudi Arabia, standardized cognitive assessments-such as the General Aptitude Test (GAT) and Scholastic Achievement Admission Test (SAAT)-are widely used for admissions. This study evaluates the predictive validity of these tests, alongside English proficiency measures, in forecasting student performance in an introductory physics course-a foundational subject in science-based programs.
This retrospective, quantitative study analyzed data from 250 Saudi college students enrolled in a required introductory physics course. Predictor variables included GAT scores (critical thinking and reasoning), SAAT scores (content knowledge in science and math), and English proficiency, assessed via three metrics: preparatory-year English course average, reading test scores, and communication skills test scores. Both simple linear regression and multiple regression analyses were conducted to evaluate the individual and combined predictive contributions of these variables to final physics course grades.
All predictors were statistically significant. Among them, reading proficiency was the strongest individual predictor, accounting for 19.6% of the variance in physics grades, followed by GAT (9.4%) and SAAT (7.9%). Communication test scores explained a smaller portion (7.2%). The combined model explained 29.3% of the total variance in physics performance, leaving approximately 70% of the variance unexplained by the selected cognitive measures.
Although GAT, SAAT, and English reading proficiency contribute modestly to predicting physics course performance, their limited combined predictive power points to the need for more comprehensive admissions criteria. Non-cognitive factors-such as motivation, study habits, or self-efficacy-may significantly influence academic outcomes but remain unmeasured in current systems. These findings support calls for reforming admissions practices in Saudi health science education to adopt a more holistic and evidence-informed approach.
准确预测学业成绩对于选拔学生进入竞争激烈的医学和健康科学专业至关重要。在沙特阿拉伯,标准化认知评估,如一般能力倾向测试(GAT)和学业成就入学考试(SAAT),被广泛用于招生。本研究评估了这些测试以及英语水平测量指标在预测学生在基础物理课程(科学类专业的一门基础学科)中的表现方面的预测效度。
这项回顾性定量研究分析了250名注册必修基础物理课程的沙特大学生的数据。预测变量包括GAT分数(批判性思维和推理能力)、SAAT分数(科学和数学方面的知识)以及英语水平,通过三个指标进行评估:预科英语课程平均分、阅读测试分数和沟通技能测试分数。进行了简单线性回归和多元回归分析,以评估这些变量对最终物理课程成绩的个体和综合预测贡献。
所有预测因素均具有统计学意义。其中,阅读能力是最强的个体预测因素,占物理成绩方差的19.6%,其次是GAT(9.4%)和SAAT(7.9%)。沟通测试分数解释的比例较小(7.2%)。综合模型解释了物理成绩总方差的29.3%,所选认知测量指标无法解释约70%的方差。
尽管GAT、SAAT和英语阅读能力对预测物理课程成绩有一定贡献,但其有限的综合预测能力表明需要更全面的录取标准。非认知因素,如动机、学习习惯或自我效能感,可能会显著影响学业成绩,但在当前系统中尚未得到衡量。这些发现支持了沙特健康科学教育中改革招生做法以采用更全面和基于证据的方法的呼吁。