ABSTRACT

We examined whether students were accurate in predicting their test performance in both low-stakes and high-stakes testing contexts. The sample comprised U.S. high school students enrolled in an advanced placement (AP) statistics course during the 2017–2018 academic year (N = 209; M_age = 16.6 years). We found that even two months before taking the AP exam, a high stakes summative assessment, students were moderately accurate in predicting their actual scores (κ_weighted = .62). When the same variables were entered into models predicting inaccuracy and overconfidence bias, results did not provide evidence that age, gender, parental education, number of mathematics classes previously taken, or course engagement accounted for variation in accuracy. Overconfidence bias differed between students enrolled at different schools. Results indicated that students’ predictions of performance were positively associated with performance in both low- and high-stakes testing contexts. The findings shed light on ways to leverage students’ self-assessment for learning.

摘要

我们检查了学生在低风险和高风险测试环境中预测他们的考试成绩是否准确。样本包括在 2017-2018 学年参加高级安置 (AP) 统计课程的美国高中生（N = 209；M_年龄 = 16.6 岁）。我们发现，即使在参加 AP 考试（一项高风险的总结性评估）前两个月，学生们在预测他们的实际分数方面也相当准确（κ_加权 = .62)。当相同的变量被输入到预测不准确和过度自信偏差的模型中时，结果并没有提供证据表明年龄、性别、父母教育、以前上过的数学课的数量或课程参与度是导致准确性变化的原因。在不同学校就读的学生之间存在过度自信偏差。结果表明，学生对表现的预测与低风险和高风险测试环境中的表现呈正相关。研究结果揭示了如何利用学生的自我评估进行学习。