Department of Preventive Dental Sciences, College of Dentistry, Prince Sattam Bin Abdulaziz University, Al Kharj, Saudi Arabia.
Department of Oral Medicine and Diagnostic Sciences, College of Dentistry, University of Illinois at Chicago, Chicago, Illinois, USA.
Int J Med Educ. 2023 Oct 6;14:137-144. doi: 10.5116/ijme.64f6.e3db.
To examine the impact of dental students' usage patterns within an adaptive learning platform (ALP), using ALP-related indicators, on their final exam performance.
Track usage data from the ALP, combined with demographic and academic data including age, gender, pre- and post-test scores, and cumulative grade point average (GPA) were retrospectively collected from 115 second-year dental students enrolled in a blended learning review course. Learning performance was measured by post-test scores. Data were analyzed using correlation coefficients and linear regression tests.
The ALP-related variables (without controlling for background demographics and academic data) accounted for 29.6% of student final exam performance (R=0.296, F=4.37, p=0.000). Positive significant ALP-related predictors of post-test scores were improvement after activities (β=0.507, t=2.101, p=0.038), timely completed objectives (β=0.391, t=2.418, p=0.017), and number of revisions (β=0.127, t=3.240, p=0.002). Number of total activities, regardless of learning improvement, negatively predicted post-test scores (β= -0.088, t=-4.447, p=0.000). The significant R change following the addition of gender, GPA, and pre-test score (R=0.689, F=17.24, p=0.000), indicated that these predictors explained an additional 39% of the variance in student performance beyond that explained by ALP-related variables, which were no longer significant. Inclusion of cumulative GPA and pre-test scores showed to be the strongest and only predictors of post-test scores (β=18.708, t=4.815, p=0.038) and (β=0.449, t=6.513, p=0.038), respectively.
Track ALP-related data can be valuable indicators of learning behavior. Careful and contextual analysis of ALP data can guide future studies to examine practical and scalable interventions.
利用自适应学习平台（ALP）相关指标，研究牙科学员在该平台上的使用模式对期末考试表现的影响。
从 115 名参加混合学习复习课程的二年级牙科学员中，回顾性收集与人口统计学和学术数据相关的自适应学习平台使用数据，包括年龄、性别、预考和后测成绩以及累计绩点（GPA）。使用后测成绩衡量学习表现。采用相关系数和线性回归检验进行数据分析。
在未控制背景人口统计学和学术数据的情况下，ALP 相关变量占学生期末考试成绩的 29.6%（R=0.296，F=4.37，p=0.000）。后测成绩的积极显著 ALP 相关预测因素为活动后成绩提高（β=0.507，t=2.101，p=0.038）、按时完成目标（β=0.391，t=2.418，p=0.017）和修订次数（β=0.127，t=3.240，p=0.002）。无论学习成绩提高与否，总活动次数均呈负相关，预测后测成绩（β=-0.088，t=-4.447，p=0.000）。加入性别、累计 GPA 和预考成绩后，R 值显著增加（R=0.689，F=17.24，p=0.000），表明这些预测因素在 ALP 相关变量之外，额外解释了 39%的学生成绩变化，而这些变量不再显著。纳入累计 GPA 和预考成绩后，它们是后测成绩（β=18.708，t=4.815，p=0.038）和（β=0.449，t=6.513，p=0.038）的最强且唯一预测因素。
跟踪 ALP 相关数据可以成为学习行为的有价值指标。对 ALP 数据进行仔细和上下文分析，可以指导未来的研究，以检验实用且可扩展的干预措施。
