Demographic_Academic_Performance_Biochemistry_Data

The dataset comprises novel aspects, specifically in terms of biochemistry student's academic performance prediction at an early stage using academic and demographic features. The dataset may enable other researchers to conduct comparative studies and compare the findings of their local dataset with ours to further extend and understand the depth and breadth of phenomena under research. Researchers can investigate/compare whether demographic or academic features affect students’ performance based on region, country, program, and semester-wise. The datasets offered may provide an opportunity for researchers interested in performing potential experiments to extend their knowledge about the phenomena from different perspectives: • For educational research, the question of whether the student’s performance can be predicted by analyzing the demographic and academic (pre-admission) features. • Students’ performance can be predicted at an early stage for various departments. • Students’ performance can be predicted at the semester level and degree level. • Also, the relationship between students’ performance and demographic and academic (pre-admission) features can be further explored. • These datasets can make an important contribution to the pragmatic policy-related indicators to adjust the admission criteria so far.本数据集具备新颖的研究视角，具体聚焦于利用学术特征与人口统计学特征，对生物化学专业学生的学业表现进行早期预测。本数据集可供其他研究者开展对比研究，将其本地数据集的研究结果与本数据集的结果进行比对，从而进一步拓展并深化对所研究现象的认知广度与深度。研究者可基于地区、国家、培养项目以及学期维度，探究人口统计学特征或学术特征是否会对学生学业表现产生影响。 本数据集可为有意愿开展相关实验的研究者提供契机，使其能够从多维度拓展对该研究现象的认知，具体包括： - 针对教育研究领域，可探究通过分析人口统计学特征与学术（入学前）特征，是否能够预测学生的学业表现； - 可针对不同院系开展学生学业表现的早期预测研究； - 可分别从学期与学位项目层面开展学生学业表现预测研究； - 此外，还可进一步探究学生学业表现与人口统计学特征、学术（入学前）特征之间的关联； - 截至目前，本数据集可为调整招生标准的实用政策相关指标提供重要参考依据。