自适应多元化评测模型数据集（生物）

本数据集基于957名学习者在2020至2022年间参加的6次英语阶段考试答题记录构建。数据来源于学习者在每道题目上的实际作答得分，通过线下采集并整理为表格格式，学习者个人信息已脱敏处理。数据集包含6个阶段考试的.csv文件，数据量约为1.83MB，文件命名清晰，便于直接使用。数据内容涵盖学习者在每道题目上的得分情况，统计频率为每学期两次，共6次考试。每行数据代表一位学习者，分配唯一标识符并在六次考试中保持一致；每列表示一道试题，按顺序命名，单元格内记录学生在各题上的得分。数据集支持Excel等常用软件直接打开，为自适应测评模型的研究与实践提供高数据支撑，适用于学习者知识状态分析和测评模型优化等研究场景。该数据集支撑了专利“一种考试属性和学生知识水平的评估方法”，可用于探索学习者在不同阶段的能力变化，帮助教育工作者制定针对性的教学策略。通过分析得分数据，研究人员能够识别学习者的薄弱环节并优化教学内容。此外，该数据集为教育技术开发提供基础数据，支持智能学习系统的设计，推动自适应测评模型的发展，提高评估的精准性与有效性。这些研究将促进个性化学习，提升教育质量和学习效果。This dataset is constructed based on the answer records of 957 learners who took 6 staged English proficiency exams between 2020 and 2022. The data is derived from the actual scores of learners on each question, collected offline and organized into tabular format, with learners' personal information fully de-identified. This dataset contains 6 .csv files corresponding to the staged exams, with a total size of approximately 1.83 MB. The files are clearly named for direct out-of-the-box usage. The data covers learners' scores on each test question, with a total of 6 exams administered twice per semester. Each row represents a single learner, assigned a unique identifier that remains consistent across all 6 exams; each column corresponds to a test question, named in sequential order, with cell entries recording the learner's score on that specific question. The dataset can be directly opened via common software such as Microsoft Excel, providing high-quality data support for the research and practice of adaptive assessment models, and is suitable for research scenarios including learner knowledge state analysis and assessment model optimization. This dataset supports the Chinese patent titled "An Assessment Method for Exam Attributes and Student Knowledge Levels", and can be used to explore learners' ability changes across different stages, helping educators develop targeted teaching strategies. By analyzing the score data, researchers can identify learners' weak areas and optimize teaching content. Furthermore, this dataset provides foundational data for educational technology development, supports the design of intelligent learning systems, promotes the advancement of adaptive assessment models, and enhances the accuracy and effectiveness of assessments. These studies will facilitate personalized learning and improve educational quality and learning outcomes.

搜集汇总

背景与挑战

背景概述

该数据集基于957名学习者在2020至2022年间参加的6次英语阶段考试答题记录构建，包含脱敏处理后的得分数据，以.csv格式存储，数据量约为1.83MB。它旨在支持自适应测评模型的研究与应用，适用于学习者知识状态分析、测评模型优化等教育技术场景。