German Student Responses to Probability Theory and Statistics Bachelor Course (WuS24): Evaluated with Rubrics

Description: This dataset contains questions and answers from an introductory computer science bachelor course on statistics and probability theory at Hochschule Bonn-Rhein-Sieg. The dataset includes three questions and a total of 90 answers, each evaluated using binary rubrics (yes/no) associated with specific scores. Dataset Components: questions.csv: Contains the details of the three questions. Columns: question_id: Unique identifier for each question question: The text of the question solution: The reference answer for the question max_score: The maximum score for this question rubrics.csv: Contains the grading rubrics for each question. Columns: question_id: Unique identifier for each question rubric_id: Unique identifier for each rubric within a question rubric: The rubric phrased as a question score: The score associated with fulfilling the rubric answers.csv: Contains 90 student answers to the questions. Columns: answer_id: Unique identifier for each answer question_id: Unique identifier of the question that is answered answer: The text of the student's answer score: The score associated with fulfilling the rubric answer_rubrics.csv: Contains the evaluations of rubrics for each answer. Columns: answer_id: The identifier of the answer. question_id: The identifier of the question. rubric_id: The identifier of the rubric for that question. label: Indicates if the rubric crierion is fulfilled for the specific answer (true / false). Working with the Dataset: The easiest way to work with this dataset is using the class `RubricsDataset` defined in the file `dataloader.py`. Example: from dataloader import RubricsDatasetdataset = RubricsDataset.from_directory("data") dataset.get_question(1) # Get a dictionary containing info about the first question, including rubrics dataset.get_answers(1) # Get all the answers for the first question as a list. Each answer is a dictionary with answer, score, rubrics.## 数据集说明 本数据集源自波恩-莱茵-西格应用科学大学（Hochschule Bonn-Rhein-Sieg）计算机科学本科入门级统计学与概率论课程的问答素材，包含3道题目与总计90份学生作答，所有作答均通过关联特定分值的二元评分标准（是/否）完成评估。 ## 数据集组成 ### questions.csv 存储3道题目的详细信息，字段说明如下： - question_id：每道题目的唯一标识符 - question：题目文本内容 - solution：该题目的参考答案 - max_score：该题目的最高分值 ### rubrics.csv 存储每道题目的评分细则，字段说明如下： - question_id：每道题目的唯一标识符 - rubric_id：该题目下每条评分细则的唯一标识符 - rubric：以问句形式表述的评分条目 - score：满足该评分条目可获得的对应分值 ### answers.csv 存储90份学生针对题目的作答内容，字段说明如下： - answer_id：每份作答的唯一标识符 - question_id：所作答题目的唯一标识符 - answer：学生作答的文本内容 - score：该作答的最终得分 ### answer_rubrics.csv 存储每份作答的评分细则评估结果，字段说明如下： - answer_id：对应作答的唯一标识符 - question_id：对应题目的唯一标识符 - rubric_id：对应题目的评分细则唯一标识符 - label：标识该作答是否满足对应评分标准条目（取值为`true`/`false`，即是/否） ## 数据集使用方法 使用本数据集最便捷的方式是调用`dataloader.py`文件中定义的`RubricsDataset`类。 示例代码： python from dataloader import RubricsDataset dataset = RubricsDataset.from_directory("data") dataset.get_question(1) # 获取包含第1道题目信息及对应评分细则的字典 dataset.get_answers(1) # 获取第1道题目的所有作答，以列表形式返回。每份作答为包含作答内容、得分及评分细则评估结果的字典。