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.