Anonymized Student Performance Data from Two Linear Algebra Courses Using STACK at the University of Trieste (2023/24)

This dataset contains anonymized student performance records from two Linear Algebra courses offered in the Engineering BSc program at the University of Trieste, Italy. The data comes from two academic years: 2022/23 (Pre-STACK): Before the STACK e-assessment system was introduced. 2023/24 (Post-STACK): After STACK was integrated into both courses. The University policy only records final grades of students who passed the exam. Therefore, the datasets only include students who scored 18 points or more, which is the minimum passing grade. 📁 Files included: anonymized_Lin_Alg_course_A_preSTACK.csv anonymized_Lin_Alg_course_B_preSTACK.csv combined_Lin Alg_course_A_Post_STACK.csv combined_Lin Alg_course_B_Post_STACK.csv 📌 Variables in Each File: student_ID: A randomly generated anonymized identifier for each student. The ID format indicates the course and whether the data is from the Pre-STACK or Post-STACK period.Example: student_ID023_COURSE_A_POSTSTACK final_exam_grade: The student’s final exam score, on a scale from 0 to 30. Only passing scores (≥18) are included. In the Post-STACK datasets: Variable Meaning num_quiz_submissions The total number of times a student submitted STACK quizzes in the entire course. quiz_submission_variability This shows how consistent or varied the student's quiz submissions were. A lower value means they were fairly consistent across attempts. avg_quiz_score The average score the student achieved across all STACK quizzes. This provides a general measure of their performance in the quizzes. cat_total_score The total score obtained from STACK-based Continuous Assessment Tests (CATs).