Flipped Classroom Calculus Achievement Data

Columns

• student: Unique identifier for each student in the course.
• gender: Categorical indicator of the student's gender (1 = female; 2 = male).
• vgroup: Designates the experimental group regarding viewing timing (-1 = watched video before lecture; 1 = watched video after lecture).
• v6_02, v6_04, v7_01, v7_04, v7_071, v7_072, v7_08: Binary flags indicating whether specific videos were watched (1 = watched 80% or more of the video length; 0 = not watched). The dataset contains flags for 26 individual videos in total.
• videosum: The total count of videos watched by the student.
• final_raw: The raw score achieved by the student on the cumulative final course exam.
• sat_math: The student's scaled SAT-Math score (out of 800).
• math_place: Institutional calculus readiness score (out of 100).
• watched20: A grouping flag identifying students who watched 20 or more videos.

Distribution

• Format: CSV (Comma Separated Values)
• Size: 11.73 kB
• Structure: 34 columns, 147 valid records (rows).
• Data Integrity: 100% valid records with no missing or mismatched values reported in the sample analysis.

Usage

• Educational Research: Assessing the impact of video interventions on learning outcomes in STEM subjects.
• Pedagogical Strategy: Evaluating "flipped classroom" methodologies (content consumption before vs. after class).
• Performance Analysis: Correlating standardized test scores (SAT) and readiness scores with final course performance.
• Engagement Tracking: Investigating patterns in digital resource consumption among university students.

Coverage

• Target Population: Students enrolled in a Calculus II class.
• Subject Matter: Mathematics (Calculus).
• Demographics: Includes gender data to facilitate analysis of demographic trends in engagement and achievement.
• Update Frequency: Expected annually.

License

Who Can Use It

• Academic Researchers: Conducting studies on higher education pedagogy and educational technology.
• Data Analysts: Practising exploratory data analysis (EDA) on behavioural and performance datasets.
• Mathematics Educators: Looking for evidence-based insights to structure course materials.
• EdTech Developers: Designing engagement metrics for learning management systems.

Dataset Name Suggestions

• Calculus II Video Engagement and Grades
• Student Performance with Worked Example Videos
• Flipped Classroom Calculus Achievement Data
• Math Education Video Usage Metrics

Attributes