Student records, course data, academic performance
Access times, resource types, user roles, and engagement metrics
This dataset logs detailed interactions between students and teachers with digital learning resources, including access times, resource types, user roles, and engagement metrics. It is designed to support adaptive learning research, platform usage analysis, and educational resource optimization across diverse contexts and devices.
Student demographics, course details, instructor information, grades
This dataset provides detailed records of student enrollments and completions in online courses, including student demographics, course details, instructor information, grades, completion status, and engagement metrics. It is designed for education technology analytics, enabling research into learning outcomes, course effectiveness, and personalized education pathways.
Session frequency, participant feedback, session outcomes
This dataset provides detailed analytics on peer tutoring sessions within academic institutions, including session frequency, participant feedback, session outcomes, and academic improvement indicators. It enables institutions to evaluate and optimize their peer tutoring programs by analyzing session effectiveness, attendance, and student progress.
Educational resource utilization, capturing user interactions
This dataset provides detailed logs of educational resource utilization, capturing user interactions, access patterns, feedback, and contextual curriculum information. It enables educators and administrators to optimize curriculum planning, improve resource allocation, and analyze engagement trends across different user roles and devices.
Session timing, interaction counts, device usage, and instructor information
This dataset provides detailed records of student attendance and engagement in virtual classroom sessions, including session timing, interaction counts, device usage, and instructor information. It enables educational institutions to monitor participation, analyze engagement trends, and support interventions for remote learning success.
Student feedback on courses, enriched with sentiment analysis labels
This dataset provides detailed student feedback on courses, enriched with sentiment analysis labels and scores, course and instructor metadata, and student academic context. It enables educators and administrators to systematically analyze curriculum effectiveness, identify areas for improvement, and track sentiment trends over time for data-driven decision making.
Models personalized curriculum progressions for adaptive learning
This dataset models personalized curriculum progressions for adaptive learning, capturing detailed learner-module interactions, completion statuses, scores, and adaptive recommendations. It enables EdTech startups to analyze and optimize individualized learning pathways, supporting dynamic curriculum design and learner success tracking.
Student assessment scores across subjects, grade levels
This dataset provides a comprehensive record of student assessment scores across subjects, grade levels, and curriculum standards, enabling educators to analyze performance trends and identify areas for curriculum improvement. It includes detailed information on students, teachers, schools, and assessment types, supporting longitudinal tracking and actionable insights for educational stakeholders.
Student behavioral and demographic data linked to specific course enrollments, enabling
This dataset provides detailed student behavioral and demographic data linked to specific course enrollments, enabling EdTech platforms to analyze and predict course completion likelihood. It includes engagement metrics such as session attendance, assignment and quiz performance, forum participation, and a predicted probability of completion, making it ideal for improving student success rates and personalizing interventions.
17 cols
Time spent, module completion, quiz scores, discussion activity
This dataset provides detailed engagement metrics for students enrolled in online courses, including time spent, module completion, quiz scores, discussion activity, and assignment submissions. It enables educators and edtech platforms to analyze learning behaviors, optimize course design, and deliver personalized recommendations to improve student outcomes.
Demographic and course-level attributes
This dataset provides a detailed record of student enrollments, progress, and completion outcomes across courses, including demographic and course-level attributes. It enables in-depth analysis of completion rates, dropout risks, and curriculum effectiveness, supporting data-driven strategies to improve student retention and success. The dataset is ideal for educational institutions seeking actionable insights into student engagement and course performance.
Summary of student quiz performance across multiple subjects
This dataset provides a comprehensive summary of student quiz performance across multiple subjects, capturing scores, completion status, timing, and indicators for targeted tutoring and curriculum improvement. It enables educators and administrators to identify struggling students, analyze subject-level trends, and make data-driven decisions to enhance learning outcomes.
Every student add and drop action for courses
This dataset logs every student add and drop action for courses, capturing detailed context such as student demographics, course information, and timing. It enables in-depth analysis of enrollment trends, supports forecasting of classroom and instructor needs, and helps identify scheduling bottlenecks or student behavior patterns. Ideal for academic planning, policy evaluation, and institutional research.
Progress status, time spent, scores, and attempts
This dataset tracks individual student lesson completion rates, including progress status, time spent, scores, and attempts, across various lessons and curricula. It enables educators and analysts to identify engagement trends, monitor learning progress, and inform curriculum improvements based on real student interaction data.
Aggregates detailed student feedback on university courses
This dataset aggregates detailed student feedback on university courses, capturing both quantitative ratings and qualitative comments for curriculum review and instructional improvement. It includes course, instructor, and student context, making it ideal for analyzing teaching effectiveness, identifying curriculum gaps, and prioritizing updates based on real student experiences.
Enrollment, completion statistics, and improvement flags for each module
This dataset provides detailed tracking of learning module completion rates across educational organizations, including enrollment, completion statistics, and improvement flags for each module and reporting period. It supports identification of modules needing content or structural enhancements and enables data-driven decisions to improve learner outcomes and course effectiveness.
Student-level view of academic performance, attendance
This dataset provides a detailed, student-level view of academic performance, attendance, and intervention history, enabling educators to monitor progress, identify at-risk students, and tailor support strategies. It includes assessment scores, course and teacher information, intervention records, and attendance tracking, making it ideal for data-driven educational improvement and early warning systems.
Columns and codes found in the sample rows of all 89 education datasets.
Generated
One sentence in. A dataset with that pattern out.
| attendance_pct | subject | mark | student_id |
|---|---|---|---|
| 74 | Mathematics | 49 | S1042 |
| 96 | English Language | 72 | S1043 |
| 78 | Biology | — | S1044 |
| 91 | History | 66 | S1045 |
A pattern you asked for Everything else