Hybrid Class Engagement Metrics
This dataset provides detailed engagement metrics for students in hybrid (online and onsite) classes, including participation rates, interaction counts, completion status, and feedback ratings. It enables education teams and EdTech startups to compare remote versus in-person engagement, optimize course delivery, and analyze instructor effectiveness across learning modalities.
Sample rows
preview · 8 of 75 rows · all 16 columns| engagement_idstring | completion_statusstring | onsite_engagement_scorefloat | location_citystring | student_idstring | class_idstring | class_titlestring | session_datedate | delivery_modestring | participation_ratefloat | interaction_countinteger | remote_engagement_scorefloat | feedback_ratinginteger | instructor_idstring | location_statestring | location_countrystring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ENG001 | completed | blank | blank | STU101 | CLS1001 | Introduction to Python | 2024-04-08 | online | 88.2 | 5 | 91.7 | 5 | INS201 | blank | blank |
| ENG002 | completed | 82.5 | San Francisco | STU102 | CLS1002 | Data Visualization | 2024-03-29 | onsite | 77.4 | 3 | blank | 4 | INS202 | CA | USA |
| ENG003 | partial | blank | blank | STU103 | CLS1001 | Introduction to Python | 2024-04-08 | online | 65.1 | 2 | 68.3 | 3 | INS201 | blank | blank |
| ENG004 | completed | 95.8 | Chicago | STU104 | CLS1003 | Advanced Spreadsheets | 2024-04-01 | onsite | 92.6 | 7 | blank | 5 | INS203 | IL | USA |
| ENG005 | not_completed | 60.4 | San Francisco | STU105 | CLS1002 | Data Visualization | 2024-03-29 | onsite | 57.9 | 1 | blank | 2 | INS202 | CA | USA |
| ENG006 | completed | blank | blank | STU106 | CLS1004 | Business Analytics | 2024-04-12 | online | 74.8 | 3 | 78.9 | 4 | INS204 | blank | blank |
| ENG007 | completed | 87.2 | Chicago | STU107 | CLS1003 | Advanced Spreadsheets | 2024-04-01 | onsite | 85.4 | 5 | blank | 4 | INS203 | IL | USA |
| ENG008 | not_completed | blank | blank | STU101 | CLS1004 | Business Analytics | 2024-04-12 | online | 42.2 | 0 | 45.7 | 2 | INS204 | blank | blank |
| ENG009 | completed | 83.7 | Austin | STU108 | CLS1005 | Machine Learning Basics | 2024-03-25 | onsite | 80.3 | 4 | blank | 5 | INS205 | TX | USA |
| ENG010 | partial | 70.2 | Austin | STU109 | CLS1005 | Machine Learning Basics | 2024-03-25 | onsite | 68.7 | 3 | blank | 3 | INS205 | TX | USA |
| ENG011 | completed | blank | blank | STU110 | CLS1006 | Marketing Fundamentals | 2024-04-15 | online | 95.6 | 8 | 97.8 | 5 | INS206 | blank | blank |
| ENG012 | partial | blank | blank | STU111 | CLS1006 | Marketing Fundamentals | 2024-04-15 | online | 54.3 | 2 | 56.1 | 3 | INS206 | blank | blank |
| ENG013 | partial | 66.2 | San Francisco | STU112 | CLS1002 | Data Visualization | 2024-03-29 | onsite | 63.8 | 2 | blank | 3 | INS202 | CA | USA |
| ENG014 | completed | 93.9 | Chicago | STU113 | CLS1003 | Advanced Spreadsheets | 2024-04-01 | onsite | 90.7 | 9 | blank | 5 | INS203 | IL | USA |
| ENG015 | completed | blank | blank | STU114 | CLS1007 | Intro to Statistics | 2024-04-10 | online | 73.5 | 3 | 76.2 | 4 | INS207 | blank | blank |
| ENG016 | not_completed | blank | blank | STU115 | CLS1007 | Intro to Statistics | 2024-04-10 | online | 36.9 | 1 | 39.1 | 2 | INS207 | blank | blank |
| ENG017 | completed | 87.3 | Denver | STU116 | CLS1008 | Digital Marketing | 2024-04-17 | onsite | 81.2 | 6 | blank | 5 | INS208 | CO | USA |
| ENG018 | partial | 61.4 | Denver | STU117 | CLS1008 | Digital Marketing | 2024-04-17 | onsite | 58.9 | 2 | blank | 3 | INS208 | CO | USA |
| ENG019 | completed | blank | blank | STU118 | CLS1009 | Project Management | 2024-03-27 | online | 84.5 | 5 | 86.2 | 5 | INS209 | blank | blank |
| ENG020 | partial | blank | blank | STU119 | CLS1009 | Project Management | 2024-03-27 | online | 62.4 | 2 | 65.9 | 3 | INS209 | blank | blank |
What the 75 rows show
from the 75-row sampleCompleted (completion status) stands out: mean onsite_
- 80.1median onsite_
engagement_ score - 2delivery modes
- 9location states
- 22class titles
- 73.7median participation_
rate - 5median interaction_
count
Median 80.1, from 45.8 to 96.3.
- string 10
- integer 2
- float 3
- date 1
Columns
16 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 10 columns | |||
engagement_id | string | Unique identifier for each engagement recordunique | ENG001 |
student_id | string | Unique identifier for the student | STU101 |
class_id | string | Unique identifier for the class | CLS1001 |
class_title | string | Title or name of the class | Introduction to Python |
delivery_mode | string | Mode of class delivery: online or onsiteonline · onsite | online |
completion_status | string | Indicates if the student completed the session requirementscompleted · not_completed · partial | completed |
instructor_id | string | Unique identifier for the instructor of the class session | INS201 |
location_city | string | City where the onsite class session was held (blank for online sessions)10 cities · optional | San Francisco |
location_state | string | State where the onsite class session was held (blank for online sessions)9 states · optional | CA |
location_country | string | Country where the onsite class session was held (blank for online sessions)optional | USA |
| Numbers 5 columns | |||
participation_rate | float | Percentage of class time the student was actively participating (0-100)0 to 100 | 88.2 |
interaction_count | integer | Number of interactions (questions asked, comments made, polls answered) by the student during the session0 or more | 5 |
remote_engagement_score | float | Engagement score for remote (online) sessions, calculated by the platform (0-100)0 to 100 · optional | 91.7 |
onsite_engagement_score | float | Engagement score for onsite sessions, calculated by the platform (0-100)0 to 100 · optional | 82.5 |
feedback_rating | integer | Student's feedback rating for the session (1-5)1 to 5 · optional | 5 |
| Dates and times 1 column | |||
session_date | date | Date of the class session | 2024-04-08 |
Use it for
An education dashboard
Onsite_
engagement_ score by completion_ status and a breakdown of location_ city. Excel, Power BI or Tableau. Why do the 23 completed rows have a mean onsite_
engagement_ score of 87.1? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Engagements75ENG001completedENG00282.5completedENG003partial
A software demo
Believable engagements with student_
id, class_ id and class_ title to fill a screen in front of a buyer.
blueprint · hybrid-class-engagement-metrics
Behind this dataset
Same schema. As many rows as you need.
These 75 rows came out of a blueprint — 16 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
- Each student must have unique ID
- Session type (online/onsite) recorded for every class
- Engagement scores calculated from attendance, participation, and assignment completion
- Completion rates only count if all core activities are fulfilled
- Anomaly flags added for extremely low engagement sessions
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- hybrid-class-engagement-metrics