Education
17 columns
100 rows
8 formats

Learning Module Completion Rates

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.

last updated 12 Jul 2025
by GoMask

The brief that made it

Identifying modules with low completion rates for targeted content or structural improvements

Sample rows

preview · 8 of 100 rows · all 17 columns

organization_idstring	module_statusstring	completion_ratefloat	improvement_flagboolean	course_titlestring	organization_namestring	course_idstring	module_idstring	module_titlestring	module_sequenceinteger	total_learnersinteger	learners_completedinteger	average_completion_time_minutesfloat	module_last_updateddatetime	reporting_period_startdate	reporting_period_enddate	improvement_notesstring
ORG001	active	0.9167	false	Introduction to Biology	North Valley Institute	C1001	M1	Cell Structure and Function	1	120	110	46.2	2024-04-12T10:18:00	2024-04-01	2024-04-30	blank
ORG001	active	0.8583	false	Introduction to Biology	North Valley Institute	C1001	M2	Genetics Basics	2	120	103	52.1	2024-04-13T15:20:00	2024-04-01	2024-04-30	blank
ORG001	active	0.6667	true	Introduction to Biology	North Valley Institute	C1001	M3	Evolution and Diversity	3	120	80	58.8	2024-04-14T09:47:00	2024-04-01	2024-04-30	Completion rate below threshold; review module engagement.
ORG001	active	0.6417	true	Introduction to Biology	North Valley Institute	C1001	M4	Plant Physiology	4	120	77	62	2024-04-15T18:33:00	2024-04-01	2024-04-30	Module flagged for low completion rate.
ORG001	active	0.8421	false	Organic Chemistry	North Valley Institute	C1002	M1	Structure and Bonding	1	95	80	49.4	2024-03-29T14:04:00	2024-03-01	2024-03-31	blank
ORG001	active	0.7263	false	Organic Chemistry	North Valley Institute	C1002	M2	Hydrocarbons	2	95	69	51.3	2024-03-30T11:41:00	2024-03-01	2024-03-31	blank
ORG002	active	0.7875	false	World History	South Ridge College	C2001	M1	Ancient Civilizations	1	80	63	44	2024-04-08T13:53:00	2024-04-01	2024-04-30	blank
ORG002	active	0.725	false	World History	South Ridge College	C2001	M2	Middle Ages	2	80	58	42.7	2024-04-09T16:20:00	2024-04-01	2024-04-30	blank
ORG002	active	0.675	true	World History	South Ridge College	C2001	M3	Modern Era	3	80	54	47.5	2024-04-09T19:10:00	2024-04-01	2024-04-30	Consider updating assessments for better engagement.
ORG002	active	0.9306	false	Introduction to Literature	South Ridge College	C2002	M1	Literary Genres	1	72	67	38.9	2024-03-20T10:25:00	2024-03-01	2024-03-31	blank
ORG002	active	0.8333	false	Introduction to Literature	South Ridge College	C2002	M2	Poetry Analysis	2	72	60	41.6	2024-03-21T13:40:00	2024-03-01	2024-03-31	blank
ORG002	under_review	0.6111	true	Introduction to Literature	South Ridge College	C2002	M3	Modern Novels	3	72	44	57.3	2024-03-22T17:55:00	2024-03-01	2024-03-31	Module flagged for structural review.
ORG003	active	0.9286	false	Calculus I	East Coast Polytechnic	C3001	M1	Limits and Continuity	1	140	130	61.4	2024-03-31T12:00:00	2024-03-01	2024-03-31	blank
ORG003	active	0.7429	false	Calculus I	East Coast Polytechnic	C3001	M2	Derivatives	2	140	104	65.7	2024-04-01T10:10:00	2024-03-01	2024-03-31	blank
ORG003	active	0.6429	true	Calculus I	East Coast Polytechnic	C3001	M3	Integrals	3	140	90	74.5	2024-04-02T15:38:00	2024-03-01	2024-03-31	Module flagged for improvement due to low completion.
ORG003	active	0.8939	false	Linear Algebra	East Coast Polytechnic	C3002	M1	Vectors and Spaces	1	132	118	58.8	2024-04-03T08:32:00	2024-04-01	2024-04-30	blank
ORG003	active	0.8258	false	Linear Algebra	East Coast Polytechnic	C3002	M2	Matrices	2	132	109	61.6	2024-04-04T14:49:00	2024-04-01	2024-04-30	blank
ORG003	under_review	0.6742	true	Linear Algebra	East Coast Polytechnic	C3002	M3	Eigenvalues and Eigenvectors	3	132	89	70.2	2024-04-05T11:12:00	2024-04-01	2024-04-30	Flagged for extra support materials.
ORG004	active	0.9222	false	Introduction to Psychology	Westside University	C4001	M1	Foundations of Psychology	1	90	83	39.2	2024-03-26T09:42:00	2024-03-01	2024-03-31	blank
ORG004	active	0.8333	false	Introduction to Psychology	Westside University	C4001	M2	Cognitive Development	2	90	75	44.5	2024-03-27T13:17:00	2024-03-01	2024-03-31	blank

What the 100 rows show

from the 100-row sample

Under_review (module status) stands out: 15 of its 15 rows have improvement_flag = true, against 20 of 85 for the rest.

35%improvement_flag = true
0.79median completion_rate
25organizations
25organization names
2median module_sequence
92median total_learners

Improvement flag rate by module_statusimprovement_flag = true

Under_review (module status)'s mean completion_rate is 0.60, against 0.82 for active and 0.77 for archived.

completion_rate100 rows, in bands of 0.05

Every row with completion_rate under 0.7 has improvement_flag = true. None above it.

course_title100 rows · top 10 of 39 values

Introduction to Psychology5
Introduction to Data Science5
Introduction to Biology4
Linear Algebra4
Environmental Science4
World History3
Introduction to Literature3
Calculus I3
Statistics3
Computer Science Fundamentals3

17 columns by typefrom the column list below

string 8
integer 3
float 2
date 2
datetime 1
boolean 1

Columns

17 columns in four groups

blueprint · 17 columns
column	type	description	example
Text 8 columns
`organization_id`	string	Unique identifier for the educational organization.	ORG001
`organization_name`	string	Name of the educational organization.	North Valley Institute
`course_id`	string	Unique identifier for the course.	C1001
`course_title`	string	Title of the course.	Introduction to Biology
`module_id`	string	Unique identifier for the learning module within the course.	M1
`module_title`	string	Title of the learning module.	Genetics Basics
`module_status`	string	Current status of the module (e.g., active, archived, under_review).active · archived · under_review	active
`improvement_notes`	string	Optional notes or comments regarding needed improvements for the module.optional	Revise case studies.
Numbers 5 columns
`module_sequence`	integer	The order of the module within the course (e.g., 1 for first module).1 or more	1
`total_learners`	integer	Total number of learners enrolled in the module.0 or more	120
`learners_completed`	integer	Number of learners who have completed the module.0 or more	110
`completion_rate`	float	Percentage of enrolled learners who completed the module (0.0 - 1.0).0 to 1	0.9167
`average_completion_time_minutes`	float	Average time (in minutes) taken by learners to complete the module.0 or more · optional	46.2
Dates and times 3 columns
`module_last_updated`	datetime	Timestamp of the last update to the module content or structure.optional	2024-04-12T10:18:00
`reporting_period_start`	date	Start date of the reporting period for the completion data.	2024-04-01
`reporting_period_end`	date	End date of the reporting period for the completion data.	2024-04-30
True or false 1 column
`improvement_flag`	boolean	Indicates if the module has been flagged for content or structural improvement.	false

Use it for

An education dashboard
The improvement_flag rate, completion_rate by module_status and a breakdown of course_title. Excel, Power BI or Tableau.
Why do 35 of 100 rows have improvement_flag = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Organizations100
ORG0010.9167active
ORG0010.6667active
ORG0010.6417active
A software demo
Believable organizations with organization_name, course_id and course_title to fill a screen in front of a buyer.

This dataset100 rows17 columns

Yours1,000 rows17 columns

blueprint · learning-module-completion-rates

Behind this dataset

Same schema. As many rows as you need.

These 100 rows came out of a blueprint — 17 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.

Rules it was built with

Each module assigned difficulty level
Incomplete attempts over 20% trigger review
Completion date required per student
Feedback collected post-completion

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

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: learning-module-completion-rates

What should your data show?

No signup. No card.

Sample rows

What the 100 rows show

Columns

Use it for

An education dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Education

What should your data show?