Education
23 columns
120 rows
8 formats

Student Performance Tracking

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.

opened 35 times
last updated 12 Jul 2025
by GoMask

The brief that made it

Early identification and support of at-risk students

Sample rows

preview · 8 of 120 rows · all 23 columns

student_idstring	attendance_statusstring	scorefloat	intervention_flagboolean	teacher_idstring	first_namestring	last_namestring	date_of_birthdate	genderstring	grade_levelstring	school_idstring	enrollment_datedate	course_idstring	course_namestring	assessment_idstring	assessment_typestring	assessment_datedate	score_maxfloat	attendance_datedate	intervention_typestring	intervention_datedate	at_risk_flagboolean	notesstring
S00001	present	89.5	false	T001	Olivia	Lopez	2008-10-14	female	10	SCH001	2023-08-21	C101	Biology	A1001	test	2024-02-10	100	2024-02-10	none	blank	false	Consistent high performer, actively participates in group projects.
S00002	absent	52	true	T002	Mason	Choi	2010-01-30	male	8	SCH002	2022-09-05	C102	Mathematics	A1002	quiz	2024-03-01	70	2024-03-01	tutoring	2024-03-08	true	Missed quiz due to absence; referred to after-school tutoring.
S00003	present	94	false	T003	Emma	Nguyen	2007-06-22	female	11	SCH003	2021-09-10	C103	English Literature	A1003	assignment	2024-02-19	100	2024-02-19	none	blank	false	Insightful essay submission, demonstrates leadership in class discussions.
S00004	present	80	false	T004	Noah	Patel	2009-09-13	male	9	SCH001	2022-08-29	C104	World History	A1004	project	2024-01-26	90	2024-01-26	none	blank	false	Shows creativity and teamwork in group project. Solid research skills.
S00005	late	61.5	true	T005	Avery	Smith	2011-05-05	non-binary	7	SCH004	2023-01-17	C105	Physical Education	A1005	assignment	2024-03-03	80	2024-03-03	counseling	2024-03-07	true	Late to class; referred to school counselor for support.
S00006	present	95.5	false	T006	Lucas	Johnson	2006-12-01	male	12	SCH002	2020-09-04	C106	Spanish	A1006	final	2024-02-28	100	2024-02-28	none	blank	false	Excellent work on final exam; positive role model for peers.
S00007	present	68	false	T001	Isabella	Davis	2008-07-10	female	10	SCH005	2023-08-15	C101	Biology	A1007	quiz	2024-02-15	70	2024-02-15	none	blank	false	Quick to grasp new concepts; helpful to classmates.
S00008	absent	0	true	T002	Ethan	Baker	2012-03-12	male	6	SCH003	2023-09-06	C102	Mathematics	A1008	assignment	2024-02-22	70	2024-02-22	parent meeting	2024-02-29	true	Absent for assessment; parent meeting scheduled for academic concerns.
S00009	present	73	false	T003	Mia	Lee	2010-11-25	female	8	SCH001	2022-08-30	C103	English Literature	A1009	project	2024-03-01	80	2024-03-01	none	blank	false	Solid project presentation; steady improvement noted.
S00010	late	61	true	T004	Benjamin	Martinez	2009-04-03	male	9	SCH004	2022-09-12	C104	World History	A1010	test	2024-02-13	90	2024-02-13	tutoring	2024-02-20	true	Arrived late for assessment; additional support recommended.
S00011	present	86	false	T005	Sophia	Wang	2007-08-28	female	11	SCH005	2021-09-07	C105	Physical Education	A1011	assignment	2024-03-05	90	2024-03-05	none	blank	false	Excellent effort in fitness assessment; leads by example.
S00012	present	38	true	T006	Logan	Garcia	2011-02-15	male	7	SCH003	2023-01-23	C106	Spanish	A1012	final	2024-02-25	100	2024-02-25	special education	2024-03-04	true	Low final exam performance; special education support initiated.
S00013	blank	1000	false	T001	Harper	Kim	2008-04-16	female	10	SCH002	2023-08-28	C101	Biology	A1013	other	2024-03-07	1000	blank	none	blank	false	Received bonus for science fair participation; exceptional achievement.
S00014	present	66	false	T002	Elijah	Zhang	2007-09-11	male	11	SCH001	2021-08-30	C102	Mathematics	A1014	quiz	2024-02-18	70	2024-02-18	none	blank	false	Consistently meets math targets; positive attitude in class.
S00015	excused	82	false	T003	Amelia	Clark	2010-11-08	female	8	SCH006	2022-09-06	C103	English Literature	A1015	assignment	2024-03-04	100	2024-03-04	none	blank	false	Assignment submitted late due to excused absence; quality analysis.
S00016	blank	78	false	T004	Aiden	Rodriguez	2009-12-19	prefer not to say	9	SCH002	2022-08-22	C104	World History	A1016	final	2024-02-27	100	blank	none	blank	false	Shows strong understanding of course content; inclusive classroom member.
S00017	absent	20	true	T005	Ella	Brown	2012-06-15	female	6	SCH005	2023-09-11	C105	Physical Education	A1017	assignment	2024-02-23	80	2024-02-23	counseling	2024-03-01	true	Missed class and assignment; support plan initiated with counselor.
S00018	present	83	false	T006	James	Green	2008-02-24	male	10	SCH006	2023-08-25	C106	Spanish	A1018	test	2024-03-09	100	2024-03-09	none	blank	false	Demonstrates improvement in language skills; on track for proficiency.
S00019	present	86.5	false	T001	Charlotte	Rivera	2007-03-19	female	11	SCH002	2021-09-13	C101	Biology	A1019	project	2024-01-31	90	2024-01-31	none	blank	false	Led team in science project; strong communication skills.
S00020	absent	0	true	T002	Jack	Young	2012-01-02	male	6	SCH003	2023-09-05	C102	Mathematics	A1020	assignment	2024-02-21	70	2024-02-21	parent meeting	2024-02-27	true	Absent for math assessment; parent-teacher meeting scheduled.

What the 120 rows show

from the 120-row sample

Absent (attendance status) stands out: 17 of its 17 rows have intervention_flag = true, against 16 of 73 for the rest.

33%intervention_flag = true
70.8median score
4genders
6assessment types
6intervention types
8grade levels

Intervention flag rate by attendance_statusintervention_flag = true

score120 rows, in bands of 100

Median 70.8, from 0.0 to 1,000.

teacher_id120 rows · top 10 of 26 values

T0019
T0029
T0038
T0048
T0058
T0068
T1056
T1086
T1106
T1015

23 columns by typefrom the column list below

string 14
float 2
date 5
boolean 2

Columns

23 columns in four groups

blueprint · 23 columns
column	type	description	example
Text 14 columns
`student_id`	string	Unique identifier for each studentunique	S00001
`first_name`	string	Student's first name	Olivia
`last_name`	string	Student's last name	Lopez
`gender`	string	Student's gendermale · female · non-binary · prefer not to say · optional	female
`grade_level`	string	Current grade or year of the student (e.g., '10', '11', '12', 'Freshman', 'Sophomore')8 levels	10
`school_id`	string	Unique identifier for the school the student attends	SCH001
`course_id`	string	Unique identifier for the course10 courses	C101
`course_name`	string	Name of the course	Biology
`teacher_id`	string	Unique identifier for the course instructor	T001
`assessment_id`	string	Unique identifier for the assessment (test, quiz, assignment, etc.)	A1001
`assessment_type`	string	Type of assessment (e.g., 'quiz', 'test', 'assignment', 'project', 'final')6 values	test
`attendance_status`	string	Attendance status for the student on a given datepresent · absent · late · excused · optional	present
`intervention_type`	string	Type of intervention provided to the student (if any)6 values · optional	none
`notes`	string	Additional notes or comments regarding the student's performance or interventionsoptional	Consistent high performer…
Numbers 2 columns
`score`	float	Numeric score the student achieved on the assessment0 to 100	89.5
`score_max`	float	Maximum possible score for the assessment0 or more	100
Dates and times 5 columns
`date_of_birth`	date	Student's date of birth	2008-10-14
`enrollment_date`	date	Date the student enrolled at the school	2023-08-21
`assessment_date`	date	Date when the assessment was administered	2024-02-10
`attendance_date`	date	Date of attendance recordoptional	2024-02-10
`intervention_date`	date	Date when the intervention was initiatedoptional	2024-03-08
True or false 2 columns
`intervention_flag`	boolean	Indicates whether the student has been flagged for intervention	false
`at_risk_flag`	boolean	Indicates whether the student is currently identified as at-risk	false

Use it for

An education dashboard
The intervention_flag rate, score by attendance_status and a breakdown of teacher_id. Excel, Power BI or Tableau.
Why do 39 of 120 rows have intervention_flag = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Students120
S0000189.5present
S0000252absent
S0000561.5late
A software demo
Believable students with first_name, last_name and date_of_birth to fill a screen in front of a buyer.

This dataset120 rows23 columns

Yours10,000 rows23 columns

blueprint · student-performance-tracking

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 23 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 student must have scores for all subjects
Attendance below 75% triggers alert
Missing assignments logged per subject
Students with GPA <2.0 flagged for counseling

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

Open the blueprint in Data Factory

1 credit per row. New accounts start with 25 free credits.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: student-performance-tracking

What should your data show?

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Sample rows

What the 120 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?