Name: Predict Students Dropout And Academic Success
Creator: Kaggle
License: https://www.apache.org/licenses/

About this Dataset

Predict Students Dropout And Academic Success

Dataset Column Descriptions

This dataset includes various features that were known at the time of student enrollment. Below is a description of each column in the dataset:

Marital Status: The marital status of the student (e.g., single, married, divorced).
Application Mode: Refers to the mode or type of application the student submitted to enroll in the course.
Application Order: Indicates the order in which the student applied for the course. For example, whether it was the student’s first, second, or third choice.
Course: The course or degree program the student is enrolled in (e.g., Computer Science, Engineering, etc.).
Daytime/Evening Attendance: Specifies whether the student attends the course during the day or in the evening, representing their attendance schedule.
Previous Qualification: The type of academic qualification the student had before enrolling in the course (e.g., high school diploma, vocational training).
Previous Qualification (Grade): The final grade or score associated with the student's previous qualification.
Nationality: The nationality of the student.
Mother's Qualification: The highest academic qualification attained by the student's mother.
Father's Qualification: The highest academic qualification attained by the student's father.

These features represent important demographic, academic, and socio-economic factors, which are crucial for predicting a student's academic outcome.

Tables

Predict Student Dropout And Academic Success

@kaggle.syedfaizanalii_predict_students_dropout_and_academic_success.predict_student_dropout_and_academic_success

123.3 kB
4,424 rows
37 columns

CREATE TABLE predict_student_dropout_and_academic_success (
  "marital_status" BIGINT,
  "application_mode" BIGINT,
  "application_order" BIGINT,
  "course" BIGINT,
  "daytime_evening_attendance" BIGINT,
  "previous_qualification" BIGINT,
  "previous_qualification_grade" DOUBLE  -- Previous Qualification (grade),
  "nacionality" BIGINT,
  "mother_s_qualification" BIGINT  -- Mother\u0027s Qualification,
  "father_s_qualification" BIGINT  -- Father\u0027s Qualification,
  "mother_s_occupation" BIGINT  -- Mother\u0027s Occupation,
  "father_s_occupation" BIGINT  -- Father\u0027s Occupation,
  "admission_grade" DOUBLE,
  "displaced" BIGINT,
  "educational_special_needs" BIGINT,
  "debtor" BIGINT,
  "tuition_fees_up_to_date" BIGINT,
  "gender" BIGINT,
  "scholarship_holder" BIGINT,
  "age_at_enrollment" BIGINT,
  "international" BIGINT,
  "curricular_units_1st_sem_credited" BIGINT  -- Curricular Units 1st Sem (credited),
  "curricular_units_1st_sem_enrolled" BIGINT  -- Curricular Units 1st Sem (enrolled),
  "curricular_units_1st_sem_evaluations" BIGINT  -- Curricular Units 1st Sem (evaluations),
  "curricular_units_1st_sem_approved" BIGINT  -- Curricular Units 1st Sem (approved),
  "curricular_units_1st_sem_grade" DOUBLE  -- Curricular Units 1st Sem (grade),
  "curricular_units_1st_sem_without_evaluations" BIGINT  -- Curricular Units 1st Sem (without Evaluations),
  "curricular_units_2nd_sem_credited" BIGINT  -- Curricular Units 2nd Sem (credited),
  "curricular_units_2nd_sem_enrolled" BIGINT  -- Curricular Units 2nd Sem (enrolled),
  "curricular_units_2nd_sem_evaluations" BIGINT  -- Curricular Units 2nd Sem (evaluations),
  "curricular_units_2nd_sem_approved" BIGINT  -- Curricular Units 2nd Sem (approved),
  "curricular_units_2nd_sem_grade" DOUBLE  -- Curricular Units 2nd Sem (grade),
  "curricular_units_2nd_sem_without_evaluations" BIGINT  -- Curricular Units 2nd Sem (without Evaluations),
  "unemployment_rate" DOUBLE,
  "inflation_rate" DOUBLE,
  "gdp" DOUBLE,
  "target" VARCHAR
);