To facilitate the studies on modelling the learners and understanding on their learning process, we report the SLP (Smart Leaarning Partner) Dataset, that has collected learners' demographic information, cognitive intelligence information, family and school information. Moreover, by leveraging on an online learning platform, the dataset also aggregated the regularly captured academic performance data of learners during their three-year study on eight different subjects, including Chinese, mathematics, English, physics, chemistry, biology, history and geography.
The dataset is free to use. For more information, please see Section "Column Headings" below.
If this dataset is helpful for you, please cite our work：
Yu Lu, Yang Pian, Ziding Shen, Penghe Chen, Xiaoqing Li, “SLP: A Multi-Dimensional and Consecutive Dataset from K-12 Education,” in Proceedings of the 29th International Conference on Computers in Education Conference (ICCE'2021), vol. 1. Asia-Pacific Society for Computers in Education, 2021, pp. 261–266. [PDF]
BibTeX (.bib)：| No. | Field Name | Description |
|---|---|---|
| 1 | student_id | The unique identification number of student |
| 2 | student_gender | The gender of student |
| 3 | school_id | The unique identification number of student’s school |
| 4 | class_id | The unique identification number of student’s class |
| No. | Field Name | Description |
|---|---|---|
| 1 | school_id | The unique identification number of student |
| 2 | school_type | The type of school, typically including regular junior secondary school, combined secondary school, nine-year school, and secondary school for minority |
| 3 | dist_to_downtown | The distance from school to the region’s downtown |
| 4 | rate_higher_education | The proportion of the teachers with a bachelor degree or above |
| 5 | rate_master_degree_or_above | The proportion of the teachers with a master degree or above |
| No. | Field Name | Description |
|---|---|---|
| 1 | student_id | The unique identification number of student |
| 2 | subject_abbr | The abbreviation of subject |
| 3 | exam_id | The unique identification number of test |
| 4 | question_id | The unique identification number of question |
| 5 | concept | The concept(s) associated with the question |
| 6 | score | The student’s score on the question |
| 7 | full_score | The full score of the question |
| 8 | time_access | The system access time of the student |
| No. | Field Name | Description |
|---|---|---|
| 1 | student_id | The unique identification number of student |
| 2 | age_father | The age of student’s father |
| 3 | age_mother | The age of student’s mother |
| 4 | edubg _father | Father’s education background |
| 5 | edubg _mother | Mother’s education background |
| 6 | affiliation_father | The employer’s type typically including public sector, state-owned enterprise, collective enterprise, private enterprise, foreign-funded enterprise, etc. |
| 7 | affiliation_mother | The employer’s type typically including public sector, state-owned enterprise, collective enterprise, private enterprise, foreign-funded enterprise, etc. |
| 8 | family_income | The annual income of the student’s family |
| 9 | is_only_child | Whether the student is the only child of the family |
| 10 | live_on_campus | Whether the student lives on campus or not |
| 11 | gathering_frequency_father | How often the student gathering with his/her father |
| 12 | gathering_frequency_mother | How often the student gathering with his/her mother |
| 13 | family_traveling_times | How many times the student went traveling with the family last year |
| No. | Field Name | Description |
|---|---|---|
| 1 | student_id | The unique identification number of student |
| 2 | psy_score | The student’s cognitive intelligence score |
