---
language:
- en
- cs
task_categories:
- text-classification
pretty_name: Edustories
dataset_info:
  features:
  - name: id
    dtype: int64
  - name: description
    dtype: string
  - name: anamnesis
    dtype: string
  - name: problems_annotated
    dtype: string
  - name: problems_possible_annotated
    dtype: string
  - name: solution
    dtype: string
  - name: solutions_annotated
    dtype: string
  - name: solutions_possible_annotated
    dtype: string
  - name: outcome
    dtype: string
  - name: implications_annotated
    dtype: string
  - name: implications_possible_annotated
    dtype: string
  - name: age, school year
    dtype: string
  - name: hobbies
    dtype: string
  - name: diagnoses
    dtype: string
  - name: disorders
    dtype: string
  - name: approbation
    dtype: string
  - name: practice_years
    dtype: string
  - name: description_cs
    dtype: string
  - name: anamnesis_cs
    dtype: string
  - name: solution_cs
    dtype: string
  - name: outcome_cs
    dtype: string
  - name: annotator_id
    dtype: string
  splits:
  - name: train
    num_bytes: 9251557
    num_examples: 1492
  download_size: 4842560
  dataset_size: 9251557
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: mit
---

# Dataset Card for Edustories dataset

This repository contains data available in the [Edustories.cz](https://edustories.cz/) platform. 
The data contains structured descriptions of situations from classses documented by candidate teachers.
Each of the entries, also called casuistics, is structured into a `description` of the background, `anamnesis` describing the situation, 
a `solution` describing the intervention of the teacher in the situation, and `outcome` describing the final state of the intervetion.

Each of the entries was semi-automatically parsed from the original, free-text journal and associated with additional information from our database.
All the entries were anonymised.

In addition, our annotators manually associated each entry with a set of multiple categories that best fit the described situation, intervention and outcome.

## About the dataset

The dataset comes from student teachers, who collect case studies from their supervising teachers at their teaching practicum. These data are collected through standardized forms that the student teachers complete with their accompanying teachers. The collection of the dataset runs between 2023-2026. All students involved in the collection are informed of the use of the data and have given written consent. Additional case studies will be collected on an ongoing basis, through registered users of the Edustories.cz platform that choose to publish their anonymous case studies. All data is subject to multiple stages of anonymisation, so they do not contain any real names of schools, school staff or students.

## Dataset format

The dataset contains the following attributes:

* **Identifier** `id`. Selected entries have duplicate annotations, allowing to evaluate cross-annotator agreements
* **Structured story**: `description`, `anamnesis`, `solution` and `outcome` that describe the situation, intervention and its outcome in a free text
* **Annotated labels**: `problems_annotated`, `solutions_annotated`, `implications_annotated` associating each problem, solution and outcome into a set of pre-defined categories.
* **Uncertain labels**: `problems_possible_annotated`, `solutions_possible_annotated`, `implications_possible_annotated` containing assignments to the same, categories but where the annotators were not sure of the correctness of their assignment.
* **Student attributes** (currently in CS): `age, school year`, `hobbies`, `diagnoses`, `disorders` detailing the profile of the student(s) acting in the entry
* **Teacher attributes** (currently in CS): `approbation` and `practice_years` of the teacher acting in the entry
* **Structured story in Czech**: `description_cs`, `anamnesis_cs`, `solution_cs` and `outcome_cs` containing structured parts of the story in the original, Czech language.

## Notes

This dataset is a work-in-progress: Currently, it contains a small portion of missing entries that will be filled in the next annotation round(s). 
As our databases of teaching stories grows, we plan to extend the dataset with more, likely unlabeled stories. 
If requested by our users, we will also consider translating Czech-specific (Student and Teacher) attributes to English.

Please feel free to leave a comment in the Community section in case you have any questions or suggestions.

This dataset is curated and maintained by [Jan Nehyba](https://www.muni.cz/en/people/106930-jan-nehyba), [Jiřina Karasová](https://www.muni.cz/en/people/514894-jirina-karasova) and [Michal Štefánik](https://michal-stefanik.github.io/) from Masaryk University.