metadata

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 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, Jiřina Karasová and Michal Štefánik from Masaryk University.