barthfab/PISA_tests

Dataset Card: PISA Multimodal (Parallel & Not-Parallel)

Summary

This dataset contains 48 parallel multimodal samples (paired TXT↔PDF) derived from PISA studies up to 2012, plus 47 non-parallel samples (TXT-only or PDF-only). Each sample may include multiple questions. Content is available in German and English.

Source & usage: Materials are published by the OECD and are provided here for non-commercial use only. Please verify that your usage complies with OECD terms.

Quality note: Some of the parallel samples are noisy (e.g., OCR artifacts or imperfect alignments). These are explicitly labeled in the filename so they can be filtered out during experiments.

Organization & Splits

• train — parallel split: 48 samples (TXT and matching PDF).
• not_parallel — 47 samples where only TXT or only PDF is present.
  Note: In this split, one of Content or PDF can be null. (Counts reflect the provided corpus; they may change if you add/remove files.)

Languages

• German: deu_Latn
• English: eng_Latn

Tasks

• Reading comprehension
• Math problem solving

Data Fields (Columns)

• ID (int32) — Running index of the sample (per build script).
• Task Name (string) — Base name of the material (filename stem before the last underscore), e.g., Bookshelves.
• PDF (Pdf feature) — Full PDF object (stored via datasets.Pdf). May be null in not_parallel if missing.
• Language (string) — Language code of the folder, e.g., deu_Latn or eng_Latn.
• Task (string) — Task category from the folder name: reading or math.
• Content (string) — Full text from the paired .txt. May be null in not_parallel if missing.
• TXT Filename (string) — Basename of the associated .txt file (if present).
• PDF Filename (string) — Basename of the associated .pdf file (if present).

Source Data & Provenance

• Origin: Items compiled from OECD PISA materials (≤2012).
• Derivation: Parallel pairs were formed by matching TXT and PDF stems; the not_parallel split contains items missing one counterpart.

Licensing & Usage

• License: Other / Non-commercial. The content is published by the OECD. Redistribution and use should comply with OECD non-commercial terms. This card is not legal advice—please review the official terms for your use case.

How to Load

from datasets import load_dataset
# From the Hub (replace with your repo id)
ds = load_dataset("your-username/your-dataset")
# Parallel split
train = ds["train"]
# Not-parallel split
not_parallel = ds["not_parallel"]
# Example access
row = train[0]
print(row["Task Name"], row["Language"], row["Task"])
# PDF is a Pdf feature record with a path/bytes:
print(row["PDF"])

Intended Uses & Limitations

• Intended: research on multimodal QA, OCR+NLP, cross-lingual evaluation, dataset tooling.
• Not intended: commercial exploitation of OECD content; deployment without verifying rights.
• Limitations: Some samples include multiple questions per PDF/TXT; not_parallel items are incomplete by design; some parallel items are flagged as noisy in filenames.

Citation

If you use this dataset, please cite the OECD PISA materials appropriately and reference this dataset card.