ygong/BloomVQA
Dataset Card for BloomVQA Dataset Description BloomVQA is a dataset based on picture stories designed for educating young children. It aims to facilitate comprehensive evaluation and characterization of vision-language models on comprehension tasks. The dataset contains tasks reflecting 6 different levels of comprehension and underlying cognitive processes, as laid out in Bloom's Taxonomy, a classic framework widely adopted in education research. This… See the full description on the dataset page: https://huggingface.co/datasets/ygong/BloomVQA.
Dataset Card for BloomVQA
Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
BloomVQA is a dataset based on picture stories designed for educating young children. It aims to facilitate comprehensive evaluation and characterization of vision-language models on comprehension tasks. The dataset contains tasks reflecting 6 different levels of comprehension and underlying cognitive processes, as laid out in Bloom's Taxonomy, a classic framework widely adopted in education research. This underlying hierarchical taxonomy enables graded model evaluation, automatic data augmentation and novel metrics characterizing model consistency.
The core dataset contains 1200 multiple-choice samples collected via Amazon Mechanical Turk based on 20 picture stories downloaded from Creative Commons resources Book Dash and Storyweaver.
<!-- Provide the basic links for the dataset. -->
Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
Each multiple-choice sample contains 1 question and 4 free-form answers including 1 correct answer and 3 incorrect answers. Each sample is labeled with the title of picture story and the level of comprehension as defined in Bloom's Taxonomy.