Datasets
Overview
- Train machine learning algorithms to evaluate student essays for writing and language proficiency.
- Analyze a dataset of persuasive essays by students to examine the writing and linguistic differences between different student populations in the United States.
- Train generative AI algorithms to create reading comprehension questions for elementary and middle school students.
- Analyze students’ enjoyment, engagement, and learning progress on game-based learning platforms (Ex. Jo Wilder and the Capitol Case).
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Datasets
The Quest Dataset
The Learning Agency Lab’s data science competition, “The Quest for Quality Questions: Improving Reading Comprehension through Automated Question Generation,” was designed to build AI algorithms that can automatically generate questions for testing young learners’ reading comprehension.
Jo Wilder Dataset
Just as there are many ways to learn there are many ways to assess learning. Game-based learning is different in that it allows students to engage with educational content in a dynamic way that traditional classroom experiences do not typically provide.
PERSUADE Dataset
Why do students write the way they do? And are they any good at it? Understanding the nuance of how students write remains a complex challenge – one that can be aided by deeper insight into how various writing components ultimately come together to form effective essays and other text.