Spring 2027

Applied Quantitative Education Research

Introduces quantitative research methods in empirical education research, focusing on data exploration, manipulation, visualization, and simple analyses with secondary datasets using R or other programming languages.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

What you’ll be able to do

  • Apply basic quantitative research methods to education research

  • Employ statistical software to import, manage, transform, visualize and analyze education data and research.

  • Develop skills necessary to interpret secondary datasets in education research using appropriate quantitative methods.

Source: UW Guide

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Prerequisites

Course map

ED POL 209

EDPOL 309 used by

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Professors

Spring 2027

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Calendar & sections

Spring 2027

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Student experience

the class

Introduces how quantitative research methods are applied in empirical education research. Focused on data exploration, manipulation, visualization, and simple analyses with secondary datasets and R or other programming language.

difficulty & workload

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Topics

  • Quantitative research methods in empirical education research
  • Data exploration, manipulation, visualization, and simple analyses with secondary datasets
  • Programming with R or other languages

Skills

  • Applying basic quantitative research methods to education research
  • Using statistical software to import, manage, transform, visualize, and analyze education data
  • Interpreting secondary datasets in education research using quantitative methods

Grades

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Sources & history

UW–Madison

Catalog & offerings

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
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Full model traces

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "d8a16bd19bfb43884f8557631d49cbbb7dd22f78fa595f0cf5ef5917eda2cd9c",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}