Fall 2026

Item Response Theory Methods and Applications

EDPSYCH 871 introduces item response theory (IRT) as a measurement framework, contrasting it with classical test theory and factor analysis.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

Recent recorded grades — Spring 2008: 3.94 GPA, 100.0% A/AB (n=9 letter grades); Spring 2011: 3.92 GPA, 100.0% A/AB (n=6 letter grades); Spring 2020: 4.00 GPA, 100.0% A/AB (n=12 letter grades).

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

ED PSYCH 761 or PSYCH 610

EDPSYCH 871

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.

Meeting source records

No records available.

Student experience

the class

Recent recorded grades — Spring 2008: 3.94 GPA, 100.0% A/AB (n=9 letter grades); Spring 2011: 3.92 GPA, 100.0% A/AB (n=6 letter grades); Spring 2020: 4.00 GPA, 100.0% A/AB (n=12 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Classical test theory and factor analysis as alternative measurement theories.
  • Dichotomous and polytomous IRT models and multidimensional extensions.
  • Differential item functioning and computerized adaptive/multi-stage testing.
  • Integration of process-related data and novel item formats.

Skills

  • Examination of dichotomous and polytomous IRT models and multidimensional extensions.
  • Application of maximum likelihood and Bayesian estimation methods.
  • Application of IRT in test construction, linking, equating, and adaptive testing.
  • Integration of process-related data and novel item formats in IRT modeling.

Grades

Latest available · Spring 2020— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2020

More grade details Grade mix, volume & source data

Not enough comparable courses for Fall 2026 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records

No offering records for the selected term.

Raw records 
[]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews

No records available.

Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "ec8cefc415e1f5fd7f6ede769a38268720682daf70d11f4f4d4b98c307ba03f3",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}