Fall 2026

Design of Research in Curriculum and Instruction

An introductory survey of the empirical foundations of research in curriculum and instruction, focusing on the development of research methods and tools.

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

Summary

Recent recorded grades — Fall 2011: 3.81 GPA, 100.0% A/AB (n=8 letter grades); Fall 2012: 3.63 GPA, 80.0% A/AB (n=15 letter grades); Spring 2014: 4.00 GPA, 100.0% A/AB (n=6 letter grades).

Grade history

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average GPA
letter grades
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AB
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Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
CURRIC 715

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

Prerequisite text tree
  • Graduate/professional standing

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Fall 2026

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SectionModeEnrolled / capacityWaitlist

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Meeting source records

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Student experience

the class

Recent recorded grades — Fall 2011: 3.81 GPA, 100.0% A/AB (n=8 letter grades); Fall 2012: 3.63 GPA, 80.0% A/AB (n=15 letter grades); Spring 2014: 4.00 GPA, 100.0% A/AB (n=6 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Empirical foundations of research

Skills

  • Research methods and tools

Grades

Latest available · Spring 2014— 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 2014

More grade details Grade mix, volume & source data

Sources & history

UW–Madison

Catalog & offerings

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Catalog observation history

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Student reviews

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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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
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "ffd3eaa585ef48153c3ed823228fb7734ef3bdf912f73da267d646a50b8c22d0",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}