Fall 2026

Grammatical Variability of Language

Introduction to theories of grammatical variation among world languages, focusing on syntactic phenomena.

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

Summary

Recent recorded grades — Spring 2019: 4.00 GPA, 100.0% A/AB (n=13 letter grades); Fall 2020: 4.00 GPA, 100.0% A/AB (n=13 letter grades); Spring 2023: 3.93 GPA, 100.0% A/AB (n=7 letter grades).

Grade history

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average GPA
letter grades
A
AB
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Prerequisites

Course map

LINGUIS 101 or 301

LINGUIS 309

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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

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SectionModeEnrolled / capacityWaitlist

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Meeting source records

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Student experience

the class

Recent recorded grades — Spring 2019: 4.00 GPA, 100.0% A/AB (n=13 letter grades); Fall 2020: 4.00 GPA, 100.0% A/AB (n=13 letter grades); Spring 2023: 3.93 GPA, 100.0% A/AB (n=7 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Syntactic phenomena in world languages

Skills

  • Understanding theories of syntactic variation across languages.

Grades

Latest available · Spring 2023— 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 2023

More grade details Grade mix, volume & source data

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

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Student reviews

Original comments behind the course and instructor summaries.

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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": "cb4972da8cc3ba8a52353418486cec02693b2fcef5cb48e775115aab23ade885",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}