Spring 2027

Basic Concepts of Music Theory

Survey of basic music theory tools, compositional forms, and musical styles with practical listening maps and composition projects.

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

Summary

1 / 6

Past student reviews · Jamie Henke

Grades relied heavily on take-home projects that required significant time, so students advised completing them promptly rather than delaying. While exams were straightforward, keeping up with assigned homework was essential for success.

What you’ll be able to do

  • Use a complete set of tools provided for a lifelong knowledge and interest in music, and having transformed as a student from a passive to active listener.

  • Discuss the evolution of music and music theory and relate this to where music is today.

  • Create original compositions applying concepts learned.

Source: UW Guide

Grade history

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

All recorded terms · compare terms & instructors

Prerequisites

Course map

None

  • None
MUSIC 151

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

Prerequisite text tree
  • None

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

JAMIE HENKE is recorded teaching in Fall 2006, Spring 2007, Fall 2007, Spring 2008, Fall 2008, Spring 2009, Fall 2009, Spring 2010, Fall 2010, Spring 2011, Fall 2011, Spring 2012, Fall 2012, Spring 2013, Fall 2013, Spring 2014, Fall 2014, Spring 2015, Fall 2015, Spring 2016, Fall 2016, Spring 2017, Fall 2017, Spring 2018, Fall 2018, Spring 2019, Fall 2019, Spring 2020, Fall 2020, Fall 2021, Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Fall 2024, Spring 2025, Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

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

Calendar & sections

Spring 2027

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
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Student experience

the class

Past student reviews · Jamie Henke

Students described Dr. Henke as knowledgeable and engaging, with clear expectations for tests. The course involved fun group activities and was generally considered easy to navigate if you attended class.

Recent recorded grades — Spring 2025: 3.56 GPA, 80.0% A/AB (n=90 letter grades); Fall 2025: 3.60 GPA, 80.0% A/AB (n=110 letter grades); Spring 2026: 3.59 GPA, 78.5% A/AB (n=93 letter grades).

difficulty & workload

Past student reviews · Jamie Henke

Grades relied heavily on take-home projects that required significant time, so students advised completing them promptly rather than delaying. While exams were straightforward, keeping up with assigned homework was essential for success.

Past student reviews · Jamie Henke

Dr. Henke was accommodating and quick to provide feedback, but she was very picky about music journals, requiring careful checking. Some students found unresponsive classmates frustrating during group projects.

Topics

  • Music theory fundamentals and compositional forms.
  • Development of music and survey of musical styles.
  • Listening maps and simple composition projects.

Skills

  • Application of basic music theory tools and compositional forms.
  • Creation of listening maps and simple musical compositions.
  • Transitioning from passive to active music listening.

Grades

Historical instructor

Spring 2027 · Projected

Before grades are released

– average GPA

Approximate 80% prediction interval

About this estimate

The course’s semester-average GPA, not an individual student’s grade. The center uses 5 same-season terms, weighted toward recent results.

The range uses the finite-sample 80th-percentile rank of absolute errors from earlier same-season forecasts. Each forecast uses only records from earlier terms. At least four forecasts are required; bounds are rounded outward and limited to 0–4. This is an empirical estimate: changing instructors or grading policies can reduce its coverage.

8 earlier forecasts · 0.06 GPA average error.

Grades over time

Through Spring 2027

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1280 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

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.

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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
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
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

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "75cc9937bade14cc5226489b70766cfe1f8cb4f98cf9347dbae06ff3624c7f2b",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}