Science and Practice of Resistance Training
Recorded 2026-10-14Science and Practice of Resistance Training
Covers principles of resistance training and physiological effects via lectures and demonstrations for practitioners seeking detailed scientific understanding.
Summary
Past student reviews · Patrick Hills-Meyer
The exam was tough due to the large volume of information, and it was unclear what specifically to study for preparation.
What you’ll be able to do
Detail scientific rationale behind resistance training program design variables.
Design a resistance training program.
Differentiate resistance training programs based on desired training outcomes.
Evaluate efficacy and safety of resistance training program.
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapNone
- None
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- None
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
PATRICK HILLS-MEYER is recorded teaching in Fall 2016. 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 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 0 / 20 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Meeting source records
Student experience
the class
Past student reviews · Patrick Hills-Meyer
Patrick Hills-Meyer delivered lengthy but fun lectures, using humor to engage students while occasionally appearing harsh due to jokes.
Recent recorded grades — Spring 2025: 4.00 GPA, 100.0% A/AB (n=17 letter grades); Fall 2025: 3.85 GPA, 100.0% A/AB (n=17 letter grades); Spring 2026: 3.97 GPA, 100.0% A/AB (n=19 letter grades).
difficulty & workload
Past student reviews · Patrick Hills-Meyer
The exam was tough due to the large volume of information, and it was unclear what specifically to study for preparation.
Past student reviews · Patrick Hills-Meyer
Students were advised to show interest in the content and perform well in labs, while the final assessment was an easy project.
Topics
- Principles of resistance training
- Physiological effects of resistance training
- Resistance training program design variables
Skills
- Detailing scientific rationale behind resistance training program design variables
- Designing resistance training programs
- Differentiating resistance training programs based on desired outcomes
- Evaluating efficacy and safety of resistance training programs
Grades
Latest available · Spring 2026— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Spring 2026
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
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.
Selected offering source records
Raw records
[
{
"run_id": "20261014T203208-0851c9a1",
"semester": "1274",
"observed_at": "2026-10-14 17:50:09.728220+00:00",
"offering_id": "1274:742:024125",
"course_id": "KINES 140",
"course_uid": "course_3afe20a1c233b4bf7d4876f5",
"term_id": "1274",
"source_course_id": "024125",
"source_subject_id": "742",
"title": "Science and Practice of Resistance Training",
"credits_min": 2,
"credits_max": 2,
"typically_offered": "Fall, Spring"
}
]Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "Qwen/Qwen3.8-27B",
"model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
"task_version": "17",
"output_id": "882111474894eba6d3b6cafcd248e96aee3db3b0dc97c678382a1fc34fb4742d",
"requirements_status": "valid",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
}