Spring 2027

Introduction to Human Factors

Introduction to Human Factors covers human capabilities and limits in system design, exploring cognitive, physical, and psychosocial perspectives to support user needs and evaluate system performance.

offering recorded3 credits
Recorded instructors · Spring 2027 John Lee3.7/5

Summary

1 / 6

Past student reviews · John Lee

Grades were split between exams, weekly online reading quizzes, design examples, and weekly case study analyses.

What you’ll be able to do

  • Recognize the strengths and limits of human perceptual, cognitive and physical abilities and their implications for system design

  • Describe human factors tools, techniques and methods commonly used to design and improve system performance

  • Evaluate and recommend work and task designs based on human factors and ergonomic principles

  • Define the ethical application of human factors in designing products and processes

Source: UW Guide 1 UW Guide 2

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
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F

All recorded terms · compare terms & instructors

Prerequisites

Course map

(I SY E 210,B M E 325,E C E 331,MATH/​STAT 309, 409, 431,STAT 311, 324, 371,MATH 331, 531,PSYCH 210, orC&E SOC/​SOC 360, or concurrent registration), graduate/professional standing, or member of Engineering Guest Students

ISYE/PSYCH 349 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027
Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 3.88/5 from 8 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

For this course: 2.3/5 raw quality · 2.7/5 difficulty · 3 reviews

RMP profile ↗ · All captured review dates; profile matched by name.

Past student reviews · John Lee

John Lee graded the course using exams, weekly online reading quizzes, design examples, and case study analyses. Students found the lectures boring and noted that completing the weekly readings, quizzes, and case studies provided sufficient preparation for the exams.

A recent student reported that John Lee deviated from the syllabus by reducing the number of graded assignments and changing an in-class exam to a final, which they found frustrating.

Recent recorded grades — Spring 2017: 3.66 GPA, 86.7% A/AB (n=83 letter grades); Spring 2018: 3.47 GPA, 73.2% A/AB (n=97 letter grades); Spring 2026: 3.77 GPA, 88.8% A/AB (n=98 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

Past student reviews · Hannah Silber, Ranjana Mehta

Hannah Silber’s tests and homework were clear, and one student found the material interesting and liked the workload. A student found lectures could drag on. Ranjana Mehta’s class included unannounced activities worth 50% of the grade, fill-in-the-blank exam sections, and no practice problems.

DOUGLAS WIEGMANN is recorded teaching in Spring 2011, Spring 2012, Spring 2013, Fall 2016, Fall 2017, Fall 2018, Fall 2020, Fall 2021. Recorded history may be incomplete and does not establish a future schedule.

HANNAH SILBER is recorded teaching in Fall 2016, Spring 2019, Fall 2019, Spring 2020, Spring 2022, Fall 2022, Spring 2023, Fall 2023, Spring 2024, Spring 2025, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

JOHN LEE is recorded teaching in Fall 2012, Fall 2013, Fall 2014, Spring 2017, Spring 2018, Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

RANJANA MEHTA is recorded teaching in Fall 2024. 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
LEC 001Classroom Instruction0 / 1200
LEC 001Classroom Instruction0 / 1200

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

Meeting source records
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Student experience

the class

Past student reviews · John Lee

Students found the lectures boring but noted that completing weekly readings, quizzes, and case studies provided sufficient preparation for exams.

Recent recorded grades — Spring 2025: 3.89 GPA, 96.7% A/AB (n=120 letter grades); Fall 2025: 3.93 GPA, 97.2% A/AB (n=108 letter grades); Spring 2026: 3.77 GPA, 88.8% A/AB (n=98 letter grades).

difficulty & workload

Past student reviews · John Lee

Grades were split between exams, weekly online reading quizzes, design examples, and weekly case study analyses.

Past student reviews · John Lee

One student reported that John Lee changed the syllabus, required his own textbook, and altered scheduled in-class exams.

Topics

  • Human characteristics from cognitive, physical, and psychosocial perspectives.
  • Case studies identifying the human role in accidents and design improvements.
  • Applications in consumer product design, human-computer interaction, workplace safety, and healthcare delivery.

Skills

  • Recognizing human perceptual, cognitive, and physical abilities and their implications for system design.
  • Describing human factors tools, techniques, and methods for designing and improving system performance.
  • Evaluating and recommending work and task designs based on human factors and ergonomic principles.
  • Defining the ethical application of human factors in designing products and processes.

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 · 0.18 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
ISYE/PSYCH 349 · Spring 2027

Introduction to Human Factors

Recorded 2026-10-29
ISYE/PSYCH 349 · Spring 2027

Introduction to Human Factors

Recorded 2026-10-29
Raw records 
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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 2026-10-29

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
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  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "5f346bc1a89dcaa161ca54d70eccfbd6572b29ae77e768f7d38c545dd9249539",
  "requirements_status": "needs_review",
  "dataset_revision": "c9cd06eaa45f9ddf7e69faa38b89ff3d3dd995dd",
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}