Fall 2026

An Introduction to Geographic Information Systems

An introduction to Geographic Information Systems focusing on the design and implementation of automated procedures for spatial data storage, analysis, and display.

offering recorded4 credits
Recorded instructors · Fall 2026 A-Xing Zhu3.4/5Qianheng ZhangYing Nie

Summary

1 / 7

The course is challenging with tough exams and harsh grading. Labs are difficult to follow with general instructions, and the workload includes pop quizzes.

Grade history

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average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

Sophomore standing, member of Engineering Guest Students, or declared in Capstone Certificate in GIS Fundamentals

    • Sophomore standing
    • member of Engineering Guest Students
    • declared in Capstone Certificate in GIS Fundamentals
    take one
CIVENGR/ENVIRST/GEOG 377 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
  • Any of
    • Sophomore standing
    • member of Engineering Guest Students
    • declared in Capstone Certificate in GIS Fundamentals

Professors

Fall 2026
/5Adjusted rating
/5RMP difficulty
captured reviews
About this rating

Raw average: 3.14/5 from 21 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: 3.0/5 raw quality · 3.4/5 difficulty · 13 reviews

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

A-Xing Zhu receives criticism for unclear explanations, difficult-to-understand lectures, and poor exam question phrasing. Reviewers describe his teaching style as boring and hard to follow, with some finding his accent and writing style significant barriers to comprehension.

Other reviewers praise Zhu as an excellent, enthusiastic instructor who knows his material and is willing to help. They note that while his accent can be challenging, it does not hinder understanding, and he effectively simplifies complex topics with real-life examples.

Recent recorded grades — Fall 2024: 3.02 GPA, 32.4% A/AB (n=74 letter grades); Fall 2025: 3.29 GPA, 50.7% A/AB (n=75 letter grades); Spring 2026: 3.52 GPA, 76.6% A/AB (n=77 letter grades).

No course-specific feedback yet.

Historical instructors & teaching patterns

A-Xing Zhu is the current instructor, but no reviews exist for his teaching. Historical reviews for Guiming Zhang describe him as a good instructor, though TAs were more crucial to student success. The course is in-depth with helpful labs.

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

GUIMING ZHANG is recorded teaching in Spring 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Online Only10 / 800
LAB 301Classroom Instruction4 / 200
LAB 302Classroom Instruction2 / 200
LAB 303Classroom Instruction3 / 200
LAB 304Classroom Instruction1 / 200
LEC 001Online Only13 / 802
LAB 301Classroom Instruction1 / 200
LAB 302Classroom Instruction3 / 200
LAB 303Classroom Instruction5 / 202
LAB 304Classroom Instruction4 / 200
LEC 001Online Only77 / 8010
LAB 301Classroom Instruction20 / 202
LAB 302Classroom Instruction18 / 204
LAB 303Classroom Instruction16 / 200
LAB 304Classroom Instruction23 / 204

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

A-Xing Zhu is passionate and helpful, but reviews disagree on his lecture clarity and engagement. Some find his explanations clear and enthusiastic, while others find them boring or hard to understand due to his accent.

Recent recorded grades — Spring 2025: 3.43 GPA, 75.0% A/AB (n=80 letter grades); Fall 2025: 3.29 GPA, 50.7% A/AB (n=75 letter grades); Spring 2026: 3.52 GPA, 76.6% A/AB (n=77 letter grades).

difficulty & workload

The course is challenging with tough exams and harsh grading. Labs are difficult to follow with general instructions, and the workload includes pop quizzes.

Students report conflicting experiences with labs; some find them useful and applicable, while others find them frustrating and unhelpful for learning GIS skills. The course also relies heavily on memorizing lecture content.

Topics

  • Spatial information
  • Spatial databases
  • Information manipulation and display techniques
  • Geospatial software systems and management

Skills

  • Design and implement automated procedures for spatial data storage, analysis, and display
  • Manage spatial databases and geospatial software systems

Grades

Historical instructor

Fall 2026 · 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 · 0.23 GPA average error.

Grades over time

Through Fall 2026

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

1283 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.

Download part 1
Selected offering source records
CIVENGR/ENVIRST/GEOG 377 · Fall 2026

An Introduction to Geographic Information Systems

Recorded 2026-09-07
CIVENGR/ENVIRST/GEOG 377 · Fall 2026

An Introduction to Geographic Information Systems

Recorded 2026-09-07
CIVENGR/ENVIRST/GEOG 377 · Fall 2026

An Introduction to Geographic Information Systems

Recorded 2026-09-07
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 2026-09-07

Download the original dataset
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "30385091a206d14f13a21e929676bef379c0a80a6c7d8ab6f0e8a523f2d2687c",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}