Topics in Information Studies - Technological Aspects
LIS 341 explores information technology and management topics such as digital productivity, publishing, and preservation.
Summary
Historical reviews of Jiepu Jiang: Reviewers characterized the course as easy to pass and low-stress compared to typical STEM classes. One student found it hard due to a lack of programming experience in text mining.
Grade history
↗letter grades
All recorded terms · compare terms & instructors
Prerequisites
Course mapSophomore standing
- Sophomore standing
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Sophomore standing
Professors
Fall 2026No instructors recorded for this selection.
Historical instructors & teaching patterns
Historical reviews of Jiepu Jiang: Jiepu Jiang receives high praise for being accessible, responsive, and effective at explaining course material. Reviewers describe him as well-versed and understanding, with one calling him one of the best professors at UW-Madison. However, the course content itself is noted as challenging for students lacking programming experience in text mining.
JIEPU JIANG is recorded teaching in Fall 2020. 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 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
No records available.
Student experience
the class
Historical reviews for Jiepu Jiang describe a highly accessible and well-versed instructor who explains concepts clearly and supports student learning. Students found the course easy to pass and enjoyable, though one noted difficulty without prior programming experience.
Recent recorded grades — Spring 2020: 3.74 GPA, 82.4% A/AB (n=17 letter grades); Fall 2020: 3.81 GPA, 93.8% A/AB (n=16 letter grades); Fall 2021: 3.93 GPA, 96.7% A/AB (n=30 letter grades).
difficulty & workload
Historical reviews of Jiepu Jiang: Reviewers characterized the course as easy to pass and low-stress compared to typical STEM classes. One student found it hard due to a lack of programming experience in text mining.
Historical reviews of Jiepu Jiang: Students praised the instructor's quick responses to questions and understanding nature. The class was described as a favorite for learning new tech tools without the stress of traditional STEM teaching styles.
Topics
Grades
Latest available · Fall 2021— not enough history to project Fall 2026.
Grade distribution · % of letter grades
Grades over time
Through Fall 2021
More grade details Grade mix, volume & source data
Where this course fits relative to
Latest available grades · Fall 2021 · 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
1157 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
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
No offering records for the selected term.
Raw records
[]
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 gradesModel outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "8ee4e9d460b433422cf64a6a0f0cc81c98aa8274f27231330935ec6f56f1d977",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}