Data Storytelling with Visualization

LIS 407 introduces data storytelling through visualization, teaching students to summarize, analyze, and communicate data effectively using software tools while addressing bias and limitations.

offering recorded3 credits
Recorded instructors · Fall 2026 Chaoqun NiJialin Liu

Summary

1 / 6

Historical reviews of Xiang Zheng: Workload is manageable if students complete homework on time and attend class to follow demonstrations, though understanding concepts requires effort.

Grade history

average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

Sophomore standing and satisfied Quantitative Reasoning (QR) A

    • Sophomore standing
    • satisfied Quantitative Reasoning (QR) A
    take all
LIS 407

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

Prerequisite text tree
  • All of
    • Sophomore standing
    • satisfied Quantitative Reasoning (QR) A

Professors

Fall 2026

Recent recorded grades — Spring 2023: 3.48 GPA, 75.0% A/AB (n=24 letter grades); Spring 2024: 3.69 GPA, 83.3% A/AB (n=42 letter grades); Fall 2025: 3.66 GPA, 86.0% A/AB (n=86 letter grades). Includes jointly taught sections.

Recent recorded grades — Spring 2025: 3.65 GPA, 81.4% A/AB (n=86 letter grades); Fall 2025: 3.66 GPA, 86.0% A/AB (n=86 letter grades). Includes jointly taught sections.

Historical instructors & teaching patterns

No reviews exist for current instructors Chaoqun Ni or Jialin Liu. Historical reviews for Jeffrey Kritzman and Xiang Zheng describe generally positive experiences with clear instruction and helpfulness, though Kritzman was noted as repetitive with readings.

CHAOQUN NI is recorded teaching in Spring 2023, Spring 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

JEFF KRITZMAN is recorded teaching in Spring 2025. Recorded history may be incomplete and does not establish a future schedule.

JIALIN LIU is recorded teaching in Spring 2025, Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

XIANG ZHENG is recorded teaching in 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

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 002Classroom Instruction120 / 12010

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

Historical reviews describe the course as easy and enjoyable, with supportive instructors and engaging projects, though some note repetitive readings.

Recent recorded grades — Spring 2025: 3.64 GPA, 82.0% A/AB (n=128 letter grades); Fall 2025: 3.57 GPA, 82.1% A/AB (n=156 letter grades); Spring 2026: 3.43 GPA, 73.6% A/AB (n=121 letter grades).

difficulty & workload

Historical reviews of Xiang Zheng: Workload is manageable if students complete homework on time and attend class to follow demonstrations, though understanding concepts requires effort.

Historical reviews of Jeffrey Kritzman, Xiang Zheng: Students appreciate unique projects and instructors who stay after class to answer questions, though one reviewer found assigned readings repetitive.

Topics

  • Data visualization.
  • Challenges and limitations of data visualizations.
  • Misrepresentation and bias in data.
  • Visualization software platforms.

Skills

  • Summarizing, analyzing, and communicating data.
  • Using visualization software platforms.
  • Planning visualizations based on data, audience, and goals.
  • Identifying limitations, misrepresentation, and bias in visualizations.

Grades

Latest available · Spring 2026— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

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Grades over time

Through Spring 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.

Selected offering source records
LIS 407 · Fall 2026

Data Storytelling with Visualization

Recorded 2026-09-07
Raw records
[
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:544:026072",
    "course_id": "LIS 407",
    "course_uid": "course_26a3253bb559893e7f2e983f",
    "term_id": "1272",
    "source_course_id": "026072",
    "source_subject_id": "544",
    "title": "Data Storytelling with Visualization",
    "credits_min": 3,
    "credits_max": 3,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
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": "d96e6d8e726fd2eeed19323116a8d68aa830e02889173f7ace096f4a591b6cfc",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}