Digital Media & Technology in Schools

CURRIC 709 introduces secondary educators to digital media technologies and how to design instructional units that incorporate them meaningfully.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Fall 2023: 4.00 GPA, 100.0% A/AB (n=21 letter grades); Fall 2024: 4.00 GPA, 100.0% A/AB (n=23 letter grades).

Grade history

average GPA
letter grades
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AB
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Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
CURRIC 709

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

Prerequisite text tree
  • Graduate/professional standing

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Fall 2026

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SectionModeEnrolled / capacityWaitlist

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Meeting source records

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Student experience

the class

Recent recorded grades — Fall 2023: 4.00 GPA, 100.0% A/AB (n=21 letter grades); Fall 2024: 4.00 GPA, 100.0% A/AB (n=23 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Major topics in digital media in teaching
  • Instructional unit design with technology integration

Skills

  • Understanding the role of digital media technologies in secondary education
  • Designing instructional units that meaningfully incorporate technology

Grades

Latest available · Fall 2024— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2024

More grade details Grade mix, volume & source data

Not enough comparable courses for Fall 2026 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

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Raw records
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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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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": "eaca68af5a3ed79915e525e9dd6175dcaac56d35c5aefeb0860e6cf6c5f80f42",
  "requirements_status": "needs_review",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}