Doctoral Experiential Component

The Doctoral Experiential Component is an advanced placement providing applied experiences within a student's concentration area.

offering recorded6 credits
Recorded instructors · Spring 2027 Daniel Rortvedt

Summary

What you’ll be able to do

  • Demonstrate advanced synthesis of knowledge gained in a chosen area including research, policy, leadership, administration, entrepreneurshp, program development or advocacy through successful achieving of individually customized learning goals.

  • Model professional and leadership skills needed to work with multiple stakeholders successfully

  • Communicate effectively with others in a professional setting: a. Interact effectively with clients, colleagues, other professionals, and community members from diverse cultural and ethnic backgrounds on a one-on-one basis and within the context of groups and b. Communicate effectively with varied audiences for varied purposes

  • Complete a Capstone Project connected to the DEC site which meets both the site needs as well as the student learning goals

Source: UW Guide

Grade history

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average GPA
letter grades

No recorded grade history.

All recorded terms · compare terms & instructors

Prerequisites

Course map

OCC THER 664

OCCTHER 883

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

Prerequisite text tree

Professors

Spring 2027
Historical instructors & teaching patterns

DANIEL RORTVEDT is recorded teaching in Spring 2024, Spring 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

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
FLD 001Online Only0 / 330

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

Meeting source records

No records available.

Student experience

the class

An advanced placement that provides an opportunity for applied experiences within their concentration area.

difficulty & workload

No workload feedback recorded.

Topics

  • Applied experiences within a specific concentration area.
  • Research, policy, leadership, administration, entrepreneurship, program development, or advocacy.
  • Capstone Project connected to the Doctoral Experiential Component (DEC) site.

Skills

  • Advanced synthesis of knowledge in areas such as research, policy, leadership, administration, entrepreneurship, program development, or advocacy.
  • Professional and leadership skills for working with multiple stakeholders.
  • Effective communication with diverse clients, colleagues, professionals, and community members in one-on-one and group contexts.
  • Completing a Capstone Project connected to the DEC site that meets site and student learning goals.

Grades

Instructor

Grade distribution · % of letter grades

No grades available yet.

More grade details Grade mix, volume & source data

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
OCCTHER 883 · Spring 2027

Doctoral Experiential Component

Recorded 2026-10-14
Raw records
[
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:695:025814",
    "course_id": "OCCTHER 883",
    "course_uid": "course_a564d04d4a78bd20004eb33a",
    "term_id": "1274",
    "source_course_id": "025814",
    "source_subject_id": "695",
    "title": "Doctoral Experiential Component",
    "credits_min": 6,
    "credits_max": 6,
    "typically_offered": "Not Applicable"
  }
]
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Madgrades

Grade history

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Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "7687b4aaef0e5a58b6eebe9eace091baa81fb18ec488ee91794db18ac09c6767",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}