WGU D302: Implementing and Evaluating E-Learning Solutions

D302 at a Glance: The Last Mile of Your Capstone

D302, Implementing and Evaluating E-Learning Solutions, is the third and final capstone course in WGU's graduate learning-design track. It is worth 5 competency units, which makes it heavier than the 3-CU courses surrounding it, and it sits in the last term of the standard path. By the time you open it, you have already identified an instructional problem, reviewed the literature, designed a research methodology, and built a working e-learning module. D302 is where that module finally meets real learners and where you find out what your design actually did.

Direct answer: D302 has no multiple-choice exam. You pass by submitting performance-assessment tasks in which you implement your planned design-based research study, analyze the data you collected, refine your e-learning solution based on that data, and report your findings. Write to the rubric line by line, ground every claim in evidence you personally collected, and submit early enough to absorb one round of revisions.

The course appears in the M.Ed., Education Technology and Instructional Design guidebook, and it appears under the program's earlier name, M.S., Learning Experience Design and Educational Technology, with the same course description and the same 5-CU placement in the final term. So if you enrolled before the program was renamed, nothing about the course itself has changed. The listed prerequisite is Developing an E-Learning Solution and Research Methodology, and that prerequisite is not a formality — D302 assumes you are carrying a finished prototype and an approved methodology into the course on day one.

This course matters beyond the transcript. The design-based action research study you finish here is the most portable artifact in the entire program — the thing you show a hiring manager when you claim you can evaluate a learning product rather than just build one. Treat D302 as a paperwork exercise and you finish with a passing grade and nothing to show. Treat it as a genuine study and you finish with a portfolio piece.

What D302 Actually Asks You to Produce

WGU's published course description centers on the closing phases of the design-based research process: implement, test, refine, reflect, and report. In practice, your submitted work has to demonstrate the following:

• Methodology refinement. Explaining how you would strengthen the design-based research methodology you brought in from the previous course, based on what actually happened when you ran it.
• Implementation and testing. Putting the e-learning module in front of learners and testing your implementation strategies rather than just the content.
• Observation and iteration. Documenting what you saw as participants moved through the module, and treating those observations as data rather than anecdotes.
• Data analysis. Analyzing the data your study generated, using methods consistent with the plan you already had approved.
• Evidence-driven redesign. Enhancing or redesigning parts of the module because of what the data told you, and making the causal link explicit.
• Findings, contributions, and recommendations. Discussing what your study found, what it contributes, and what you would recommend to a designer facing the same instructional problem.
• The written study. Summarizing the whole design-based action research effort in a coherent report an outside reader could follow.

Notice what is absent from that list: there is no content to memorize, no formula sheet, and no timed testing window. Everything is applied. Your grade depends on the quality of your evidence and the precision of your writing.

How Hard Is D302, and How Long Does It Realistically Take?

The intellectual difficulty of D302 is moderate. Nothing in it is conceptually harder than what you already survived in the two preceding capstone courses, and the scaffolding is genuinely good. The difficulty lives somewhere else: in logistics and in precision.

Logistics first. You need real participants who will actually complete your module inside your term, and that is the part of this course you control least. If your study depends on a classroom, a training cohort, or a workplace team, their calendar becomes your calendar, and a two-week delay on their side is a two-week delay on yours. For most people the binding constraint here is participant availability, not writing speed.

Precision second. Capstone-level evaluators read against the rubric strictly, and the revision requests worth guarding against are the predictable ones: claims stated but not evidenced, and an analysis section that describes data without ever interpreting it. Plan for the possibility of one revision cycle rather than treating a returned submission as failure — on a capstone this size it is an ordinary part of the process.

As a planning assumption, budget four to eight weeks of focused effort, with the participant-facing portion front-loaded. If you have committed participants lined up before the term opens, you can beat that comfortably. If you start recruiting after the course opens, you probably will not.

A Working Plan for Finishing the Study and the Report

Week 1 — lock the logistics. Before you write a word, confirm participants, confirm access to the module, and confirm the consent and data-handling approach you established in the previous course, where ethical data collection is taught. Re-read your own methodology as if a stranger wrote it and note anything that will not survive contact with reality.

Weeks 2 to 3 — run and observe. Implement the module and take structured field notes while it happens. Use a simple observation template with fixed columns so your notes are comparable across participants. Write a short analytic memo the same day as each session, while your memory is intact. These memos become the raw material for your reflection sections, and reconstructing them weeks later is a reliable way to end up with thin, unconvincing writing.

Week 4 — analyze before you argue. Sort and code your data first, then decide what you believe. Reversing that order is how students end up cherry-picking evidence for a conclusion they had already chosen. If you are shaky on coding qualitative data or on describing quantitative results honestly, our guide to D581 Introduction to Research Methods covers the same fundamentals D302 expects you to already have.

Weeks 5 to 6 — redesign and write. Make your revisions to the module first, so you can describe real changes rather than hypothetical ones. Then draft the report section by section against the rubric, with the rubric open beside you. Use active recall against your own study: close the draft and try to state your finding, your evidence, and your recommendation out loud in three sentences. Anywhere you stumble is a section that is not yet argued, only asserted.

Two other guides on this site are worth keeping open while you work. The analytics and assessment-alignment thinking in D293 Assessment and Learning Analytics — a course in this same program — is the same lens D302 wants you to turn on your own product, and the accessibility and barrier-removal habits covered in D635 Practices for Inclusive Classrooms often suggest the most defensible redesign recommendations. You can browse related material on the School of Education hub or the full guide index.

Where D302 Submissions Usually Come Back

• Describing data instead of analyzing it. "Three participants scored lower on the second attempt" is a description. Analysis explains what that pattern means for your instructional problem.
• Recommendations with no traceable source. Every recommendation should trace to a specific piece of evidence from your own study, not to general best practice or to the literature review you wrote two courses ago.
• Hiding a disappointing result. A study showing your module did not improve outcomes is a perfectly passable study. Concealing it produces an unpassable one, because the reasoning stops making sense.
• Drifting from the approved methodology without saying so. Deviations are normal. Undocumented deviations read as sloppiness.
• Skipping the reflection. The iterative, reflective element is explicitly part of the course, and treating it as filler costs points that are cheap to earn.
• Starting the write-up before the data is complete. It almost always produces a report that argues toward a predetermined conclusion.
• Waiting until the last three weeks of the term. If a revision cycle lands, a late start is the most reliable way to need a term extension.

D302 Readiness Checklist

• Can you state your instructional problem, research question, and proposed solution in three plain sentences without notes?
• Can you name your confirmed participants and the dates they will work through your module?
• Can you explain your data collection method and why it fits your research question?
• Can you describe how you are handling consent and storing participant data responsibly?
• Can you show a structured observation or memo for every session you ran, written the same day?
• Can you point to a specific data pattern behind each change you made to the module?
• Can you explain what your study contributes and where its limitations lie?
• Can you match each section of your draft to the specific rubric criterion it satisfies?
• Can you submit with at least three weeks left in your term to absorb a revision?

D302 FAQ

Does D302 have an objective assessment?

No. D302 is assessed through performance assessment tasks — submitted work evaluated by an evaluator against a rubric. There is no proctored multiple-choice exam and nothing to schedule with a proctor. Every published competency for the course is an applied, produce-a-deliverable statement rather than a body of knowledge to be tested.

How many competency units is D302 worth?

Five competency units, according to WGU's published program guidebooks. It is placed in the final term of the standard path, and at 5 CUs it is the largest single course in the program — every other course in the program is listed at 3 CUs.

What do I need to finish before starting D302?

Developing an E-Learning Solution and Research Methodology is the listed prerequisite, and that course itself follows Identifying Learner Needs and a Research Problem. You should arrive with a functional e-learning module and a research methodology already designed.

Can I accelerate through D302?

Sometimes, but the ceiling is set by your participants rather than by your reading speed. Because you must actually implement the module and collect data, acceleration depends almost entirely on how quickly you can get real learners through your study. Line them up before the term starts if speed matters to you.

What if my e-learning solution didn't improve outcomes?

That is a legitimate research finding and it does not fail you. Design-based research expects iteration. Report what happened, interpret why it may have happened, and make recommendations grounded in that interpretation. Honest negative results, well analyzed, read stronger than vague positive ones.

How many participants do I need?

WGU does not publish a universal number, and the right answer depends on the methodology you already had approved in the prior course. Confirm the expectation with your course instructor before you begin collecting data rather than after.