WGU D301: Developing an E-Learning Solution and Research Methodology

Where D301 Sits in the Capstone Sequence

WGU D301, Developing an E-Learning Solution and Research Methodology, is the middle course in a three-part capstone sequence that appears in WGU's education technology master's programs — the MEd Education Technology and Instructional Design and its M.S. Learning Experience Design and Educational Technology counterpart. By the time you reach it you have already identified a real instructional problem, described the learners it affects, and framed a research problem worth investigating. D301 is where you stop describing the problem and start building something that answers it, then plan — carefully and ethically — how you will find out whether it worked.

Direct answer: D301 is passed by submitting performance assessment tasks that evaluators score against a rubric, not by sitting a proctored objective assessment. Build one genuinely functional e-learning module that traces back to the instructional problem you defined in the prior capstone course, then write a research methodology that a stranger could execute step by step. Address every rubric line explicitly, in the rubric's own vocabulary, and submit early enough to survive one revision cycle.

According to WGU's published course description, D301 covers the next two phases of the design-based research process: designing and developing an e-learning solution, and designing a research methodology to test how well that solution addressed the instructional problem. It also continues the Design Thinking work from earlier courses, asking you to ideate potential solutions before committing to one, and to begin prototyping a module of instruction rather than describing it on paper. A third strand runs throughout: designing research studies that ensure the safety of human subjects and the ethical collection, storage, and reporting of data.

In the published course sequence, D301 follows Identifying Learner Needs and a Research Problem and leads into the final capstone, Implementing and Evaluating E-Learning Solutions. That chain matters more than it looks. Anything vague you leave behind in D301 becomes an obstacle in the next course, because that is where you carry out the plan you write here. Students who treat D301 as a box to check often spend the final capstone repairing a methodology that was never executable in the first place.

What the D301 Tasks Actually Ask You to Produce

Task structure and rubric wording change from term to term, so treat your current course page as the authority — nothing here replaces it. Across the versions students describe, the deliverables cluster into four areas that map onto the course's published focus:

• Solution ideation. Generating and comparing more than one plausible response to your instructional problem, with a defensible reason for the one you choose. A single idea presented as inevitable rarely satisfies this.
• A working e-learning module. Not a storyboard, not a wireframe — a prototype module a learner could open and complete, built with authoring or LMS tools available to you and grounded in learning theory and instructional design principles.
• A research methodology. Your design (qualitative, quantitative, or mixed), participants and how you will recruit them, instruments, procedures, and your plan for analyzing what you collect so that it answers the research questions you already wrote.
• Ethics and human subjects protection. Informed consent or parental permission, confidentiality, secure data storage, and honest reporting — the safety and data-handling expectations the course explicitly teaches.

Almost every task also asks for alignment: the module has to answer the problem, the methodology has to measure the module, and the analysis plan has to fit the data the instruments will actually produce. Evaluators read for that chain of logic, and a break anywhere in it is a common reason a submission comes back.

How Hard Is D301, and How Long Should You Budget?

Many students describe D301 as demanding rather than conceptually difficult. There is no content to memorize and no timed exam to survive; the challenge is production. You are wearing two hats — designer and researcher — and each has its own rubric. Learners who arrive with authoring-tool experience often find the module the easy half and the methodology the slow half; those from a research-heavy background report the reverse.

Term length is the honest planning unit here, not weeks. Tasks queue for evaluation, revisions take real calendar time, and any study touching human participants adds review steps outside your control. Students commonly report that the safest approach is to get a draft in front of your course instructor early, treat the first evaluation as feedback rather than a verdict, and leave slack for at least one resubmission.

Building the Module and the Methodology in Parallel

The most repeated piece of peer advice about this course is not to work sequentially. Drafting the methodology while you build the module tends to improve both documents, because each one keeps exposing loose thinking in the other. A practical way to run that:

• Turn the rubric into your outline. Copy every rubric aspect into a document and write your draft underneath each one. It makes gaps visible while they are still cheap to fix, and it guarantees you are writing against the only source that scores you.
• Rehearse the methodology out loud. Explain your design, sample, instruments, and analysis to someone with no background in it. Anywhere you hesitate or hand-wave is a section an evaluator will flag. Redraft, then explain again a few days later — spacing the retelling exposes reasoning you had only memorized, not understood.
• Prototype small, then expand. Build one complete slice of the module — a single objective with its instruction, practice, and check — before scaling. A finished small thing beats a half-built large thing every time an evaluation window arrives.
• Pilot the module on a friendly reader. Watching one person click through it will reveal broken navigation, unclear directions, and untested assumptions faster than any amount of self-review.
• Keep a decision log. Note why you chose each design element and each methodological move, with the source that supports it. Rubrics ask for justification, and reconstructing your reasoning weeks later is painful.
• Shore up your measurement vocabulary. If validity, reliability, sampling, and analysis plans feel shaky, a focused refresher pays for itself — our D293 Assessment and Learning Analytics guide covers the measurement thinking behind your instruments, and D772 Statistical Data Literacy covers reading and reporting data honestly.

Mistakes That Send D301 Submissions Back

The recurring problems in this course are structural, not stylistic:

• Scope creep in the module. Designing a whole course when the task asks for a module. Ambition is not scored; completeness against the rubric is.
• A methodology that cannot actually be run. Naming participants you have no route to recruit, or an instrument you have no time to build, guarantees trouble in the final capstone.
• Analysis that does not match the data. Promising statistical comparisons while collecting only open-ended responses, or the reverse. State the data type first, then the analysis.
• Ethics handled as a formality. One sentence saying data will be kept confidential is not a plan. Say where data lives, who can reach it, how consent or permission is obtained, and how results will be reported without exposing anyone.
• Losing the thread back to the problem. The module drifts toward whatever was fun to build instead of what the learner analysis identified. Re-read your prior capstone deliverable before finalizing.
• Under-citing. Design decisions and methodological choices both need support. Unsupported assertions read as opinion, and rubrics ask for evidence — the same standard of arguing from sources that runs through related coursework such as D637 Curriculum and Instructional Strategies for Meaningful Learning.
• Submitting without a proofread. Graduate-level mechanics and consistent APA formatting are part of what is evaluated, and they are the cheapest points in the course to protect.

D301 Readiness Checklist

• Can you state your instructional problem and your research questions from memory, in two sentences each?
• Can you name at least two solutions you considered and explain why you chose the one you built?
• Can a reader open your e-learning module and complete it end to end without you narrating?
• Can you point to the learning theory or design principle behind each major element of the module?
• Can you describe your research design, participants, and recruitment plan in a way someone else could carry out?
• Can you show that your analysis plan fits the kind of data your instruments will actually produce?
• Can you explain your consent, confidentiality, and data-storage arrangements without hedging?
• Have you checked with your course instructor whether your planned study needs institutional review before anyone collects anything?
• Can you match every rubric aspect to a specific place in your submission where it is addressed?
• Have you left enough term remaining to revise and resubmit if the first evaluation asks for changes?

D301 FAQ

Is D301 an objective assessment or a performance assessment?

It is performance-assessment based. You submit capstone deliverables — an e-learning solution and a research methodology — that evaluators score against a rubric. There is no proctored objective assessment to schedule for this course.

What do I actually have to build?

A prototype module of instruction, not a description of one. WGU's course description says learners begin prototyping a module that addresses the instructional problem identified earlier in the sequence. Use tools you can realistically access, and check your current task instructions for format requirements.

Does my study need institutional review?

It depends on your study. WGU applies institutional review expectations to student research involving human participants or protected data, and D301 itself teaches designing studies that keep human subjects safe and handle data ethically. Because the exact workflow and thresholds change, confirm the current process with your course instructor before you approach anyone — not after your methodology is written.

How long does D301 take?

There is no reliable single number, because it depends on your topic, your access to participants, and how many revision cycles you need. Students commonly report that the module and the methodology together consume a substantial part of a term once evaluation queues and a revision cycle are counted, and that starting both in the first weeks is what prevents an extension.

What if a task is returned?

A returned task is normal in capstone courses and is not a course failure. Evaluators identify which rubric aspects fell short; you revise those sections and resubmit. Budgeting time for that cycle up front is the single most useful planning move in this course.

How does D301 connect to the rest of the program?

It follows Identifying Learner Needs and a Research Problem and feeds directly into D302 Implementing and Evaluating E-Learning Solutions, where you carry out the plan you write here. You can browse related coursework on our School of Education hub or in the full WGU course guide index.

For the official course description and current program structure, see WGU's MEd Education Technology and Instructional Design program page. This guide is an independent study resource and is not affiliated with or endorsed by Western Governors University.