| Course | D581 Introduction to Research Methods |
|---|---|
| Task | Task 2 |
| Paper type | Research design proposal |
| Length | About 1,100 words, 4 pages |
| Format | APA 7 |
| School | Western Governors University (WGU) |
| Program | BS Psychology |
| Updated | September 2026 |
Free sample paper for D581 Task 2
Two Districts, Two Waves, Seven Nights Each: A Quasi-Experimental Design to Test Whether a Four-Day School Week Changes Adolescent Sleep, With Sampling, Measures, Ethics and Bias Controls
Student Name
Leavitt School of Health, Western Governors University
D581: Introduction to Research Methods, Task 2
Course Instructor
Month Day, Year
Two Districts, Two Waves, Seven Nights Each: A Quasi-Experimental Design to Test Whether a Four-Day School Week Changes Adolescent Sleep, With Sampling, Measures, Ethics and Bias Controls
Introduction
The previous task asked whether switching a rural district's high schools to a four-day week alters three things about teenagers' sleep, namely school-night hours, the week's total and how regular bedtimes are, when set beside a similar district that stays on five days. The question matters because most high school students already sleep less than recommended on school nights (Wheaton et al., 2018) and adolescent biology pushes sleep later (Carskadon, 2011). This paper proposes the study design to answer it. It describes the research design, the sample and how it will be selected, the measures and procedures for data collection, the planned analysis, ethical protections for minors and the steps taken to reduce bias.
Research Design
The study uses a quantitative quasi-experimental design called difference-in-differences. Sleep will be measured in two districts at two points: in the spring before the schedule change and in the spring of the first year of the four-day week. The treatment district, a composite rural Colorado district of about 1,100 students, will adopt the four-day schedule. The comparison district, a neighboring district of similar size, poverty rate and geography, will keep its five-day schedule. The effect of the schedule is estimated as the change in the treatment district minus the change in the comparison district. Subtracting the comparison district's change removes influences that affect both districts over the year, such as students growing a year older or regional events.
A randomized experiment would give stronger evidence of cause, but it is not possible to assign districts or students to school schedules. Difference-in-differences was the approach Morton (2021) used to study the four-day week's effects on finance and achievement, and it is well suited to a policy change that happens in some places and not others.
Sample and Selection
Population: students in grades 9 to 11 in the two districts at baseline, so that the same students can be followed into the next year before most graduate. Sampling: all eligible students in both districts, about 260 in the treatment district and 240 in the comparison district, will be invited. A census approach avoids the selection problems of choosing some classrooms over others. Based on participation in similar school-based sleep studies, a 45% to 55% consent rate is expected, yielding roughly 120 students per district.
Inclusion criteria: enrolled in grades 9 to 11 at baseline, parental consent and student assent. Exclusion criteria: a diagnosed sleep disorder under current treatment, or a condition that prevents wearing a wrist device. Students who move away will be recorded as lost to follow-up.
Measures
Sleep duration and timing will be measured objectively with research-grade wrist actigraphs worn continuously for seven days and nights, a method widely used in adolescent sleep studies because it records sleep without relying on memory. Students will also complete a brief daily sleep diary to mark bedtimes and wake times, which helps score the actigraphy data. From these, the three outcomes defined in the previous task will be calculated: mean sleep on nights before school, the seven-day sleep total and how widely sleep onset times vary. A short questionnaire will record covariates: grade, sex, commute time, employment, sports participation and screen use after 10 p.m. School start and end times will be taken from district records.
Procedures
Data collection will take place during the same two spring weeks each year, avoiding holidays and testing weeks, since sleep changes around those events. Research assistants will distribute devices during a homeroom period, explain how to wear them and collect them after seven days. Students will receive a $25 gift card at each wave for returning the device and diary, regardless of how much they slept, so the incentive does not reward particular results. Parents will receive a summary of their own child's sleep on request.
Analysis Plan
The main analysis will use mixed-effects regression with repeated measurements nested within students, testing the interaction between district and time for each outcome. The interaction term estimates the difference-in-differences effect. Covariates will be added to test whether results hold when accounting for grade, sex, commute and activities. The study will report effect sizes with confidence intervals, not only p values, because a small sample can miss a real effect that matters to districts.
Ethical Considerations
Because participants are minors, the study requires approval from an institutional review board, written parental permission and written student assent. Students may withdraw at any time without consequence, and teachers will not know who participated. Data will be stored under study ID numbers on encrypted university servers, separate from names. Actigraphs record movement, not location. If a student's data suggest very short sleep, for example under five hours on most nights, the family will receive general sleep health information and a suggestion to talk with a health care provider.
Threats to Validity and Bias Controls
Selection bias: families who consent may differ from those who do not. Consent rates and basic demographics will be compared with district enrollment data, and results will be interpreted in light of any differences. Nonequivalent groups: the districts may differ in ways that change over time. Using a comparison district of similar size and poverty, and examining three years of attendance trends before the change to confirm the districts were moving in parallel, reduces this risk. History: an event affecting only one district, such as a new start time unrelated to the four-day week, would bias results; school calendars will be reviewed for such changes. Measurement bias: actigraphy data will be scored by a technician who does not know which district a record came from. Attrition: students lost to follow-up will be compared with those who remain. Researcher bias: hypotheses and the analysis plan will be registered publicly before data collection begins, so results cannot be reshaped after the fact.
Conclusion
A difference-in-differences design comparing two similar rural districts, with objective seven-day actigraphy at two time points, can estimate whether a four-day school week changes adolescent sleep. Careful sampling, ethical protections for minors and specific controls for selection, history, measurement and researcher bias make the findings useful to districts deciding whether to adopt the schedule, while the study reports honestly what a quasi-experimental design can and cannot show.
References
Carskadon, M. A. (2011). Sleep in adolescents: The perfect storm. Pediatric Clinics of North America, 58(3), 637-647. https://doi.org/10.1016/j.pcl.2011.03.003
Morton, E. (2021). Effects of four-day school weeks on school finance and achievement: Evidence from Oklahoma. Educational Researcher, 50(1), 30-40. https://doi.org/10.3102/0013189X20948023
Wheaton, A. G., Jones, S. E., Cooper, A. C., & Croft, J. B. (2018). Short sleep duration among middle school and high school students: United States, 2015. Morbidity and Mortality Weekly Report, 67(3), 85-90. https://doi.org/10.15585/mmwr.mm6703a1
What the D581 Task 2 instructions ask
The second D581 task asks you to design the study that would answer your research question. Most versions ask for the research design and why it fits, the population and sampling method, measures and data collection procedures, how the data would be analyzed, ethical considerations and strategies to reduce bias. You design the study but do not carry it out. The evaluator reads for alignment and realism: the design should match the question, the sample should be obtainable, the measures should produce the variables you defined, and the bias section should name specific threats with specific controls. A design that claims to prove cause without random assignment will draw comments.
How this D581 Task 2 example is built
The proposal restates the question in one sentence and explains why the topic matters. The design section names difference-in-differences, explains it in plain terms and justifies it against a randomized trial that is not possible. Sampling covers population, method, expected consent and inclusion rules. Measures and procedures describe the devices, diaries, timing, incentive and parent feedback. The analysis plan names the model and the key interaction and commits to effect sizes. Ethics covers review board approval, consent and assent, privacy and a response to worrying results. The bias section lists six threats, each with a control, before a conclusion that is candid about how far a two-district comparison can go.
Where the D581 Task 2 rubric puts the marks
D581 Task 2 aspects are each rated competent, approaching competence or not evident against your task rubric. A design aspect checks that the research design is identified and appropriate for the question. A sampling aspect asks for the population, sampling method and size. A data collection aspect looks for measures and procedures that produce the variables you defined. Some versions score the analysis plan separately. An ethics aspect checks protections for participants, with extra care for minors or vulnerable groups. A bias aspect asks for specific threats and mitigation strategies. Evaluators reward alignment across all parts and professional writing with APA citations.
D581 Task 2 help: what sends it back
The most frequent return is a mismatch between design and claims. A comparison of two districts cannot prove cause the way a randomized trial can, so say what your design can show and name its limits. Second, sampling is often vague. Give the population, how people will be recruited, expected numbers and inclusion rules. Third, bias sections tend to list threats without controls. Pair each threat with a step that reduces it. Fourth, ethics for minors is frequently incomplete. Include review board approval, parental permission, student assent and data protection. Finally, check that each measure produces a variable from your first task, since alignment is what the evaluator is reading for. A simple table pairing each variable with its instrument and analysis makes that check easy for you and for the reader.
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D581 Task 2 questions, answered
Which research designs fit D581 Task 2?
The design should match your question. Experiments test cause with random assignment, while quasi-experimental and correlational designs fit questions where assignment is not possible, as in the sample.
What is difference-in-differences in D581?
A design that compares the change over time in a group exposed to something with the change in a similar group that was not, so shared influences cancel out.
What ethics apply to a D581 study with minors?
Studies with minors need institutional review board approval, parental permission, student assent, the right to withdraw, confidential data storage and a plan for responding to concerning results.
Is the D581 study in the sample real?
No. Both districts and every study detail are hypothetical, as a design proposal should be; the sleep and school-schedule research it builds on is real.
Where can I find a free D581 Task 2 sample paper?
Scroll up for the full proposal, bias table and all, with notes. Share your own question and the D581 task, and the first custom design is written at no charge.