| Course | PHLT 8044 Advanced Program Evaluation |
|---|---|
| Week | Week 4 |
| Paper type | Evaluation questions paper |
| Length | About 1,040 words, 6 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | PhD in Public Health |
| Updated | October 2026 |
Free sample paper for PHLT 8044 Week 4
Evaluation Questions for a State School Water Access Program: Turning "Does It Improve Health?" Into Six Answerable Questions Placed on the Rossi, Lipsey and Henry Hierarchy, and Naming the Rung It Cannot Yet Reach
Student Name
Walden University
PHLT 8044: Advanced Program Evaluation
Instructor Name
Month Day, Year
Evaluation Questions for a State School Water Access Program: Turning "Does It Improve Health?" Into Six Answerable Questions Placed on the Rossi, Lipsey and Henry Hierarchy, and Naming the Rung It Cannot Yet Reach
From a Question No One Could Answer
The legislature's question about the school water access program is whether it improves students' health. As written, no dataset could settle it: health is not defined, the comparison is not named and the time frame is open. This paper breaks the question into six questions, each specific enough that a defined body of data could answer it, and places each on the evaluation hierarchy described by Rossi et al. (2019). That hierarchy runs from assessing need, through program theory and design, to implementation, outcomes and efficiency, on the reasoning that each level depends on the ones below it: there is little point in asking whether a program changed outcomes if it was never delivered as designed. The questions draw on the logic model, whose intermediate results are where most of them sit.
The Questions
Table 1
Evaluation Questions, Their Rung on the Hierarchy and Whether the Program Can Reach It Now
| No. | Question | Rung | Answerable now? | |
|---|---|---|---|
| 1 | Among students in program schools, what share report drinking sugary drinks daily, and does it differ by school income level? | Need | Yes, from the state student survey | |
| 2 | Are stations placed where students choose drinks, and do students trust the water? | Theory and design | Yes, from site visits and a short student survey | |
| 3 | Are stations working, filters replaced on schedule, bottles distributed and promotion delivered in every program school? | Implementation | Yes, from logs and meter counts | |
| 4 | Compared with schools not yet in the program, did cafeteria sugary drink purchases per enrolled student fall in program schools in the year after installation? | Outcome | Yes, from food service sales data | |
| 5 | Compared with those schools, did students' self-reported whole-day sugary drink intake fall? | Outcome | Yes, with an added survey in a sample of schools | |
| 6 | What does the program cost per sugary drink serving displaced at school? | Efficiency | Yes, if question 4 yields an estimate | |
Note. A seventh question, on weight, is discussed below as a rung the program cannot yet reach.
Why These Questions, and in This Form
Need Comes First
Question 1 asks whether the problem the program addresses is present among its students and where it is greatest. If daily sugary drink intake is already low in some program schools, the program has little room to work there, and outcome comparisons should account for that. Asking by school income level also prepares the equity analysis the legislature will expect.
Theory and Design
Question 2 tests two assumptions from the logic model that the program's success depends on: that stations are near the point of choice and that students trust the water. A program whose stations sit in empty hallways could fail for reasons unrelated to whether water helps, and knowing that before outcome data arrive would prevent a misleading conclusion.
Implementation
Question 3 asks whether the program happened as designed. It is answerable now from maintenance logs, distribution records and meter data, and its answer conditions the outcome questions: a school whose stations were broken for half the year is not a fair test.
Outcomes
Questions 4 and 5 are the core impact questions. Each names its comparison, schools not yet in the program; its population, enrolled students; its measure; and its time frame. Question 4 uses cafeteria purchases, which are objective and available for both program and comparison schools, but it misses drinks brought from home. Question 5 adds whole-day intake through a short survey, which tests whether students compensate after school, the link the logic model identified as most likely to break. Together they bracket the effect: one objective but partial, one complete but self-reported.
Efficiency
Question 6 asks what each displaced sugary drink serving costs, which a budget office can compare with other uses of the money. It depends on question 4 producing an estimate, so it sits highest on the hierarchy among the questions the evaluation can reach.
The Rung the Program Cannot Yet Reach
The legislature's original interest was weight. A question such as "Did the program slow weight gain among students?" belongs on the outcome rung, but the evaluability assessment found that the program's design, hallway stations and a two-week promotion, makes a measurable effect on weight unlikely within the evaluation's time frame, and that only about one district in three screens students' BMI. Studies that found weight effects involved cafeteria-based water access or year-long education (Muckelbauer et al., 2009; Schwartz et al., 2016). Asking the weight question now would likely produce a null result that says more about the design and data than about water. The paper therefore recommends stating openly that weight is not being judged in this cycle, and naming what would make it judgeable: stations moved closer to cafeterias, a longer promotion and BMI data agreements with more districts.
Questions Considered and Set Aside
Several other questions were proposed and deliberately left out. Advocates asked whether better hydration improves attention and test scores; no feasible measure would separate a water effect from everything else that moves scores in a year. The food service director asked how much revenue cafeterias lose when sugary drink sales fall; that matters for districts, but it is a consequence of question 4 rather than a separate evaluation question, and it can be reported alongside it. Teachers asked about classroom disruption from bottles; that is an implementation concern better handled through principals than through the evaluation. Setting these aside keeps the evaluation focused on the questions its users need answered before the budget decision, while noting that the revenue figure will be easy to add.
How the Questions Serve the Decision
The intended users face one decision: whether to expand the program next biennium. Questions 3 through 6 bear directly on it. A program delivered well that lowers sugary drink purchases at modest cost has a case for expansion; a program delivered poorly has a case for repair before expansion; a program delivered well that changes nothing has a case for redesign. Questions 1 and 2 shape where expansion, or repair, should happen first.
References
Muckelbauer, R., Libuda, L., Clausen, K., Toschke, A. M., Reinehr, T., & Kersting, M. (2009). Promotion and provision of drinking water in schools for overweight prevention: Randomized, controlled cluster trial. Pediatrics, 123(4), e661-e667. https://doi.org/10.1542/peds.2008-2186
Rossi, P. H., Lipsey, M. W., & Henry, G. T. (2019). Evaluation: A systematic approach (8th ed.). SAGE.
Schwartz, A. E., Leardo, M., Aneja, S., & Elbel, B. (2016). Effect of a school-based water intervention on child body mass index and obesity. JAMA Pediatrics, 170(3), 220-226. https://doi.org/10.1001/jamapediatrics.2015.3778
What the PHLT 8044 Week 4 instructions ask for
The fourth assignment usually asks students to turn a broad stakeholder question into a set of specific evaluation questions. Faculty expect every question to specify its comparison, the people it covers, the yardstick and the window of time, so that some dataset could settle it. Placing questions on an evaluation hierarchy, such as the one described by Rossi, Lipsey and Henry, shows how they depend on one another: implementation questions come before outcome questions because outcomes mean little if the program was not delivered. A table listing questions, their level and whether they can be answered now is common. Strong papers also explain which questions were set aside and why, and say plainly which important question the program cannot yet answer. Most papers run three or four pages.
Inside the PHLT 8044 Week 4 example
The paper opens with the legislature's question, explains why no dataset could answer it as written and introduces the hierarchy. A six-row table lists questions on need, theory and design, implementation, two outcomes and efficiency, with each one's rung and current answerability. Sections then explain each group: need first, to see where the problem is greatest; theory and design, to test placement and trust; implementation, to condition outcome results; outcomes, where purchases and whole-day recall bracket the effect; and efficiency, which depends on the purchase estimate. A section lists questions considered and set aside. Another explains why weight cannot yet be judged and what would make it judgeable, and the paper closes by linking the questions to the expansion decision.
Where the marks sit in the PHLT 8044 Week 4 rubric
Graders reward questions specific enough to answer and an explicit link to the hierarchy. Questions phrased as broad aims, without comparison, population, measure or time frame, lose credit. The paper should explain why lower rungs come first and should connect each question to the program theory. Credit goes to bracketing the outcome with complementary measures, here objective but partial purchases and complete but self-reported recall. Honesty about the rung the program cannot reach, with the reasons and the conditions that would change it, is a distinguishing feature of strong work. Setting aside other questions with reasons shows judgment about scope. The table should match the text, and the questions should serve the users' decision.
PHLT 8044 Week 4 help from the desk
Evaluation question papers often list aims instead of questions. Keep revising each one until it says what is compared with what, for whom, by which yardstick and over which months. Put questions in hierarchy order and explain the dependency. Use two measures where one would be partial. Say which questions you dropped and why. Admit which important question cannot be answered yet, and name what would make it answerable. Check that every question in your set could be answered by a specific dataset you could name. Any broad question a sponsor asks can be broken down in the same way.
Get a PHLT 8044 Week 4 example written to your instructions
Hand over the Week 4 prompt and rubric plus the aim your program states, whether taken from a grant, a report or a mission statement. Five or so answerable questions come back in 24-48h, and the first set carries no charge. Wording is built for the sealant stand-in until you name your own program.
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PHLT 8044 Week 4 questions, answered
Where can I find a free PHLT 8044 Week 4 sample paper?
The full Week 4 paper is reproduced here, turning a broad health question about a school water program into six answerable questions placed on the Rossi, Lipsey and Henry hierarchy.
Why ask implementation questions in an outcome evaluation?
Because outcomes depend on delivery. If stations were broken for half the year in some schools, their results would not be a fair test of the program.
How many evaluation questions should a set carry?
Your prompt usually sets the number, and a handful is typical. This sample uses six because that covers each rung of the hierarchy without spreading the evaluation too thin.
Why measure both cafeteria purchases and whole-day intake?
Purchases are objective but miss drinks from home; whole-day recall is complete but self-reported. Together they bracket the program's effect on sugary drinks.
Why not evaluate the program's effect on weight now?
The program's design makes a weight effect unlikely within a year, and BMI data exist in only a third of districts, so a weight question would likely produce an uninformative null result.