| Course | NUR 673 Producing and Evaluating Programs for Academic and Practice Settings |
|---|---|
| Module | Module 6 |
| Paper type | Course evaluation case study analysis |
| Length | About 615 words, 5 pages |
| Format | APA 7 student paper |
| School | Arizona State University |
| Program | MS in Nursing |
| Updated | October 2026 |
Free sample paper for NUR 673 Module 6
What the Data Say About Adult Health II: A Course Evaluation Case Study With Four Prioritized Changes
Student Name
Edson College of Nursing and Health Innovation, Arizona State University
NUR 673: Producing and Evaluating Programs for Academic and Practice Settings
Instructor Name
Month Day, Year
What the Data Say About Adult Health II: A Course Evaluation Case Study With Four Prioritized Changes
The Course and the Data
Adult Health II carries 6 credits in the second semester of a prelicensure BSN, combining lecture, simulation and 90 clinical hours. The case provides five sources of evaluation data from the last academic year.
| Data source | Finding |
|---|---|
| End-of-course student ratings | Overall 3.9 of 5; "exams reflect what was taught" 3.1; "feedback helped me improve" 3.3 |
| Exam item analysis | 9 of 160 items with a negative discrimination index; mean point-biserial 0.18 |
| Standardized medical-surgical test | 61% of students at or above the program's benchmark, against a target of 75% |
| Clinical partner feedback | Students strong in skills and communication; weak in prioritizing when several patients deteriorate |
| Course outcomes | 88% pass the course; 7% fail on exam average alone while passing clinical |
Analysis
The data agree on one theme: students can perform tasks but struggle to prioritize and to apply knowledge in unfamiliar situations. Clinical partners describe it directly, the standardized test results reflect it, and the item statistics suggest that the course exams are not measuring it well. Items with negative discrimination, answered correctly more often by weaker students, are usually flawed or keyed incorrectly, and a low average point-biserial points to an exam that separates stronger from weaker students poorly (Oermann et al., 2024). Student ratings on exam alignment and feedback confirm that learners also sense a disconnect.
The 7% who fail on exam average alone while passing clinical deserve attention. Some may genuinely lack knowledge, but if the exams contain flawed items, some of these failures may reflect the test rather than the student, which raises a fairness concern.
Stakeholder Perspectives
Students want exams that match class content and feedback they can use. Clinical partners want graduates who can prioritize across a patient assignment. Faculty want to protect the course's pass rate while raising standardized test performance, and program leaders are accountable for licensure outcomes. These interests largely point the same way: better-built assessments of clinical judgment and more feedback before high-stakes exams.
Emerging Trends
Two trends bear on the course. Case-based licensure items now test clinical judgment along the steps of the NCSBN model, and a course that tests mostly recall leaves students underprepared (Dickison et al., 2019). Generative AI tools are now widely available to students, which affects written assignments and calls for clear course guidance on acceptable use and for assessments that ask students to show their reasoning.
Proposed Changes, in Priority Order
1. Exam quality review. Before next term, review all items with negative or low discrimination, revise or retire them and blueprint each exam so that at least 40% of items assess analysis. Measure: mean point-biserial above 0.25 and no negatively discriminating items after the first administration.
2. Case-based clinical judgment items and a weekly unfolding case. Add one unfolding case per week in class, with case-based items on each exam. Measure: standardized test benchmark attainment rising toward 75% over two cohorts.
3. Formative feedback before each exam. Add a low-stakes practice quiz with rationales one week before each exam. Measure: the rating on feedback rising above 4.0.
4. Prioritization in clinical. Give students a multi-patient prioritization activity at the start of each clinical day, with debriefing. Measure: clinical partner ratings of prioritization at the end of term.
Conclusion
The evaluation data point to a single weakness, the assessment and teaching of clinical judgment, rather than to many unrelated problems. Fixing the exams comes first, because the other measures depend on trustworthy assessment. The course evaluation cycle should then repeat after one term, as the readings describe evaluation as continuous rather than a one-time event (Billings & Halstead, 2024).
References
Billings, D. M., & Halstead, J. A. (Eds.). (2024). Teaching in nursing: A guide for faculty (7th ed.). Elsevier.
Dickison, P., Haerling, K. A., & Lasater, K. (2019). Integrating the National Council of State Boards of Nursing Clinical Judgment Model into nursing educational frameworks. Journal of Nursing Education, 58(2), 72-78. https://doi.org/10.3928/01484834-20190122-03
Oermann, M. H., Gaberson, K. B., & De Gagne, J. C. (Eds.). (2024). Evaluation and testing in nursing education (7th ed.). Springer Publishing.
Reading the NUR 673 Module 6 assignment instructions
Module 3 of NUR 673 turns from student assessment to course and curriculum evaluation, and Week 6 brings the Case Study: Course Evaluation, worth 10 points. The syllabus asks you to analyze evaluation data, stakeholder feedback and emerging trends to propose course-level changes. The week's topics are course and curriculum evaluation strategies and the use of evaluation data, stakeholder feedback and emerging trends to inform course or curriculum changes. The case itself and its data are in Canvas. Expect to work with several kinds of evidence at once, such as student ratings, exam statistics, standardized test results and feedback from clinical partners, and to propose changes that are specific and measurable rather than general.
Inside the NUR 673 Module 6 example
The sample presents the case data in a table with five sources, then analyzes them together to find a common theme, the gap between task performance and clinical judgment. It explains what negative discrimination and a low point-biserial mean for exam quality and raises a fairness concern about students failing on exams alone. A stakeholder section sets out what students, clinical partners, faculty and program leaders want and shows where their interests meet. An emerging trends section covers clinical judgment testing and generative AI. Four changes are listed in priority order, each linked to its data and paired with a measure. The conclusion explains the order and calls for the evaluation cycle to repeat.
Where the marks sit in the NUR 673 Module 6 rubric
Up to 10 points go to the course evaluation case under its Canvas rubric. Course evaluation analyses are generally credited for accurate interpretation of each data source, synthesis across sources, attention to stakeholder perspectives, use of emerging trends that genuinely affect the course and proposed changes that are specific, prioritized, feasible and paired with evaluation measures. Analyses lose points when they report data without interpreting it, when they propose changes unconnected to the findings, when stakeholders are named but not considered and when trends are listed without relevance to the course. Using item analysis terms correctly matters, since the course quiz on item analysis tests the same concepts. Changes that the course team could carry out within one term carry more weight than wishes that depend on new resources.
NUR 673 Module 6 help from the desk
The usual weakness is a list of recommendations that could apply to any course. Tie every change to a finding in the case data. Another is treating each data source separately; look for the theme the sources share. Interpret item statistics correctly: negative discrimination signals a problem item, not a hard one. Prioritize your changes and explain the order. Give each change a measure, so the evaluation can continue. Address stakeholders by name and interest. Include emerging trends only where they affect the course. If you send the desk the Canvas case and its data, it can help you organize the analysis. Remember that a fair reading of student ratings treats them as one source among several, neither dismissed nor taken alone.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Arizona State University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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NUR 673 Module 6 questions, answered
Where can I find a free NUR 673 Module 6 sample paper?
The NUR 673 Module 6 sample above is a full course evaluation case study analyzing five data sources and proposing four prioritized course changes with measures.
What data are used in a nursing course evaluation?
Student ratings, exam item statistics, standardized test results, clinical partner feedback and course outcomes such as pass rates, ideally analyzed together.
What does a negative discrimination index mean?
Weaker students answered the item correctly more often than stronger students, which usually signals a flawed or miskeyed item.
How should course changes be proposed after an evaluation?
As specific, prioritized changes tied to the findings, each with a measure that shows whether it worked at the next evaluation.
When is the NUR 673 course evaluation case study due?
As Week 6 ends, in the course and curriculum evaluation module, for 10 points.