NR 537 Week 4 Scholarly Discussion Item Analysis

Grace J.
August 29, 2025August 29, 2025
CU MSN, NR-537

Student Name

Chamberlain University

NR-537: Assessment & Evaluation in Education

Prof. Name

Date

Scholarly Discussion

Item Analysis

Conducting an item analysis is a critical step before making any decisions regarding test items, as it helps prevent negative consequences that may arise from poorly constructed assessments. Item analysis involves both quantitative and qualitative approaches to determine the validity and reliability of a test (Kaur et al., 2016).

The qualitative component includes collecting perceptions, opinions, and experiences of both learners and staff nurses regarding the test. This is typically achieved through interviews or focus group discussions, which provide deeper insights into which questions may have been confusing, ambiguous, or misaligned with course content (Quaigrain & Arhin, 2017). By engaging students in this process, educators can identify whether problematic items need to be revised, eliminated, or retained.

On the other hand, the quantitative component focuses on analyzing test scores. Reviewing each learner’s performance on individual items helps highlight patterns of difficulty. For example, an item difficulty index is calculated to determine the proportion of students answering a question correctly. Difficulty is usually expressed as a percentage, where higher percentages suggest easier items and lower percentages reflect more challenging ones (Quaigrain & Arhin, 2017).

What Qualitative Information Would I Provide?

The qualitative data would involve gathering students’ and nurses’ feedback on their experiences with the test. These insights may include their feelings about question clarity, relevance to course objectives, and overall fairness of the assessment. By listening to learners, educators can determine if poor performance was due to confusing wording, complex question framing, or lack of coverage in instruction.

Additionally, qualitative findings help differentiate between test-related issues and student-related challenges. For instance, learners may reveal that they struggled not because of content gaps but because the questions were phrased in an overly complicated manner.

What Quantitative Information Would I Provide?

The quantitative data would include item difficulty scores for each question. This allows educators to identify which items were too easy (e.g., 100% correct responses) or too hard (e.g., 0% correct responses). Items with extreme values often signal flawed design—either being overly obvious or unnecessarily complex.

Furthermore, item discrimination indices could be calculated to measure how well each test question differentiates between high- and low-performing students. A good test item should allow stronger students to succeed while identifying weaker students who may need more instruction.

Comparison of Qualitative and Quantitative Data in Item Analysis

Aspect	Qualitative Data	Quantitative Data
Source	Learners’ and nurses’ perspectives through interviews/discussions	Test scores and statistical measures from the assessment
Focus	Perceptions of fairness, clarity, and relevance of items	Item difficulty, discrimination index, and overall performance analysis
Purpose	Identify confusing, ambiguous, or unfair questions	Identify overly easy, overly difficult, or non-discriminative test items
Strength	Provides context and reasoning behind learner struggles	Provides objective, numerical evidence of item performance
Example	Students report a question was unclear due to complex wording	Calculation shows only 20% of students answered the item correctly, indicating potential test problem

Why Is It Important to Use Both Approaches?

Using both qualitative and quantitative methods ensures a more comprehensive evaluation of test quality. While quantitative analysis shows where the problems lie (e.g., in certain items), qualitative analysis explains why these problems exist. For example, a high failure rate on a specific item could result from poor test design rather than student incompetence. Conversely, if learners admit they did not study adequately, the poor scores might reflect knowledge gaps instead of assessment flaws (Kaur et al., 2016).

Thus, combining these approaches enables educators to make informed decisions about revising or discarding test items. This process not only strengthens the validity and fairness of the test but also ensures that assessments truly reflect the intended learning outcomes.

References

Kaur, M., Singla, S., & Mahajan, R. (2016). Item analysis of in use multiple choice questions in pharmacology. International Journal of Applied and Basic Medical Research, 6(3), 170–173. https://doi.org/10.4103/2229-516X.186965