Item difficulty index spss software

How can we calculate item difficulty index of a questionnaire. Of 30 items, 11 items were of higher difficulty level dif i 60%. Below is a discussion on interpreting item statistics from classical test tehory, adapted from the iteman manual. This article describes the functions of a sas macro and an spss syntax that produce common statistics for conventional item analysis including cronbachs alpha, item difficulty index pvalue or item mean, and item discrimination indices dindex, point biserial and biserial correlations for dichotomous items and itemtotal correlation for polytomous items. When a set of items are consistent, they can make a measurement scale such as a sum scale. Improve questions for future test administrations or to adjust credit on current attempts.

A measure of whether an item was too easy or too hard. From the results of the study and analysis in classical theory, it can be concluded that statistically there are differences in the average difficulty index of the items if the. Item analysis discrimination and difficulty index 1. Item analysis is an important probably the most important tool to increase test effectiveness. Interpreting the item analysis report stony brook university. In other words, the person s ability matches the item difficulty. Item reliability statistical reference guide analyse. Using excel test item analysis, difficulty index for pc items duration. Application of item analysis to assess multiplechoice. The name of this index is counterintuitive, as one actually gets a measure of how easy the item is, not the difficulty of the item. An item analysis provides three kinds of important information about the quality of test items. As the proportion of examinees who got the item right, the pvalue might more properly be called the item easiness index, rather than the item difficulty. In distractor analysis, however, we are no longer interested in how test takers select the correct answer, but how the distracters were able to function effectively by drawing the test takers away from the correct answer. Cronbachs alpha is the most popular measure of item reliability.

Subtract the difficulty index for the low scores group from the difficulty index for the high scores group. Difficulty index, discrimination index, reliability and rasch. Compute a difficulty index for each item for in structed. Application of item analysis to assess multiplechoice examinations.

Item6 has a high difficulty index, meaning that it is very easy. Analyze choice of distracters for questionable multiplechoice items. Comparative study of the difficulty index of items. Evaluation of multiple choice questions using item. This means that 70% of the test takers passed the item, and more students in the top group than the bottom group got the item correct. Mean of the tscore for all observations in a set of data is always 50, and the standard deviation is always 10 purpose. A good item discriminates between students who scored high or low on the examination as a. Difficulty index, discrimination index, reliability and rasch measurement analysis 1. The statistical software package, ibm spss statistics 20.

Item difficulty item difficulty is simply the percentage of students who answer an item correctly. Compute the pointbiserial correlation for each item using the correl function. What spss menu tab permits you to begin the process of calculating a new variable. The probability that person 2 can answer item 1 correctly is 0. Evaluate how items discriminate between masters and nonmasters for each objective. The eta coefficient is the ratio of the between groups sum of squares to the total sum of squares and has a range of 0 to 1.

Item reliability statistical reference guide analyseit. It is a scientific way of improving the quality of tests and test items in an item bank. Item analysis examples so, a test item may have an item difficulty of. The item difficulty index of each model was tested statistically using spss software, whether there was a significant average difference between the two test models. Difficulty index, discrimination index, reliability and. Put all the survey data into spss making each item its own variable, 2. According to forsyth, the first ten items on this scale measure ethical idealism and the second ten items measure ethical relativism. To determine the difficulty level of test items, a measure called the difficulty index is used. Spss offers procedure reliability to perform an item analysis. The most important elements of such an analysis are the corrected itemscale correlation, cronbachs alpha for the entire scale, and measures of cronbachs alpha if each individual item was deleted from the scale. Mean for difficulty index, discrimination index and distractor efficiency were 38. Provides descriptive statistics of item distributions across all items in the scale. Item analysis provides statistics on overall performance, test quality, and individual questions.

Part iv compares the item responses versus the total score distribution for each item. Ive prepared a questionnaire using likert scale on globalization of health as per international patients. These problems can be corrected, resulting in a better test, and better measurement. The following steps in spss will allow for item analysis.

Optimally, an item will encourage a widespread distribution of scores if its difficulty index is approximately 0. Difficulty index teachers produce a difficulty index for a test item by calculating the proportion of students in class who got an item correct. When formalized, the procedure is called item analysis. Data analysis using item response theory methodology. Tutorial on item analysis in testing, including item discrimination, using the discrimination index, and item difficulty. According to forsyth, the first ten items on this scale measure ethical idealism and. Spss is a powerful statistical tool for measuring item analysis and an ideal way for educators to create and evaluate valuable, insightful classroom testing. Mar 17, 2016 difficulty index, discrimination index, reliability and rasch measurement analysis 1. The most important elements of such an analysis are the corrected itemscale correlation. Clarkson university center for online teaching and learning. The item difficulty index is often called the pvalue because it is a measure of proportion for example, the proportion of students who answer a particular question correctly on a test.

Item difficulty the difficulty for dichotomous items like these can be found by simply calculating the mean for each item for dichotomous items the mean is the proportion of 1s. Statistics include scale mean and variance if the item were to be deleted from the scale, correlation between the item and the scale that is composed of other items, and cronbachs alpha if the item were to be deleted from the scale. Calculating difficulty, discrimination and reliability index. Evaluation of multiple choice questions using item analysis. Comparative study of the difficulty index of items displayed. The more students got the item right, the less difficult the item was. Summary item analysis is an extremely useful set of procedures available to teaching professionals.

Item reliability is the consistency of a set of items variables. This data helps you recognize questions that might be poor discriminators of student performance. The larger the proportion, the more students who have learned. How can we calculate item difficulty index of a questionnaire on. When an alternative is worth other than a single point, or when there is more than one correct alternative per question, the item difficulty is the average score on that item divided by the highest number of points for any one alternative. How can we calculate item difficulty index of a questionnaire on likert scale in spss. Based on item analysis, an item was found to have a difficulty index of 48% and a discrimination index of 42%. The aim is to divide the group into 3 groups, upper 27%, middle 46% and lower 27%. Our psychometric software is widely used around the world, and i often receive questions on how to interpret the output. Two principal measures used in item analysis are item difficulty and item discrimination. Understanding item analyses office of educational assessment. The discrimination index was used as a measure of how well the item. Item analysis can help you evaluate how well your objective items are actually working. Item analysis uses statistics and expert judgment to evaluate tests based on the.

For polytomous items items with more than one point, classical item difficulty is the mean response value. Item analysis and alpha factor analysis with spss imagine that you are using forsyths ethics position questionnaire click the link to see the questionnaire in some of your research. The item analyses we discuss here are pointbiserial correlations and pvalues. This is done by studying the students responses to each item.

This measure asks teachers to calculate the proportion of students who answered the test item accurately. An item analysis is a valuable, yet relatively easy, procedure that teachers can use to answer both of these questions. Item analysis basic concepts real statistics using excel. Sep 10, 2016 tutorial on item analysis in testing, including item discrimination, using the discrimination index, and item difficulty. When the student has a 50% chance to answer the item correctly, the. The discrimination index, item total correlation, and item difficulty measure and classification are presented in table 2 for the breeding and genetics examination. Agreeableness conscientiousness extraversion neuroticism openness the. Implications of problematic items in terms of test scores. These programs represent an improvement over the existing sas and spss. Part iii of the item analysis output, an item quintile table, can aid in the interpretation of part iv of the output.

Based on a paper entitled the selection of upper and lower groups for the validation of test items written by kelley, t. Pvalues are found by using the difficulty index formula, and they are reported in a range between 0. Distractor analysis is an extension of item analysis, using techniques that are similar to item difficulty and item discrimination. Item4 and item5 are typical items, where the majority of items are responding correctly.

Item difficulty analysis p for maximal performance items only, an index of what proportion of the people got the item correct. All items were analysed for difficulty index, discrimination index and distractor efficiency. A simple guide to the item response theory irt and rasch. The item analysis results were then combined with program participant feedback to. Item analysis with spss software linkedin slideshare. Data entered in ms excel 2007 and spss 21 analysed with statistical test of significance. We will show how to compute and interpret these statistics using two different programs. Arbitrarily, the point at which the trace line for an item crosses the. To write effective items, it is necessary to examine whether they are measuring the fact, idea, or concept for which they were intended. Calculating difficulty, discrimination and reliability. The ideal p value uncorrected for a norm referenced test is. This computation results in the correlation of the item score and the total score minus that item score. Assessmentquality test constructionteacher toolsitem.

Item discrimination if the test and a single item measure the same thing, one would expect people who do well on the test to answer that item correctly, and those who do. In general, the mindset flowchart in this study is presented in figure 2. This measure asks teachers to calculate the proportion. When normreferenced tests are developed for instructional purposes, to assess the effects of educational programs, or for educational research purposes, it can be very important to conduct item and test analyses. You may encounter cases in which the estimated correlations exceed 1. Sas macro and spss syntax for classical item analysis. A nonfunctioning distractor was defined as an option with a response. Apr 02, 2015 the aim is to divide the group into 3 groups, upper 27%, middle 46% and lower 27%. To examine the difference in one continuous dependent variable between two and only two independent groups e. We will be publishing additional posts on other topics like distractor analysis and item response theory, but you can also check out our tutorial videos on our. Item analysis technique to improve test items and instruction. The eta coefficient is an additional index of discrimination computed using an analysis of variance with the item response as the independent variable and total score as the dependent variable. Pdf difficulty index, discrimination index and distractor.

Compute a difficulty index for each item for instructed and uninstructed groups. This article describes the functions of a sas macro and an spss syntax that produce common statistics for conventional item analysis including cronbachs alpha, item difficulty index pvalue or item mean, and item discrimination indices d index, point biserial and biserial correlations for dichotomous items and item total correlation for polytomous items. Select the new reports link in the available analysis section or select view analysis in the status receipt at the top of the page. In addition, item analysis is valuable for increasing instructors skills in test. Nov, 20 item difficulty item difficulty is simply the percentage of students who answer an item correctly. Nov 01, 2015 this feature is not available right now. For each group, calculate a difficulty index for the item. The discrimination index, itemtotal correlation, and item difficulty measure and classification are presented in table 2 for the breeding and genetics examination. Difficulty index, discrimination index and distractor. Analysis of the difficulty and discrimination indices of multiple. Item analysis is a technique which evaluates the effectiveness of items in tests. Item and analysis manual software to get the item difficulty index. May 28, 2017 the following steps in spss will allow for item analysis. The most important elements of such an analysis are the corrected item scale correlation, cronbachs alpha for the entire scale, and measures of cronbachs alpha if each individual item was deleted from the scale.