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The Wright Map is usually used to describe the results of either dichotomous or polytomic responses based on the Rasch or IRT models. Wright's map image is used to see item difficulty or the level of problem difficulty with the distribution of the estimated ability (person's ability). From the picture above, the distribution of items is between -0.5 to 1.8, while the distribution of respondents’ abilities is 0 to 3. That means that respondents have high abilities, while the items on the measuring instrument measure people with moderate abilities. In simple terms, the tendency of respondents to choose the “strongly agrees” choice over the other answer choices.

Figure 3 The Wright Map is usually used to describe the results of either dichotomous or polytomic responses based on the Rasch or IRT models. Wright's map image is used to see item difficulty or the level of problem difficulty with the distribution of the estimated ability (person's ability). From the picture above, the distribution of items is between -0.5 to 1.8, while the distribution of respondents’ abilities is 0 to 3. That means that respondents have high abilities, while the items on the measuring instrument measure people with moderate abilities. In simple terms, the tendency of respondents to choose the “strongly agrees” choice over the other answer choices.

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Table 1. Matrix Block 1 Design
Table 1. Matrix Block 1 Design
Table 2. Item fit statistic The table above is the result item fit analysis using the Partial Credit Model (PCM) approach. The criteria used are chi-square with a p-value > 0.05. If the p-value is not significant, then the item fits the model. The results show several items that do not fit the model, i.e. items number 2, 4, 6, 10, 13, 15, 21, and 23.
Table 2. Item fit statistic The table above is the result item fit analysis using the Partial Credit Model (PCM) approach. The criteria used are chi-square with a p-value > 0.05. If the p-value is not significant, then the item fits the model. The results show several items that do not fit the model, i.e. items number 2, 4, 6, 10, 13, 15, 21, and 23.
Overall, the higher and steeper the curve, the greater information obtained from the item, while the lower and sloping curve is less. The item measures a wide range of abilities. Next is the test information plot that describes the overall item information. The test tool is more suitable for measuring ability or latent trait zero (6 = 0). Thus, the measuring instrument is more likely to measure people with intermediate abilities.
Overall, the higher and steeper the curve, the greater information obtained from the item, while the lower and sloping curve is less. The item measures a wide range of abilities. Next is the test information plot that describes the overall item information. The test tool is more suitable for measuring ability or latent trait zero (6 = 0). Thus, the measuring instrument is more likely to measure people with intermediate abilities.
International Journal of Research in Counseling and Education, Open Access Journal: http://ppsfip.ppj.unp.ac.id
International Journal of Research in Counseling and Education, Open Access Journal: http://ppsfip.ppj.unp.ac.id
Figure 3. Distribution Model and Item Contribution
Figure 3. Distribution Model and Item Contribution
Based on results of the correlation between factors, the highest correlation is between the second factor and the fourth factor of 0.734 with a significance of <0.001. Then, the third factor is not correlated with other factors, it connotes that the factor meets the discriminant validity criteria where it can be said that the third factor measures different things. While the first, second, and fourth factors are correlated with each other, the three factors meet the convergent validity criteria that will produce the same results. For example, the higher the first factor, the higher the score on the second and fourth factors.
Based on results of the correlation between factors, the highest correlation is between the second factor and the fourth factor of 0.734 with a significance of <0.001. Then, the third factor is not correlated with other factors, it connotes that the factor meets the discriminant validity criteria where it can be said that the third factor measures different things. While the first, second, and fourth factors are correlated with each other, the three factors meet the convergent validity criteria that will produce the same results. For example, the higher the first factor, the higher the score on the second and fourth factors.
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