Assignment Prompt & Instructions
please see attachment
– a year ago
**files (3)**
– ## DataAnalysis11.docx
– ## SampleWriteupanalysis-1.pdf
– ItemAnalysis1.xls
**## DataAnalysis11.docx**
**Data Analysis #1 (100 pts)**
**Part 1:**(50 pts) Excel workbook: Using the attached Template; score and compute the following statistics for the participants.
Item score: individual performance on each test item (minus the 2-3 essay items (2.5 pts)
Individual raw and mean score: (2.5 pts)
Item Difficulty: (10 pts)
Item Discrimination: (10Pts)
Test or Class Mean Median and Mode scores: (10 pts)
Frequency Distribution & Curve: (5 pts)
Standard Deviation: (5 pts)
Skewness: (5pts)
**Part 2:**(50 pts) Performance Analysis: Using your findings from Part 1 interpret the performance of the sample and make relevant suggestions. This should be completed in two reflective paragraphs no longer than 1 page total .
1. Summary of Class results (25 points): Discuss and cite specific data that accurately summarizes your class/sample performance on the given assessment. Talk about measures of central tendency (mean, median, mode, frequency distribution, curve, skewness, and objective performance) their meanings and interpretations and what implications do they have on future instruction (how should you use these results).
2. Item Analysis and Reliability (25 points): Discuss relative aspects and findings from your item analysis. What are some potential threats to these findings, how could they be improved and what implications do they have on future instruction (how should you use these results).
**## SampleWriteupanalysis-1.pdf**
Performance Analysis
1. Based on the data analysis from this test, the class scored poorly. The mean score
of the test was a score of fifty-one. A mean score from seventy-five to eighty-five would
have been an optimal score. Because they scored lower on the mean than seventy-five,
either the students didn’t know the material, the test was poorly written, or the mean was
affected by outliers. The mode of the test was sixty-one. This is my most frequent score,
but it only focuses on one group of students. The median score of the test was fifty-six. A
reliable test should have the mean, median, and mode within five points of each other.
My scores were fairly close to each other. The median and the mode were five points
apart and the mean and the median were five points apart, but if you compare the mode to
the median it is ten points apart. There are probably some reliability issues with my test. I
should probably go back over the test and review each item to figure out which items the
students did poorly on and which ones the students did well on. The highest score on the
test out of all fifteen students was a seventy. The majority of the class failed the test. The
frequency distribution graph was bimodal with a high peak and a low peak. There wasn’t
a very good range of scores, so it did not make a bell curve. The graph was negatively
skewed and the skew score was 2.27. This means that there were more scores below the
mean. My standard deviation was 2.28. The standard deviation is the group score around
the mean. A good score is 7-13. My standard deviation is low and this means that too
many students scored close to the same level whether that level is good or bad. In this
case, the students all scored on a low level. My mean score for test objective one was
about forty-four and my mean score for test objective two was fifty. Neither of these
mean scores was very high, so this indicates that the objectives were not covered
effectively in class and the students were probably unprepared for the test. In order to
help my students do better next time on the test, I should probably allow more time to
cover the material and use different teaching methods than I used to prepare for this test. I
could probably have a review with the students the day before to make sure they know
the objectives before administering the test. Using this data from the analysis of the test
scores, I can analyze what is wrong with the test items or determine a weakness in my
teaching of a subject covered under the objective. This information will help solve the
mystery of why the students did so poorly on the test. I should analyze any changes I
made in teaching practices, because this probably affected the students’ ability to learn
the material effectively. I can go back and look at each question and find out what items
students struggled on. Based on the measures of central tendency, the skew, the
frequency distribution, the standard deviation, and the mean scores of the test objectives,
there is definitely good reason to go back and alter the test to make it more reliable for
future students.
Item Analysis and Reliability
2. There was a mixture of results in my item analysis. According to item difficulty,
items two, four, seven, ten, fourteen, and eighteen were a little too easy for the students.
Multiple-choice items tend to have the best reliability when their item difficulty is about
.69. According to the scores for item difficulty, items three, five, six, nine, eleven,
twelve, thirteen, fifteen, twenty, twenty-one, twenty-two, twenty-three, twenty-two, and
twenty-three were too difficult for the students. In response to the scores on item
difficulty, I should go back and work on making the easier questions a little more
challenging and making the more difficult questions less difficult. Some of the scores fell
around .69, so I would keep those. As far as item discrimination, some questions proved
to be good items based on the discrimination between the upper and lower students. Item
discrimination is meant to show the comparison of students who were prepared for the
test minus the students who were less prepared and got the right answer on the item. An
item discrimination of .4 or higher usually demonstrates a good item based on
discrimination. All of the test items, except one, two, nine, sixteen, eighteen, nineteen,
and twenty proved to be good items based on item discrimination. In order to fix the bad
items from the test based on item discrimination, I should consider the readability, the
distractors, and check to see if the item matches the objective being tested. I find that
based on item difficulty and item discrimination, most of my test items should be revised
and some items discarded. Two items that should be thrown out or revised are items five
and nine. Using distractor analysis to analyze the questions, we can understand what
might need to be changed to make the item better. On question five, options B and C
should be discarded because the less-prepared students scored better than the better-
prepared students. Option A is a good distractor because both the less-prepared students
and the better-prepared students chose it equally. Option D was the correct answer and it
is reliable because the less-prepared students scored lower than the better-prepared
students. On question nine, options A, C, and D should be discarded or revised because
the less-prepared students scored higher than the better-prepared students. Split-half
reliability determines if the test was reliable as a whole. This test scored a .6 which is a
good score to prove reliability. Some potential threats to the reliability of the test were the
testing environment, a change in teaching practices, and if the items didn’t measure the
objectives. I could improve these by changing the testing environment, altering my
teaching methods to a more reliable method, and revising or discarding test items that
didn’t measure the objectives. The results from this analysis can be used to make the test
more reliable in the future. The mean scores of the essays were 2.53 and 1.8. I ensured
the consistency of the essay scores by using a rubric. The essays were graded randomly to
ensure reliability as well. The cover sheet with the student’s name was covered so the
essays were graded anonymously.
**ItemAnalysis1.xls**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/itemanalysis1-xls)
**ItemAnalysis1.xls**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/itemanalysis1-xls)
**## DataAnalysis11.docx**
**Data Analysis #1 (100 pts)**
**Part 1:**(50 pts) Excel workbook: Using the attached Template; score and compute the following statistics for the participants.
Item score: individual performance on each test item (minus the 2-3 essay items (2.5 pts)
Individual raw and mean score: (2.5 pts)
Item Difficulty: (10 pts)
Item Discrimination: (10Pts)
Test or Class Mean Median and Mode scores: (10 pts)
Frequency Distribution & Curve: (5 pts)
Standard Deviation: (5 pts)
Skewness: (5pts)
**Part 2:**(50 pts) Performance Analysis: Using your findings from Part 1 interpret the performance of the sample and make relevant suggestions. This should be completed in two reflective paragraphs no longer than 1 page total .
1. Summary of Class results (25 points): Discuss and cite specific data that accurately summarizes your class/sample performance on the given assessment. Talk about measures of central tendency (mean, median, mode, frequency distribution, curve, skewness, and objective performance) their meanings and interpretations and what implications do they have on future instruction (how should you use these results).
2. Item Analysis and Reliability (25 points): Discuss relative aspects and findings from your item analysis. What are some potential threats to these findings, how could they be improved and what implications do they have on future instruction (how should you use these results).
**## SampleWriteupanalysis-1.pdf**
Performance Analysis
1. Based on the data analysis from this test, the class scored poorly. The mean score
of the test was a score of fifty-one. A mean score from seventy-five to eighty-five would
have been an optimal score. Because they scored lower on the mean than seventy-five,
either the students didn’t know the material, the test was poorly written, or the mean was
affected by outliers. The mode of the test was sixty-one. This is my most frequent score,
but it only focuses on one group of students. The median score of the test was fifty-six. A
reliable test should have the mean, median, and mode within five points of each other.
My scores were fairly close to each other. The median and the mode were five points
apart and the mean and the median were five points apart, but if you compare the mode to
the median it is ten points apart. There are probably some reliability issues with my test. I
should probably go back over the test and review each item to figure out which items the
students did poorly on and which ones the students did well on. The highest score on the
test out of all fifteen students was a seventy. The majority of the class failed the test. The
frequency distribution graph was bimodal with a high peak and a low peak. There wasn’t
a very good range of scores, so it did not make a bell curve. The graph was negatively
skewed and the skew score was 2.27. This means that there were more scores below the
mean. My standard deviation was 2.28. The standard deviation is the group score around
the mean. A good score is 7-13. My standard deviation is low and this means that too
many students scored close to the same level whether that level is good or bad. In this
case, the students all scored on a low level. My mean score for test objective one was
about forty-four and my mean score for test objective two was fifty. Neither of these
mean scores was very high, so this indicates that the objectives were not covered
effectively in class and the students were probably unprepared for the test. In order to
help my students do better next time on the test, I should probably allow more time to
cover the material and use different teaching methods than I used to prepare for this test. I
could probably have a review with the students the day before to make sure they know
the objectives before administering the test. Using this data from the analysis of the test
scores, I can analyze what is wrong with the test items or determine a weakness in my
teaching of a subject covered under the objective. This information will help solve the
mystery of why the students did so poorly on the test. I should analyze any changes I
made in teaching practices, because this probably affected the students’ ability to learn
the material effectively. I can go back and look at each question and find out what items
students struggled on. Based on the measures of central tendency, the skew, the
frequency distribution, the standard deviation, and the mean scores of the test objectives,
there is definitely good reason to go back and alter the test to make it more reliable for
future students.
Item Analysis and Reliability
2. There was a mixture of results in my item analysis. According to item difficulty,
items two, four, seven, ten, fourteen, and eighteen were a little too easy for the students.
Multiple-choice items tend to have the best reliability when their item difficulty is about
.69. According to the scores for item difficulty, items three, five, six, nine, eleven,
twelve, thirteen, fifteen, twenty, twenty-one, twenty-two, twenty-three, twenty-two, and
twenty-three were too difficult for the students. In response to the scores on item
difficulty, I should go back and work on making the easier questions a little more
challenging and making the more difficult questions less difficult. Some of the scores fell
around .69, so I would keep those. As far as item discrimination, some questions proved
to be good items based on the discrimination between the upper and lower students. Item
discrimination is meant to show the comparison of students who were prepared for the
test minus the students who were less prepared and got the right answer on the item. An
item discrimination of .4 or higher usually demonstrates a good item based on
discrimination. All of the test items, except one, two, nine, sixteen, eighteen, nineteen,
and twenty proved to be good items based on item discrimination. In order to fix the bad
items from the test based on item discrimination, I should consider the readability, the
distractors, and check to see if the item matches the objective being tested. I find that
based on item difficulty and item discrimination, most of my test items should be revised
and some items discarded. Two items that should be thrown out or revised are items five
and nine. Using distractor analysis to analyze the questions, we can understand what
might need to be changed to make the item better. On question five, options B and C
should be discarded because the less-prepared students scored better than the better-
prepared students. Option A is a good distractor because both the less-prepared students
and the better-prepared students chose it equally. Option D was the correct answer and it
is reliable because the less-prepared students scored lower than the better-prepared
students. On question nine, options A, C, and D should be discarded or revised because
the less-prepared students scored higher than the better-prepared students. Split-half
reliability determines if the test was reliable as a whole. This test scored a .6 which is a
good score to prove reliability. Some potential threats to the reliability of the test were the
testing environment, a change in teaching practices, and if the items didn’t measure the
objectives. I could improve these by changing the testing environment, altering my
teaching methods to a more reliable method, and revising or discarding test items that
didn’t measure the objectives. The results from this analysis can be used to make the test
more reliable in the future. The mean scores of the essays were 2.53 and 1.8. I ensured
the consistency of the essay scores by using a rubric. The essays were graded randomly to
ensure reliability as well. The cover sheet with the student’s name was covered so the
essays were graded anonymously.
**ItemAnalysis1.xls**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/itemanalysis1-xls)
**## DataAnalysis11.docx**
**Data Analysis #1 (100 pts)**
**Part 1:**(50 pts) Excel workbook: Using the attached Template; score and compute the following statistics for the participants.
Item score: individual performance on each test item (minus the 2-3 essay items (2.5 pts)
Individual raw and mean score: (2.5 pts)
Item Difficulty: (10 pts)
Item Discrimination: (10Pts)
Test or Class Mean Median and Mode scores: (10 pts)
Frequency Distribution & Curve: (5 pts)
Standard Deviation: (5 pts)
Skewness: (5pts)
**Part 2:**(50 pts) Performance Analysis: Using your findings from Part 1 interpret the performance of the sample and make relevant suggestions. This should be completed in two reflective paragraphs no longer than 1 page total .
1. Summary of Class results (25 points): Discuss and cite specific data that accurately summarizes your class/sample performance on the given assessment. Talk about measures of central tendency (mean, median, mode, frequency distribution, curve, skewness, and objective performance) their meanings and interpretations and what implications do they have on future instruction (how should you use these results).
2. Item Analysis and Reliability (25 points): Discuss relative aspects and findings from your item analysis. What are some potential threats to these findings, how could they be improved and what implications do they have on future instruction (how should you use these results).
**## SampleWriteupanalysis-1.pdf**
Performance Analysis
1. Based on the data analysis from this test, the class scored poorly. The mean score
of the test was a score of fifty-one. A mean score from seventy-five to eighty-five would
have been an optimal score. Because they scored lower on the mean than seventy-five,
either the students didn’t know the material, the test was poorly written, or the mean was
affected by outliers. The mode of the test was sixty-one. This is my most frequent score,
but it only focuses on one group of students. The median score of the test was fifty-six. A
reliable test should have the mean, median, and mode within five points of each other.
My scores were fairly close to each other. The median and the mode were five points
apart and the mean and the median were five points apart, but if you compare the mode to
the median it is ten points apart. There are probably some reliability issues with my test. I
should probably go back over the test and review each item to figure out which items the
students did poorly on and which ones the students did well on. The highest score on the
test out of all fifteen students was a seventy. The majority of the class failed the test. The
frequency distribution graph was bimodal with a high peak and a low peak. There wasn’t
a very good range of scores, so it did not make a bell curve. The graph was negatively
skewed and the skew score was 2.27. This means that there were more scores below the
mean. My standard deviation was 2.28. The standard deviation is the group score around
the mean. A good score is 7-13. My standard deviation is low and this means that too
many students scored close to the same level whether that level is good or bad. In this
case, the students all scored on a low level. My mean score for test objective one was
about forty-four and my mean score for test objective two was fifty. Neither of these
mean scores was very high, so this indicates that the objectives were not covered
effectively in class and the students were probably unprepared for the test. In order to
help my students do better next time on the test, I should probably allow more time to
cover the material and use different teaching methods than I used to prepare for this test. I
could probably have a review with the students the day before to make sure they know
the objectives before administering the test. Using this data from the analysis of the test
scores, I can analyze what is wrong with the test items or determine a weakness in my
teaching of a subject covered under the objective. This information will help solve the
mystery of why the students did so poorly on the test. I should analyze any changes I
made in teaching practices, because this probably affected the students’ ability to learn
the material effectively. I can go back and look at each question and find out what items
students struggled on. Based on the measures of central tendency, the skew, the
frequency distribution, the standard deviation, and the mean scores of the test objectives,
there is definitely good reason to go back and alter the test to make it more reliable for
future students.
Item Analysis and Reliability
2. There was a mixture of results in my item analysis. According to item difficulty,
items two, four, seven, ten, fourteen, and eighteen were a little too easy for the students.
Multiple-choice items tend to have the best reliability when their item difficulty is about
.69. According to the scores for item difficulty, items three, five, six, nine, eleven,
twelve, thirteen, fifteen, twenty, twenty-one, twenty-two, twenty-three, twenty-two, and
twenty-three were too difficult for the students. In response to the scores on item
difficulty, I should go back and work on making the easier questions a little more
challenging and making the more difficult questions less difficult. Some of the scores fell
around .69, so I would keep those. As far as item discrimination, some questions proved
to be good items based on the discrimination between the upper and lower students. Item
discrimination is meant to show the comparison of students who were prepared for the
test minus the students who were less prepared and got the right answer on the item. An
item discrimination of .4 or higher usually demonstrates a good item based on
discrimination. All of the test items, except one, two, nine, sixteen, eighteen, nineteen,
and twenty proved to be good items based on item discrimination. In order to fix the bad
items from the test based on item discrimination, I should consider the readability, the
distractors, and check to see if the item matches the objective being tested. I find that
based on item difficulty and item discrimination, most of my test items should be revised
and some items discarded. Two items that should be thrown out or revised are items five
and nine. Using distractor analysis to analyze the questions, we can understand what
might need to be changed to make the item better. On question five, options B and C
should be discarded because the less-prepared students scored better than the better-
prepared students. Option A is a good distractor because both the less-prepared students
and the better-prepared students chose it equally. Option D was the correct answer and it
is reliable because the less-prepared students scored lower than the better-prepared
students. On question nine, options A, C, and D should be discarded or revised because
the less-prepared students scored higher than the better-prepared students. Split-half
reliability determines if the test was reliable as a whole. This test scored a .6 which is a
good score to prove reliability. Some potential threats to the reliability of the test were the
testing environment, a change in teaching practices, and if the items didn’t measure the
objectives. I could improve these by changing the testing environment, altering my
teaching methods to a more reliable method, and revising or discarding test items that
didn’t measure the objectives. The results from this analysis can be used to make the test
more reliable in the future. The mean scores of the essays were 2.53 and 1.8. I ensured
the consistency of the essay scores by using a rubric. The essays were graded randomly to
ensure reliability as well. The cover sheet with the student’s name was covered so the
essays were graded anonymously.
**ItemAnalysis1.xls**
This file is too large to display. [View in new window](https://www.sweetstudy.com/files/itemanalysis1-xls)