The document discusses techniques for conducting item analysis to improve test items and instruction. It defines item analysis as a process that examines student responses to individual test items to assess item quality and identify areas for improvement. Item analysis provides valuable information for revising weak items, emphasizing areas of content students struggle with, and gaining insight into student understanding. The document outlines key item analysis statistics like difficulty, discrimination, and reliability, which measure item and test quality. It also describes the typical steps to performing item analysis, including calculating statistics, evaluating items, and revising tests.
EXAMINING DISTRACTORS AND EFFECTIVENESS
Distractors are the multiple choice response options that are not the correct answer. They are plausible but incorrect options that are often developed based upon students’ common misconceptions or miscalculations. Item analysis software typically indicates the percentage of students who selected each option, distractors and key.
educ 11
The document summarizes the analysis of a 40-item multiple choice test administered to 7th grade students. The analysis examined the test's validity, reliability, difficulty, distinguishing characteristics, and response patterns. The summary is:
(1) Validity analysis found 3 valid items (7.5%) and 37 invalid items (92.5%) that should be replaced, as they could not accurately measure ability.
(2) Reliability was high, with 21 items very reliable and the rest highly reliable, allowing consistent ability measurement.
(3) Difficulty varied, with 4 hard, 13 average, and 23 easy items, showing most items were easy for the students.
This document discusses various aspects of item analysis, including item difficulty, item discrimination, and distractor analysis. Item difficulty examines how many students answered each item correctly to determine if it was too easy or difficult. Item discrimination assesses how well each item differentiated between high-scoring and low-scoring students. Distractor analysis evaluates how effective the incorrect answer options were at attracting responses away from the correct answer. Performing item analysis helps improve test quality by identifying flawed or ambiguous items and assessing student learning needs.
This document provides information about item analysis, including:
- Item analysis examines student responses to test questions to assess question and test quality. It helps improve questions for future tests or identify problems for a single test.
- Item analysis also helps instructors develop better test construction skills and identify areas of course content needing more emphasis or clarity.
- Steps provided calculate the percentage of students answering each question correctly, and classify question difficulty to determine if a question should be accepted or rejected.
Administering, Analyzing, and Improving the Test or AssessmentNema Grace Medillo
The document provides guidance on administering, analyzing, and improving tests and assessments. It discusses assembling tests by grouping similar item formats and arranging items from easy to hard. When administering tests, steps should be taken to induce a positive testing attitude and minimize distractions. Tests should be scored carefully and item analysis conducted to identify problematic items in need of revision or elimination. Both quantitative and qualitative item analysis methods are described. The goal is to analyze test items, identify areas for improvement, and ensure the test effectively measures the intended objectives.
The document discusses examples of qualitative item analysis of test items. It provides examples of analyzing items based on difficulty index, discrimination index, and effectiveness of distractors. Based on the analysis, the teacher would decide to retain, revise, or reject each item. For ambiguous, miskeyed, or guessing items, the conclusion is usually to revise or reject the item. For difficult items with good discrimination, the conclusion may be to retain but modify distractors. The analysis helps teachers improve the quality of test items.
This document provides an overview of item analysis, which is a technique instructors can use to evaluate test questions and improve instruction. Item analysis generates reports that show response patterns, statistics like difficulty and discrimination indices, and summary data for a test. This information helps instructors identify effective and ineffective questions, ensures questions validly measure objectives, and guides rewriting questions to better assess student understanding.
The document discusses techniques for conducting item analysis to improve test items and instruction. It defines item analysis as a process that examines student responses to individual test items to assess item quality and identify areas for improvement. Item analysis provides valuable information for revising weak items, emphasizing areas of content students struggle with, and gaining insight into student understanding. The document outlines key item analysis statistics like difficulty, discrimination, and reliability, which measure item and test quality. It also describes the typical steps to performing item analysis, including calculating statistics, evaluating items, and revising tests.
EXAMINING DISTRACTORS AND EFFECTIVENESS
Distractors are the multiple choice response options that are not the correct answer. They are plausible but incorrect options that are often developed based upon students’ common misconceptions or miscalculations. Item analysis software typically indicates the percentage of students who selected each option, distractors and key.
educ 11
The document summarizes the analysis of a 40-item multiple choice test administered to 7th grade students. The analysis examined the test's validity, reliability, difficulty, distinguishing characteristics, and response patterns. The summary is:
(1) Validity analysis found 3 valid items (7.5%) and 37 invalid items (92.5%) that should be replaced, as they could not accurately measure ability.
(2) Reliability was high, with 21 items very reliable and the rest highly reliable, allowing consistent ability measurement.
(3) Difficulty varied, with 4 hard, 13 average, and 23 easy items, showing most items were easy for the students.
This document discusses various aspects of item analysis, including item difficulty, item discrimination, and distractor analysis. Item difficulty examines how many students answered each item correctly to determine if it was too easy or difficult. Item discrimination assesses how well each item differentiated between high-scoring and low-scoring students. Distractor analysis evaluates how effective the incorrect answer options were at attracting responses away from the correct answer. Performing item analysis helps improve test quality by identifying flawed or ambiguous items and assessing student learning needs.
This document provides information about item analysis, including:
- Item analysis examines student responses to test questions to assess question and test quality. It helps improve questions for future tests or identify problems for a single test.
- Item analysis also helps instructors develop better test construction skills and identify areas of course content needing more emphasis or clarity.
- Steps provided calculate the percentage of students answering each question correctly, and classify question difficulty to determine if a question should be accepted or rejected.
Administering, Analyzing, and Improving the Test or AssessmentNema Grace Medillo
The document provides guidance on administering, analyzing, and improving tests and assessments. It discusses assembling tests by grouping similar item formats and arranging items from easy to hard. When administering tests, steps should be taken to induce a positive testing attitude and minimize distractions. Tests should be scored carefully and item analysis conducted to identify problematic items in need of revision or elimination. Both quantitative and qualitative item analysis methods are described. The goal is to analyze test items, identify areas for improvement, and ensure the test effectively measures the intended objectives.
The document discusses examples of qualitative item analysis of test items. It provides examples of analyzing items based on difficulty index, discrimination index, and effectiveness of distractors. Based on the analysis, the teacher would decide to retain, revise, or reject each item. For ambiguous, miskeyed, or guessing items, the conclusion is usually to revise or reject the item. For difficult items with good discrimination, the conclusion may be to retain but modify distractors. The analysis helps teachers improve the quality of test items.
This document provides an overview of item analysis, which is a technique instructors can use to evaluate test questions and improve instruction. Item analysis generates reports that show response patterns, statistics like difficulty and discrimination indices, and summary data for a test. This information helps instructors identify effective and ineffective questions, ensures questions validly measure objectives, and guides rewriting questions to better assess student understanding.
UMT, Test Construction 2, Test Construction II, Item Analysis, Test Analysis, Test Construction, Discrimination Index, Difficulty Index, Waqas A. Khan, Prof. Dr. Abdul Hameed, Abdul Hameed, Dr. Abdul Hameed, SSH, University of Management and Technology, University of Management & Technology, www.waqas.org
Item analysis involves statistical analysis of test items to evaluate their effectiveness. It examines student responses to individual test questions to assess question and overall test quality. Key indicators include the item difficulty index, item discrimination index, and distractor power analysis. Conducting regular item analysis helps improve instruction, identifies areas needing remediation, and builds a bank of high-quality test questions.
Item analysis is used to improve test quality by examining item difficulty, discrimination, and distractors. There are three main elements: examining difficulty level by calculating the percentage answering correctly; determining discrimination by comparing percentages of high-scoring and low-scoring students answering correctly; and examining distractors in multiple choice questions. The process involves arranging students by score, separating into upper and lower groups, recording responses, and calculating difficulty and discrimination indices using specific formulas.
1) The document discusses the process of item analysis and validation for tests, which includes a try-out phase, item analysis phase to determine difficulty level, and item revision phase.
2) Two important characteristics analyzed are item difficulty, expressed as a percentage of students answering correctly, and the discrimination index which evaluates if items can differentiate between higher and lower performing students.
3) Formulas and interpretation guidelines are provided to evaluate item difficulty, discrimination index, and reliability. The purpose is to determine a test's overall validity and reliability.
The document discusses item analysis, which refers to a statistical technique that helps teachers evaluate how effective test items are by calculating the difficulty index, discrimination index, and analyzing distractors to identify very easy, very difficult, or non-functional items so tests can be improved. It provides examples of how to calculate the difficulty and discrimination indexes and examines distractors to determine if any options are not plausible choices. The goal of item analysis is to analyze test items and identify problems that can be addressed to create a better test and assessment.
This document discusses various techniques for analyzing test items to improve instruction, including item difficulty, discrimination, biserial correlation, and guidelines for item development. Item difficulty looks at the proportion of students answering correctly to determine if an item is easy or hard. The discrimination index measures how well items differentiate high- and low-scoring students. Biserial correlation relates performance on an item to overall test score. Guidelines recommend improving items that do not correlate well or have non-functioning distractors. The goal is to have a test that reliably discriminates student ability levels.
Item analysis is a process used to evaluate test questions and assess the quality of a test. It involves both qualitative and quantitative procedures. Quantitatively, it examines the difficulty index, discrimination index, and distractor power of each question. The difficulty index indicates how many students answered correctly, the discrimination index shows if a question distinguishes between high- and low-scoring students, and distractor power evaluates the effectiveness of incorrect answer options. Conducting item analysis helps improve the validity and reliability of assessments by identifying high- and low-quality questions.
Administering, analyzing, and improving the test or assessmentNema Grace Medillo
The document provides guidance on test development and administration. It discusses assembling the test, administering it, scoring it, and analyzing results both quantitatively and qualitatively. Quantitative analysis includes calculating difficulty levels and discrimination indices to evaluate items. Qualitative analysis examines items' match to objectives and technical quality. The document also describes modifications for criterion-referenced tests, such as using pre- and post-tests as upper and lower groups for analysis. Overall, the guidance aims to help avoid common pitfalls and improve tests and assessments.
This document discusses item analysis, which examines student responses to test questions. There are two types: quantitative, which uses statistics like difficulty and discrimination indices, and qualitative, which involves expert review. Difficulty index measures the proportion of students answering correctly, ranging from very difficult to very easy. Discrimination index measures an item's ability to distinguish high-scoring from low-scoring students. Qualitative analysis involves experts proofreading tests for issues like ambiguity before administration.
The document discusses item analysis, which examines student responses to individual test items to evaluate quality and identify areas for improvement. Item analysis provides diagnostic information at both the class and individual level. It also helps build future tests by revising weak items and spreading difficulty levels. Doing occasional item analysis helps teachers become better at test construction and documentation, and provides data to address issues with administrators. The document outlines classical item analysis statistics including reliability, difficulty, and discrimination indices. It provides examples of how to calculate these statistics and interpret the results.
The document discusses how to evaluate the quality of test items through item analysis, which assesses item difficulty, how well items differentiate high and low performers, and the quality of distractors. Item analysis helps ensure test items are valid and reliable by identifying poorly performing items that should be improved or discarded. The results of item analysis can provide insights into how to enhance the measurement properties of a test.
The document discusses item analysis which is used to evaluate the quality and performance of test items. It addresses several key aspects of item analysis including calculating the index of difficulty and discrimination for each item, examining distractors, and using the results to identify issues and determine if items should be retained, modified, or discarded. The purpose is to select the best items for the final test form and identify areas for improvement.
This document discusses language testing and test construction. It defines a test as a measuring device that assesses achievement of training objectives. Tests should be valid, reliable and fair. The purposes of tests are to assess progress, compare performance, diagnose weaknesses, and improve understanding. Good tests have a clear structure with competence-based categories and use of operational verbs. Test analysis qualitatively and quantitatively evaluates item difficulty, discrimination, and answer distribution to improve test validity and reliability. Reliability is measured using methods like Kuder-Richardson and Spearman-Brown.
The document discusses classical item and test analysis using the Classical Item and Test Analysis Spreadsheet (CITAS). CITAS is a free Excel tool that calculates important test-level statistics like reliability and item-level statistics like difficulty and discrimination from student response data. It provides summaries of test scores and reliability and calculates item difficulty, discrimination, and supplemental statistics. The examples show how CITAS can be used to evaluate test and item quality for classroom assessments.
1. The document discusses analyzing test items through quantitative and qualitative methods. It defines key terms like difficulty index, discrimination index, and describes how to calculate them.
2. The document provides examples of analyzing test items based on student response data. It shows how to determine the difficulty level, identify effective or ineffective distractors, and ways to improve test items based on the analysis.
3. The goal of the analysis is to evaluate how well items discriminate between higher and lower performing students, identify issues, and determine if items should be retained or modified to make them more effective.
The document discusses item analysis for multiple choice questions (MCQs). Item analysis involves analyzing student performance on individual test questions to evaluate question quality. It provides information on question difficulty level and ability to differentiate between higher and lower performing students. The difficulty index is calculated as the percentage of students who answered the question correctly. The discrimination index shows how well each question separates students who scored high on the test from those who scored low. Questions with moderate difficulty and high discrimination are considered ideal.
This document provides guidelines for conducting a try-out test and performing item analysis on a test. It explains that a try-out test should be conducted on a sample similar to the actual test takers and under similar conditions to prepare for the real test administration. Item analysis evaluates the quality of test items using metrics like item difficulty index and item discrimination index calculated based on comparing response rates of high-scoring and low-scoring test takers. The document provides examples of computing these indexes and interpreting their values to identify items that need revision or removal.
Item analysis is used to judge the quality of test items by systematically analyzing their performance. It involves ranking students based on their scores, dividing them into high and low groups, and calculating difficulty and discrimination indices. The difficulty index indicates how easy or difficult an item is based on the number of students answering it correctly. The discrimination index estimates how well an item distinguishes between students with high and low ability levels. Item analysis is an important part of test construction and evaluation to improve the quality of assessment.
Lesson 21 designing the questionaire and establishing validity and reliabiltymjlobetos
The document provides steps for designing a valid and reliable questionnaire. It discusses establishing validity by ensuring the questionnaire measures the intended construct through face validity, content validity, criterion-related validity including concurrent and predictive validity, and construct validity. Reliability is established through test-retest reliability, split-half reliability, and measuring internal consistency using Cronbach's alpha. The steps also include pilot testing the questionnaire to identify issues and revising it based on feedback before final use.
UMT, Test Construction 2, Test Construction II, Item Analysis, Test Analysis, Test Construction, Discrimination Index, Difficulty Index, Waqas A. Khan, Prof. Dr. Abdul Hameed, Abdul Hameed, Dr. Abdul Hameed, SSH, University of Management and Technology, University of Management & Technology, www.waqas.org
Item analysis involves statistical analysis of test items to evaluate their effectiveness. It examines student responses to individual test questions to assess question and overall test quality. Key indicators include the item difficulty index, item discrimination index, and distractor power analysis. Conducting regular item analysis helps improve instruction, identifies areas needing remediation, and builds a bank of high-quality test questions.
Item analysis is used to improve test quality by examining item difficulty, discrimination, and distractors. There are three main elements: examining difficulty level by calculating the percentage answering correctly; determining discrimination by comparing percentages of high-scoring and low-scoring students answering correctly; and examining distractors in multiple choice questions. The process involves arranging students by score, separating into upper and lower groups, recording responses, and calculating difficulty and discrimination indices using specific formulas.
1) The document discusses the process of item analysis and validation for tests, which includes a try-out phase, item analysis phase to determine difficulty level, and item revision phase.
2) Two important characteristics analyzed are item difficulty, expressed as a percentage of students answering correctly, and the discrimination index which evaluates if items can differentiate between higher and lower performing students.
3) Formulas and interpretation guidelines are provided to evaluate item difficulty, discrimination index, and reliability. The purpose is to determine a test's overall validity and reliability.
The document discusses item analysis, which refers to a statistical technique that helps teachers evaluate how effective test items are by calculating the difficulty index, discrimination index, and analyzing distractors to identify very easy, very difficult, or non-functional items so tests can be improved. It provides examples of how to calculate the difficulty and discrimination indexes and examines distractors to determine if any options are not plausible choices. The goal of item analysis is to analyze test items and identify problems that can be addressed to create a better test and assessment.
This document discusses various techniques for analyzing test items to improve instruction, including item difficulty, discrimination, biserial correlation, and guidelines for item development. Item difficulty looks at the proportion of students answering correctly to determine if an item is easy or hard. The discrimination index measures how well items differentiate high- and low-scoring students. Biserial correlation relates performance on an item to overall test score. Guidelines recommend improving items that do not correlate well or have non-functioning distractors. The goal is to have a test that reliably discriminates student ability levels.
Item analysis is a process used to evaluate test questions and assess the quality of a test. It involves both qualitative and quantitative procedures. Quantitatively, it examines the difficulty index, discrimination index, and distractor power of each question. The difficulty index indicates how many students answered correctly, the discrimination index shows if a question distinguishes between high- and low-scoring students, and distractor power evaluates the effectiveness of incorrect answer options. Conducting item analysis helps improve the validity and reliability of assessments by identifying high- and low-quality questions.
Administering, analyzing, and improving the test or assessmentNema Grace Medillo
The document provides guidance on test development and administration. It discusses assembling the test, administering it, scoring it, and analyzing results both quantitatively and qualitatively. Quantitative analysis includes calculating difficulty levels and discrimination indices to evaluate items. Qualitative analysis examines items' match to objectives and technical quality. The document also describes modifications for criterion-referenced tests, such as using pre- and post-tests as upper and lower groups for analysis. Overall, the guidance aims to help avoid common pitfalls and improve tests and assessments.
This document discusses item analysis, which examines student responses to test questions. There are two types: quantitative, which uses statistics like difficulty and discrimination indices, and qualitative, which involves expert review. Difficulty index measures the proportion of students answering correctly, ranging from very difficult to very easy. Discrimination index measures an item's ability to distinguish high-scoring from low-scoring students. Qualitative analysis involves experts proofreading tests for issues like ambiguity before administration.
The document discusses item analysis, which examines student responses to individual test items to evaluate quality and identify areas for improvement. Item analysis provides diagnostic information at both the class and individual level. It also helps build future tests by revising weak items and spreading difficulty levels. Doing occasional item analysis helps teachers become better at test construction and documentation, and provides data to address issues with administrators. The document outlines classical item analysis statistics including reliability, difficulty, and discrimination indices. It provides examples of how to calculate these statistics and interpret the results.
The document discusses how to evaluate the quality of test items through item analysis, which assesses item difficulty, how well items differentiate high and low performers, and the quality of distractors. Item analysis helps ensure test items are valid and reliable by identifying poorly performing items that should be improved or discarded. The results of item analysis can provide insights into how to enhance the measurement properties of a test.
The document discusses item analysis which is used to evaluate the quality and performance of test items. It addresses several key aspects of item analysis including calculating the index of difficulty and discrimination for each item, examining distractors, and using the results to identify issues and determine if items should be retained, modified, or discarded. The purpose is to select the best items for the final test form and identify areas for improvement.
This document discusses language testing and test construction. It defines a test as a measuring device that assesses achievement of training objectives. Tests should be valid, reliable and fair. The purposes of tests are to assess progress, compare performance, diagnose weaknesses, and improve understanding. Good tests have a clear structure with competence-based categories and use of operational verbs. Test analysis qualitatively and quantitatively evaluates item difficulty, discrimination, and answer distribution to improve test validity and reliability. Reliability is measured using methods like Kuder-Richardson and Spearman-Brown.
The document discusses classical item and test analysis using the Classical Item and Test Analysis Spreadsheet (CITAS). CITAS is a free Excel tool that calculates important test-level statistics like reliability and item-level statistics like difficulty and discrimination from student response data. It provides summaries of test scores and reliability and calculates item difficulty, discrimination, and supplemental statistics. The examples show how CITAS can be used to evaluate test and item quality for classroom assessments.
1. The document discusses analyzing test items through quantitative and qualitative methods. It defines key terms like difficulty index, discrimination index, and describes how to calculate them.
2. The document provides examples of analyzing test items based on student response data. It shows how to determine the difficulty level, identify effective or ineffective distractors, and ways to improve test items based on the analysis.
3. The goal of the analysis is to evaluate how well items discriminate between higher and lower performing students, identify issues, and determine if items should be retained or modified to make them more effective.
The document discusses item analysis for multiple choice questions (MCQs). Item analysis involves analyzing student performance on individual test questions to evaluate question quality. It provides information on question difficulty level and ability to differentiate between higher and lower performing students. The difficulty index is calculated as the percentage of students who answered the question correctly. The discrimination index shows how well each question separates students who scored high on the test from those who scored low. Questions with moderate difficulty and high discrimination are considered ideal.
This document provides guidelines for conducting a try-out test and performing item analysis on a test. It explains that a try-out test should be conducted on a sample similar to the actual test takers and under similar conditions to prepare for the real test administration. Item analysis evaluates the quality of test items using metrics like item difficulty index and item discrimination index calculated based on comparing response rates of high-scoring and low-scoring test takers. The document provides examples of computing these indexes and interpreting their values to identify items that need revision or removal.
Item analysis is used to judge the quality of test items by systematically analyzing their performance. It involves ranking students based on their scores, dividing them into high and low groups, and calculating difficulty and discrimination indices. The difficulty index indicates how easy or difficult an item is based on the number of students answering it correctly. The discrimination index estimates how well an item distinguishes between students with high and low ability levels. Item analysis is an important part of test construction and evaluation to improve the quality of assessment.
Lesson 21 designing the questionaire and establishing validity and reliabiltymjlobetos
The document provides steps for designing a valid and reliable questionnaire. It discusses establishing validity by ensuring the questionnaire measures the intended construct through face validity, content validity, criterion-related validity including concurrent and predictive validity, and construct validity. Reliability is established through test-retest reliability, split-half reliability, and measuring internal consistency using Cronbach's alpha. The steps also include pilot testing the questionnaire to identify issues and revising it based on feedback before final use.
International Journal of Mathematics and Statistics Invention (IJMSI) inventionjournals
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
objective test scoring and essay scoringSANCHAYEETA2
The document summarizes objective and essay test scoring methods. It discusses manual, stencil, and machine scoring for objective tests. It also describes point and holistic scoring for essay questions. The key advantages and disadvantages of each method are outlined. Objective test scoring aims to reduce guessing, while essay questions assess higher-order thinking but are more time-consuming to administer and grade.
The document discusses guidelines for grading tests and performance tasks. It covers topics such as the purposes of grading, different scoring methods like number right scoring and negative marking, types of test scores like raw scores and percentile ranks, and guidelines for grading essays. The key points are:
- Grades communicate learner achievement and provide feedback. Scoring should be clear, consistent, and aligned to learning outcomes.
- Common scoring methods include counting correct answers, subtracting points for wrong answers, and partial credit systems.
- Test scores take forms like raw scores, percentages, criterion-referenced scores based on standards, and norm-referenced scores comparing performance to peers.
- Essay grading guidelines include identifying criteria
This document summarizes the use of online testing in mathematics courses to help students transition to university. It describes the Pearson MyMathTest website used to deliver four sequential tests covering secondary school topics. Students could take the tests anytime and received a 10% grade for successfully completing all four. The tests aimed to help students identify knowledge gaps and self-remediate. Instructors could track student performance and class averages. Analysis of exam results found students in 2009 who used the online tests scored 4% higher on average than those in 2008 who did not have this resource. Student feedback was generally positive about practicing skills and improving competency through flexible, self-paced testing.
The document analyzes the validity, reliability, difficulty, distinguishing characteristics, and response patterns of a 40-item multiple choice test administered to 7th grade students. The analysis found that 3 items were valid, the test had high reliability, difficulty levels varied but most items were easy, characteristics varied from poor to excellent, and most items and distractors were good with room for improvement. In conclusion, most items could be used again but some invalid items need replacing to effectively measure student ability.
1. The document discusses the important qualities of a good measuring instrument, which include validity, reliability, objectivity, administrability, scorability, comprehensiveness, interpretability, and economy.
2. Validity refers to a test measuring what it intends to measure, and is established through expert judgment, correlation with other valid criteria, or factor analysis. Reliability means consistency of results and is determined by test-retest correlation or splitting results into sets.
3. Other qualities include objectivity in scoring, clear instructions for easy administration and scoring, wide sampling of test areas, interpretable results, and low cost.
Here are some suggestions to make sample tests more useful:
1. Ensure tasks are aligned with course objectives and real-world language use. This improves construct validity.
2. Pilot tests with a small sample to check reliability, practicality and receive feedback. Revise unclear/flawed items.
3. When possible, incorporate interactive elements that require productive skills like discussions or role-plays. This increases authenticity.
4. Balance question types (e.g. multiple choice, short answer, essay) to accommodate different learner strengths. Too much of one type reduces practicality.
5. Provide clear scoring criteria and train raters to ensure consistency. Reliability impacts test usefulness.
6
Validity in Psychological Testing refers to the test measure what it claims to measure. The presentation discusses categories in validating procedures such as construct identification, criterion prediction and content description in psychological testing.
Test validity refers to validating the appropriate use of a test score for a specific context or purpose. Validity is determined by studying test results in the intended setting of use, as a test may be suitable for one purpose but not another. Validity is a matter of degree rather than an absolute quality, and establishing validity requires empirical evidence and theoretical justification that the intended inferences from test scores are adequate and appropriate.
This document discusses understanding student growth projection data and establishing growth goals. It addresses reading growth reports, considering different types of growth goals, setting goals to close achievement gaps, and factors that affect measuring growth like standard error and classroom testing conditions. The document also discusses advantages of different testing terms and issues like gaming the system to manipulate growth results.
To all the people who will read this presentation, I hope you will with this. The content of this presentation are get from the Psychological Assessment book. And this is not all mine.
Final Project ScenarioA researcher has administered an anxiety.docxAKHIL969626
Final Project Scenario
A researcher has administered an anxiety survey to students enrolled in graduate level statistics courses. The survey included three subscales related to statistics anxiety: (a) interpretation anxiety, (b) test anxiety, and (c) fear of asking for help. For the items that comprised the scales, students were asked to respond using a 5 point likert-type scale ranging from (1) No Anxiety to (5) High Anxiety. Therefore, higher scores on the anxiety subscales implied higher levels of anxiety.
In addition to the statistics anxiety subscales, the survey contained a subscale related to the use of statistical software and a subscale related to self-perceived confidence concerning general computer use. Students responded to items on the statistical software subscale using a response range from (1) Strongly Disagree to (7) Strongly Agree. For the computer confidence subscale, students responded to items using a range from (1) Strongly Disagree to (5) Strongly Agree. For each of these subscales, higher scores implied higher levels of confidence.
The researcher determined the score for each subscale by computing the mean response for the items associated with the subscale. This technique resulted in subscales that had the same possible range and the items that made up the subscale.
A subsample of the researcher’s dataset contains the following variables that should be used for completing the four final projects. The variables included in the dataset are:
Variable name:
Label:
Values:
gender
1: Female
2: Male
race
1: White
2: Non-White
age
courses
Number of online courses completed
1: 0-2 courses
2: 3-7 courses
3: 8 or more courses
interpret
Anxiety associated with reading and interpreting output from analyses
test
Anxiety associated with taking a test in a statistics course
help
Anxiety associated with asking for help during a statistics course
software
Self-reported level of confidence is using statistical software
computer
Self-reported confidence in general computer use
Final Project 1:
Use SPSS to conduct the necessary analysis of the Age variable and answer each of the following questions.
Questions:
1. What is the value of n?
2. What is the mean age?
3. What is the median age?
4. What was the youngest age?
5. What was the oldest age?
6. What is the range of ages?
7. What is the standard deviation of the ages?
8. What is the value of the skewness statistic?
9. What are the values of the 25th, 50th, and 75th percentiles?
10. Present the results as they might appear in an article. This must include a table and narrative statement that provides a thorough description of the central tendency and distribution of the ages.
Final Project 2
One of the researcher’s questions involved the difference in scores on the Interpretation Anxiety subscale between male and female respondents. Use SPSS to conduct the analysis that is appropriate for this research question and answer each o ...
This document discusses error and accuracy in test scores. It defines error as the difference between a test taker's obtained score and their true score. The standard error of measurement (SEM) estimates this error and is used to determine a range or "band" around a score within which a test taker's true score likely falls. Sources of error include factors related to the test taker, the test itself, test administration, and scoring. Understanding error is important to avoid overinterpreting small differences in scores and to recognize the fallibility of all test scores.
Standardized tests are designed and administered consistently to allow for comparison of student performance. Tests are given to a sample group to determine average scores and the spread of scores. This establishes norms that individual students can be compared to. There are two main types of standardized tests - norm-referenced tests which compare students to peers, and criterion-referenced tests which assess knowledge of a defined subject area. Tests go through a process of development that includes trying out drafts, analyzing results, revising weak questions, and further testing to establish reliability and validity.
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This document contains 20 multiple choice questions from 5 versions of an RLGN 104 Test 2 from Liberty University. The questions cover topics like the cosmological argument, the design argument, the trinity, types of fallacies, evidence and critical thinking.
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RLGN 104 - Test 1(5 Versions) Answers, Liberty University, Secure high grade
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CEFS 521 Quiz -3, Liberty University_3 Version answer, secure HIGHSCORE
1. CEFS 521 Quiz -3, Liberty University_3 Version
answer, secure HIGHSCORE
CEFS 521 Quiz 3, Liberty University • Question 1 1.5 out
of 1.5 points An administrator and the school
psychologist were observing a child to assess for
behavioral problems. An error may occur in reviewing
what the two observers notice. This is reported as: •
Question 2 1.5 out of 1.5 points When the researcher
interprets the reliability coefficient, the closer the score is
to 0: • Question 3 1.5 out of 1.5 points You are attempting
to account for time sampling error and decide to
administer the test a second time. In discussing reliability,
you report this as what method of estimating reliability? •
Question 4 1.5 out of 1.5 points The test manual reports a
reliability coefficient (r) of .92, which means: • Question
5 1.5 out of 1.5 points Keisha receives a 79 on the test.
This is her: • Question 6 1.5 out of 1.5 points A researcher
administers an achievement test to the same group of
participants on three different occasions. In reporting the
2. results, he describes the error that occurs from repeatedly
testing the same individuals. This is called: • Question 7
1.5 out of 1.5 points A test was administered to a group of
students the morning after homecoming. Several of the
students appeared tired and some were coughing and
sneezing. These factors may result in what type of error: •
Question 8 1.5 out of 1.5 points Several test takers
complained that items on the test were vague and
confusing. This creates concern for: • Question 9 1.5 out
of 1.5 points If the reliability coefficient of a test is
determined to be .27, what percentage is attributed to
random chance or error? • Question 10 1.5 out of 1.5
points Jose has developed a test that has poor reliability.
He can seek to increase reliability by: • Question 11 1.5
out of 1.5 points According to Messick (1989),
consequential validity includes • Question 12 1.5 out of
1.5 points In terms of accurate prediction of a criterion
variable, a person who is predicted to do well during the
first semester of college (based on an SAT score) and then
3. does poorly would fall into the __________ quadrant. •
Question 13 1.5 out of 1.5 points The goal of factor
analysis is to • Question 14 1.5 out of 1.5 points
Exploratory factor analysis can be used to • Question 15
1.5 out of 1.5 points The tripartite view of validity
includes content validity, criterion validity, and •
Question 16 1.5 out of 1.5 points Validity coefficients
greater than _________ are considered in the very high
range. • Question 17 1.5 out of 1.5 points
_________________ is calculated by correlating test
scores with the scores of tests or measures that assess the
same construct. • Question 18 1.5 out of 1.5 points A test
designed for elementary school children was administered
to 11th grade students. To these students the test seemed
extremely childish and inappropriate. They cooperated
poorly with the testing procedure and as a result this
negatively impacted the outcome of the test. Which of the
following would have best addressed this problem? •
Question 19 1.5 out of 1.5 points The following are all
4. examples of constructs in education EXCEPT: • Question
20 1.5 out of 1.5 points Evidence of homogeneity refers to
CEFS 521 Quiz 3, Liberty University QUESTION 1 1.5
points The researcher reports the standard error of
measurement (SEM). This is: a different term for the
standard deviation the spread of scores of a single
individual if he/she took a test repeated times the spread
of scores of a group of test takers on a single test a
measure to use alone as an index of reliability 1.5 points
QUESTION 2 You are attempting to account for time
sampling error and decide to administer the test a second
time. In discussing reliability, you report this as what
method of estimating reliability? Alternate forms Test-
retest Split-half reliability Internal consistency reliability
1.5 points QUESTION 3 If the reliability coefficient of a
test is determined to be .27, what percentage is attributed
to random chance or error? 27% 73% 2.7% unknown
percentage 1.5 points QUESTION 4 Several test takers
complained that items on the test were vague and
5. confusing. This creates concern for: time-sampling error
interrater differences quality of test items test-taker
variables 1.5 points QUESTION 5 A researcher is
concerned with measuring internal consistency reliability
and has decided to use the Kuder- Richardson Formulas
with a Likert Scale test. This is a problem because the:
test does not have dichotomous test items researcher
needs a second test for comparison test does not measure
internal consistency reliability researcher is concerned
with content sampling error 1.5 points QUESTION 6 A
researcher wants to measure content-sampling error with
a Likert scale test. Which of the following methods would
be best? Test-retest Coefficient Alpha The Kuder-
Richardson formulas Interrater differences 1.5 points
QUESTION 7 A test was administered to a group of
students the morning after homecoming. Several of the
students appeared tired and some were coughing and
sneezing. These factors may result in what type of error:
time-sampling error test administration quality of test
6. items test-taker variables 1.5 points QUESTION 8 Keisha
receives a 79 on the test. This is her: true score reported
score observed score predicted score 1.5 points
QUESTION 9 When interviewing test takers who had an
achievement test on three different occasions, participants
reported that they had remembered some of the answers
from the previous test administration. This is known as:
practice effect content effect test-retest effect carryover
effect 1.5 points QUESTION 10 An administrator and the
school psychologist were observing a child to assess for
behavioral problems. An error may occur in reviewing
what the two observers notice. This is reported as:
content-sampling error time-sampling error interrater
differences test-taker variables 1.5 points QUESTION 11
Validity coefficients greater than _________ are
considered in the very high range. .50 .60 .70 .80 1.5
points QUESTION 12 What information is included on a
Multitrait-Multimethod Matrix? subtests and correlations
between each subtest methods of assessment, traits
7. examined, and correlations loading factors and
correlations of subtests false positives, false negatives,
true positives, and true negatives 1.5 points QUESTION
13 According to Messick (1989), consequential validity
includes evaluating the actual and potential consequences
of a given test assessing the social impact of a test's
interpretations both a and b neither a nor b 1.5 points
QUESTION 14 ___________________________ is a
threat to validity that implies that a test is too narrow and
fails to include important dimensions or aspects of the
identified construct. Content underrepresentation Content-
irrelevant variance Construct underrepresentation
Construct-irrelevant variance 1.5 points QUESTION 15
Scores on the Kaufman Assessment Battery for Children
have been shown to differ significantly between children
with ADHD and children who are gifted. This is an
example of which type of validity evidence? Discriminant
validity evidence Group differentiation studies Age
differentiation studies Experimental differentiation studies
8. 1.5 points QUESTION 16 Exploratory factor analysis can
be used to investigate the differences between groups
develop new testing instruments confirm expectations
about a scale's dimensions determine if a test produces
negative consequences 1.5 points QUESTION 17
_________________ are concepts, ideas, or hypotheses
that cannot be directly measured or observed Constructs
Variables Standards Specifications 1.5 points QUESTION
18 The goal of factor analysis is to measure the
effectiveness of specific interventions in research reveal
how scores differ from one group to the next prove the
age of the individuals taking the test impacts their scores
decrease the number of variables into fewer, more general
variables 1.5 points QUESTION 19 In terms of accurate
prediction of a criterion variable, a person who is
predicted to do well during the first semester of college
(based on an SAT score) and then does poorly would fall
into the __________ quadrant. true positive true negative
false positive false negative 1.5 points QUESTION 20
9. When discussing the relationship between reliability and
validity, which of the following is true? High reliability
always indicates low degree of validity. High reliability
always indicates high degree of validity. Low reliability
always indicates high degree of validity. Low reliability
always indicates low degree of validity. CEFS 521 Quiz
3, Liberty University QUESTION 1 1. When interviewing
test takers who had an achievement test on three different
occasions, participants reported that they had remembered
some of the answers from the previous test
administration. This is known as: practice effect content
effect test-retest effect carryover effect 1.5 points
QUESTION 2 1. The test manual reports a reliability
coefficient (r) of .92, which means: 92% of the variance
in scores is attributed to error 92% of the variance in
scores is explained by real differences nothing
conclusively because it depends on the method used
nothing conclusively because it depends on the source of
measurement error 1.5 points QUESTION 3 1. Keisha
10. receives a 79 on the test. This is her: true score reported
score observed score predicted score 1.5 points
QUESTION 4 1. You are reading about reliability of a
test in the test manual and notice that the researchers
report using a Spearman-Brown coefficient. You can infer
that internal consistency reliability was measured using:
the Kuder-Richardson formulas coefficient alpha split-
half reliability test-retest 1.5 points QUESTION 5 1. A
researcher wants to measure internal consistency in a test
that measures two different constructs (self-esteem and
depression) without subdividing the items into the two
construct groupings. Which of the following would be the
best method to use in measuring internal consistency?
Split-half reliability The Kuder-Richardson formulas
Coefficient alpha Any of the above methods would be
equally appropriate 1.5 points QUESTION 6 1. You are
attempting to account for time sampling error and decide
to administer the test a second time.In discussing
reliability, you report this as what method of estimating
11. reliability? Alternate forms Test-retest Split-half
reliability Internal consistency reliability 1.5 points
QUESTION 7 1. A researcher wants to measure content-
sampling error with a Likert scale test. Which of the
following methods would be best? Test-retest Coefficient
Alpha The Kuder-Richardson formulas Interrater
differences 1.5 points QUESTION 8 1. The researcher
determines that the reliability coefficient is .65. This
means the reliability is: generally acceptable because it is
over .50 generally acceptable for only interrater reliability
not generally acceptable not generally acceptable unless it
is a new test 1.5 points QUESTION 9 1. The researcher
reports the standard error of measurement (SEM). This is:
a different term for the standard deviation the spread of
scores of a single individual if he/she took a test repeated
times the spread of scores of a group of test takers on a
single test a measure to use alone as an index of reliability
1.5 points QUESTION 10 1. A researcher is concerned
with measuring internal consistency reliability and has
12. decided to use the Kuder- Richardson Formulas with a
Likert Scale test. This is a problem because the: test does
not have dichotomous test items researcher needs a
second test for comparison test does not measure internal
consistency reliability researcher is concerned with
content sampling error 1.5 points QUESTION 11 1. The
goal of factor analysis is to measure the effectiveness of
specific interventions in research reveal how scores differ
from one group to the next prove the age of the
individuals taking the test impacts their scores decrease
the number of variables into fewer, more general
variables 1.5 points QUESTION 12 1. Comparing pre and
post-test scores of two groups, one group that experienced
an intervention and one group that did not, is an example
of factor analysis. contrasted group studies. experimental
results. age differentiation studies. 1.5 points QUESTION
13 1. ___________________________ is a threat to
validity that implies that a test is too narrow and fails to
include important dimensions or aspects of the identified
13. construct. Content underrepresentation Content-irrelevant
variance Construct underrepresentation Construct-
irrelevant variance 1.5 points QUESTION 14 1. In terms
of accurate prediction of a criterion variable, a person
who is predicted to do well during the first semester of
college (based on an SAT score) and then does poorly
would fall into the __________ quadrant. true positive
true negative false positive false negative 1.5 points
QUESTION 15 1. The tripartite view of validity includes
content validity, criterion validity, and discriminate
validity convergent validity content validity construct
validity 1.5 points QUESTION 16 1. The
______________ is characterized by assessing both
convergent and discriminant validity evidence and
displaying data on a table of correlations. multitrait-
multimethod matrix contrasted group study age
differentiation study factor matrix 1.5 points QUESTION
17 1. A test designed for elementary school children was
administered to 11th grade students. To these students the
14. test seemed extremely childish and inappropriate. They
cooperated poorly with the testing procedure and as a
result this negatively impacted the outcome of the test.
Which of the following would have best addressed this
problem? Evidence of homogeneity Discriminant
evidence Evidence based on consequences of testing
Evidence based on response processes 1.5 points
QUESTION 18 1. _________________ is calculated by
correlating test scores with the scores of tests or measures
that assess the same construct. Convergent validity
Discriminant validity Face validity Content validity 1.5
points QUESTION 19 1. Criterion measures that are
chosen for the validation process must be relevant
uncontaminated reliable All of the above 1.5 points
QUESTION 20 1. What information is included on a
Multitrait-Multimethod Matrix? subtests and correlations
between each subtest methods of assessment, traits
examined, and correlations loading factors and
15. correlations of subtests false positives, false negatives,
true positives, and true negatives
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