The presentation discusses the various aspects of the Administration of the Test and Analysis of Students’ Performance

1. Administration of the test and
analysis of students’ performance
Gautam Kumar
Assistant Professor
University Department of Teacher Education
Utkal University, Bhubaneswar

2. Common Terms Related to Test Administration and its Analysis
Analysis: The examination and evaluation of the relevant information to
select the best course of action from among various
alternatives.
Test: A procedure for critical evaluation; a means of determining the
presence, quality, or truth of something.
Scoring: It means to evaluate and assign a grade.
Report: A document containing information organized in a narrative,
graphic, or tabular form, prepared on ad hoc, periodic, recurring,
regular, or as required basis.

3. Administration of the test
Administering the written test is perhaps the most important aspect of the
examination process. The atmosphere the test administrator creates in the test
room and the attitude the test administrator displays in performing his/her
duties is extremely important and are clearly visible in the performance of the
students.
The test administrator's manner, bearing, and attitude may well inspire
confidence in examinees and put them at ease while appearing in the testing
process.
A test administration procedures have great impact on student test performance.

4. Steps in Test Administration
• Before the test: preparedness before starting the exam.
• After Distributing Test Papers: environment and ease of participating in
the exam process.
• During the Test: Facility and comfort of participating in the test.
• After the Test: fair scoring, analysis and reporting of test.

5. Grading of Test
Grading refers to the process of using symbols, such as letter to indicate various
types of students’ progress (Nitko 2001).

6. Common Methods of Grading
Letter grades:
There is a great flexibility in the number of grades that can be adopted i.e. 3 –
11.
Limitations:
• Meaning of grades may vary widely
• Do not describe strengths/weakness of students
Strengths:
• Easy to use
• Easy to interpret theoretically
• Provide a concise summary

7. Common Methods of Grading
Number/Percentage grades
(5, 3, 2, 1, 0) or (98%, 80%, 60% etc.) It is same as letter grades. Only difference is that instead
of letters numbers of percentage is used.
Strengths:
• Easy to use
• Easy to interpret theoretically
• Provide a concise summary
• May be combined with letter grades
• More continuous than letter grades
Limitations:
• Meaning of grades may vary widely
• Do not describe strengths/weaknesses of students
• Meaning may need to be explained or interpret

8. Common Methods of Grading
CHECK LIST AND RATING SCALE
They are more detailed and since they are too detailed it is cumbersome for teachers to
prepare
Strengths
• Present detailed lists of students’ achievements
• Can be combined with letter grades
• Good for clinical evaluation
Limitations:
• May become too detailed to easily comprehend
• Difficult for record keeping.

9. Common Methods of Grading
Advantages of Grades
• Grades are divided in to 5 – 7 divisions to which student’s performance is
assigned as compared to 101 (0 – 100) divisions of conventional marking.
• It is a convenient method.
• Chances of errors are minimized
Limitation of Grades:
• The assigned grades varies from teacher to teacher.
• Do not indicate students strengths or weaknesses
• Foster unfair competition among students.

10. Common Methods of Grading
Scoring Essay type Questions
Evaluating essay response the evaluator should:
• Evaluator should use appropriate method to minimize bias
• Pay attention to the significant and relevant aspects of the answer
• Be careful not to let personal idiosyncrasy affect assessment
• Apply uniform standard to all the papers

11. METHOD OF GRADING ESSAY TYPE QUESTION
Analytical grading : (Point method)
In this method of the ideal answer to a question is specified in advance, although need not be
in the amplitude the ideal or model answer is broken down into specific point.
Advantages:
• It can yield very reliable scores
• The preparation of detailed answer may bring to the teachers.
• The sub division of the model answer can make it easier to discuss with the students the
marks awarded to them.
Limitations:
• It is very laborious and time consuming
• In attempting to identify the elements, undue attention may be given to the specific
aspect.

12. METHOD OF GRADING ESSAY TYPE QUESTION
Global grading:
In this method the ideal answer is not sub divided into the specific points and
component points. The examiner is interacted to read the responses rapidly
from a general impression and using some standard and standard assign

13. METHOD OF GRADING ESSAY TYPE QUESTION
Global grading:
In this method the ideal answer is not sub divided into the specific points and
component points. The examiner is interacted to read the responses rapidly
from a general impression and using some standard and standard assign

14. METHOD OF GRADING ESSAY TYPE QUESTION
Sequential Grading
In order to bring more objectivity more answers can be scored beautifully. This
is the same teacher valuing answer of a particular question.

15. METHOD OF GRADING ESSAY TYPE QUESTION
Computer Software
The “Software” learns a specific subject area by scanning appropriate
documents. Then, the software is fed graded essays to set up the grading
standards.

16. SCORING OBJECTIVE TESTS
Hand graded:
• Due to human effort, mistakes may occur. Having two graders grade exams
help to catch 90% of those simple mistakes in grading.
Machine Scoring:
• As accurate as the answer code given to the computer.
• Some testing publishers will only release or sell their products to
individuals who have undergone special training or have a particular degree in
the related field

17. TYPES OF SCORE
Raw Scores:
A raw score is an original datum, or observation, that has not been transformed.
It is an unaltered measurement. For example, let's say you took a test in class
and scored 85.
A raw score by itself has no meaning. It can be interpreted only by comparing it
with some standard such as total number of items for a test or with raw scores
earned by a comparison group.
Uses: A raw score provides an indication of the variability in performance
among students in a classroom.

18. ANALYSIS OF RAW SCORES
Mean: The mean is equal to the sum of all the values in the data set divided by
the number of values in the data set.
Median: The median is the middle score for a set of data that has been arranged
in order of magnitude. The median is less affected by outliers and
skewed data.
Mode: The mode is the most frequent score in our data set.

19. ANALYSIS OF RAW SCORES
Percentile Rank: A percentile is a measure that tells us what percent of the
total frequency scored at or below that measure. A percentile rank is the
percentage of scores that fall at or below a given score.
Advantages:
• Easy to understand and interpret.
• Not affected by outliers

20. ANALYSIS OF RAW SCORES
Stanine (Standard nine): Stanine scores express test results in equal steps that
range from 1 (lowest) to 9 (highest). The average is a score of 5. In general,
stanine scores 1, 2 & 3 are below average, 4, 5 & 6 are average and 7, 8 & 9 are
above average

21. ANALYSIS OF RAW SCORES
Standard Scores: The standard scores indicate a student’s relative position in a
group. It expresses test performance in terms of standard deviation units from
the mean.
The mean is the arithmetical average. The standard deviation is a measure of
the spread of scores in a group.

22. ANALYSIS OF RAW SCORES
Z – Score
• Z score is a conversion of raw data to a standard score, when the
conversion is based on the population mean and population standard deviation.
• When a full data set is available with us, we can compute the Z score. Z
score is the subtraction of the population mean from raw score and then divides
the result with population standard deviation.
Z – Score = Raw Score –Mean/Standard deviation
Note: If a z-score is positive, its' corresponding raw score is above the mean.
If a z-score is negative, its' corresponding raw score is below the mean.

23. ANALYSIS OF RAW SCORES
T Scores:
T score is a conversion of raw data to the standard score when the conversion is
based on the sample mean and sample standard deviation. When the population data set
is not available, then we have to pick up some sample data to compute the sample mean
and population standard deviation.
T score is the subtraction of individual standard deviation from individual mean and
then divide the result with sample standard deviation whole result multiplied by sample
size. Its formula is as given below:
t = {(x ̅- μ)/s}*
x ̅ = Sample Mean
μ = Population Mean
s = Sample Standard deviation
n = sample size

24. Q & A
Friday, 07 August 2020 Gautam I UUDTE I Utkal University 24