How do you calculate mean, median, mode, and standard deviation?
Standardized testing instruments reduce the capacity and ability of children into a numerical derivative called the score. The mean, median, mode, and standard deviation are some of the means of assessing distribution of the scores so arrived at (Hoy & Adams, 2015). Mean is the average score and is calculated by adding all the scores of all students then dividing the total with the number of students assessed (Hoy & Adams, 2015). The median is the score of the average pupil or pupils arrived at by arranging all the numbers chronologically from the largest to the smallest value (Hoy & Adams, 2015).
If the number of pupils is odd, the median is the number at the very middle. If the students are an even number, the median becomes the mean between the two middle numbers. Mode refers to the most frequent score. It is simply calculated by checking how many times a score appears. The one with the highest appearances is the mode (Hoy & Adams, 2015). Standard deviation is the average dispersion from the mean score. To calculate the standard deviation, the mean will be subtracted from each score. The squares of the respective differences will be added together and divided with the number of pupils tested. The square root of the result is the standard deviation (Hoy & Adams, 2015).
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What are percentile ranks, standard deviations, z scores, T scores, and stanine scores?
All the above mentioned are means of establishing relations between scores in a standardized test (Watt, 2015). Percentile rank determines numbers against a preset percentile after all the scores have been transformed into percentages (Wellington, 2015). Any percentage can be used. If for example, 67% is the percentile used, all scores equal to or below 67% fall within this percentage rank. Standard deviation is the calculated average dispersion from the average score. The standard deviation can be positive or negative depending on whether the deviation is higher or lower that the mean (Watt, 2015). The measure of whether the deviation is higher or lower than the mean is the Z score (Wellington, 2015).
If the actual instead of average deviation is being sought, this is known as the T score (Watt, 2015). Under a T score, the average is always 50 any 10 point deviation from 50 is one standard deviation above or below the mean (Wellington, 2015). A 70 will, therefore, be two standards above a mean while a 10 will be four standards below the mean. Finally, the stanine score is a version of the T score that is limited to integers (Watt, 2015). The average, therefore, becomes 5, the highest score is nine while the lowest score is a zero (Wellington, 2015). In this manner, any score can be reduced to an integer value.
How can you improve reliability and validity in testing ?
The basic principle behind a standard test is keeping all other variables at a constant so that the scores are a pure reflection of the pupil’s respective capacities. Unfortunately, pupils and students are humans and cannot be calibrated. This implies that Calibration must be on the test instruments and result derivative formulae. Standard, therefore, becomes a relative term instead of an actual definite one. The more standard circumstances of a test are, the more accurate the results. On a test by test basis, the best and indeed only way to improve reliability and validity of testing is to understand the respective circumstances and variability of the group being tested and calibrate the test accordingly.
What do results of achievement, aptitude, and diagnostic tests tell teachers?
Achievement tests are outcome tests and tell the teacher how much the pupils has learnt and/or developed. Aptitude tests measure capacity and potential for future learning. Diagnostic tests are undertaken at extreme circumstances to assess if a student fits in a normal class or will require specialized teaching or affirmative attention.
How would you prepare students (and yourself) for taking standardized tests?
Standard tests gauge a particular set of primary capacities and capabilities. There are however, several secondary factors and circumstances that can interfere with the tests and fudge the results (Mendell et al, 2015). For example, except in an elementary or linguistic setting, a standard test will not measure literacy. The ability to read and write will therefore be an assumed constant. Further, fortitude may also not be a primary measure yet panic will easily interfere with results. To prepare students for a standardized test, as a teacher I would seek to understand the primary measurable factors. I would then train the students on the secondary factors to avoid their interference (Mendell et al, 2015). I would also seek to learn possible variables such as command of English language for foreign students. This will enable limiting of their effects to the final score.
What are the strengths and weaknesses of alternative forms of assessment such as portfolios?
Alternative testing forms mainly involve testing students from the perspective most relevant to the individual student with little or no comparison with other students (Bevitt, 2015). One of the strength of this mode lies in the fact that today’s learning is more holistic that specific. There are many elements of learning that are, therefore, particular to the individual student (Bevitt, 2015). Further, specialization in academics is now beginning from a very early stage. Some students are basically trained in one discipline with all the others being secondary. A good example is the advent of football academies.
Among the weaknesses of alternative testing is inaccuracy. The score mainly depends on the individual student and the assessor. It is easy for one or both to be wrong leading to inaccurate testing (Bevitt, 2015). This makes the reliability and validity of this testing to be relative and not absolute. Another weakness lies in the fact that different tests and testing regimens have to be continuously developed to meet the ever changing circumstances (Bevitt, 2015).
References
Bevitt, S. (2015). Assessment innovation and student experience: a new assessment challenge and call for a multi-perspective approach to assessment research. Assessment & Evaluation in Higher Education , 40 (1), 103-119.
Hoy, W. K., & Adams, C. M. (2015). Quantitative research in education: A primer . New York: Sage Publications.
Mendell, M. J., Eliseeva, E. A., Davies, M. M., & Lobscheid, A. (2015). Do classroom ventilation rates in California elementary schools influence standardized test scores? Results from a prospective study. Indoor Air, 26 (4):546-57. doi: 10.1111/ina.12241
Watt, A. (2015). Fundamentals of Quantitative Research in the Field of Teaching English as a Foreign Language. In The Praxis of English Language Teaching and Learning (PELT) , 97-120. Sense Publishers: Sense Publishers.
Wellington, J. (2015). Educational research: Contemporary issues and practical approaches . London: Bloomsbury Publishing.
