Data everywhere
Student’s Name
Institutional Affiliation
Course Name and Date
Instructor’s Name
Submission Date
Data everywhere
Data are facts and figures collected for analysis or a reference. Learners widely use data in studying different academic units. The teachers also use a wide range of data so that they can gather sufficient information to instruct the learners. There are several sources of data that the teachers and learners can use to extract the data of interest. For instance, teachers can use primary or secondary data sources as well as learners. Also, the correct data can be gathered through either quantitative or qualitative means. In this paper, I will discuss how data is useful in learning.
Mean, Median and Mode
Mean is the measurement of averages. It can also be described as the arithmetic or geometric average (Aworanti, 2016). On the other hand, the median is defined as the measurement of the variable or variables in the middle. The mode is the measures the most appearing or the frequently occurring variable. For instance, the heights of ten elves are 37, 36, 35, 35, 33, 33, 33, 32, 30 and 26 (Aworanti, 2016). Using this data, we can determine its mean, mode and median.
Mathematically, mean is given by the summation of the observations/the number of observations. Mean=ƩX/N implying that, 330/10=33. Therefore, the mean of the data is 33. The median is calculated by arranging the observations in ascending order and then identifying the middle term or observation. That is 26, 30, 32, 33, 33, 33, 35, 35, 36 and 37. The middle observations are 33 and 33. Median is the value in between the observations and is (33+33)/2, which is 33. The mode is the most occurring observation, and in our case for the above data, the mode is 33.
Educational Assessment
The bar graph shows the ability rates for the learners. In this case, there are many learners under the underrated ability rank. They account for approximately 77.2% (Kwon, Lee & Shin, 2017). The leaners under the overrated ability account for 47.1% while the learners with the outstanding ability account for 13.3% (Kwon, Lee & Shin, 2017). This data implies that most learners failed in the summative assessment while the minor ones performed above average. For instance, some learners gave incorrect answers to the assessment. The questions concerning the calculation of mean and median for grouped data seemed to challenge most of the learners.
Applying the Data
I can use the data to instruct the learners on how to study and also teach them on the areas to restudy so that they may decipher the academic content in those areas satisfactorily. The incorrect data choices show that the learners were not sufficiently informed (Dixson & Worrell, 2016). This is because their performances im-plies more failure than good scores. For example, questions 2 and 7 were failed by 10 and 8 learners, respectively (Dixson & Worrell, 2016). Every learner scored in question 4 of the summative assessment.
Few learners failed in questions 1, 3, 5, 8, 9 and 10 (Dolin et al., 2018). In reteaching the failed concepts, I can instruct leaners to review the essential areas in which they did not understand the concept. I can use secondary sources to reteach them because these sources will give a wide range of data in need. I can provide feedback on the test results to my learners through writing report forms to them recording their performances.
Interpreting Mean, Median and Mode
Mean is the measure of averages while the median is the measure of the middle observation. On the other hand, the mode is the most occurring observation (Dolin et al., 2018). These three concepts, however, have one similarity that, they are all measures of central tendency. Mean would be appropriately used in the cases of computing learners’ mean score (Dolin et al., 2018)e. Median may be used in the calculation of cutpoints while mode can be used in computing the frequently appearing observations like the numbers of white cars. I can use this data to the learners or the learners’ parents when sharing the learner’s results to inform them about their progress in academic work.
In conclusion, statistics is essential because it enables learners to acquire techniques to collect, record, describe and interpret various data types for their advantage. In the case of the above summative assessment for the learners, they would be able to use statistics to gather both qualitative and quantitative data to help them in the evaluation.
References
Aworanti, O. A. (2016). Information and Communications Technology (ICT) in Nigeria Educational Assessment System–Emerging Challenges. Universal Journal of Educational Research, 4(6), 1351-1356.
Dixson, D. D., & Worrell, F. C. (2016). Formative and summative assessment in the classroom. Theory into practice, 55(2), 153-159.
Dolin, J., Black, P., Harlen, W., & Tiberghien, A. (2018). Exploring relations between formative and summative assessment. In Transforming assessment (pp. 53-80). Springer, Cham.
Kwon, S. K., Lee, M., & Shin, D. (2017). Educational assessment in the Republic of Korea: lights and shadows of high-stake exam-based education system. Assessment in Education: Principles, Policy & Practice, 24(1), 60-77.