Article Analysis: Losing Local Control
Article Analysis: Losing Local Control
Article: ‘Losing Local Control’
What is the purpose of the data-based decision making strategy (i.e., describe, compare, correlate, or predict)?
The purpose of this data-based decision making strategy is correlate the theory of economies of scale with the outcomes in schools. The article notes that recent surveys reveal that U.S student rank poorly yet there is a steady increase in spending in the school. The proponents of economies of scale posit that school and district are similar to goods and services industries. Thus, the cost of schooling should fall as a greater number of students are enrolled in school and district. Unfortunately, United States has experience the opposite of the economies of scale theory. The expenditure in U.S public school is the highest across the world. The author is attempting to test the validity of the economies of scale theory in the trends exhibited in U.S public school spending.
The study investigates the revenues used in the production in public schools versus the quality of products produced as a result of the invested funding. The quality of outcomes measured includes both academic and non-academic achievement. The article argues that in the normal business situation as the organisation increases the number of products that it produces a value of unit production tends to fall. In this study, the expenditure in school is not only soaring high, but the quality tends to decrease. Moreover, this spending does not reflect that the law of economies scale holds for the school.
How is the focus/purpose of the data-based decision making strategy stated (i.e., what stage of the data-based decision making strategy process is addressed specifically)?
The article addresses the purpose of decision making strategy after examining existing literature about expenditure trends in public schools and districts. The author tests why larger organisations and larger subunits tend produce less per unit value? The author attempts to apply the same analogy in determining the trends in the public schools and district. The author stated a considerably moderate literature concerning the trends exhibited in public schools and districts as well as business firms. In addition, the captured literature provided a correlation between the falling unit cost as the value of production increased. Largely, after stating all these analogies, the article does not directly illustrate the purpose of the study, but leaves the reader to make inference from the literature provided to establish the supposed research.
How is the data-based decision making strategy framed or stated (e.g., in light of what concerns, issues, concepts, or theories)?
The article considered the arguments of Buchanan (1968), Gooding & Wagner (1985) as well as Olson (1971) which questioned why larger organisation spend less producing a unit value. According to these authors, they suggested larger private and public organisations tend to lose value or efficiency because they concentrate in large productions. The article used the propositions of authors such as Strang (1987) and Kincaid (1992) which submitted that although specialisation as a form of bureaucratic growth was originally intended to mean well, it had harmful psychological impacts. This author points on the trend experienced in elementary schools as an example of the impacts of this notion. The coordination between the local and state functions experienced some hitches that affected funding patterns as good promotion of specific interests that at times lock out the potentiality of the learners.
Further, this article made an in depth review of the literature concerning school size and outcomes. Such review includes the position of Fowler (1992) concerning the disagreement of Barker and Gump (1964) as well as Conant (1967). In a study that examined the response of 2,024 questionnaires, Conant was pleased that large comprehensive high schools exposed the learners to a wide array of options to choose On the other hand, Baker and Gump learned that the outcome of students in small schools was more impressive and students in a small school excelled both socially and psychology. The in-depth reviews of the literature, as well as theories, tend to give the direction of the study. Arguably, whereas the intention of the author is to correlate economies of scale and the outcomes in public schools and districts, the literature reviewed does not only offer supportive details about the data base-based decision making strategy, but also defines the anticipated outcomes.
What understanding of methods and methodology must one have in order to make sense of the policy’s development?
One must demonstrate an understanding of descriptive, analytical skills in order to make inference from the data supplied in this strategy. The data supplied in this article are critical in making observation concerning the correlation between economies of scale and the expenditure and outcome in districts and schools. Largely, the analysis of behavior of the data investigated largely depended on the skill to create descriptive tables of data provided as well as monitoring the trend exhibited by the tested quantity. The result of the tabulated data was used in making observations and conclusions about the tested hypothesis. Largely, the behavior of data as observed allows one to make some conclusion about the correlation of the tested data with unrestricted possibilities. Moreover, the decision concerning the data based decision making largely depended on the ability of the make read and interpret the analyzed data effectively.
Construct the way in which the data-based decision making strategy was to be designed: How were sites and/or subjects selected?
The variable analyzed was selected from voluntary participants in thirty seven district states. The information obtained from the National Education Association concerning the district schools was used in data decision making strategy. The variable covered the size of the district, school size, and the public enrolment. These variables were divided but the number of districts and public schools in every state. The variables selected also focused on the state share which is offered to each prekindergarten through the 12th grade.
The data constitute achievement, minority, expenditure, district size, and state share. The student achievement in the selected districts states was critical in decision making strategy. Similarly, the data of minority schools, expenditure in each school, the size of the district, the share of the state, as well as the size of the school was instrumental in this analysis.
How were data generated? What is/are the source(s) of data?
The data was generated from the statistics released by National Education Association in 1992. These generated data was original as it had been recorded from the statistics collected. How were data analyzed and interpreted?
The data were analysed through tabulation into tables in which the frequency of the trends exhibited by the tested variables were observed. The distributive tables illustrated trends that each variable showed. Using the distributive tables, the analyst was able to identify as well as make conclusion about the tested variable. At a glance, one can identify the outcome as well providing reasons why a given trend was observed.
What role did the policy analyst(s) play?
The policy analyst tabulated the raw data into a distributive table which demonstrated the outcome of the observations made. By creating the distributive, the policy analyst created a chance for any reader to acknowledge the finding of this research data. Largely, the table tends to support a given proposition by providing probable reasons that led to the outcome.
How does the way in which the data-based decision making strategy was developed fit with the original conceptualization of the problem?
What criticisms would you raise of the data-based decision making strategy process utilized?
The data decision making strategy utilised is quite effective because its accuracy his very high. The method is scientific hence the deviation of the anticipated results can be detected from the errors recorded during the tabulation and computation of the results. If this data based decision making, the error margin was insignificant, thus it did not affect the posted outcome. From this result, one can support that outcome that averagely large districts and large schools and states tend to project poor achievements. Moreover, the data based decision making strategy has supported confirmed the proposition of some authors that had rejected the conception that economies of scale should apply in public schools in the same way as it does in goods and service industry.
