Economics And Quantitative Analysis Higher Education in United States

Question: Describe about online universities that are facing challenges in sector of higher education in United States? Answer: Introduction The current study is focusing on the online universities that are facing challenges in sector of higher education. The report will be conducting various analyses of online colleges that are present in United States. Moreover, for the report 29 online colleges have been selected so that better result can be drawn. Background Online Universities has been growing at rapid speed that provides academic knowledge to the large number of students. On the other hand, the continuous development in the online universities has posed challenges to the higher education sector (Morrison, 2012). The online education database is engaged in forming better online colleges that are accredited. In US, the online college has grown in significant numbers over the past years. Methods The method that can be used for the particular study will be based on descriptive analysis, scatter diagram and regression equation so that better result can be generated. Moreover, the methods can be helpful in discussing the results and proposing a recommendation for the universities (McCormick and Lucas, 2013). On the other hand, in order to discuss the descriptive analysis, mean, standard deviation, minimum and maximum value will be calculated on the basis on retention rate and graduation rate so that better value can be drawn for online colleges in US. Results Descriptive analysis of retention rate and graduation rate Retention Rate Graduation Rate Mean 57.41379 41.75862 Standard Deviation 23.24023 9.865724 Maximum Variable 100 61 Minimum Variable 4 25 Scatter Diagram with retention rate Figure 1: Retention Rate and Graduation Rate Figure 2: Retention Rate Scatter Diagram Estimated Regression Equation RR(%) GR(%) (x-mean) (y-mean) (x-mean)2 (y-mean)2 (x-mean) (y-mean) 7 25 -50.4138 -16.7586 2541.551 280.8514 844.8656 51 25 -6.41379 -16.7586 41.13674 280.8514 107.4863 4 28 -53.4138 -13.7586 2853.033 189.2996 734.9001 29 32 -28.4138 -9.75862 807.3436 95.23068 277.2794 33 33 -24.4138 -8.75862 596.0333 76.71344 213.8312 47 33 -10.4138 -8.75862 108.4471 76.71344 91.21046 63 34 5.586207 -7.75862 31.20571 60.1962 -43.3413 45 36 -12.4138 -5.75862 154.1023 33.16171 71.48633 60 36 2.586207 -5.75862 6.688466 33.16171 -14.893 62 36 4.586207 -5.75862 21.03329 33.16171 -26.4102 67 36 9.586207 -5.75862 91.89536 33.16171 -55.2033 65 37 7.586207 -4.75862 57.55054 22.64447 -36.0999 78 37 20.58621 -4.75862 423.7919 22.64447 -97.962 75 38 17.58621 -3.75862 309.2747 14.12723 -66.0999 54 39 -3.41379 -2.75862 11.65398 7.609988 9.41736 45 41 45 -0.75862 2025 0.575505 -34.1379 38 44 -19.4138 2.241379 376.8954 5.023781 -43.5137 51 45 -6.41379 3.241379 41.13674 10.50654 -20.7895 69 46 11.58621 4.241379 134.2402 17.9893 49.1415 60 47 2.586207 5.241379 6.688466 27.47206 13.55529 37 48 -20.4138 6.241379 416.7229 38.95482 -127.41 63 50 5.586207 8.241379 31.20571 67.92033 46.03805 73 51 15.58621 9.241379 242.9298 85.40309 144.038 78 52 20.58621 10.24138 423.7919 104.8859 210.8312 48 53 -9.41379 11.24138 88.6195 126.3686 -105.824 95 55 37.58621 13.24138 1412.723 175.3341 497.6932 68 56 10.58621 14.24138 112.0678 202.8169 150.7622 100 57 42.58621 15.24138 1813.585 232.2996 649.0725 100 61 42.58621 19.24138 1813.585 370.2307 819.4174 TOTAL 16993.93 2725.31 4259.341 Regression equation Y = b0 + b1x b1= 4259.341 / 16993.93 = 0.2506 b0 = 41.758- (0.2506) (57.41) = 27.371 Therefore, the regression equation can be written as y= 27.371 + 0.2506x Slope Coefficient of determination Standard Deviation of retention Rate= sqrt (16993.93 / 29) = sqrt (0.80138) = 24.207 Standard Deviation of Graduation Rate = sgrt (2725.31 / 29) = sqrt (0.34019) = 9.69 Therefore, the slope coefficient (r2) is R2= [(1/29) * 4259.341 / (24.207 * 9.69)]2 = 0.39208 Summary Output Regression Statistics Multiple R 0.670245 R Square 0.449228 Adjusted R Square 0.428829 Standard Error 7.456105 Observations 29 ANOVA df SS MS F Significance F Regression 1 1224.286 1224.286 22.02211 6.95E-05 Residual 27 1501.024 55.5935 Total 28 2725.31 Intercept X Variable 1 Coefficients 25.4229 0.284526 Standard Error 3.746284 0.060631 t Stat 6.786166 4.692772 P-value 2.74E-07 6.95E-05 Lower 95% 17.73616 0.160122 Upper 95% 33.10964 0.40893 Lower 95.0% 17.73616 0.160122 Upper 95.0% 33.10964 0.40893 Discussion The two variables that are retention rate and graduation rate represents that mean of each variable are different. For retention rate, mean value is 57.41 and for graduation rate mean value is 41.758. Therefore, it can be analyzed that retention rate is successful in engaging the students in comparison to graduation rate (Bejou and Bejou, 2012). On the other hand, it can be analyzed that standard deviation of retention rate is high to 23.240 due to presence of large variable values in the retention rate whereas in graduation rate many variables has same value and due to that standard deviation is low at 9.86. Apart from that, two universities that is National University and Florida University of US has maximum value under retention rate whereas in graduation rate only Florida National College has maximum value but that too at 61 only. On the other hand, the minimum variable according to retention rate is University of Phoenix and in graduation rate is Western International University and South University. The scatter diagram that has been presented shows that the there is positive correlation among the two variables that is retention rate and graduation rate. As per the scatter diagram, with the increase in x axis there is also significant increase in the y axis. The retention rate as an independent variable also shows that they are positively linked with the universities and due to that universities are able to address growth as per retention rate values (Boden, 2011). On the other hand, it can be depicted that if there is growth of universities as per retention rate then the colleges or universities can also seek growth as per graduation rate. Apart from that some universities has less retention rate such as University of Phoenix and Western International University in comparison to graduation rate. On the other hand, the retention rate is higher as many students join the school and studies in same college next year (Haydarov, Moxley and Anderson, 2012). Moreover, it can be analyzed as per retention rate that a university has more pleas to the students. If there is one unit change in the retention rate then there is significant change in graduation rate. In the next calculation that is estimation of regression equation, it can be concluded that independent variable that is retention rate is linked with the dependent variable of graduation rate of universities. If the retention rates of students are high then it can help in improving the graduation rate of students in colleges (Heuser, Drake and Owens, 2012). The regression estimation helped in knowing the relationship between two variables that is graduation rate and retention rate and their dependency on each other. Therefore, average value in context to dependent variables can be estimated if independent variable is fixed. Apart from that, the dependent variable of graduation rate changes when there is change in the independent variable of retention rate. The estimated regression equation can be effective in predicting graduation rate on the basis of retention rate. The slope coefficient that is R2 which is 0.392 shows that almost 40% of variation in the dependent variable (graduation rate) can be define by the independent variables (retention rate). As per the Regression Statistics, the coefficient of determination is around 44% which means that dependent variable is explained by retention rate. On the other hand, the multiple correlation coefficients are valued at 0.670245 which indicates that there is positive correlation among the retention and graduation rate. Further, it can be concluded that the there is no indication of statistical significance between the retention and graduation rate correlation as it fall in the range of -1 to +1. Regression Equation provide a good fit The regression does not provide good fit as only 44% of the graduation rate variable is explained by the retention rate. On the other hand, the r square is not that high to show better results. Moreover, it can be analyzed that variables are not much closer to regression line as the variable fail to define 100% of the variance (Heyneman, 2012). Therefore, retention rate does not cover all the variance of graduation rate variance. The regression equation can be in the good line if the dependent variable would have been explained by more than 50% by independent variable. Moreover the SS residual value in analysis of variance shows that the given value representing dependent variables variation is not explained. Reviewing results as president of South University After having a closer look to the result, it can be presented that the performance of the south University is not quite good in comparison to other universities in US. The retention rate of south University is 51% which is higher in comparison to Western International University, University of Phoenix, American InterContinental University, etc. Apart from that, the graduation rate is low at 25% which may show that the student may not be financially strong to have a full graduation on time (Hoyert et al. 2012). However, it can be concluded that students are not able to receive the graduation degree on time can be due to less preparation or lack of resources. Moreover, the university retains students for longer time but when it comes to providing graduation degree, university fails in doing so. Reviewing results as president of University of Phoenix After considering the results, yes it is a major concern for the university and its performance against the other online universities. The university has a low graduation rate which means that university is not able to provide full degree course to the students in time and due to that university fails to retain the students. The graduation rate for University of Phoenix is 28% which is very low in comparison to Liberty University, Westwood College and some other universities (Letkiewicz et al., 2014). Further, the retention rate is low at 4% which means that Phoenix University is not likely to retain students as students transfer themselves Phoenix University to other university. The retention rate of the university is the most lowest in relation to other university of US such as Peirce College, Kaplan University, AshFord University, etc. Therefore, it can be considered that University of Phoenix has to improve their performance standard so that maximum number of students gets gradua ted from the university itself and also in due course time (Loft and Holt, 2010). Recommendations In order to improve the universitys retention rate and graduation rate, the senior management of the universities can follow the following proposals. Solve Academic Issues: The academic problem has to be solved so that adequate preparation can be provided to the students in order to meet the demands of academic of universities coursework. The content of the courses can be delivered in interesting way that can arouse interest among the students (Mybrcc.edu, 2015). Form Centers: For increasing the retention and graduation rate of students, the universities can form centers that can help in student success. The universities can provide centers such as Math and Science Tutorial Center or Tutor Lab that can provide great assistance in enhancing their knowledge and doing assignments with much positive approach. Communication: The universities can conduct conversation with the students and congratulate them for doing excel in the courses that can motivate them to pursue in the same university till the completion of the courses. Moreover, the importance of holding a degree has to be communicated to the students so that they do not leave the university in between the course (Roggow, 2014). Motivate: The students may feel de-motivated if they are not provided right guidance from the professors or teachers and it can lead to bad college experience. Therefore, it is important for the universities to provide right guidance and support to the students so that they can perform well and get higher grades. Orientation Program: The program can be helpful for the students to seek information from the faculty advisor so that students can make a plan for the forthcoming fall semester. On the other hand, students can be able to understand the way of using online registration system, academic requirements, etc. Therefore, it encourages students to complete the course from one education institution only (Units.miamioh.ed, 2015). Conclusion The challenges in maintaining the retention and graduation rates in universities is tough task as many students either transfer from university to other or due to some financial problem they have to leave the course in between. The study focused on different statistical methods to evaluate the problem and recommendation has been provided so that retention and graduation rate can be increased. References Bejou, D. and Bejou, A. (2012). Shared Governance and Punctuated Equilibrium in Higher Education: The Case for Student Recruitment, Retention, and Graduation. Journal of Relationship Marketing, 11(4), pp.248-258. Boden, G. (2011). Retention and Graduation Rates: Insights from an Extended Longitudinal View. Journal of College Student Retention: Research, Theory and Practice, 13(2), pp.179-203. Haydarov, R., Moxley, V. and Anderson, D. (2012). Counting Chickens Before They Are Hatched: An Examination of Student Retention, Graduation, Attrition, and Dropout Measurement Validity in an Online Master's Environment. Journal of College Student Retention: Research, Theory and Practice, 14(4), pp.429-449. Heuser, B., Drake, T. and Owens, T. (2012). Evaluating Cross-National Metrics of Tertiary Graduation Rates for OECD Countries: A Case for Increasing Methodological Congruence and Data Comparability. Journal of College Student Retention: Research, Theory and Practice, 14(1), pp.9-35. Heyneman, S. (2012). Introduction: Student Progress toward Graduation: An International Topic of Concern. Journal of College Student Retention: Research, Theory and Practice, 14(1), pp.1-8. Hoyert, M., O'dell, C. and Hendrickson, K. (2012). Using Goal Orientation to Enhance College Retention and Graduation Rates. plat, 11(2), p.171. Letkiewicz, J., Lim, H., Heckman, S., Bartholomae, S., Fox, J. and Montalto, C. (2014). The Path to Graduation: Factors Predicting On-Time Graduation Rates. Journal of College Student Retention: Research, Theory and Practice, 16(3), pp.351-371. Loft, B. and Holt, M. (2010). Increasing STEM Graduation Rates. International Journal of Applied Geospatial Research, 1(3), pp.76-77. McCormick, N. and Lucas, M. (2013). Assessing the Effectiveness of the Redesigned Mathematics Program on Graduation and Retention Rates of Underprepared Students. Journal of Studies in Education, 3(3), p.92. Morrison, M. (2012). Graduation Odds and Probabilities among Baccalaureate Colleges and Universities. Journal of College Student Retention: Research, Theory and Practice, 14(2), pp.157-179. Mybrcc.edu, (2015). Improving Student Retention and Graduation Rates. [online] Available at: https://www.mybrcc.edu/intranet/attachments/article/110/Improving%20Student%20Retention%20and%20Graduation%20Rates.pdf [Accessed 7 Jan. 2015]. Roggow, M. (2014). Improving Student Performance Outcomes and Graduation Rates Through Institutional Partnerships. New Directions for Community Colleges, 2014(165), pp.25-35. Units.miamioh.ed, (2015). Guide to Improving Retention and Graduation Rates in Academic Departments Programs. [online] Available at: https://www.units.miamioh.edu/oir/2020plan/Retention_Guide.pdf [Accessed 7 Jan. 2015].