scholarly journals No Internet = No High School Diploma? Data to Identify Counties at-risk of Increased Dropout Rates during the COVID-19 Pandemic (I1.A5)

Author(s):  
Lincoln Groves ◽  
Linsey Dyson ◽  
Lauren Homel ◽  
Atul Kachare ◽  
Hiwot Tesfaye ◽  
...  
2009 ◽  
Vol 19 (1) ◽  
Author(s):  
Cheryll Duquette ◽  
Stephanie Fullarton

The purpose of this qualitative study was to examine the educational and em-ployment experiences of 10 adults who had recently been diagnosed as having a learning disability. Seven of the participants eventually obtained a high school diploma or the equivalent and they all had held a variety of entry-level jobs. The participants felt that having an undiagnosed learning disability had negatively af-fected their past, present, and future educational and employment opportunities. The importance of a caring adult to advocate on behalf of at-risk students and a set of goals, skills, and abilities that should be developed while in school emerged from the findings.


2009 ◽  
Vol 7 (1) ◽  
pp. 83-104 ◽  
Author(s):  
Phitsamay Uy

In the world of K–12 education, the growing numbers of dropouts are a major concern. This article examines the dropout rates of Chinese and Vietnamese high school students. Using logistic regression analysis, this article examines the influence of ethnicity, gender, and socioeconomic status (SES) on dropout rates. The distinct contribution of this analysis lies within the intraethnic comparisons within the Asian American student population and its use of longitudinal data. The results of the study support existing research that gender and SES are related to dropout rates. Moreover, an interesting interaction between ethnicity and SES exists.


2021 ◽  
Vol 13 (01) ◽  
pp. e51-e56
Author(s):  
Lauren Hennein ◽  
Kimberly A. Spaulding ◽  
Veronika Karlegan ◽  
Ogonna N. Nnamani Silva ◽  
Alejandra G. de Alba Campomanes

Abstract Objective Eye health among the homeless community is important, as poor vision makes this population vulnerable and adds significantly to the social and health burden. There is limited knowledge on patient follow-up rates for their eye conditions and barriers to accessing care in this population. The purpose of this retrospective chart review study is to examine follow-up rates and barriers to care for patients referred from a free, medical-student run ophthalmology clinic at a homeless shelter. Methods All patients evaluated at a free ophthalmology clinic from September 2017 to September 2018 were included; no patients were excluded. If indicated, patients were referred for advanced ophthalmologic care at a local county hospital and free eyeglasses at a nonprofit organization. Primary outcomes were follow-up rates at the county hospital and nonprofit organization. Secondary outcomes included prespecified baseline variables hypothesized to be associated with follow-up rates. These categorical variables were compared with Chi-square testing to determine their association with follow-up rates. The hypothesis being tested was formulated before data collection. Results Of the 68 patients, 84% were males with a mean age of 50 years. Overall, 40 patients were referred for free eyeglasses and 17 to the county hospital. Of those referred, 14 patients presented for free eyeglasses and 7 presented to the county hospital. About 79% of patients with a pre-established primary care provider presented to their appointment compared with 20% of those without one (p = 0.03). The 44% of patients with a high school diploma presented while all patients without a high school diploma failed to present (p = 0.04). Vision-threatening conditions identified at the shelter clinic did not affect follow-up rates (p = 0.79). Conclusion Less than half of referred patients in our study presented to their appointments. Barriers to presentation included no primary care provider and lower educational status, with no improvement in follow-up rates among those referred for vision-threatening conditions. Interventions such as health coaching with particular attention to educating patients on the effects of vision-threatening conditions may be warranted, particularly for those not looped into the health care system and those of lower educational attainment.


1978 ◽  
Vol 62 (420) ◽  
pp. 51-56
Author(s):  
H.B. Pinkney ◽  
Thomas H. Fisher

2020 ◽  
Vol 5 (1) ◽  
pp. 5-9
Author(s):  
Chandra Ramadhan Atmaja Perdana ◽  
Hanung Adi Nugroho ◽  
Igi Ardiyanto

File scanned documents are commonly used in this digital era. Text and image extraction of scanned documents play an important role in acquiring information. A document may contain both texts and images. A combination of text-image classification has been previously investigated. The dataset used for those research works the text were digitally provided. In this research, we used a dataset of high school diploma certificate, which the text must be acquired using optical character recognition (OCR) method. There were two categories for this high school diploma certificate, each category has three classes. We used convolutional neural network for both text and image classifications. We then combined those two models by using adaptive fusion model and weight fusion model to find the best fusion model. We come into conclusion that the performance of weight fusion model which is 0.927 is better than that of adaptive fusion model with 0.892.


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