Integrative Approach for a Transformative Freshman-Level STEM Curriculum

D’Souza, Malcolm J.; Curran, Kathleen L.; Olsen, Paul E.; Nwogbaga, Agashi P.; Stotts, Stephanie

doi:10.19030/tlc.v13i2.9632

Cited by 12 publications

(11 citation statements)

References 13 publications

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“…To further educate its students on human-health issues, the College revised its liberal arts core-curriculum (D’Souza et al, 2016) to incorporate experiential experiences in public health topics, and introduced course-embedded Statistical Analysis System (SAS) data-mining and geo-spatial analysis (using ArcGIS) training, available to all undergraduate majors (D’Souza et al, 2017; D’Souza et al, 2015; D’Souza et al, 2017). To accommodate such ongoing curricula changes and accessibility to dynamic undergraduate research projects within an all-encompassing umbrella, the College in 2017, launched the Undergraduate Center for Analytics, Talent, and Success (UR-CATS).…”

Section: Introductionmentioning

confidence: 99%

Data Talks: Obesity-Related Influences on US Mortality Rates

D’Souza

Bautista

Wentzien

2018

RHS

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Background: In the US, obesity is an epidemiologic challenge and the population fails to comprehend this complex public health issue. To evaluate underlying obesity-impact patterns on mortality rates, we data-mined the 1999–2016 Center for Disease Control WONDER database’s vital records. Methods: Adopting SAS programming, we scrutinized the mortality and population counts. Using ICD-10 diagnosis codes connected to overweight and obesity, we obtained the obesity-related crude and age-adjusted causes of death. To understand divergent and prevalence trends we compared and contrasted the tabulated obesity-influenced mortality rates with demographic information, gender, and age-related data. Key Results: From 1999 to 2016, the obesity-related age-adjusted mortality rates increased by 142%. The ICD-10 overweight and obesity-related death-certificate coding showed clear evidence that obesity factored in the male age-adjusted mortality rate increment to 173% and the corresponding female rate to 117%. It also disproportionately affected the nation-wide minority population death rates. Furthermore, excess weight distributions are coded as contributing features in the crude death rates for all decennial age-groups. Conclusions: The 1999–2016 data from ICD-10 death certificate coding for obesity-related conditions indicate that it is affecting all segments of the US population.

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Section: Introductionmentioning

confidence: 99%

Data Talks: Obesity-Related Influences on US Mortality Rates

D’Souza

Bautista

Wentzien

2018

RHS

Self Cite

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“…In a 2015 GIS and SAS project ( D’Souza, Kashmar, et al, 2015 ), undergraduates in our mentored research program ( D’Souza, Kashmar, et al, 2015 ; D’Souza, Curran, Olsen, Nwogbaga, & Stotts, 2016 ; D’Souza & Wang, 2012 ; D’Souza, Kroen, Stephens, & Kashmar, 2015 ) analyzed available Delaware obesity-related data. We found ( D’Souza, Kashmar, et al, 2015 ) an association between age and educational achievement and the state’s obesity prevalence.…”

Section: Introductionmentioning

confidence: 99%

Investigation Of Obesity-Related Mortality Rates In Delaware

D’Souza

Wentzien

Bautista

et al. 2017

AJHS

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As Delaware’s adult obesity crisis continues to be a leading public health concern, we evaluated Delaware’s 1999–2014 vital records to examine the association between obesity and mortality. We used the Delaware population death records from the Centers for Disease Control and Prevention (CDC) WONDER database and the Delaware Health Statistics Center (DHSC).Together with the vital records, we incorporated Microsoft Excel, SAS (Statistical Analysis System) and GIS (geographic information system) tools to analyze obesity influences from county residence, economic status, education, gender, and race. Using the 15-year (1999–2014) time span with the CDC WONDER database, we observed a statistically significant 28.7% increase in the age-adjusted Delaware obesity-related mortality rates (where obesity was a contributory factor). Furthermore, obesity influenced death counts in all three Delaware counties (New Castle, Kent, and Sussex). Kent County experienced the largest increase (66.0%), followed by New Castle County (47.4%), and Sussex County (25.2%).The DHSC mortality rates for all leading causes of death from 2000 to 2011 indicated relatively stable mortality rates for Delaware. However, using CDC WONDER data, the Delaware mortality rate for obesity as a single underlying cause in 2011 was 56.9% higher than mortality rate in 2000.

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“…This result is supported by research conducted by (Salam, Ibrahim, & Sukardjo, 2019a) that learning models can improve mathematics learning outcomes. This is because integrative learning can help students see the relationship between mathematics subject matter that is interrelated to one another, even interdisciplinary relationships (D'Souza et al 2016). Likewise, research conducted by (Becker & Park, 2011), that integrative learning models are effective for improving understanding of mathematical concepts both in elementary schools and at universities.…”

Section: Discussionmentioning

confidence: 99%

Effectiveness of integrative learning models in improving understanding of mathematical concepts

Salam

Ja'far

Prajono

2020

Journal for the Education of Gifted Young Scientists

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This research is whether the integrative learning model is effective in increasing understanding of mathematical concepts. The integrative learning model is intended to practice critical thinking skills and develop a deep understanding of building systematic knowledge simultaneously using a variety of thinking skills. The pretest-posttest control group design was used in the quasi-experimental design of this study. This research was conducted in Senior High School (SHS) 6 Kendari class XI.2 as an experimental class and XI.4 as a control class. The experimental class is taught the integrative learning model, while the control class is taught by the direct learning model. The results of this study are: (1) the integrative learning model can increase the average value of students 'understanding of mathematical concepts from ̅ = 60.56 to ̅ = 77.61 and the average understanding of students' mathematical concepts increases from ̅ = 60.11 to ̅ = 68.87 with direct learning models, (2) integrative and direct learning models are effective in increasing understanding of mathematical concepts, and (3) integrative learning models are more effective in improving understanding of mathematical concepts compared to direct learning models.

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Integrative Approach for a Transformative Freshman-Level STEM Curriculum

Abstract: ABSTRACT

Cited by 12 publications

References 13 publications

Data Talks: Obesity-Related Influences on US Mortality Rates

Data Talks: Obesity-Related Influences on US Mortality Rates

Investigation Of Obesity-Related Mortality Rates In Delaware

Effectiveness of integrative learning models in improving understanding of mathematical concepts

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