PEMANFAATAN MODEL KELAS SEBAGAI SUMBER BELAJAR DALAM PEMBELAJARAN IPS UNTUK MENGEMBANGKAN KARAKTER DAN KECERDASAN EMOSIONAL SISWA KELAS IV SEKOLAH DASAR NEGERI 74 KOTA BENGKULU

Penelitian ini bertujuan untuk : (1) Mengembangkan model kelas sebagai sumber belajar dalam pembelajaran IPS, (2) Mengembangkan karakter siswa melalui pemanfaatan model kelas sebagai sumber belajar dalam pembelajaran IPS, (3) Mengembangkan kecerdasan emosional siswa melalui pemanfaatan model kelas sebagai sumber belajar dalam pembelajaran IPS, dan (4) Meningkatkan hasil belajar kognitif siswa melalui pemanfaatan model kelas sebagai sumber belajar dalam pembelajaran IPS. Metode yang digunakan yaitu Penelitian Tindakan Kelas (PTK). Penelitian ini dilaksanakan secara kolaboratif antara 2 orang dosen PGSD, 2 orang guru SD, da 5 orang mahasiswa PGSD. Hasil penelitian menunjukkan bahwa : (1) Pengembangan model kelas sebagai sumber belajar dalam pembelajaran IPS dilakukan melalui empat tahap yaitu : orientasi, elaborasi dan interpretasi, aplikasi ide dan evaluasi, (2) Pemanfaatan model kelas sebagai sumber belajar dalam pembelajaran IPS dapat mengembangkan karakter siswa, (3) Pemanfaatan model kelas sebagai sumber belajar dalam pembelajaran IPS dapat mengembangkan kecerdasan emosional siswa, dan (4) Pemanfaatan model kelas sebagai sumber belajar dalam pembelajaran IPS dapat meningkatkan hasil belajar kognitif siswa. Saran yang disampaikan yakni : (1) Guru dan calon guru diharapkan memanfaatkan model kelas dalam pembelajaran IPS, dan (2) Kepala sekolah diharapkan mendorong guru untuk selalu menerapkan pembelajaran dengan memanfaatkan model kelas

Associations of All-Cause Mortality with Census-Based Neighbourhood Deprivation and Population Density in Japan: A Multilevel Survival Analysis

<div><p>Background</p><p>Despite evidence that neighbourhood conditions affect residents' health, no prospective studies of the association between neighbourhood socio-demographic factors and all-cause mortality have been conducted in non-Western societies. Thus, we examined the effects of areal deprivation and population density on all-cause mortality in Japan.</p><p>Methods</p><p>We employed census and survival data from the Japan Public Health Center-based Prospective Study, Cohort I (n = 37,455), consisting of middle-aged residents (40 to 59 years at the baseline in 1990) living in four public health centre districts. Data spanned between 1990 and 2010. A multilevel parametric proportional-hazard regression model was applied to estimate the hazard ratios (HRs) of all-cause mortality by two census-based areal variables —areal deprivation index and population density—as well as individualistic variables such as socioeconomic status and various risk factors.</p><p>Results</p><p>We found that areal deprivation and population density had moderate associations with all-cause mortality at the neighbourhood level based on the survival data with 21 years of follow-ups. Even when controlling for individualistic socio-economic status and behavioural factors, the HRs of the two areal factors (using quartile categorical variables) significantly predicted mortality. Further, this analysis indicated an interaction effect of the two factors: areal deprivation prominently affects the health of residents in neighbourhoods with high population density.</p><p>Conclusions</p><p>We confirmed that neighbourhood socio-demographic factors are significant predictors of all-cause death in Japanese non-metropolitan settings. Although further study is needed to clarify the cause-effect relationship of this association, the present findings suggest that health promotion policies should consider health disparities between neighbourhoods and possibly direct interventions towards reducing mortality in densely populated and highly deprived neighbourhoods.</p></div

Hazard ratios and model statistics of the shared frailty survival model with the interaction terms of the two areal factors (Model 5A).

<p>Estimate: estimate hazard ratios for the factors and estimated values for the model statistics (Model 5A: adjusted by age, sex, public health centre district, histories of diabetes and hypertension, and body mass index); Qs  =  Quartiles, CI  =  confidence interval; trend p: p value of trend test; Explained geographical variance: percentage of reduction in Theta of fitted models compared to Model 0 shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097802#pone-0097802-t002" target="_blank">Table 2</a>; Difference of AIC: the subtraction of the AIC of the fitted model from the AIC of Model 0 shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097802#pone-0097802-t002" target="_blank">Table 2</a>.</p

Hazard ratios and model statistics of the shared frailty survival model with the interaction terms of the dichotomised areal factors (Model 5B).

<p>Estimate: estimated hazard ratios for the factors and estimated values for the model statistics (Model 5B: adjusted by age, sex, public health centre district, histories of diabetes and hypertension, and body mass index); Qs  =  Quartiles, CI  =  confidence interval; Explained geographical variance: percentage of reduction in Theta of fitted models compared to Model 0 shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097802#pone-0097802-t002" target="_blank">Table 2</a>; Difference in AIC: the subtraction of AIC of fitted model from AIC of Model 0 shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097802#pone-0097802-t002" target="_blank">Table 2</a>.</p

Study flow chart.

<p>Study flow chart.</p

Flow of study population.

<p>Flow of study population.</p

Baseline characteristics in women (n = 45,229).

<p>Baseline characteristics in women (n = 45,229).</p

Risk Estimates for Development of Diabetes According to Weight Gain and Known Risk Factors Among Never Smoking Men and Those who Newly Quit Smoking (Between Baseline and 5-Year Surveys) in the Japan Public Health Center-Based Study, Between 5-Year Survey and 10-Year Survey.

1<p>Multivariate analysis was not adjusted for weight change.</p>2<p>Who stopped smoking between the baseline and 5-year surveys.</p>3<p>Multivariate analysis was not adjusted for BMI at 5-year follow-up.</p>4<p>Multivariate analysis was not adjusted for alcohol intake.</p>5<p>Multivariate analysis was not adjusted for physical activity level. Median value was 33.65 METs/day.</p>6<p>Multivariate analysis was not adjusted for family history of diabetes.</p>7<p>Age, BMI, history of hypertension, alcohol intake, family history of diabetes, weight change between baseline and 5-year surveys, study area, and leisure-time physical activity.</p

Characteristics of 33,959 Women According to Smoking Status in Baseline and 5-Year Surveys in the Japan Public Health Center-Based Prospective Study.

1<p>The numbers differ as a result of missing data for physical activity level for which it was 28,370, and years since quitting of former smokers for which it was 399.</p>2<p>Who stopped smoking between the baseline and 5-year surveys.</p

Characteristics of 25,875 Men According to Smoking Status in Baseline and 5-Year Surveys in the Japan Public Health Center-Based Prospective Study.

1<p>The numbers differ as a result of missing data for physical activity level for which it was 21,553, and years since quitting of former smokers for which it was 5871.</p>2<p>Who stopped smoking between the baseline and 5-year surveys.</p