Black Achievement Success and Engagement Program Pamphlet 2018/2019

BASE\u27s 2018/2019 Pamphlet. Learn more at usfca.edu/bas

Effort and Achievement

Achievements have recently begun to attract increased attention from value theorists. One recurring idea in this budding literature is that one important factor determining the magnitude or value of an achievement is the amount of effort the achiever invested. The aim of this paper is to present the most plausible version of this idea. This advances the current state of debate where authors are invoking substantially different notions of effort and are thus talking past each other. While the concept of effort has been invoked in the philosophical analysis of a number of important concepts such as desert, attention, competence, and distributive justice, it has hardly ever been analyzed itself. This paper makes headway in this regard by discussing three ambiguities in the everyday notion of effort. It continues to develop two accounts of effort and shows how both of them are achievement-enhancing

Relating emotional intelligence to academic achievement among university students in Barbados

This study investigated the relationships between emotional intelligence and academic achievement among 151 undergraduate psychology students at The University of the West Indies (UWI), Barbados, making use of Barchard (2001)’s Emotional Intelligence Scale and an Academic Achievement Scale. Findings revealed significant positive correlations between academic achievement and six of the emotional intelligence components, and a negative correlation with negative expressivity. The emotional intelligence components also jointly contributed 48% of the variance in academic achievement. Attending to emotions was the best predictor of academic achievement while positive expressivity, negative expressivity and empathic concern were other significant predictors. Emotion-based decision-making, responsive joy and responsive distress did not make any significant relative contribution to academic achievement, indicating that academic achievement is only partially predicted by emotional intelligence. These results were discussed in the context of the influence of emotional intelligence on university students’ academic achievement.peer-reviewe

Signaling, Incentives and School Organization in France, The Netherlands, Britain and the United States: Lessons for Education Economics

[Excerpt] What causes differences in secondary school achievement across these four nations? The first two sections of the paper describe the achievement differences among the four countries and examine the proximate causes of the differentials. I conclude that these achievement differentials are caused by differences in the quality of teachers and of student time and effort inputs devoted to academic achievement

Mathematics achievement gaps between suburban students and their rural and urban peers increase over time

In this brief, authors Suzanne Graham and Lauren Provost examine whether attending a school in a rural, urban, or suburban community is related to children’s mathematics achievement in kindergarten, and whether increases in mathematics achievement between kindergarten and eighth grade differ for children in rural, urban, and suburban schools. They also consider whether achievement differs by region of the country and for children of different racial and ethnic groups. Finally, they discuss the impact of a family’s socioeconomic status, and the ways in which place and socioeconomic status together affect both early mathematics achievement levels and change over time. They report that rural and urban kindergarten students have slightly lower average mathematics achievement levels than their suburban peers. In addition, the average increase in mathematics achievement from kindergarten to eighth grade for rural and urban children is smaller than the increase for suburban children, resulting in a widening achievement gap over time

The Relation among Parental Factors and Achievement of African American Urban Youth

Research has repeatedly suggested that SES is a major factor in diminishing academic achievement of African American urban youth; however, there are other factors also influencing children’s achievement. In an effort to examine how other factors contribute to academic achievement, this study, investigated a subsample of 60 low-resource middle school parents and students (41 boys and 19 girls). Several questions addressed the relation of SES to achievement, support, social support and mother’s well-being, respectively. Additionally, the relations between mother’s well-being, and students’ perceived monitoring by their parents, and negative learning attitudes were examined as were the perception of parental monitoring and academic achievement, negative learning attitudes and achievement. The results revealed a significant relation between perceived social support and mother’s well-being but in a negative direction. Parents reporting lower levels of well-being reported higher levels of social support. The results also revealed that youth who perceived their parents to monitor their activities more had higher levels of achievement. These findings illustrate the importance of the perceptions of adolescents as well as the potential role of parental monitoring on adolescents’ academic achievement. Although several factors were examined, only those factors with significant relationships will be discussed

The Influence of Environment to Students’ Motivation and The Effect to Student Achievement Grade Audio Video Department SMK Muh. Kutowinangun Kebumen

This research aims to determine: 1) the influence of school environment to student achievement. 2) the influence of family environment to student achievement. 3) the influence of communities to student achievement. 4) the influence of industrial environments to student achievement. 5) the influences of students’ motivation to student achievement. (6) the influence of school environment, family environment, communities, industrial environments and students’ motivation to student achievement from student XII grade Audio Video department SMK Muh. Kutowinangun Kebumen. This research is an Ex-post facto with quantitative approach. The population is a class XII student of Audio Video department SMK Muh. Kutowinangun Kebumen school year 2011/2012 which amounts to 36 students. Methods of data collection using questionnaires Likert scale models for all variables. The validity of research instruments performed by analysis of the items calculated by the formula Product moment correlation. Reliability of the instrument calculated using Cronbach Alpha. Prior to the first data analysis conducted descriptive analysis and testing requirements analysis including tests of normality, linearity tests, and multicollinearity test. Data analysis techniques are used to test the hypothesis is a technical product moment regression analysis.. The results showed that: (1) there is a positive relationship between school environment (X1) with student achievement (Y) are indicated coefficient R = 0,335. The coefficient of determination (R2) = 0,112. (2) there is a positive relationship between family environment (X2) with student achievement (Y) are indicated coefficient R = 0,578. The coefficient of determination (R2) = 0,334. (3) there is a positive relationship between communities (X3) with student achievement (Y) are indicated coefficient R = 0,485. The coefficient of determination (R2) = 0,235. 4) there is a positive relationship between industrial environments (X4) with student achievement (Y) are indicated coefficient R = 0,367. coefficient of determination (R2) = 0,135. (5) there is a positive relationship between students’ motivation (X5) with student achievement (Y), are indicated coefficient R = 0,658. coefficient of determination (R2) = 0,434. (6) there is a positive relationship between school environment (X1), family environment (X2), between communities (X3), industrial environments (X4) and students’ motivation (X5) together in the readiness of student achievement (Y), are indicated coefficient R = 0,725. coefficient of determination (R2) = 0,526