Getting to Know from Our Millennials Students: Different Perception of Career Expectations and Career Goals

Research on career expectations and career goals was becoming a concern for practitioners in the HRM field. Career is important because it is a need that must be cultivated in an employee, to be able to boost their performance. Meanwhile, based on their characteristics, employees have different views about career expectations and goals. This study aims to analyze career expectations and goals from the perspective of the millennial generation based on gender, achievement and domicile. This study involved 200 students of final semester and measured their perceptions of career expectations as to future employees by using SPSS Two-Sample Independent Mean Test for the average difference test. By using the average difference test, this study found that perceptions of career expectations differ based on gender and achievement. Implication and future research agenda provided for direction of future work.

A REFLECTION ON GENDER ACHIEVEMENT IN SCIENCES’ RURAL SCHOOL SETTINGS OF MULTICULTURAL SOUTH AFRICA

The participation of learners in science is important to a country’s socio-economic development impediments, therefore, the argument is that the girl learner should be increasingly encouraged to perform well in STEM related subjects (STATS SA). UNESCO indicates 35% women representative in STEM as students in higher education globally, whilst less than 40% of South Africa’s scientists, engineers and technologists are women. This situation also relates to the South African education system, particularly in rural schools where girl learners are outperformed by boy learners in STEM, especially, in subjects such as Life Sciences and Physical Sciences. The purpose of this reflective paper is to ascertain the factors prohibiting excellent achievement of females in sciences in rural high schools of South Africa. The data has been gathered from numerous documents such as national and provincial analysis of result, examination and assessment directorate analysis and the district statistics in solidifying our investigation as couched by document analysis. Based on our observations and experiences of the conditions prevailing in rural high schools and less participation of female learner access in STEM, suggestions are put forth as to how their performance can be improved. The investment thereof in the body of knowledge will be to fulfil the concern not only of the country but the world at large when the number of female participants increase in STEM.

BALANCING GENDER ACHIEVEMENT AND KNOWLEDGE RETENTION IN MATHEMATICS USING COMPUTER ANIMATION INSTRUCTIONAL PACKAGE (CAIP)

The study was carried out to investigate the effectiveness of Computer Animation Instructional Package on balancing gender achievement and knowledge retention in mathematics in secondary schools. The study was a quasi-experimental type adopting the pre-test, posttest non-equivalent control design type. The population of the study comprised of all senior secondary 1(SS1) students of Government owned secondary schools in Owerri North Local Government Area of Imo State. The sample for the study was 225 students from two purposively selected secondary schools consisting of 127 females and 98 males. The instrument for data collection was a researcher made 30-item objective test questions titled “Mathematics achievement Test (MAT)”. It had reliability coefficient of 0.91 determined using Kuder-Richardson (KR21.). The experiment group was taught Surface area and volume of solids using Computer Animation Instructional Package (CAIP) while, the control group was taught the same concept using traditional approach. The data generated was analyzed using mean and standard deviation to answer research questions while the hypotheses were tested at 0.05 level of significance using Analysis of Covariance (ANCOVA). The result of the study revealed that Computer Animation Instructional Package (CAIP) reduced gender disparity associated with mathematics achievement as there was no significant difference between the mean achievement scores of male and female students taught mathematics using Computer Animation Instructional Package (CAIP). Also there was no significant difference between the posttest and delayed posttest mean achievement scores of students taught mathematics using Computer Animation Instructional Package(CAIP). Based on the result it was recommended that, Mathematics teachers should use Computer Animation Instructional Package (CAIP) to teach mathematics as to reduce gender disparity in mathematics achievement and enhance knowledge retention in secondary schools.

The Effect of Developmental Math on STEM Participation in Community College: Variation by Race, Gender, Achievement, and Aspiration

We use regression discontinuity design to examine the impact of placing into developmental math on science, technology, engineering, and mathematics (STEM) participation in community colleges and whether these relationships differ for underrepresented racially minoritized (URM), women, STEM-oriented, and STEM-aspiring students. Results show that lower math placement was a deterrent to both math progression and STEM participation, especially for those at the margin of placement in transfer-level math. Subgroup analyses suggest that lower math placement may have supported women, and to a lesser extent URM students, in completing transferable STEM credits. For STEM-oriented students, we find suggestive evidence that lower placement deterred them from accumulating transferable credits. We discuss how community colleges can support these students and bolster the community college STEM pathway.

Do Gender Differences in Academic Attainment Correspond with Scholastic Attitudes? An Exploratory Study in a U.K Secondary School

Research has examined how standardized tests give rise to gender differences in English and STEM attainment, but little research has explored gender differences in classroom-based attainment and the degree to which these correspond to differences in school-related attitudes. To explore the extent to which gender-achievement gaps in classroom-based performance parallel differences in self-perceptions and scholastic attitudes. An independent sample of first (n = 187, age 11–12, Study 1) and second-year students (n = 113, age 12–13, Study 2) from a UK comprehensive secondary school completed a questionnaire measuring academic mindset, self-efficacy, self-concept, competence beliefs, personal and social self-esteem, and endorsement of gender-subject and career stereotypes. Responses were then matched to their respective classroom grades in English, mathematics, science, and computing. Girls outperformed boys in English in their first year but reported lower global self-esteem and greater endorsement of science-career stereotypes. Conversely, girls outperformed boys in mathematics in their second year, but paradoxically reported lower self-concept and competence beliefs in mathematics and science, and higher competence beliefs in English. Across both studies, mindset, self-efficacy, competence beliefs, and social self-esteem were positively related to English attainment; academic self-efficacy was positively related to mathematics attainment; and mindset, self-efficacy, self-concept, and competence beliefs were positively related to science attainment. Gender-achievement gaps in classroom-based academic attainment are complex and highly nuanced; they appear to vary between school subjects across years and may not correspond with similar differences in self-perceptions and scholastic attitudes.

Gender achievement gaps: the role of social costs to trying hard in high school

In American high schools female students put greater effort into school and outperform boys on indicators of academic success. Using data from the High School Longitudinal Study of 2009, we found female students’ greater academic effort and achievement was partly explained by different social incentives to trying hard in school experienced by male and female students. Males were 1.75 times as likely to report they would be unpopular for trying hard in school and 1.50 times as likely to report they would be made fun of for trying hard in school. Social costs to trying hard in school were directly associated with less rigorous mathematics course-taking and indirectly associated with lower GPA in STEM courses through lower academic effort.

Teachers' gaze over space and time in a real-world classroom

Reading students’ faces and their body language, checking their worksheets, and keeping eye contact is a key trait of teacher competence. The new technology of mobile eye-tracking provides researchers with possibilities to explore teaching from the viewpoint of teacher gaze, but also introduces many new method questions. This study had the primary aim to investigate teachers´ attention distribution over space: the number and durations of several types of their gazes, and how their gaze depends on the factors of students´ gender, achievement, and position in the classroom. Results show that teacher gaze was distributed unevenly across both space and time. Teachers looked at the most-watched students 3-8 times more often than at the least-watched ones. Students sitting in the first row and the middle section received significantly more gaze than those sitting outside this zone. All three teachers made more single gaze visits - looking at the students but making no eye contact - than mutual gazes or student material gazes. The three teachers’ gaze distribution also varied substantially from lesson to lesson. Our results are important for understanding teacher behavior in real classrooms, but also point to the relevance of appropriate method design in future classroom studies with eye-tracking.

Perbandingan Algoritme C4.5 and Naive Bayes untuk Mengetahui Masa Studi

This research was to make comparisons between Algorithms C4.5 and Naive Bayes which is implemented on the data of graduation of Universitas Amikom Purwokerto students from 2011 to 2013 for Strata 1, Informatics Engineering study program for the renowned study. Attributes are NIM, gender, Achievement Index Semester 1 through 6 and graduation period. The test results with both algorithms use the Selection-Based Correlation feature feature (CFS) and testing methods using Confusion Matrix. Known Algorithm C4.5 has an accuracy of 72.679% with Precision value of 0.742, Remember 0.936 and F - Measure 0.828 whereas Naive Bayes obtained an accuracy of 73.6074% with a Precision value of 0.755, Remember 0.924 and F - Measure 0.831