Restrictive Reciprocal Obligations: Perceptions of Parental Role in Career Choices of Sub-Saharan African Migrant Youths

This study employed interpretivist, grounded theory method and utilized semi-structured interviews to explore how 31 African migrant high school and university students from eight sub-Saharan African representative countries and currently residing in Townsville, Australia, perceived the roles of their parents in their career development. The study findings revealed that the support (financial, social and emotional) and encouragement (sacrificial love, role modeling and guidance) received from parents underpinned the youths’ perceptions of their parents as influential in their career trajectories. Though participants acknowledged their indebtedness to parents and the system that nurtured them, they faced a dilemma conforming to parental preference or personal conviction, which presented “a fork in the career decision-making road.” Study findings indicate that participants’ reactions and strategies for negotiating parental approval differ based on entry status and gender. Most participants, particularly those with professional entry status, conformed to their parents’ career choice for fear of failure, while a few who followed their personal interests negotiated parental approval through dialogue and educating parents. Male participants with humanitarian entry status opposed their parents’ career preferences and followed their own personal interests. Taken together, all participants had strong desire to obtain parental approval and whether sought early or later, the main focus for all participants was prioritizing family needs and obligations. The practical implications of these findings for all stakeholders are discussed.

To what extent do preclinical veterinary students in the UK utilize online resources to study physiology

Online resources are becoming increasingly important in undergraduate education and have been associated with a number of advantages and positive outcomes on students’ learning experience. However, online resource use by veterinary students for physiology learning remains poorly understood. Thus the present questionnaire-based study aims to investigate the extent to which first- and second-year veterinary students use online resources, including online video clips and social media, in their physiology learning and if this is influenced by factors of age, gender, entry status, or year of study. One-hundred and twenty-two students across seven UK universities completed the survey. Traditional resources (the lecturer and recommended textbooks) were the most preferred sources for physiology learning. Nonetheless, 97.5% of students used Internet search engines to explore physiology topics. Furthermore, students’ tendency to contact their instructor regarding a physiology question was low. Rather, 92.6% said they would first search for an answer online. Particularly popular was the use of online video clips with 91.1% finding them valuable for physiology learning and 34.21% finding them more useful for understanding physiology than university taught material or lecture slides. YouTube was the most common online video clip platform used by students. Most students stated that they would enjoy interacting with course materials on an instructor-led social media page, but only 33.9% currently use social media to discuss physiology-related issues with classmates. Additionally, most students expressed concerns regarding the reliability of online resources but attempts to fact-check these resources were relatively low. Therefore, online resources represent an essential part of veterinary students’ physiology learning and this suggests that educators can significantly improve student engagement and understanding of physiology by integrating these resources.

Does the first job affect current youth working status in Bangladesh?

PurposeThis paper evaluates how the first job when individuals entered the labor market affects the probability of youth being currently employed in formal or informal work in Bangladesh.Design/methodology/approachThe analysis is based on data from the ILO School-to-Work Transition Surveys. The authors use a full-information maximum likelihood approach to estimate a two-equation model, which accounts for selection into the labor market when estimating the impact of entry status on current work outcomes. The main equation outcome follows a multinomial distribution thus avoiding a priori assumptions about the level of individual’s utility associated with each work status.FindingsThe authors find that entering the labor market in a vulnerable employment position (i.e. contributing family work or self-employment) traps into vulnerable employment and prevents the transition to both informal and, especially, formal paid work. This finding holds when accounting for endogeneity of the entry status and it is valid both in the short and in the long run. Young women are less likely to enter the labor market, and once entered they are less likely to access formal paid wok and more likely to being inactive than young men. Low education anticipates the entry in the labor market, but it is detrimental for future employment prospects.Originality/valueThe findings indicate the presence of labor market segmentation between vulnerable and non-vulnerable employment and suggest the endpoint quality of the school-to-work transition is crucial for later employment prospects of Bangladeshi youth.

Penerapan algoritma C5.0 pada analisis faktor-faktor pengaruh kelulusan tepat waktu mahasiswa Teknik Informatika UMM

AbstrakKelulusan tepat waktu mahasiswa merupakan salah satu permasalahan yang sulit untuk diatasi oleh setiap pihak perguruan tinggi, begitu pula pada jurusan Teknik Informatika Universitas Muhammadiyah Malang. Permasalahan ini harus segera diatasi mengingat kualitas mahasiswa akan mempengaruhi sebuah akreditasi perguruan tinggi maupun jurusan. Oleh karena itu, perlu dilakukan analisis faktor-faktor pengaruh kelulusan tepat waktu mahasiswa Teknik Informatika UMM. Penelitian ini menggunakan algoritma C5.0 untuk melakukan seleksi fitur penting dan analisis regresi untuk melakukan estimasi peluang kelulusan tepat waktu mahasiswa. Variabel bebas yang digunakan adalah jenis kelamin, asal daerah, status masuk, SKS semester 4, SKS semester 6, IP semester 2, IP semester 4, IP semester 6, IPK semester 2, IPK semester 4, IPK semester 6, jenis SMA, status SMA, pendidikan orang tua, dan pekerjaan orang tua. Hasil implementasi algoritma C5.0 pada penelitian ini mampu melakukan seleksi fitur dengan menghasilkan 8 dari total keseluruhan 15 fitur dengan nilai akurasi yang lebih baik dibandingkan nilai akurasi yang menggunakan keseluruhan fitur. Serta, penelitian ini mampu memberikan model regresi dengan nilai akurasi sebesar 82%.Abstract Timely graduation of college students is one of the problems that is difficult to overcome by each college, as well as in the Department of Informatics, University of Muhammadiyah Malang. This problem must be resolved immediately, considering the quality of students will affect the accreditation of university and its majors. So, it is necessary to analyze the factors that influence the timely graduation of Informatics Engineering students in UMM. This study uses the C5.0 algorithm to do feature selection and regression analysis to estimate the opportunities of timely graduation. The independent variables used are gender, regional origin, entry status, academic credit system in 4th semester, academic credit system in 6th semester, grade point of 2nd semester, grade point of 4th semester, grade point of 6th semester, grade point average of 2nd semester, grade point average of 4th semester, grade point average of 6th semester, type of senior high school, status of senior high school, parent’s education, and parent’s job. The results of the implementation of the C5.0 algorithm in this study were able to do feature selection by producing 8 out of total 15 features with better accuracy than the value of accuracy using all features. And this study is able to provide a regression model with an accuracy value of 82%.