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Factors Affecting Student’s Migration for Studying Abroad: A study of the Majha Region of Punjab

2022· article· en· W4312870636 on OpenAlexaboutno aff
Ashutosh Verma Komalpreet Singh

Bibliographic record

VenueCentral European Management Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsRivalryVariety (cybernetics)InstitutionTest (biology)Study abroadEconomic growthPolitical scienceDemographic economicsPsychologyMarketingSociologyBusinessEconomicsSocial scienceMathematics

Abstract

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The global rivalry in the market for students to study abroad has been much fiercer in recent years. As a result of the increasing level of global competitiveness, a nation's and/or an institution's capacity to understand and satisfy the needs of the market is critical to its success in recruiting and maintaining foreign students. Migration has begun to take the place of senior secondary school as the primary route to higher education in several parts of India, notably in the state of Punjab. The choice to pursue an education in a foreign country is one that is heavily impacted by a variety of variables. The research was conducted on a group of one hundred and twenty students from the Majha district of Punjab (India) and have aspirations of moving to a new country. This research is an effort to analyze some of the elements that impact students' choices to study abroad based on the demographic features of the students themselves. The "t-test" was used to conduct the analysis independently. According to the data, it was shown that male students had a greater interest in studying in another country than female students. Rural kids, in contrast to their urban counterparts, have a strong interest in traveling outside of the country. In addition, students who are married and students who are part of traditional households have a greater influence on the choice to study abroad. The research has repercussions for both the development of policies and the evaluation of student mobility in actual practice. References Chen, L. H. (2007). Choosing Canadian graduate schools from afar: East Asian students’ perspectives. Higher Education, 54, 759–780 Deepika and Janki Aggarwal (2021). Factors Contributing to International Migration of Youth in Doaba region of Punjab Nawanshahr and Garhshankar, Punjab- An Empirical Study. Psychology and Education, 58(5), 3371-3381. Dinbabo, Mulugeta, and Sergio Carciotto. 2015. International migration in Sub-Saharan Africa (SSA): A call for a global research agenda. African Human Mobility Review, 154–77. Dora, M., Ibrahim, N., Ramachandran, S., Kasim, A., & Saad, M. (2009). A Study on Factors That Influence Choice of Malaysian Institution of Higher Learning for International Graduate Students. Journal of Human Capital Development, 2(1), 105-113. Eliason, S., Tuoyire, D. A., Awusi-Nti, C., & Bockarie, A. S. (2014). Migration Intentions of Ghanaian Medical Students: The Influence of Existing Funding Mechanisms of Medical Education (“The Fee Factor”). Ghana Medical Journal, 48(2), 78–84. 6. Gurinder Kaur , Gian Singh , Dharampal , Rashmi , Rupinder Kaur , Sukhvir Kaur , and Jyoti. 2021 Socio-economic and Demographic Analysis of International Migration from Rural Punjab: A Case Study of Patiala District Indian Journal of Economics and Development ,17(1), 55-67. Kaur, Gurjinder (2019), “Overseas Migration of Students from Punjab”,IJRAR - International Journal of Research and Analytical Reviews, 6(1), 1053-1059. Komalpreet ,S and Verma, A (2022, 9 24-25). Factors Affecting Student’s Intention to Study Abroad with reference to Majha Belt of Punjab. International conference on strategic perspective, Jalandhar, Punjab, India. Kim, S. (2015). The influence of social relationships on international students' intentions to remain abroad: multi-group analysis by marital status. The International Journal of Human Resource Management, 26(14), 1848-1864. doi:10.1080/09585192.2014.963137 Lee, E., & Moon, M. (2013). Korean nursing students' intention to migrate abroad. Nurse education today, 33(12), 1517-1522. Pimpa, N. (2005). Marketing Australian Universities to Thai Students. Journal of Studies in International Education, 9(2), 137-146. doi:10.1177/1028315305274857 Mazzarol, T, & Soutar, G. (2002) Push-pull factors influencing international students’ destination choice. The International Journal of Educational breaking-myth-here-indian-student-numbers- Management, 16 (2), 82-90. Nikhil Rampal, Reeti Agarwal (2022,February,2) Few jobs, bad pay, so why should we stay’? Behind Punjab youngsters’ rush for IELTS, migration . https://theprint.in/india/few-jobs-bad-pay-so-why-should-we-stay-behind-punjab-youngsters-rush-for-ielts-migration/837041/\ Padlee, S., Kamaruddin, A., & Baharun, R. (2010). International Students, Choice Behavior for Higher Education. International Journal of Marketing Studies, 2(2), 202-211. Rajan, S. Irudya and Wadhwan, Neha (2013), India Migration Report 2014, Routledge India, London 16. Rajeev Khanna (2020). COVID-19 could lead to spurt in Punjab migration: Study Retrieved from https://www.downtoearth.org.in/news/economy/covid-19-could-lead-to-spurt-in-punjab-migration-study-70478 Saeed Muhammad and Qaleed Khan Afridi. (2021). Factors Affecting the Migration Intentions of Business Students of Pakistan: Evidence from District Peshawar. Asian Social Studies and Applied Research (ASSAR) , 2(1) 1-8 Sanyukta Kanwal.(2022,February 18). Number of students who went abroad for higher education India 2016-2024.https://www.statista.com/statistics/1278194/india-number-of-students-who-went-abroad-for-studies/ Shanka, T., Quintal, V., & Taylor, R. (2005) Factors Influencing International Students' Choice of an Education Destination- A Correspondence Analysis, Journal of Marketing for Higher Education, 15(2), 31- 46 Sheikh, A., Naqvi, S. H. A., Sheikh, K., Naqvi, S. H. S., & Bandukda, M. Y. (2012). Physician migration at its roots: a study on the factors contributing towards a career choice abroad among students at a medical school in Pakistan. Globalization and Health, 8(1), 43. doi:10.1186/1744-8603-8-43 Tharenou, P. (2010). Women’s Self-Initiated Expatriation as a Career Option and Its Ethical Issues. Journal of Business Ethics, 95(1), 73-88. doi:10.1007/s10551-009-0348-x Vedat AKMAN (2014). Factors Influencing International Student Migration: A Survey and Evaluation of Turkey’s Case. International Journal of contemporary research in business, 5(11), 391-415. Vishal P. Deshmukh Mrs. Sankpal S.V( 2022). Factors influences for migration of Indian students.Journal of Positive School Psychology , 6(4), 381-386 Wuliji, T., Carter, S., & Bates, I. (2009). Migration as a form of workforce attrition: a nine-country study of pharmacists. Human Resources for health, 7(1), 32. doi:10.1186/1478-4491-7-32 Zeeshan, M., Sabbar, S., Bashir, S., & Hussain, R. (2013). Foreign Students’ Motivation for Studying In Malaysia. International Journal of Asian Social Science, 3(3), 833-84 Zachariah K.C.&Rajan, S.Irudaya (2015) “Dynamic of emigration and Remittances in Kerala: Results from the Kerala Migration Survey 2014” Working Paper 463 Users of Networking Sites in India

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.314
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2022
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Same venueCentral European Management JournalSame topicMigration and Labor DynamicsFrench-language works237,207