A Social Media Analytics Framework to Increase Prospective Students' Interests in STEM and TVET Education

Autor/inn/en	Adnan, Muhamad Hariz Muhamad; Ariffin, Shamsul Arrieya; Hanafi, Hafizul Fahri; Husain, Mohd Shahid; Panessai, Ismail Yusuf
Titel	A Social Media Analytics Framework to Increase Prospective Students' Interests in STEM and TVET Education
Quelle	In: Asian Journal of University Education, 16 (2020) 4, S.82-90 (9 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1823-7797
Schlagwörter	Social Media; College Bound Students; STEM Education; Vocational Education; Vocational Interests; Foreign Countries; Career Awareness; Data Analysis; Marketing; Malaysia + Suchen Sie Ihr Suchwort? Soziale Medien; STEM; Ausbildung; Berufsbildung; Berufsinteresse; Ausland; Karrierebewusstsein; Auswertung
Abstract	Recently, the promotion of science, technology, engineering and mathematics (STEM) education has become the highlight due to the shortage in the STEM workforce. Surprisingly, the enrolment rates in STEM degrees are still low in many countries. Social media has been identified as one of the main platforms that can help to increase prospective students' interest in STEM and also Technical and Vocational Education and Training (TVET) subjects. However, very little research has been done for the higher education institutions in Malaysia in leveraging social media and social media analytics effectively to increase the students' interests and awareness of STEM and TVET disciplines. Therefore, this paper aims to propose a framework to increase prospective students' interest in STEM and TVET using social media and big data analytics. The objectives of this study are to explore various social media applications in education and study these applications towards increasing students' interests and propose a suitable framework for Malaysian higher education institutions. The framework is proposed by following the theory synthesis methodology. Four main components of the framework have been proposed, namely social media, role model or mentoring, massive open online courses and big data analytics. Each component is significant and requires a considerable amount of time to develop. The suggested framework is anticipated to benefit higher education institutions with a significant gain of the number of students, revenues and positive reputations. (As Provided).
Anmerkungen	UiTM Press. Asian Centre for Research on University Learning and Teaching, Faculty of Education, Penerbit UiTM, Universiti Teknologi MARA, Bangunan Fakulti Pengurusan Hotel dan Pelancongan, 40450 Shah Alam, Selangor Darul Ehsan, Malaysia. Web site: https://education.uitm.edu.my/ajue/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01