Application of Data Mining in Predicting College Graduates Employment

He, Shouwu; Li, Xiaoying; Jia, Chen

doi:10.1109/icaibd51990.2021.9459039

Cited by 14 publications

(7 citation statements)

References 4 publications

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“…As measured by MUET, English proficiency is critical in increasing graduate employability, as supported by previous studies (Othman et al, 2018;Zainuddin et al, 2019). As measured by CGPA, academic performance influences graduates' employability, which is consistent with the study by He et al (2021). Although academic performance is not the most important predictor of graduate employability, it is important in making a good impression on a potential employer.…”

Section: Discussionsupporting

confidence: 84%

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Soft Skills and Graduate Employability: Evidence from Malaysian Tracer Study

Basir¹,

Zubairi²,

Jani³

et al. 2022

JSSH

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Recent trends in graduate employment have raised concerns among higher education providers and other stakeholders. Issues concerning the soft skills gap have been constantly raised so that industries and universities can adopt various initiatives to address this situation. In addition, employment has shifted from production to service, increasing the importance of soft skills. This study aims to map graduates’ soft skills and employment status after graduation. The Ministry of Higher Education repository was used to select 100,413 first-degree graduates who had completed their studies. Logistic regression analysis created the graduate employability predictive model, which yielded a 77% accuracy. The findings show that 85.5% of graduates were employed during data collection. The predictive model suggests that graduate employability status is affected by factors such as gender, family income, the field of study, MUET, CGPA, internship, entrepreneurship course, working experience, communication skills, analytical skills, teamwork, positive values, and general knowledge.

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Section: Discussionsupporting

confidence: 84%

“…Graduate academic achievement and qualifications are significant factors in graduate employability (He et al, 2021). Pinto and Ramalheira (2017) highlighted the significance of academic achievement and extracurricular activities in obtaining employment.…”

Section: Literature Reviewmentioning

confidence: 99%

Soft Skills and Graduate Employability: Evidence from Malaysian Tracer Study

Basir¹,

Zubairi²,

Jani³

et al. 2022

JSSH

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“…Bir 𝒂𝒙+𝒃 denklemi için bir olayın gerçekleşme olasılığı: Bu tahmin işlemi, logit dönüşümü kullanılarak gerçekleştirilir. Logit fonksiyonu ((𝑝)) olayın gerçekleşme olasılığını 0 ile 1 arasında sınırlayan bir dönüşüm sağlar [5]. Logit fonksiyonu, olasılığın doğal logaritması olan (𝑝/(1−𝑝)) olarak ifade edilir [6].…”

Section: Kullanılan Makine öğRenmesi Algoritmaları A) Logistic Regres...unclassified

“…Rastgele Orman Sınıflandırıcısı, birçok karar ağacının bir araya gelerek oluşturduğu bir denetimli ensemble (topluluk) sınıflandırma modelidir. Temel sınıflandırıcı olarak karar ağacını kullanır [5]. Leo Breiman tarafından keşfedilen bu yöntem, temeli birden çok karar ağacının ürettiği tahminlerin bir araya getirilerek değerlendirilmesine dayanmaktadır [8].…”

Section: Kullanılan Makine öğRenmesi Algoritmaları A) Logistic Regres...unclassified

Makine Öğrenmesi Teknikleriyle Potansiyel Yetenek Avı

2023

IJANSER

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Özet -Bu çalışma, futbolculardaki potansiyel yeteneklerini tahmin etmek için makine öğrenimi tekniklerini araştırmaktadır. İki veri kümesi kullanılarak futbolcuların istatistiksel özellikleri analiz edilmiş ve çeşitli makine öğrenimi algoritmaları ile potansiyel etiketler tahmin edilmiştir. Seçilen birden fazla makine öğrenmesi modellemelerinden en başarılı sonuç Rastgele Orman yaklaşımından elde edilmiştir. Sonuçlar, makine öğrenimi tekniklerinin futbolculardaki potansiyeli tahmin etmede etkili olduğunu göstermektedir. Bu yaklaşım, futbol kulüplerine, veri odaklı oyuncu seçimi yapabilme, potansiyel yetenek gösteren oyuncuları daha doğru bir şekilde tanımlayarak gelecekteki başarılarını artırma fırsatı sunmaktadır.

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“…In the context of the Internet and big in order to effectively improve the teaching methods of computer programming, teachers in higher vocational colleges use new technologies and rich teaching methods to cope with the diverse and dynamic needs of students. At present, most universities have established digital data platforms and systems, which can collect and analyze data generated in the teaching process more effectively, greatly facilitating the evaluation and research of teaching effect [5] .…”

Section: Introductionmentioning

confidence: 99%

Teaching Evaluation of Computer Programming Course in Higher Vocational Colleges Based on Big Data

2024

FER

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The computer programming course has always been considered a difficult course to get started, especially the teaching quality of computer programming courses in higher vocational schools is relatively poor, which has been a problem and challenge for schools and teachers. This paper designs a teaching evaluation method of computer programming course in higher vocational colleges based on big data. Firstly, the paper analyzes the application of big data in the computer programming course of higher vocational college, and confirms the promoting effect of big data on the teaching of computer programming course of higher vocational college. Based on the evaluation results, the author puts forward some strategies to improve the teaching quality. The research results provide valuable reference for the teaching of computer programming courses and the application of big data in higher vocational schools.

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Application of Data Mining in Predicting College Graduates Employment

Cited by 14 publications

References 4 publications

Soft Skills and Graduate Employability: Evidence from Malaysian Tracer Study

Soft Skills and Graduate Employability: Evidence from Malaysian Tracer Study

Makine Öğrenmesi Teknikleriyle Potansiyel Yetenek Avı

Teaching Evaluation of Computer Programming Course in Higher Vocational Colleges Based on Big Data

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