Research Efficiency in Higher Education: Clustering Higher Education Systems Globally

Öz

Bu araştırma, boyuttan bağımsız araştırma girdilerini ve çıktılarını karşılaştırarak küresel olarak yükseköğretim sistemlerinin (HES) araştırma verimliliği kümelerini belirlemeyi amaçlamaktadır. Araştırma, her bir araştırma çıktısının bireysel katkısını keşfetmek için ilişkisel araştırma ve HES'lerin araştırma verimliliği kümelerini tanımlamak için genel anket modeli olmak üzere iki farklı yaklaşımdan yararlanılarak tasarlanmıştır. 75 ülkenin HES'leri dahil olmak üzere, veriler UNESCO İstatistik Enstitüsü, Avrupa Patent Ofisi PATSTAT'ın veritabanından ve her HES'teki "araştırmacı başına oranlar" açısından belirli bir zaman dilimi için Web of Science Core Collection kayıtlarından toplandı; Araştırma ve Geliştirme harcamaları için 2015, makaleler ve patent başvuruları için 2018 ve başlangıçta alınan atıflar için 2018-2019. Bu veri seti üzerinden, öncelikle her bir çıktının (patent başvuruları, makaleler ve atıflar) bireysel katkısına göre HES'lerin araştırma performans puanlarını yeniden hesaplamak için regresyon analizi yapılmış ve bu değişkenler arasındaki çoklu doğrusallık bağlantıları ortadan kaldırılmıştır; ardından ülkeleri HES'lerinin araştırma verimliliği oranları açısından kategorize etmek için kümeleme analizi yapılmıştır. Analiz, dört araştırma verimliliği oranı kümesi göstermiştir: en yüksek grupta yalnızca bir ülke, daha yüksek grupta üç ülke, orta grupta 32 ülke ve daha düşük grupta 39 ülke. Analizde en yüksek araştırma verimliliği oranını gösteren HES'lerden çeşitli politika ve uygulamaları tartışan bu araştırma, küresel araştırma yapısındaki her bir ulusal ve uluslararası faktörün potansiyel katkısıyla araştırma performansını daha da iyileştirmek için öneriler sunmaktadır.

Anahtar Kelimeler

• Yüksek öğrenim sistemleri
• araştırma girdileri
• araştırma çıktıları
• araştırma verimliliği
• küresel araştırma verimliliği

Research Efficiency in Higher Education: Clustering Higher Education Systems Globally

Öz

This research aims to identify the research efficiency clusters of higher education systems (HESs) globally by comparing size-independent research inputs and outputs. The research was designed benefitting from two different approaches, correlational research to discover the individual contribution of each research output and the general survey model to define research efficiency clusters of HESs. Including 75 countries’ HESs, the data were collected from the database of the UNESCO Institute for Statistics, PATSTAT of European Patent Office, and the Web of Science Core Collection records for a designated time period in terms of “per researcher rates” in each HES; 2015 for Research & Development spending, 2018 for articles and patent applications, and 2018-2019 for initially received citations. Through this dataset, regression analysis was first performed to re-calculate the research performance scores of HESs by the individual contribution of each output (patent applications, articles, and citations) eliminating the multicollinearity connections among these variables; then, cluster analysis was carried out to categorise countries in terms of the research efficiency ratios of their HES. The analysis showed four clusters of research efficiency ratios: only one country in the highest group, three in the higher group, 32 in the middle group, and 39 in the lower group. Discussing various policies and practices from HESs displaying the top research efficiency ratio in the analysis, this research presents recommendations to further improve research performance by the potential contribution of each national and international factor in the global research structure.

Anahtar Kelimeler

• Higher education systems
• research inputs
• research outputs
• research efficiency in higher education
• global clusters of research efficiency

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