PENGEMBANGAN INSTRUMEN BELONGING-SUPPORTIVE DEEP LEARNING ENVIRONMENTS (BSDLE)

OKTAVIA, . (2026) PENGEMBANGAN INSTRUMEN BELONGING-SUPPORTIVE DEEP LEARNING ENVIRONMENTS (BSDLE). Doktor thesis, UNIVERSITAS NEGERI JAKARTA.

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Abstract

Penelitian ini bertujuan untuk mengembangkan instrumen pengukuran belonging supportive deep learning inverotment (BSDLE), BSDLE sebagai suatu lingkungan belajar yang mengintegrasikan dukungan rasa memiliki (sense of belonging) dengan penerapan pada pembelajaran deep learning, serta belum tersedianya instrumen pengukuran BSDLE yang valid dan reliabel. Sebanyak 149 butir instrumen disusun berdasarkan kajian literature kemudian dikurangi menjadi 49 item setelah melalui uji validitas isi oleh ahli menggunakan metode content validity ratio (CVR) dan content validity index (CVI). penelitian ini melibatkan 825 responden dari 5 universitas yaitu Universitas Negeri Jakarta, Universitas Islam Negeri Syarif Hidayatullah Jakarta, Universitas Pamulang, Universitas Terbuka dan Universitas Teknologi Nusantara. Berdasarkan hasil uji Confirmatory Factor Analysis (CFA) menunjukkan hasil kecocokan model yang sangat baik (RSMEA = 0,049; CFI = 0,97; NFI = 0,95; RFI=0,95). Analisis Multidimentional Item Response Theory (MIRT) menunjukkan bahwa model dengan enam faktor memberikan kesesuaian yang baik terhadap data empiris yaitu: Student Cohesiveness (SC), Task Orientation (T), Investigation (IN), Involvement (IV), Cooperative (CO), serta Faculty and Staff Relations (FR). Secara umum, keenam dimensi tersebut menunjukkan kontribusi signifikan dalam menjelaskan konstruk lingkungan belajar yang mendukung belongingness mahasiswa, dengan pola nilai loading factor dan parameter diskriminasi yang mengindikasikan validitas konstruk yang baik. analisis Differential Item Functioning (DIF) menunjukkan bahwa sebagian besar butir bebas dari bias kelompok. Hasil penelitian menunjukkan bahwa intrumen yang dikembangkan valid dan reliabel dalam mengukur BSDLE, Instrumen ini dapat digunakan untuk diagnosis pembelajaran, evaluasi mutu dan perumusan kebijakan di Universitas. Kata kunci: Belonging Supportive Deep Learning Inverotment, Deep Learning, Belonging, CFA, MIRT ***** This study aims to develop a measurement instrument for the BelongingSupportive Deep Learning Environment (BSDLE). BSDLE is conceptualized as a learning environment that integrates a sense of belonging with the implementation of deep learning practices. Despite its theoretical importance, a valid and reliable instrument to measure BSDLE has not yet been available. A total of 47 items were subjected to content validity testing by experts using the Content Validity Ratio (CVR) and Content Validity Index (CVI) methods. The study involved 825 respondents from five universities: Universitas Negeri Jakarta, Universitas Islam Negeri Syarif Hidayatullah Jakarta, Universitas Pamulang, Universitas Terbuka, and Universitas Teknologi Nusantara. The results of Confirmatory Factor Analysis (CFA) indicated an excellent model fit (RMSEA = 0.049; CFI = 0.97; NFI = 0.95; RFI = 0.95). Furthermore, Multidimensional Item Response Theory (MIRT) analysis demonstrated that a sixfactor model provided a good fit to the empirical data, comprising Student Cohesiveness (SC), Task Orientation (T), Investigation (IN), Involvement (IV), Cooperation (CO), and Faculty and Staff Relations (FR). In general, the six dimensions showed a significant contribution in explaining the construct of a learning environment that supports student belongingness, with the pattern of loading factor values and discrimination parameters indicating good construct validity. Differential Item Functioning (DIF) analysis showed that most items were free from group bias. The results of the study indicate that the developed instrument is valid and reliable in measuring BSDLE. This instrument can be used for learning diagnosis, quality evaluation and policy formulation at the University. Key: Belonging Supportive Deep Learning Inverotment, Deep Learning, Belonging, CFA, MIRT

Item Type:	Thesis (Doktor)
Additional Information:	1. Prof. Dr. Wardani Rahayu, M.Si 2. Prof. Dr. Iva Sarifah, M.Pd
Subjects:	Pendidikan > Evaluasi Pendidikan Pendidikan > Teori, Penelitian Pendidikan Pendidikan > Psikologi Pendidikan
Divisions:	PASCASARJANA > S3 Penelitian Dan Evaluasi Pendidikan
Depositing User:	Oktavia .
Date Deposited:	13 Apr 2026 08:08
Last Modified:	13 Apr 2026 08:08
URI:	http://repository.unj.ac.id/id/eprint/66162

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