HUBUNGAN KETERGANTUNGAN GENERATIVE AI DENGAN KESULITAN REGULASI EMOSI PADA MAHASISWA PENGGUNA GENERATIVE AI

Abstract

ABSTRACT

The increasing use of generative artificial intelligence (AI) in academic activities has transformed the way university students access information, complete assignments, and cope with various learning demands. While these technological advances offer substantial benefits, they have also raised concerns regarding the potential development of AI dependency and its association with students' ability to regulate emotions. This study examined the relationship between generative AI dependency and difficulties in emotion regulation using a quantitative correlational design involving 237 university students who had experience using generative AI, selected through purposive sampling. Data were collected using the Generative AI Dependency Scale and the Difficulties in Emotion Regulation Scale (DERS), both of which demonstrated satisfactory validity and reliability before being analyzed using Bayesian Pearson Correlation. The analysis yielded a correlation coefficient of r = 0.674 with a Bayes Factor (BF₁₀) of 3.822 × 10²⁹, indicating a strong positive relationship supported by very strong statistical evidence between generative AI dependency and difficulties in emotion regulation among university students. These findings provide additional empirical evidence that psychological aspects should be considered when integrating AI into higher education, emphasizing that the use of generative AI should promote not only learning effectiveness but also students' capacity for adaptive emotion regulation to support sustainable academic development.

ABSTRAK

Meningkatnya pemanfaatan generative artificial intelligence (AI) dalam aktivitas akademik telah mengubah cara mahasiswa memperoleh informasi, menyelesaikan tugas, hingga menghadapi berbagai tuntutan pembelajaran. Perubahan tersebut menghadirkan manfaat yang besar, tetapi pada saat yang sama memunculkan perhatian terhadap kemungkinan berkembangnya ketergantungan pada AI serta kaitannya dengan kemampuan mengelola emosi. Hubungan kedua aspek tersebut dianalisis melalui pendekatan kuantitatif dengan desain korelasional yang melibatkan 237 mahasiswa pengguna generative AI yang dipilih menggunakan teknik purposive sampling. Data dikumpulkan menggunakan Generative AI Dependency Scale dan Difficulties in Emotion Regulation Scale (DERS) yang telah memenuhi pengujian validitas dan reliabilitas, kemudian dianalisis menggunakan Bayesian Pearson Correlation. Pengujian menghasilkan koefisien korelasi sebesar r = 0,674 dengan nilai Bayes Factor (BF₁₀) sebesar 3,822 × 10²⁹, yang menunjukkan adanya hubungan positif dengan dukungan bukti statistik yang sangat kuat antara ketergantungan terhadap generative AI dan kesulitan regulasi emosi pada mahasiswa. Temuan ini menambah bukti empiris bahwa aspek psikologis perlu dipertimbangkan dalam pemanfaatan AI di pendidikan tinggi, sehingga penggunaan generative AI tidak hanya diarahkan pada peningkatan efektivitas belajar, tetapi juga tetap memperhatikan kemampuan regulasi emosi sebagai bagian dari pembelajaran yang berkelanjutan.