Augusto Da Costa
Instituto Superior Cristal, Timor Leste

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Self-Regulated Learning Difference between Male and Female Students Said Alhadi; Wahyu Nanda Eka Saputra; Agus Supriyanto; Augusto Da Costa; Ediyanto Ediyanto
PSIKOPEDAGOGIA Jurnal Bimbingan dan Konseling Vol 7, No 2: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/psikopedagogia.v7i2.12933

Abstract

The present study aimed to identify self-regulated learning difference between male and female students in Bantul Regency, Special Region of Yogyakarta, Indonesia. The present study employed quantitative approach with comparative design, the sample of the study was 300 students comprising of 164 male students and 135 female students. The samples were selected using stratified random sampling technique. The instrument that was employed was SRL scale. Independent Samples Test emerged as the data analysis technique to identify SRL difference between male and female students. The result of the study showed that there was significant difference between male and female students' SRL. Based on the SRL average level, female students possess higher level of SRL than male students. The result of the study can be used as initial assessment by school counselor in order to develop a guidance and counseling program concerning SRL.
Strengthening Students’ Emotional Intelligence through Deep Learning Based Individual Counseling Services Hastiani Hastiani; Amelia Atika; Rustam Rustam; Ega Monika; Aprilia Rahmwati; Augusto da Costa
Al-Ihath: Jurnal Bimbingan dan Konseling Islam Vol. 6 No. 1 (2026): January
Publisher : Program Studi Bimbingan dan Konseling Islam Institut Attanwir Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53915/jbki.v6i1.79

Abstract

This research investigates the integration of individual counseling services powered by deep learning technologies to augment students’ emotional intelligence within the unique environment of an Islamic boarding school. Specifically situated at Al Fityan Islamic Boarding School, the study engages seventh-grade participants by aligning modern technological counseling interventions with traditional Islamic character education, focusing on the core principles of akhlaq and adab. A quasi-experimental design was employed, consisting of an experimental group receiving deep learning–based individual counseling services and a control group receiving conventional counseling. Data were collected using the Emotional Intelligence Scale (EIS), structured observations, deep learning system logs, and semi-structured interviews with Islamic school counselors. Quantitative data were analyzed using independent sample t-tests and ANOVA, while the deep learning model performance was evaluated through precision, recall, and F1-score metrics. Qualitative data were analyzed using thematic analysis to capture counselors’ experiences in integrating technology with Islamic counseling principles. The results indicate a statistically significant improvement in students’ emotional intelligence in the experimental group compared to the control group (p < 0.05). The deep learning model achieved an accuracy rate of 75–80%, and the counseling chatbot attained a user satisfaction level of 82%. These findings demonstrate that deep learning–based individual counseling services are effective in strengthening students’ emotional intelligence while supporting Islamic values and enhancing the efficiency of counselors’ roles in Islamic boarding schools.