Integrating the Humanistic Learning Model in Guidance and Counseling to Enhance Self-Regulation and Academic Resilience among High School Students

Khairul Amri, Muhammad Darwis, Riski Baroroh

Abstract


High school students often face academic stress and emotional challenges that undermine their self-regulation and academic resilience—two critical competencies for 21st-century learning. Traditional guidance and counseling services often emphasize remedial approaches rather than fostering personal growth. This study explores the effectiveness of integrating the Humanistic Learning Model (HLM) into school-based counseling to enhance these psychological constructs. A quasi-experimental one-group pretest–posttest design was employed, involving 60 tenth-grade students at MAN 2 Padangsidimpuan, Indonesia. The intervention comprised six HLM-based counseling sessions emphasizing empathy, student autonomy, and reflective dialogue. Validated instruments were used to assess self-regulated learning and academic resilience before and after the intervention. Data were analyzed using paired-sample t-tests, effect size calculations (Cohen’s d), normalized gain (N-Gain), and Pearson correlation. Posttest scores showed significant improvements in both self-regulation (M = 86.92 vs. 71.48; t = 11.82, p < .001; d = 1.52) and academic resilience (M = 83.75 vs. 68.67; t = 10.97, p < .001; d = 1.41). N-Gain scores (0.62 and 0.59) indicated moderate–high practical improvement. A strong positive correlation (r = 0.68, p < .001) was found between gains in both variables. The findings demonstrate that HLM-based counseling is effective in promoting both cognitive (self-regulation) and affective (resilience) development. The model offers a student-centered approach that can enrich school counseling practices by fostering reflective, autonomous, and emotionally resilient learners.

Keywords


humanistic learning model; guidance and counseling; self-regulation; academic resilience; high school students

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References


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DOI: https://doi.org/10.35445/alishlah.v17i4.8882

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