¹Kartika Sari, ²Anak Agung Istri Ngurah Eka Karyawati, ³Luh Putu Ida Harini, ⁴Ni Ketut Tari Tastrawati, ⁵I Gede Surya Wirawan, ⁶Karolien Miracle Anggraeni, ⁷Putu Ayu Liana Prasetya D

^{1,2,3,4,5,6,7} Mathematics Department, Udayana University, Badung, Bali, Indonesia

DOI : https://doi.org/10.47191/ijsshr/v7-i12-41

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ABSTRACT

SMP Negeri 3 Selat is located in Duda Utara, Selat District, Karangasem Regency, Bali Province, Indonesia. Situational analysis shows that most teachers have not utilized artificial intelligence (AI) technology optimally in education. In fact, artificial intelligence technology has the potential to help teachers' work in improving the quality of learning. The purpose of this study was to see the effectiveness of training and mentoring activities in improving teacher knowledge about AI technology and its utilization, as well as improving teacher skills in utilizing AI technology for compiling learning administration; designing learning processes and compiling teaching materials. The data used were primary data from training and mentoring participants consisting of 20 teachers of SMP Negeri 3 Selat. The data were in the form of quantitative data, namely pretest and posttest scores. The data analysis stage began with a plot of pretest and posttest scores and a bar chart plot of grouped data, both of which showed a significant increase in scores after being given intervention in the form of training and mentoring. Paired t-test. To see how big the effect of the training and mentoring intervention was, Cohen's effect size was calculated, the percentage change in pretest and posttest scores. The paired t-test results show that there is a significant difference between the pretest and posttest scores. Based on Cohen's size, it was found that the training and mentoring intervention had a very strong effect on changes in pretest and posttest scores. In addition, it was also found that the percentage of changes in pretest and posttest was 106.85% and it can be 95% certain that the average posttest score in the population is estimated to be 32.76 to 45.24 points higher than the average pretest score, due to the intervention in the form of training and mentoring. This is reinforced by the pretest and posttest difference plot showing that there was a significant increase in scores after the intervention.

KEYWORDS:

Artificial intelligence, skills, intervention, utilization, training and mentoring

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Volume 07 Issue 12 December 2024