SEMANTRIS GOOGLE AI-BASED LEARNING TO ENHANCE STUDENTS’ VOCABULARY MASTERY - Fathur Rahman Arif Hasan; Adi Isma; Ambo Dalle; Yulie Asni (Al-Irsyad: Journal of Education Science, 2024)
Semantris Google AI-Based Learning research has examined the students' disinterest and low level of vocabulary acquisition in English subject at MTs DDI Takkalasi. The students cited difficulty in pronunciation and other reasons for their lack of enthusiasm towards English as a difficult subject. This lack of interest and motivation is due to the absence of an interesting and enjoyable learning environment, which hinders students' ability to concentrate on their studies. In addition, the limited application of modern technology in the learning process makes this a problem that must be addressed given the increasingly advanced era. The research employed a quasi-experimental design to investigate the effectiveness of an intervention in improving students' English language proficiency. The study utilized a quantitative approach, conducting pre-test and post-test analyses to measure the impact of the intervention. The pre-test served as a baseline measurement, while the post-test assessed the outcomes after implementing the intervention. The researcher employed a quota sampling technique to select participants. The results of the Semantris Google AI-Based Learning study showed a significant difference in vocabulary improvement between the two groups, as evidenced by the T-count value of 6.858, exceeding the critical T-table value of 2.060. The rejection of the null hypothesis (H0) is supported by the mean N gain value of 0.4249 obtained from the experimental class, which falls within the moderate range according to the N gain table. This finding confirms that the use of Semantris Google AI-Based Learning is very effective in improving the vocabulary mastery of MTs DDI Takkalasi students.