Keywords
science teachers
teacher readiness
teacher engagement
descriptive-explanatory design
How to Cite
Abstract
This study aimed to determine the level of readiness, engagement, competence and challenges of science teachers in using AI-based teaching strategies of selected secondary schools within the legislative district 5 in the Division of Isabela. The study utilized descriptive-explanatory design involving a total of sixteen (16) schools, two (2) schools randomly selected from each district yielding one hundred four (104) randomly selected teachers served as respondents of the study determined through multi-stage sampling. Data collection commenced using a valid and reliable survey questionnaire consisting of specific indicators to collect the quantitative data, while an interview guide was crafted to acquire the qualitative data. The study revealed that most of the teachers lack training in AI-based teaching strategies. At the same time, content and delivery tools and assessment and feedback tools are the main AI tools used for the instruction and evaluation process. More so, science teachers are "Moderately Ready", specifically along three (3) domains. However, on access to resources, they are "Slightly Ready". Moreover, science teachers are "Moderately Engaged" and "Moderately Competent" in all domains. Findings indicate that statistically substantial positive correlations are found in all areas of AI competence, and both levels of readiness and engagement clearly indicate a synergistic relationship. As teachers become more ready and engaged with AI, their ability to use these technologies for instructional motives improves. Finally, the primary identified challenge is the lack of professional AI training for teachers. These served as the fundamental basis of the capacitation plan to enhance the areas that need improvement that are critical to progressing both teacher competence and the overall quality of science education.References
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