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Teachers' Self-Efficacy with Artificial Intelligence (AI) Based Educational Tools

Authors: Sumandal, Allan H.;

Teachers' Self-Efficacy with Artificial Intelligence (AI) Based Educational Tools

Abstract

The purpose of this study was to determine the level of teachers' self-efficacy with the use of Artificial Intelligence-based educational tools. Descriptive-comparative was utilized as the research design. The investigation included twenty-five (25) AI teacher-users of Abueg National High School which was selected using a purposive sampling method. A validated self-made questionnaire in a Likert scale with four orderable gradations was employed to gather the necessary data. The statistical tools used were frequency, percentage, mean, standard deviation, and ANOVA test. Results suggest that the majority of the respondents were female, 31 to 40 years of age, 1 to 10 years in service with units in master's degree. They have a high self-efficacy with AI indicating a strong belief in their ability to use AI-based educational tools to enhance teaching and learning practices. Using ANOVA one-way, a value greater than 0.05 was observed in all variables which means there is no significant difference in the respondent's demographic profile and their level of self-efficacy with AI tools. This result accepts the hypothesis. However, it was recommended that teachers should strengthen their use of AI-based tools to improve teaching and non-teaching-related tasks. Furthermore, attending workshops or seminars about AI in education was also suggested.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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