Generative Artificial Intelligence Preparedness and Technological Competence

Cheng Zhang, Lizelle E. Villanueva
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Abstract

This research aimed to understand the technological competence and readiness of teachers at Hunan Normal University, Hunan Province, China regarding generative artificial intelligence (GAI). The main objective was to gauge the current state of teacher technological competence and strategize on enhancing their skills amidst rapid technological progress in education. Utilizing an adapted computational thinking scale from Korkmaz et al. (2017), the study evaluated the Generative Artificial Intelligence (GAI) preparedness using a four-point Likert-scale. High scores were indicative of better preparedness. Another instrument adapted from Syn-Jong and Yuhue Chang's 2016 study assessed teachers' technological proficiencies. This research sought to introduce a program boosting the technological competence of university teachers, drawing inspiration from knowledge management theories and analyzing determinants of its effectiveness. The program aims to facilitate systematic training, enabling educators to master generative AI tools, comprehend best teaching practices, and promote collaboration. Key findings included: A significant proportion of female teachers aged 41-50 are from the Colleges of Chemistry, Chemical Engineering, and Commerce. The evident preparedness amongst teachers implies the positive potential of GAI in education.Gender discrepancies exist in GAI preparedness, suggesting gender-biased perceptions.Teachers displayed high technological competence, indicating their ease with technology integration.Female educators might be more technologically aware due to factors like ease of technology integration and intensive training. Younger teachers seem more tech-savvy, and teachers from different departments exhibit varied technological proficiency.A direct relationship was observed between GAI preparedness and technological competence, suggesting those trained in GAI might have superior technological competency.Recommendations based on the study:Promote continuous professional development and encourage more collaborative efforts.Utilize the technological strengths of female teachers, fostering mentorship and balanced knowledge sharing.Strengthen support for teachers in their technological endeavors, promoting workshops and online collaborations.Provide specialized training for the College of Physical Education teachers to enhance their tech skills.Innovate teacher education initiatives to improve GAI preparedness and technological competence.Implement the proposed digital teacher training program centered on GAI, equipping teachers to seamlessly integrate GAI into their classrooms, promoting innovative and flexible teaching methods.
生成式人工智能的准备和技术能力
本研究旨在了解中国湖南省湖南师范大学教师在生成式人工智能(GAI)方面的技术能力和准备情况。主要目的是了解教师技术能力的现状,并在教育技术飞速发展的背景下制定提高教师技术能力的策略。本研究利用 Korkmaz 等人(2017 年)改编的计算思维量表,采用四点李克特量表对生成式人工智能(GAI)准备情况进行评估。高分表示准备程度较高。另一项改编自 Syn-Jong 和 Yuhue Chang 2016 年研究的工具评估了教师的技术熟练程度。这项研究试图引入一项提高大学教师技术能力的计划,从知识管理理论中汲取灵感,并分析其有效性的决定因素。该项目旨在促进系统化培训,使教育工作者掌握生成式人工智能工具,理解最佳教学实践,并促进合作。主要发现包括在 41-50 岁的女教师中,化学学院、化学工程学院和商学院的教师占了很大比例。教师明显做好了准备,这意味着 GAI 在教育中具有积极的潜力。在 GAI 的准备程度方面存在性别差异,这表明在观念上存在性别偏见。教师表现出较高的技术能力,这表明她们易于技术整合。年轻教师似乎更精通技术,来自不同部门的教师表现出不同的技术能力。GAI 准备程度与技术能力之间存在直接关系,这表明接受过 GAI 培训的教师可能具有更强的技术能力。加强对教师技术努力的支持,促进研讨会和在线合作。为体育学院教师提供专门培训,以提高他们的技术技能。创新教师教育举措,以提高 GAI 准备和技术能力。实施建议的以 GAI 为中心的数字教师培训计划,使教师能够将 GAI 无缝融入课堂,促进创新和灵活的教学方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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