在尼日利亚贝努埃州和纳萨拉瓦州的教育学院为创新信息和通信技术编码农业教育

G. E. Ekele
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引用次数: 0

摘要

目的:本研究调查了尼日利亚贝努埃州和纳萨拉瓦州教育学院为创新信息和通信技术编码农业教育。方法:本研究采用描述性调查设计。制定了三个研究问题来指导研究。研究对象是来自研究地区教育学院的51位讲师。没有抽样,因为所有人群都被用作调查对象。用于数据收集的工具是一份22个项目的问卷,名为“CAEITQ”(编码农业教育创新信息通信技术问卷)。采用信度的Cronbach Alpha法确定仪器的内部一致性,信度系数为0.77。结果-研究结果显示,受访者需要所有项目的数字设计和数据可视化,数字编程和编码分析和数字产品管理技能编码农业教育在教育学院的创新信息和通信技术。结论-研究得出的结论是,将农业教育编码为创新的信息通信技术是教师和学生从传统教学方法转变的最有力武器。建议-除其他外,建议各教育学院的农业教育讲师接受农业教育数字编程和编码分析方面的培训,以实现有效的教与学。研究意义-本研究的意义在于,在农业教育中使用数字编码、设计、可视化和编程技能将提高讲师在研究领域的有效教学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coding Agricultural Education for Innovative Information and Communication Technology in Colleges of Education in Benue and Nasarawa States, Nigeria
Purpose – The study investigated coding agricultural education for innovative information and communication technology in Colleges of Education in Benue and Nasarawa States Nigeria.Method – The study employed a descriptive survey design. Three research questions were formulated to guide the study. The population of the study was 51 lecturers from the Colleges of Education in the study area. There was no sampling as all the populations were used as respondents. The instrument used for data collection was a 22 items questionnaire developed from literature reviewed titled “CAEITQ” (Coding Agricultural Education for Innovative ICT questionnaire). The Cronbach Alpha method of reliability was used to determine the internal consistency of the instrument and a reliability coefficient of 0.77 was obtained.Results – Findings from the study revealed that respondents required all the items on digital design and data visualization, digital programming and coding analysis and digital product management skills in coding agricultural education for innovative ICT in Colleges of Education.Conclusion – It was concluded that coding agricultural education for innovative ICT is the most potent weapon for paradigm shift from the traditional method of teaching and learning by both lecturers and students.Recommendations – It was recommended amongst others that lecturers of Agricultural Education in the various Colleges of Education be trained in digital programming and coding analysis in agricultural education for effective teaching and learning.Research Implications – The implication of this study is that utilization of digital coding, design, visualization, and programming skills in agricultural education will enhance effective teaching by lecturers in the area of study.
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