Data Power in Military Education: Awareness and Understanding of Learning Analytics

Author:

Ščavničar DarkoORCID

Abstract

Abstract The rapid development, use and availability of technology is creating new opportunities in all areas of human life. The amount of data generated is enormous, followed by advances in the collection, processing and analysis of big data for a variety of purposes, such as various industries, science, healthcare and even education. Data science in education aims to better understand and improve learning processes through data–driven insights. Learning analytics studies how to use data mining, machine learning, natural language processing, visualisation and human– computer interaction approaches to help learners, educators and institutional leaders improve learning processes and teaching practices.

Publisher

Walter de Gruyter GmbH

Subject

Anesthesiology and Pain Medicine

Reference43 articles.

1. Anderson, S., 2023. Enterprise Resource Planning (ERP): Meaning, Components, and Examples. New York: Investopedia. https://www.investopedia.com/terms/e/erp.asp, 10. 9. 2023.

2. Arnold, K. E., Lonn, S., Pistilli, M. D., 2014. An Exercise in Institutional Reflection: The Learning Analytics Readiness Instrument (LARI). V Proceedings of the 4th International Conference on Learning Analytics and Knowledge. New York: ACM. Str. 163–169.

3. Arroway, P., Morgan, G., O’Keefe, M., Yanosky, R., 2016. Learning Analytics in Higher Education. Louisville: Educause Center for Analysis and Research.

4. Baker, S., in Inventado, P. S., 2016. Educational data mining and learning analytics: Potentials and possibilities for online education. V Veletsianos (ur.), Emergence and Innovation in Digital Learning. Edmonton: AU Press, Athabasca University. Str. 83–98.

5. Bichsel, J., 2012. Analytics in higher education: Benefits, barriers, progress, and recommendations. V Research report. Louisville: Educause Center for Analysis and Research – ECAR.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3