Developing a Framework for the Effective Use of Learning Analytics

Author:

Gavan Collette1

Affiliation:

1. Edge Hill University, UK

Abstract

Research and experimentation is uncovering forms of best practice and possible factors on which to centre the analysis of students in an effective way, however learning analytics has yet to be comprehensively implemented country-wide in the United Kingdom. The chapter explores the current impact of learning analytics in higher education at mome discusses and observes the current vacancies with which a framework enabled to function with data visualisation could be utilised. The deliverable seeks to design an initial framework that has the potential to be utilised in a higher education setting for more effective and insightful decision making with regards to learner retention and engagement. This framework will combine the theory and scientific action of predictive analytics with a comparison of the most suitable data visualisation toolsets that are currently available in open-source software.

Publisher

IGI Global

Reference68 articles.

1. Using Data Mining for Predicting Relationships between Online Question Theme and Final Grade.;M.Abdous;Journal of Educational Technology & Society,2012

2. Teaching computer programming courses in a computer laboratory environment

3. Barnes, D. J., Fincher, S., & Thompson, S. (1997) Introductory Problem Solving in Computer Science. In G. Daughton, & P. Magee (Eds.), Proceedings of the5th Annual Conference on the Teaching of Computing (pp. 36-39). Centre for Teaching Computing, Dublin City University, Dublin, Ireland.

4. Barron, B., & Engle, R. A. (2007) Analyzing Data Derived from Video Records. In S.J. Derry (Ed.), Guidelines for Video Research in Education: Recommendations from an Expert Panel (White paper) (pp. 24-33). Retrieved from http://drdc.uchicago.edu/what/video-research-guidelines.pdf#page=1&view=fitV,0

5. Abstraction ability as an indicator of success for learning object-oriented programming?

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