Enriching context descriptions for enhanced LA scalability: a case study

Author:

Samuelsen JeanetteORCID,Chen Weiqin,Wasson Barbara

Abstract

AbstractLearning analytics (LA) is a field that examines data about learners and their context, for understanding and optimizing learning and the environments in which it occurs. Integration of multiple data sources, an important dimension of scalability, has the potential to provide rich insights within LA. Using a common standard such as the Experience API (xAPI) to describe learning activity data across multiple sources can alleviate obstacles for data integration. Despite their potential, however, research indicates that standards are seldom used for integration of multiple sources in LA. Our research aims to understand and address the challenges of using current learning activity data standards for describing learning context with regard to interoperability and data integration. In this paper, we present the results of an exploratory case study involving in-depth interviews with stakeholders having used xAPI in a real-world project. Based on the subsequent thematic analysis of interviews, and examination of xAPI, we identified challenges and limitations in describing learning context data, and developed recommendations (provided in this paper in summarized form) for enriching context descriptions and enhancing the expressibility of xAPI. By situating the research in a real-world setting, our research also contributes to bridge the gap between the academic community and practitioners in learning activity data standards and scalability, focusing on description of learning context.

Funder

Centre for the Science of Learning & Technology (SLATE), University of Bergen, Norway

Publisher

Springer Science and Business Media LLC

Subject

Management of Technology and Innovation,Media Technology,Education,Social Psychology

Reference49 articles.

1. Advanced Distributed Learning. (2017a). xAPI specification. Retrieved from https://github.com/adlnet/xAPI-Spec

2. Advanced Distributed Learning. (2017b). xAPI specification - part one: About the experience API. Retrieved from https://github.com/adlnet/xAPI-Spec/blob/master/xAPI-About.md#partone

3. Advanced Distributed Learning. (2017c). xAPI specification - part two: Experience API data. Retrieved from https://github.com/adlnet/xAPI-Spec/blob/master/xAPI-Data.md#parttwo

4. Advanced Distributed Learning. (2017d). xAPI specification - part three: Data processing, validation, and security. Retrieved from https://github.com/adlnet/xAPI-Spec/blob/master/xAPI-Communication.md#partthree

5. Advanced Distributed Learning. (2018a). xAPI profiles specification. Retrieved from https://github.com/adlnet/xapi-profiles

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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