Category Archives: Uncategorized

Comparing xAPI and Caliper

Date: 26th August 2016
Version 1-1 of this paper was published on 14th September 2016 in order to provide corrected information about the governance of xAPI.

Authors:
David (Dai) Griffiths, University of Bolton
Tore Hoel, Oslo and Akershus University College of Applied Sciences, Oslo, Norway

Link: Review 7: Comparing xAPI and Caliper

Citation: Griffiths, D., Hoel, T. Comparing xAPI and Caliper. Learning Analytics Review, no. 7, January 2016, ISSN: 2057-7494. http://www.laceproject.eu/learning-analytics-review/lace-review-7_comparing-xapi-caliper/

Short link (for use in Twitter): http://bit.ly/2bYwOoa

Abstract: There are two principal specifications for learning analytics interoperability: Caliper, from IMS, and xAPI, from ADL. Around these two specifications are emerging ecosystems of applications and related specifications. The two specifications are introduced, and their structure and main features outlined. The differences in their approach to development are described, with Caliper being developed by a closed consortium, and xAPI in an open process. Efforts to bring the specifications closer together are outlined, and the some reflections
offered on the strategic implications of the differences between the specifications.

Is Privacy a Show-stopper for Learning Analytics? A Review of Current Issues and their Solutions

Date: 22nd April 2016

Authors:
Hendrik Drachsler, Open University, The Netherlands
Wolfgang Greller, Vienna University of Education
David Griffiths, University of Bolton
Tore Hoel, Oslo and Akershus University College of Applied Sciences, Oslo, Norway
Michael Kickmeier-Rust, TU Graz, Austria

Link: Review 6: Is Privacy a Show-stopper for Learning Analytics

Citation: Drachsler, H., Greller, W., Griffiths, D., Hoel, T. Kickmeier-Rust, M. (2016). Is Privacy a Show-stopper for Learning Analytics? A Review of Current Issues and their Solutions. Learning Analytics Review, no. 6, January 2016, ISSN: 2057-7494. http://www.laceproject.eu/learning-analytics-review/privacy-show-stopper/

Short link (for use in Twitter): http://bit.ly/lace-privacy

Abstract: This review paper considers the dangers that might be raised by learning analytics. It then explores the ethical perspectives on privacy and data which are relevant to these dangers. Finally it presents and discusses a number of current proposals from institutions which propose ways of addressing privacy problems in learning analytics.

Towards Learning Analytics Interoperability at the Workplace (LAW Profile)

Date: 12th November 2015

Author:
Fabrizio Cardinali

Link: Review 5:Towards Learning Analytics Interoperability at the Workplace (LAW Profile)

Citation:
Cardinali, F., Towards Learning Analytics Interoperability at the Workplace (LAW Profile), Learning Analytics Review no. 5, November 2015, ISSN: 2057-7494. http://www.laceproject.eu/learning-analytics-review/LAW-interoperability/

Short link (for use in Twitter): http://bit.ly/1PDW3Lu

Abstract:
This paper introduces the needs and possible options for interoperating learning analytics within industrial and corporate scenarios, directly at the workplace. It first introduces general concepts of standardization roadmaps, abstract reference frameworks, application profiles and reference implementations as key steps towards a shared approach to interoperability. It then proposes a scenario-based method to drill down to interoperability needs and options for workplace learning, using a top-down approach. The paper suggests how the community could take action to develop specific profiles and recipes from existing and emerging specifications, with the aim of producing, managing, sharing and distributing standards-based and actionable analytics for improving workplace learning within industrial verticals.

A LACE Manifesto for Learning Analytics in the Workplace (LAW)

Date: 10th August 2015

Authors:
Fabrizio Cardinali, Patrice Chazerand, Susan Flocken, Jasmine Glaser, Gabor Kismihok, Janssen Mateum, Marco Paini, Maren Scheffel, Marieke van der Schaaf, Melissa Vanarwegen

Link: Review 4: The LACE Learning Anlytics in the Workplace (LAW) Manifesto

Citation:
Cardinali, F., Chazerand, P., Flocken, S. Glaser, J., Kismihok, G,. Mateum, J., Paini, M., Scheffel, M., van der Schaaf, M., Vanarwegen, M., The LACE LAW Manifesto, Learning Analytics Review no. 4, July 2015, ISSN: 2057-7494. http://www.laceproject.eu/learning-analytics-review/law-manifesto/

Short link (for use in Twitter): http://bit.ly/lace-review-4

Abstract:
This manifesto for Learning Analytics in the Workplace builds on the results reported in Review 3: Policy recommendations for learning analytics from three stakeholder workshops. The manifesto sets out that the EU should identify and cooperate with all the relevant stakeholders, such as industry leaders, employers, workers, universities, teachers, social partners, trade and teacher unions, with the aim to identify the 21 st century skills, to improve the training of existing workforce maintaining the equilibrium between the needing of industries and society.
Moreover, the EU and national educational authorities, together with companies and social partners, could improve the research and development of IT tools that are able to help leverage a mix of formal and informal learning situations during workforce daily operations. In the final part of the Manifesto, two case studies on the use of
Learning Analytics at the workplace are presented, related to the EU project Watch Me and to SkillawareTM, an IT platform for electronic performance support.

Maren Scheffel

July 22, 2015

Date: 21st July 2015

Authors: Maren Scheffel

Link: Review 2: A Framework of Quality Indicators for Learning Analytics

Citation: Scheffel, M., A Framework of Quality Indicators for Learning Analytics, Learning Analytics Review, no. 2, July 2015, ISSN: 2057-7494. http://www.laceproject.eu/learning-analytics-review/learning-analytics-quality-indicators/

Short link (for use in Twitter): http://bit.ly/lace-review-2

Abstract:

The LACE project has established a first version of a framework of quality indicators for learning analytics, based on a group concept mapping study with experts. The group concept mapping approach is explained, and steps in the framework creation process described, as well as the framework itself. The framework was turned into an applicable tool and evaluated with a group of learning analytics experts. The results of the evaluation revealed several weak points in the first version of the framework, and the experts supplied several suggestions and recommendations on how to improve the framework further.


View Twitter conversations and metrics using [Topsy]