Translating Learning into Numbers: A Generic Framework for Learning Analytics

With the increase in available educational data, it is expected that Learning Analytics will become a powerful means to inform and support learners, teachers and their institutions in better understanding and predicting personal learning needs and performance. However, the processes and requirements behind the beneficial application of Learning and Knowledge Analytics as well as the consequences for learning and teaching are still far from being understood. In this paper, we explore the key dimensions of Learning Analytics (LA), the critical problem zones, and some potential dangers to the beneficial exploitation of educational data. We propose and discuss a generic design framework that can act as a useful guide for setting up Learning Analytics services in support of educational practice and learner guidance, in quality assurance, curriculum development, and in improving teacher effectiveness and efficiency. Furthermore, the presented article intends to inform about soft barriers and limitations of Learning Analytics. We identify the required skills and competences that make meaningful use of Learning Analytics data possible to overcome gaps in interpretation literacy among educational stakeholders. We also discuss privacy and ethical issues and suggest ways in which these issues can be addressed through policy guidelines and best practice examples

Managing IMS Learning Design

Commentary on: Chapter 15: How to Integrate Learning Design into Existing Practice. (Janssen & Hermans, 2005) Abstract: Taking IMS Learning Design (LD) beyond the domain of researchers and programmers, this short paper looks at some of the challenges of mainstreaming it within institutional strategies, processes, and cultures. The experiences of embedding EML at the Open University of the Netherlands will be taken as a reference framework for stimulating managerial attitudes, and thoughts. The paper also intends to provoke some discussion and reflection on cost benefit of Learning Design in a higher education environment. Editors: Colin Tattersall and Rob Koper

Dimensions of Mobile Augmented Reality for Learning: A First Inventory

Specht, M., Ternier, S., & Greller, W. (2011). Dimensions of Mobile Augmented Reality for Learning: A First Inventory. Journal of the Research for Educational Technology (RCET), 7(1), 117-127. Spring 2011.This article discusses technological developments and applications of mobile augmented reality (AR) and their application in learning. Augmented reality interaction design patterns are introduced and educational patterns for supporting certain learning objectives with AR approaches are discussed. The article then identifies several dimensions of a user context identified with sensors contained in mobile devices and used for the contextualization of learning experiences. Finally, an AR game concept, “Locatory”, is presented that combines a game logic with collaborative game play and personalized mobile augmented reality visualization

D2.2.1 Evaluation Framework

Drachsler, H., Greller, W., & Stoyanov, S. (2013). D2.2.1 Evaluation Framework. LinkedUp project. Heerlen, The Netherlands.The main purpose of the current deliverable D2.2.1 is to hold the current version of the Evaluation Framework and to operationalise it for the LinkedUp challenge judges into a concrete evaluation instrument. This deliverable is not intended as a very elaborated report rather than a summary of the current version of the Evaluation Framework based on the extensive studies in deliverable D2.1 – Evaluation Methods and Metrics. D2.2.1will be reconsidered in the final report of WP2 to demonstrate the development of the Evaluation Framework during the life cycle of the LinkedUp project. For this purpose it is supportive to have the first version of the Evaluation Framework as a tangible outcome and an own entity as conducted in this deliverable.LinkedU

D8.6 Dissemination, training and exploitation results

Mauerhofer, C., Rajagopal, K., & Greller, W. (2011). D8.6 Dissemination, training and exploitation results. LTfLL-project.Report on sustainability, dissemination and exploitation of the LtfLL projectThe work on this publication has been sponsored by the LTfLL STREP that is funded by the European Commission's 7th Framework Programme. Contract 212578 [http://www.ltfll-project.org

Editorial: Learning Analytics: Implications for Higher Education

29.03.2017 | Wolfgang Greller & Ulrich Hopp

Turning Learning into Numbers – A Learning Analytics Framework

Drachsler, H., & Greller, W. (2011, 30-31 August). Turning Learning into Numbers - A Learning Analytics Framework. Invite talk at SURF Learning Analytics seminar, Utrecht, The Netherlands.Presentation of the Learning Analytics framework at the SURF Learning Analytics seminar 2011. http://www.surf-academy.nl/programma/event/?id=395NeLL

Opening up! How to take full advantage of Open Educational Resources (OER) for Management Education

Terrasse, C., Marinova, B., Greller, W., Bitter-Rijpkema, M., & Schwertel, U. (2012). Opening up! How to take full advantage of Open Educational Resources (OER) for Management Education. In B. Rienties, P. Daly, S. Reeb-Gruber, K. Reid, & P. Van den Bossche, Proceedings of the 19th EDINEB Conference The Role of Business Education in a Chaotic World (pp. 145-149). Haarlem: FEBA ERD Press.General awareness and availability of Open educational resources (OER) have increased in recent years. Some institutions have already started incorporating OER in their strategies. However, compared to other educational fields, OER in Management and Business education have shown rather slow growth. This article discusses the incentives and barriers for the use of OER in Management and Business education. It reviews some useful accomplishments in the field, presents recommendations from various stakeholders and introduces the OpenScout initiative aimed at gathering OER and related tools for Management education

1st International Workshop on Learning Analytics and Linked Data

Drachsler, H., Dietze, S., Greller, W., D'Aquin, M., Jovanovic, J., Pardo, A., Reinhardt, W., & Verbert, K. (2012). 1st International Workshop on Learning Analytics and Linked Data. In S. Dawson, C. Haythornthwaite, S. Buckingham Shum, D. Gasevic, & R. Fergusson (Eds.), LAK '12 Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 9-10). New York, NY, USA: ACMThe main objective of the 1st International Workshop on Learning Analytics and Linked Data (#LALD2012) is to connect the research efforts on Linked Data and Learning Analytics in order to create visionary ideas and foster synergies between both young research fields. Therefore, the workshop will collect, explore, and present datasets, technologies and applications for Technology-Enhanced Learning (TEL) to discuss Learning Analytics approaches that make use of educational data or Linked Data sources. During the workshop, an overview of available educational datasets and related initiatives will be given. The participants have the opportunity to present their own research with respect to educational datasets, technologies and applications and discuss major challenges to collect, reuse, and share these datasets