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There is a high potential for mobile learning and support applications in the medical domain. In a recent research initiative we developed together with the School of Medicine at the University College Cork, Ireland a smartphone app to train writing of medical discharge letters that are crucial for handovers (transferring information from one caregiver to another).

The so-called CLAS app is based on the “Cork Letter-Writing Assessment Scale” (created by Bridget Maher) and benefits from synergies between our different medical research projects like Handover, EMuRgency and BioApp.

Handover of patient information is a time of particular risk and it is important that accurate, reliable and relevant information is clearly communicated between one caregiver to another. The World Health Organization (WHO) lists accurate handovers as one of its High 5 Patient Safety initiatives (Joint Commission on Accreditation of Healthcare Organizations, 2011). Improperly conducted handovers lead to wrong treatment, delays in medical diagnosis, life threatening adverse events, patient complaints, medical litigation, increased health care expenditure, increased hospital length of stay and a range of other effects that impact on the health system.

The CLAS mobile app is designed to standardise and improve handover communication between hospital and General Practice. Mobile applications such as CLAS offer exciting opportunities for improving patient safety and minimising medical error at handover and are just the tip of the iceberg with regard to harnessing the vast potential of mobile communications and how medical professionals interact with each other and more importantly, how they interact with the patients. The CLAS mobile application is currently the basic of two ongoing research projects.

1. Assessment of the quality of 200 hospital discharge letters using the CLAS scale.
2. Assessment of the effect of the CLAS intervention on the letter-writing skills of 80 fourth year medical students.

Next to the medical research, we aim to further improve the CLAS app with typical mobile application features such as taking into account sensor information from the mobile device such as GPS coordinates and audio recordings. In addition, we want to make the CLAS app more interactive by enabling the end users (doctors and patients) to synchronise handover information, thus improving the quality of information transfer at handover.

At the upcoming mLearn conference in October in Helsinki we will present further details about the CLAS app in the context of a research paper.

Learning Analytics is a hot research topic at the moment and I’m curious what impact it will have on the education systems on the long term. However, at the moment it is of high importance on all research agendas. It is even an explicit research topic within the next EU FP7 TEL call in January 2013. At CELSTEC we have recently won two new EU projects that are directly supporting our Learning Analytics research efforts:

Open Discovery Space (Started 1st of April 2012)	LinkedUp (Start’s 1st of November 2012)

Both projects addressing the main research challenges we identified during the dataTEL project. Based on those we have identified 6 main research objectives for the upcoming years:

1. Collecting, sharing and open access to educational datasets
2. Evaluation of data-driven applications
3. Legal aspects (Ownership, Privacy, ethics)
4. Visualizations of data
5. Personalization and Recommender Systems
6. Awareness support and reflection

Regarding research objective 1 – Educational data:

Open Discovery Space (ODS) and LinkedUP will make vast amounts of educational data available for end users and for data driven research. The Open Discovery Space project will be based on the ARIADNE Foundation infrastructure that has been used to already deploy an initial version of the resources at the portal that provide access to a critical mass of about 1.000.000 content resources. This existing critical mass of eLearning resources will be expanded over the runtime of the project up to ~1,550,000 resources in total. It is expected to be connected to around 15 educational portals of regional, national or thematic coverage. Besides providing the educational resources ODS will create technology to share and collect also social data about the educational resources (ratings, tags and annotations) and make them available as Linked Data. With these objectives ODS contributes to the research objectives of the Learning Analytics and Linked Data workshop we organized at the LAK12 conference.

LinkedUp also aims to make more educational datasets publicly accessible. It will therefore create a pool of existing educational datasets and organize various support and trainings activities around this data pool to stimulate the development of new and innovative data driven tools for Technology-Enhanced Learning and Learning Analytics.

LinkedUp will therefore strongly follow the Linked Data approach which has been applied successfully in a wide area of domains to expose datasets from a large variety of sources, leading to a globally distributed Web cloud of over 31 billion distinct statements. The following table provides an overview of the currently available datasets in the LOD cloud (source: http://lod-cloud.net/state).

Next to Open Educational Resources and Linked Data will LinkedUp also consider publicly accessible data from data-driven companies such as Open Calais Reuter or Mendeley. These companies provide access to their data over API’s that can be used to develop innovative data products within the LinkedUp competition.

Regarding research objective 2 – Evaluation of data applications:

There is a pressing need in Learning Analytics to make the effects of different data applications on learning and the stakeholders comparable to identify best practice examples. Until now there is no common knowledge which algorithm works better than another with a certain user model in a specific learning settings. LinkedUp directly address this challenge by developing an evaluation framework that can be applied to evaluated data –driven applications. The evaluation framework will be one of the major outcomes of the project. It will be developed together with a board of 30 experts in the field through the Group Concept Mapping approach.

Regarding research objective 3 – Legal aspects:

In this context both projects have to come up with solutions that enable the use of educational data for data support applications. Both projects will therefore mainly focus on the creative commons license model. All data sets for which this is appropriate shall be published on the project’s web site under a Creative Commons licence (http://creativecommons.org/) or another appropriate license. In addition we want to explore related initiatives like the Creative Commons Learning Resource Metadata Initiative (LRMI) that aims to merge different competing initiatives in the area of OER description and at producing a usable and well-defined RDF schema for Learning Resource description (http://wiki.creativecommons.org/LRMI). Regarding, privacy and ethics both projects will review privacy requirements and concerns in each participating country in order to develop a suitable IPR & licensing agreement for the data pools.

Research objectives 4-6 – Visualizations, Personalization, and Awareness support:

These research objectives will also be addressed by both projects at a later stage. ODS addresses all three research objectives by providing innovative navigation and visualizations tools to explore the vast amount of collected data within the ODS portal in a personalized way.  We will investigate how to combine visualization and social navigation to increase the satisfaction of users when searching for resources as well as explaining the rationale for the various selections or recommendations. Within LinkedUp we will support various projects that focus on these research objectives within the LinkedUp competition. We will organize three data competitions and support the participants with suitable datasets, technology support workshops, and provide substantial funding based on the assessment of the tools of the participating teams with the evaluation framework.

Looking forward to these exciting research activities!