University of Goettingen (GERMANY)
About this paper:
Appears in: ICERI2015 Proceedings
Publication year: 2015
Pages: 5609-5619
ISBN: 978-84-608-2657-6
ISSN: 2340-1095
Conference name: 8th International Conference of Education, Research and Innovation
Dates: 18-20 November, 2015
Location: Seville, Spain
As a consequence of the demographic change companies are facing challenges to keep the expertise and practical knowledge of its employees within the company. The knowledge of experienced employees has to be transferred to other employees before retirement. In addition to that, constant technological improvements make continuous learning necessary. At the same time the need for small learning units arises because of increasing knowledge- and technology-intensive activities. With small learning units which can be used on mobile or wearable devices, the employees are able to learn directly at the workplace. Therefore, companies should offer possibilities of workplace learning and provide flexible, collaborative training opportunities for employees.

New technologies, like mobile devices and wearable computers (wearables), can help to support work integrated learning or learning in the workplace. Smartphones, tablets, smartwatches, and smart glasses allow new learning situations where learners can access digital learning units independent of time and place. Using these technologies, employees are able to extend their knowledge at the same time and at their current location when they require it. By supporting various forms of learning, both technologies have great potentials to combine working and learning. For example by enabling situated learning on the job, mobile and wearable devices are able to enhance workplace learning. This can be achieved by the technical capabilities of the devices (e.g. specific learning content depending on the learner’s location).

The main goal of this paper is to provide assistance in technology selection for learning with mobile and wearable devices in enterprises based on identified application scenarios. Therefore, we will first focus on developing a classification framework that uses the learning context for classification. Based on this classification, application scenarios will be described for each of these categories. Following this, the use of mobile devices and wearables in the identified application scenarios will be assessed.

The results of this paper – the identified application scenarios and the suitability of the technologies – can be used as a basis for further research and for practitioners as assistance in technology selection for learning in enterprises.
Mobile Learning, Wearable Learning, Enterprises, Workplace Learning, Learning on the Job.