DIGITAL LIBRARY
A MULTIDIMENSIONAL SCALING TO ASSESMENT INNOVATION COMPETENCY
1 Universitat Politècnica de València (SPAIN)
2 Universitat Politècnica de València, Centre for Quality and Change Management (SPAIN)
3 Universitat Politécnica de Valencia, ROGLE-DOE (SPAIN)
About this paper:
Appears in: EDULEARN17 Proceedings
Publication year: 2017
Pages: 8617-8622
ISBN: 978-84-697-3777-4
ISSN: 2340-1117
doi: 10.21125/edulearn.2017.0610
Conference name: 9th International Conference on Education and New Learning Technologies
Dates: 3-5 July, 2017
Location: Barcelona, Spain
Abstract:
Currently, one of the prerequisites required by companies is that professionals improve their qualifications in soft skills. The innovation competency appears as a source of competitive advantage in the business world. Innovation has become a relevant factor for the achievement of a competitive suitable advantage of companies in the market. However, it is not easy to define innovation, since it implies the acquisition of different capabilities and skills, such as, creativity, critical thinking, initiative, independent thinking, team work, networking, etc. The main purpose of this paper is to apply a e Nonmetric Multidimensional Scaling (MDS) (PROXSCAL) to identify key dimensions underlying respondents’ students, to detect the most relevant skills to be included in assessment innovation competency as an alternative method to validate questionnaires. We used the INCODE-ICB-v6 questionnaire as the measurement instrument of innovation which measures the innovation construct with a series of 25 items, grouped into three categories: individual, teamwork and network. Responses were given a score of between 1 and 5 (1= major improvement needed; 5= excellent). The items included in the INCODE-ICB-v6 questionnaire to measure each of the competencies was defined in previous studies. The different items were presented in a random ordered list, not with the structure expected in each category. We applied a MDS, as a kind of concept mapping analysis with a sample of 918 students of a Massive Online Open Courses (MOOC) from a Spanish public university in the academic year 2014-2015, to perform an affinity diagram. This process consists of two stages. First, the participants, working individually, group the items in the category they think is best, to infer the underlying dimensions of the questionnaire according to a series of similarity or dissimilarity provided by students about the items. Then, we represent items in a perceptual map to appreciate the spatial representation of data to clarify underlying relationships. MDS analyses were carried out with two databases, one for four categories model and second for up to ten categories model. The results of multidimensional scaling confirm the structure of these three components in both models. Results shown that the internal consistency of theorist components of innovation is high in both models, for four and up to ten categories. In order to make calculations easier and faster, a routine in Visual Basic for Applications (VBA) was programmed.
Keywords:
Innovation competency, Multivariate analysis, non-metric multidimensional scaling, INCODE questionnaire.