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Towards an integrated learning analytics framework for quality perceptions in higher education: a 3-tier content, process, engagement model for key performance indicators

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  • Emmanouil Varouchas
  • Miguel-Angel Sicilia
  • Salvador Sánchez-Alonso

Abstract

The integration of quality in Higher Education is multidimensional. Higher Education administration, programs, procedures and evaluation provide the context for the application and diffusion of quality metrics. Our research intends to provide a holistic discussion on Key Performance Indicators (KPIs) related to quality in Higher Education. The analysis of recent literature resulted in the construction of two research tools. The first one is related to a structured agenda for a qualitative interview targeted at Higher Education administrators. The second is related to a quantitative research model that analyses the relations of various quality factors. We provide a mapping of quality perceptions as discussed in previous work and we construct a theoretical model for the affordances of scholars to this perception. The research design includes interviews with academic administrators and teaching staff involved in the creation of academic programmes and courses. The main contribution is an analytic discussion of their perceptions about quality that updates significantly contemporary literature in interesting dimensions. Three-dimensional value space with twenty factors is presented. The outcomes of this research work are used as input for our quantitative study. In fact, a list of 20 quality factors is exploited in three main dimensions of learning analytics namely: content, process and engagement. Key Performance Indicators are highlighted for further investigation.

Suggested Citation

  • Emmanouil Varouchas & Miguel-Angel Sicilia & Salvador Sánchez-Alonso, 2018. "Towards an integrated learning analytics framework for quality perceptions in higher education: a 3-tier content, process, engagement model for key performance indicators," Behaviour and Information Technology, Taylor & Francis Journals, vol. 37(10-11), pages 1129-1141, November.
  • Handle: RePEc:taf:tbitxx:v:37:y:2018:i:10-11:p:1129-1141
    DOI: 10.1080/0144929X.2018.1495765
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