Standardized enriched rubrics to support competeney-assessment through the SCALA methodology and dashboard

Universities have increasingly emphasized competencies as central elements of students´ development. However, the assessment of these competencies is not an easy task. The availability of data that learners generate in computer mediated learning offers great potential to study how learning takes place, and thus, to gather evidences for competency-assessment using enriched rubrics. These are the so-called electronic assessment instruments. Among them, the enriched rubrics arises as a tool to improve the assessment process. However, the lack of data interoperability and the decentralization of those educational applications set out a challenge to exploit trace data. To face these problems we have designed and developed SCALA (Supporting Competency-Assessment through a Learning Analytics approach), an analytics system that integrates usage -how the user interacts with resources- and social -how students and teachers interact among them- trace data to support competency assessment. After presenting the components of SCALA (process, model and platform), we evaluate them presenting six scenarios to know whether it is viable in terms of time, sustainability and quality assurance to normalize the heterogeneous data present in technology-rich learning environments. The results show and confirm the viability of the proposed solution and the possibility to offer real-time feedback to the teachers to assess students´.