Towards an educational data literacy framework: enhancing the profiles of instructional designers and e-tutors of online and blended courses with new competences

Abstract

In the era of digitalization of learning and teaching processes, Educational Data Literacy (EDL) is highly valued and is becoming essential. EDL is conceptualized as the ability to collect, manage, analyse, comprehend, interpret, and act upon educational data in an ethical, meaningful, and critical manner. The professionals in the field of digitally supported education, i.e., Instructional Designers (IDs) and e-Tutors (eTUTs) of online and blended courses, need to be ready to inform their decisions with educational data, and face the upcoming data-related challenges; they need to update and enhance their profiles with relevant competences. This paper proposes a framework for EDL competence profiles of IDs/eTUTs and evaluates the proposal with the participation of worldwide professionals (N = 210) with experience in digitally supported education. The evaluation aims at validating the proposal and assesses (a) the current EDL-readiness of IDs/eTUTs; and (b) the extent to which the framework captures and describes the essential EDL competences. The findings indicate that professionals are not EDL-competent yet, but the proposed dimensions and related competences are offering a solid approach to support EDL development.

Supporting teaching staff through data Analytics: A Systematic Review

“…Further, ethical and privacy issues are associated with the use of data from educational context, that implies how personal data is collected and stored as well as how it is analysed and presented to different stakeholders (Slade & Prinsloo, 2013). Accordingly, as advances in data analytics related to teaching practice have been documented in this systematic review, teaching staff are required to further develop their educational data literacy (Papamitsiou et al, 2021), which is the ethically responsible collection, management, analysis, comprehension, interpretation, and application of data from educational contexts.…”

Integrating teacher data literacy with TPACK: A self-report study based on a novel framework for teachers' professional development

“…Because inadequate data literacy knowledge can result in analytical misinterpretations with negative real-world consequences for learners (Ndukwe and Daniel, 2020 ), teachers require the knowledge to design evidence-based instruction and support learning (Mandinach et al, 2015b ). Besides, the concept of data literacy remains relatively undefined (Papamitsiou et al, 2021 ), and further research is needed to understand how TDL requirements are linked to overall teachers' knowledge.…”

“…Moreover, TDL has largely been excluded from accounts of teachers' knowledge development (Reeves and Chiang, 2018 ). Earlier teacher competence frameworks were useful for particular aspects of professional development (e.g., design, ICT, or related abilities), but could rarely accommodate emerging advances in educational data, or its usage (Papamitsiou et al, 2021 ). Marsh ( 2012 ) indicated the need for teachers to integrate data literacy with their professional knowledge.…”

Investigating teaching practices in quantitative and computational Social Sciences: A case study

“…Through an environmental scan and analysis of current Educational Data Literacy Competence Frameworks (EDL-CFs) and courses, Papamitsiou et al (2021) extended these five dimensions into seven data-related core competence pillars for DL: 1) data location, access, and collection; 2) data comprehension; 3) data interpretation and transformation; 4) data use, application, and act on; 5) data analysis; 6) data evaluation and, 7) data management. These pillars generally map with the more holistic view of the data lifecycle phases used more extensively by research and academic libraries to design services and instruction to support data-related work in academic settings.…”