How stakeholders’ data literacy contributes to student success in higher education: a goal-oriented analysis

Abstract

Student success is becoming a shared vision for quality in higher education. Majority data in higher education have not been transformed into actionable insights for quality enhancement. Data are dispersed among stakeholders, and stakeholders’ data literacy influences the effectiveness of using data for student success. However, existing studies mainly focus on students’ data literacy; the analysis of other stakeholders’ data literacy for student success is still few. This study aims to explore how stakeholders’ data literacy contributes to student success in a holistic view. The salience model is used to identify core stakeholders. The goal-modeling language iStar is used to present how stakeholders contribute to student success. A competencies matrix of data literacy is used to discuss the specific data literacy competencies that stakeholders should focus on promoting student success. A survey is conducted to validate the goal-oriented analysis and the discussions on specific competencies of data literacy for stakeholders. The goal-oriented analysis presents the complexity of interactions and dependencies among stakeholders for student success. This study helps to raise stakeholders to be aware of the importance of their data literacy and the necessity of collaboration on exploiting vast available data for student success.

Data practices in quality evaluation and assessment: Two universities at a glance

“…Our study supports the idea that there are diversified and concurrent data practices as the resultant of the context of increasing attention on data in our societies. Nonetheless, we brought some evidence on the uniqueness of each institutional contexts, and the fragmentation, to some extent, of the data approaches in each institutional context, a fact which could entail difficulties in planning institutional strategies and staff development (Yang & Li, 2020). Our study can be placed at a preliminary level of institutional analysis.…”

“…Therefore, each university could benefit from the exploration of their ongoing practices, discourses and myths relating data, aiming at a contextualised understanding of datafication and data usage (Selwyn & Gašević, 2020). Such an endeavour could go hand in hand with the reflection around the quality of higher education provision (Yang & Li, 2020). Nevertheless, as unique expression of organisational cultures, data practices might vary from one university to other.…”

“…Such an endeavour could go hand in hand with the reflection around the quality of higher education provision (Yang & Li, 2020). Nevertheless, as unique expression of organisational cultures, data practices might vary from one university to other.…”

Forschungsdatenmanagement in der Informatik

“…Inzwischen gibt es verschiedene Bestrebungen, Data Literacy verstärkt in die universitäre Lehre einzubringen, da Data Literacy-Fähigkeiten als wichtige Kompetenzen des 21. Jahrhunderts betrachtet werden (Yang & Li, 2020). Es ist besonders ratsam, eine curriculare Verankerung von FDM zu forcieren, damit die Inhalte immer disziplin-und anwendungsbezogen sind.…”

Sustaining Academic Atmospheres During Covid-19 Pandemic: Lecturers’ and Students’ Controversial Voices

“…As for students, they are expected to prepare themselves physically and mentally. Stakeholders ensure that both administrative and financial aids contribute to the success of the intake semester or academic year [3] However, academic plans are not undertaken fluently as influenced by many factors such Covid-19 pandemic. In Indonesia, the pandemic began in March 2020 and has affected many aspects including teaching and learning process in higher institution.…”