ISSN: 2226-6348
Open access
In recent years, education has experienced a shift in how schools understand learners, teachers and systems through the vast availability of educational data. The information that can be extracted from the data is valuable in reflecting a student’s growth in a holistic manner i.e. academic achievements, inclinations and soft skills. Within the School-Based Assessment (SBA) currently in practice in Malaysia, large amounts of information are generated daily, yet teachers’ readiness to interpret and use data for decision-making remains uncertain. Therefore, this concept paper aims to explore teachers’ readiness for Learning Analytics (LA) in Data-Driven Decision Making (DDDM) in the Malaysian education environment. The methodology used for this concept paper is a thorough analysis of LA through the S.O.A.R. model that measures five elements which are Strengths (S), Opportunities (O), Aspirations (A) and Results (R). The major findings show that the S.O.A.R. model effectively demonstrates LA’s potential by recognizing the strengths and opportunities that already exist in the Malaysian education context, while also outlining possible aspirations and measures of results that can be applied. By examining how the Malaysian education community (i.e. ministry, school and teachers) can leverage their existing capacities, expand future opportunities and aspire toward data-informed professionalism, the S.O.A.R. approach provides a strategic planning lens to understand how Malaysian educators can move from data collection to meaningful application. Findings from this conceptual discussion also highlight the importance of professional development, equitable digital infrastructure and a supportive data culture in realizing Malaysia’s vision of an evidence-based education system aligned with the Sustainable Development Goals (SDG 4). Further research is needed to assess educators’, school leaders’ and ministerial authorities’ readiness to apply LA in DDDM in the Malaysian education context.
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