Abstract:
This study recognizes that the provision of Vygotsky’s More Knowledgeable Others (MKOs) within the Zone of Proximal Development of online courses as a unique challenge to all stakeholders. Extending the data-driven decision making culture at the Centre for Distance and Continuing Education of University of Kelaniya to the newly introduced online course English for Communication, the aim of this study is to develop a learning analytics mindset to predict at-risk students enabling timely intervention. Further, future cohorts of the course are provided analytics on student performance thus enabling them to take decisions to improve the course especially to address the necessity for increased MKO availability. Capturing attendance data benefits the need to identify reasons for absenteeism. The instrument was a 100 mark allotting paper which evaluated three of the four skills: Reading, Writing and Speaking. The total population was stratified into 19 centres across provinces. The corpus for analysis (n= 3700) was selected under stratified random sampling procedures from which approximately 200 papers were shortlisted from each centre. Findings illustrate the diversity of Poverty and prosperity indices and Digital denizenship across the provinces have a significant influence on the performance of the population. The % mean marks distribution indicated a strong variation based on the province. Thus this study provides Learning analytics which constructs an information-rich landscape for the functional groups for understanding and optimizing the learning process of the students who offer the course. The findings benefit educational mandates of similar institutions who face the challenge of handling groups which are non-monolithic in proficiency in English and Digital denizenship but who are monolithic in size.
