Smart Learning Analytics and Frequent Formative Assessments to Improve Student Retention

摘要

In today's world of competitive educational institutions, it is imperative that the final product, the students, are of the optimal quality as required by the professional industry. Conventionally, the progress and quality of the students were only assessed in end-of-term results, or at a few standpoints, which neglected the possibility of improving the weak areas. This shortcoming of the conventional educational system resulted in a high rejection/dropout of the potentially capable students. In this work, the authors propose adaptation of a novel content delivery, formative assessment, smart analytics and instant feedback mechanism pipelined into the educational process. The proposed model can potentially circumvent the pitfalls and significantly reduce the errors of assessment, grading, and the delivery of feedback. The proposed approach concurrently assures the quality of students at each formative step within a semester's time, thus improving the quality of intake of the subsequent standpoint. The approach has been evaluated on one subject, Functional English, within a four year Computer Science Baccalaureate program. The results of the outcomes can be plausibly extended and applied onto other educational contexts.