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This study determines how educational supporting services and mentoring programs can be improved based on the users’ preferences and perception by benefiting from a data-driven design model and process innovation. To this end, the study proposed a data-driven support and decision model (DSDM) that uses a mixed methodology (qualitative and quantitative) to analyze data collected from different writing centers and coaching programs who responded to an online survey that comprised of both quantitative and qualitative items. Quantitatively, we applied a Linear and Mixed-effect logistic regression analysis to investigate the critical factors that motivate the users in seeking educational support services. And, qualitatively apply the Text mining technique to analyze the opinions given by the participants in order to establish its level of impact towards the several services offered by the coaching programs. Theoretically, the proposed research model is grounded on integration of a data-structure approach that builds on the descriptive decision theory; which studies the rationality of the decisions that users are disposed to make by means of the statistical method and textual data quantification. In turn, the method allowed us to capture the influential factors and state-of-the-art in faculties-students development and coaching programs, and to provide solutions to the ever-increasing need to improve educational supporting services and quality in a competitive and rapidly changing educational environment or market that have not been done before. Although there may be a considerable variation between the different categories of educational services offered by the coaching centers. The results of our study shows that the users hold services such as “tutoring” as a major factor that influences their visit and recommendations to the writing centers or coaching programs. Moreover, most users of the coaching programs are motivated by the need to gain “support” with their educational/academic performance and productivity.
Okoye et al. (Fri,) studied this question.