In this work we focussed on assessment and quantification of students' prior knowledge at the start of their classes and the learning and teaching feedback given by them after their classes. Using questionnaires, we collected data on prior-knowledge/Student Learning Abilities -- SLAs and, students' performance/Learning Outcomes -- LOs. Our analysis shows that typically, in any classroom the SLAs follow a non-linear trend. This pattern, identified in group learning, requires proportionally distributed intervention by staff, with more support to those in need of help with learning. We show that the above approach, underpinned by an application of Multiple Intelligences and e-learning facilities, supports weaker students and helps them to achieve higher pass percentages and better LOs. This innovation in terms of evidence-based identification of need for support and selective intervention helps in optimal use of staff time and effort as compared to a one-method-fits all approach to learner development and academic achievement.