Evaluation is an unavoidable feature in any teaching or learning scenario. The evaluation strategy of students differs widely throughout the world. Further, most of the institutes do not use any objective technique to assess the teaching performance of a teacher. The present paper defines performance metrics both for student and teacher evaluation and also discusses the methodology for calculating relevant metrics. In a decision‑making scenario, these metrics may help in providing enough insight into the assimilation capability of students and teaching capability of teachers. Once measured properly for an adequate length of time, these metrics can also be customised to provide other useful information like utility of a course modification, institutional performance etc. The system has been tested for analysing four courses in a premier engineering institute and the outcome found to be encouraging.

An abundance of research, by educational researchers and scholars of teaching and learning alike, can be found on the use of ICT to plan design and deliver learning activities and assessment activities. The first steps of the instructional design process are covered quite thoroughly by this. However, the use of ICT and quantitative methods to close the instructional design cycle by supporting sustainable decision making with respect to the evaluation of the effectiveness of teaching processes hold much unleashed potential. In this paper a business intelligence approach is followed in an attempt to take advantage ICT to enable the evaluation of the effectiveness of the process of facilitating learning. The focus is on micro‑level decision support based on data drawn from the Learning Management System (LMS). Three quantifiable measures of online behaviour and three quantifiable measures of teaching effectiveness are identified from literature to arrive at a 3x3 matrix according to which 9 measures of e‑teaching effectiveness can be derived by means of pair‑wise correlation. The value and significance of information are increased within context of other information. In this paper it is shown how the value of LMS tracking data increases within context of data from other modules or others years and that useful information is created when this tracking data is correlated with measures of teaching effectives such as results, learning styles and student satisfaction. This information context can only be created when a deliberate business intelligence approach if followed. In this paper a data warehouse model is proposed to accomplish exactly this.