Abstract:

Heterogeneity of students is a challenge in many learning environments. However, heterogeneity presents many dimensions such as gender, racial groups, cultural background and skills. In this paper, we focus on the skills dimension to deal with the problem of different backgrounds within students enrolled in MBA courses. More precisely, we consider two groups of students: 1) those with enough background of quantitative abilities such as engineers and other students with mathematical training; and 2) those with not enough mathematical background. Since an MBA can be considered general or non-specialized training, both groups of students are likely to share classrooms in most training centers.

Most MBA degrees are addressed to recent graduates, but also to people with some professional experience. We can reasonably assume that all of them want to develop a professional career in the field of business management. To this end, MBA contents include topics that are present in many business’ daily work such as Strategic Management, Economics, Finance and Accounting, Marketing, Human Resources Management, Entrepreneurship and Operations Management. Some of these subjects require the use of quantitative methods for decision-making. Different backgrounds pose a challenge to teachers of subjects with quantitative techniques as a central part of the table of contents. Mathematical models are frequently more abstract than those concepts than can be expressed in conventional language. Indeed, teachers can explain Operations Management contents in English, Spanish, but also in mathematical language. Engineers (in our context, maths lovers) with enough mathematical training will probably get bored if the level of this language is too low. On the contrary, Lawyers (in our context, maths haters) and other students without technical background will find this language too difficult to understand. Clearly, this issue is not new and different authors have proposed alternative ways to solve the problem of heterogeneity of skills. Gamification, levelling seminars or individualized teaching, the use of electronic contents, and focusing on the learning process are some examples. Summarizing, we can find alternative ways of the combined process of teaching-learning that can deal with the heterogeneity of skills problem. However, there is a lack of a methodology to obtain which percentage of teaching and learning should be allocated to each of these alternative ways.

To solve this problem, we here propose a set of logical steps to derive the optimal mix of teaching methods from a multiobjective perspective and according to the teacher preferences. More precisely, we follow the approach of evaluating teaching activities in terms of two interesting attributes, namely, Quantitative Intensity (QI) and Concept Amplitude (CA). Teaching methods with a high QI are those typical of engineering students such as mathematical modelling, formal reasoning, problem solving, algorithms description. On the other hand, teaching methods with a large CA are those typical of law students such as wide descriptions using common language, cases of study, historical reviews, definitions, classifications, quiz games, video lectures and possibly many others.

Keywords:

Heterogeneity, quantitative skills, teaching methods, engineering concepts.