Why IIMs want stu­dent di­ver­sity

MIX N MATCH En­cour­ag­ing stu­dents from other back­grounds, be­sides en­gi­neer­ing, will help break ho­mo­gene­ity at In­dian In­sti­tutes of Man­age­ment, say ex­perts

Hindustan Times (Delhi) - HT Education - - Front Page - Gauri Kohli

Engi­neers have dom­i­nated the class­rooms at In­dian In­sti­tutes of Man­age­ment (IIMs) for sev­eral years. Now, the fo­cus is shift­ing to­wards boost­ing aca­demic and gen­der di­ver­sity by al­ter­ing in­take rules. Ac­cord­ing to of­fi­cials at sev­eral IIMs, get­ting can­di­dates from ar­eas other than en­gi­neer­ing is must for break­ing the ho­mo­gene­ity on cam­pus. They also say that since the ped­a­gogy in­volves dis­cus­sion-based meth­ods, it is a strong rea­son to boost aca­demic di­ver­sity as stu­dents with dif­fer­ent per­spec­tives will make learn­ing more in­clu­sive. Be­sides engi­neers, most can­di­dates are from com­merce, arts, medicine/den­tistry, phar­macy/phar­ma­col­ogy etc. NON-ENGI­NEERS ON THE RISE Take I I M Ahmed­abad, f or in­stance. Non-en­gi­neer­ing stu­dents in the PGP batch have gone up from 5% in 2011 to 20% this year. While there were 20 nonengi­neers in the 2011-13 batch, the 2016-18 batch com­prises 80 nonengi­neers. At IIM Ban­ga­lore, the 2016-18 batch in­cludes 11% nonengi­neers, while the 2015-17 batch has more than 13% stu­dents who are not engi­neers. At IIM Trichy, non-engi­neers con­sist of 24% of the batch for the first year and 7% for the fi­nal year. IIM Kozhikode has 10.5% non-engi­neers for the PGP batch ad­mit­ted in 2016. Non­techies at IIM Ranchi have also gone up. While these were more than11% of the 2014-16 PGP­batch, this in­creased to 17% in the 201618 batch. WHY PRO­MOTE DI­VER­SITY Ac­cord­ing to Prof Anindya Sen, di­rec­tor in- charge, IIM Ranchi, “Engi­neers tend to think that there are al­ways pre­cise, me­chan­i­cal so­lu­tions to all prob­lems. How­ever, man­age­ment prob­lems which usu­ally have to do with hu­man be­ings, need a more flex­i­ble ap­proach. More­over, male stu­dents some­times lack in cer­tain soft qual­i­ties which are es­sen­tial for a har­mo­nious work­place. Hence the need for di­ver­si­fi­ca­tion - with re­spect to both aca­demic di­ver­sity and gen­der di­ver­sity.” Cit­ing an ex­am­ple of IIM Kozhikode, Prof Sony Thomas, chair­per­son (ad­mis­sions), says, “The in­sti­in­sti tute has been mak­ing de­lib­er­ate ef­forts to en­sure di­ver­sity in the class­room both aca­demic and gen­der. We give 5% weigh­tage to both non-en­gi­neer­ing stu­dents as well as women can­di­dates. How­ever, a stu­dent will not get both. For ex­am­ple, a non-en­gi­neer­ing woman ap­pli­cant will get only 5% weigh­tage. Sim­i­larly, a non-en­gi­neer­ing male ap­pli­cant will also get 5% weigh­tage. Ac­tu­ally, it is a balanc­ing act, since ma­jor pro­por­tion of fe­male ap­pli­cants are engi­neers too. For the PGP batch 2016, 89.5% are engi­neers and 26% are women.”

IIM Ahmed­abad en­deav­ours to recog­nise ex­cep­tional per­form­ers in terms of their pre­vi­ous aca­demic records, co-cur­ric­u­lar and ex­tra-cur­ric­u­lar achieve­ments, work ex­pe­ri­ence, as well as their per­for­mance in CAT across di­verse aca­demic back­grounds. “In a dis­cus­sion-based learn­ing en­vi­ron­ment, such as that of IIMA, di­ver­sity of par­tic­i­pants’ back- grounds­grounds and in­clu­siv­ity of the in­sti­tu­tion’s cul­ture con­trib­ute sig­nif­i­cantly to a pos­i­tive learn­ing en­vi­ron­ment. Putting weight on the fac­tors be­yond per­for­mance in CAT helps the in­sti­tute have a more di­verse and in­clu­sive stu­dent pool,” says a spokesper­son from the PGP ad­mis­sions com­mit­tee.

This need for di­ver­sity is also felt by the newer IIMs. As Prof Ab­hishek Totawar, chair­per­son place­ment and ex­ter­nal re­la­tions, IIM Trichy, says, “Di­ver­sity, whether aca­demic or gen­der, is im­por­tant for man­age­ment ed­u­ca­tion. This is be­cause most sub­jects are taught us­ing the case study method, for which stu­dents from dif­fer­ent aca­demic back­grounds are pre­ferred. Be­sides engi­neers who have a good back­ground in quan­ti­ta­tive anal­y­sis, we have non-engi­neers too with a strong com­mand over quant.”


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