| |9 May 2019HIGHERReviewTCS, have been saying for a while that our graduates are not ready for the job when they graduate. They call this ca-pability as employability. It is an impli-cation of the same skill. The graduate schools and industry spend their con-siderable resources, in terms of time and money, in imparting the ability to the freshly hired graduates.What is the reason behind our students lacking this skill? Of course, the USA has older institutes and have more resources. But as far as comput-er science programs in our elite insti-tutes are concerned, these are not the pressing reasons. Is it because our syl-labus is outdated? In most of the cases, it is NOT, indeed not at our elite insti-tutes. Besides the foundational com-puter science courses such as Operat-ing Systems, Computer Networks, and Data Structures, we are also teaching the specialized ones such as Machine Learning, Artificial Intelligence, IoT, etc. at our institutes. Then, how do we improve the quality of our students? Can we do something in our teaching and evaluating?When we teach the core fundamen-tals in isolation, without connecting those to practical or real-world scenar-ios, the students cannot make a mental model of how to map a given situation into an abstract question for which we have a solution. From a teacher's per-spective, this may be either trivial or not important, and hence neglected. In effect, the teachers end up putting more emphasis on detailing the solution in the abstract. Even the assignments and examinations evaluate students on their knowledge of solutions. Instead, the teacher must take practical scenarios to illustrate (a) how we can map those sce-narios to an abstract problem and (b) how we can summon our knowledge of the fundamentals to devise a solu-tion. The effect will be amplified if the teacher takes scenarios from the day -to-day lives of the students. Yes, this requires imagination and awareness of current affairs on the part of teachers. But indeed, it takes fewer efforts com-pared to creating more courses.If you look at the courses in the American institutes, even their online courses, there is a significant emphasis on the application of the learned con-cepts. For example, the Operating Sys-tem course at Stanford University asks students to implement scheduling algo-rithms to a working operating system. Andrew Ng's based a quiz for his Deep Learning course on Coursera on the data collected in a real production ap-plication of detecting images of birds. When students acquire the skill of ap-plying concepts to problems, it helps them to turn their assimilated knowl-edge into power. Although we take ex-amples of Computer Science, the mes-sage applies to all the disciplines. Our institutes need to encourage teaching of the problem-solving skill, even if it means cutting down a bit on the num-ber of concepts taught in our courses. After all, what is the use of knowing plenty of theories but not knowing which one to employ to solve a given problem? With this skill, not only our industry will get an employable work-force but our higher degree programs will also get better researchers.
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