In Search of Excellence

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Pursuit of excellence is an integral part of Academics. I had written an article in Times Of India editorial page a few years ago. I am giving that article below. Many years have passed since that article and during this period much more attention has been given to (lack of?) excellence in our country – largely due to the absence of Indian Institutions in the global ranking of universities. There is a stronger desire to have some Institutions globally ranked and respected. As global ranking is largely based on research excellence and impact, there is a need to better understand the reasons behind why excellence often eludes our institutions. I am writing a followup note on this topic – in the process I found that the article I wrote a few years ago is still very relevant. Hence am sharing it here.

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Think of the names of the best-known scientists in India, and examine their resumes. Inevitably you find that, besides being great scientists and researchers, they were heads, directors or chairpersons of various committees, advisers to ministers/the prime minister, etc. It will be very hard to find a well-known scientist in India who did not become an administrator particularly in the past few decades. (In an exercise we did, a few PhD students were asked to list the Indian scientists whose names they knew and then check their CVs all 21 scientists listed had held significant administrative positions.)

Now let us look at the best researchers in the scientifically advanced countries. Of the 27 Nobel laureates in physics of the last 10 years, only seven hold any major administrative post.

This reflects a basic difference in how science and scientists are viewed in our society and how they view themselves, as compared to the situation in the scientifically advanced countries. We still remain a very hierarchy and title conscious society, where power and title are regarded more important goals than anything else (except money perhaps). When a scientist does good work and is recognised globally, the best way the government and the civic structures seem to reward the person is by giving an administrative title and role, so he becomes a ‘big administrator’ who will rub shoulders with the ‘powers-that-be’. Not only is the thinking of administrators and government like this, this is the nature of thinking of scientists and academics also after an individual has achieved some name in science, he starts looking for ‘elevation’ as an administrator.

We do not seem to have reached a state of evolution in our scientific community where science and research can be ends in themselves, and not a means to a ‘higher’ end. To be fair, a good scientist or a researcher starts with intentions of doing great science/research. However, slowly after a decade or two, often he starts facing the ‘what next’ question. Rather than striving harder to reach a higher level in science and research, either due to complacency which over the years sets in as it is systematically encouraged, or due to lack of recognition or visibility as compared to administrators, or some other reason, remaining a scientist no longer seems sufficient. The senior scientist then starts aspiring for administrative positions with power.

This situation is not likely to change unless there is pride and satisfaction in being an academic or a researcher, and unless there are icons in society that are academics and researchers. In the last two decades, people like founders of companies such as Infosys have created new icons. This has put entrepreneurs and business people on a high pedestal you can see that they no longer feel ‘below’ the bureaucracy but treat them, and are treated as, equal (or sometimes even superior as they are rich).

Similar icons need to be created in academics scientists who are held in high esteem and are ‘stars’ not for the position they hold but for the science and academics they did and contributions they made to the furthering of science, research and education. And the way the government should support them is by giving them labs and grants, awards, monetary rewards, naming buildings, roads and the like after them, promoting them in national and global forums as icons, etc, and not merely by giving them administrative posts.

The management of scientific and academic institutions also needs to change. They have to imbibe the value system where an administrator feels pride in what scientists and academics have done rather than what he as an individual has achieved. And instead of feeling dwarfed by the fame of a scientist working ‘under’ him, an administrator ought to see that as a sign of his doing a good job that should be rewarded.

Unless we reach a stage where the stars are the scientists, and the administrators are understood to be good only to the extent they provide support to create such stars, we should not hope for much excellence. Excellence in research cannot be achieved by half-hearted commitment to the pursuit of knowledge. We must develop a value system where a star scientist wishes to remain a scientist and is respected and admired for the science and research he does.

It should, however, be added that a scientific establishment, if it is to achieve any levels of excellence, must be headed by a scientist/academic of decent calibre who understands excellence and what is needed for it. Putting an average scientist/academic or a bureaucrat in charge can be a recipe for disaster, as such a person is likely to surround himself with average people (“An A hires an A, but a B hires a C”). But the administrator must support the value system in which he is mostly a facilitator for getting good science and research done. The limelight rightfully belongs to the brilliant scientists and researchers doing excellent work.

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Introducing Engineering Design in First Year of a BTech Program

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The traditional model of engineering education for decades has been that in the first year physics, chemistry, and maths are taught as foundation courses. Then courses on different foundational areas of the discipline and engineering are taught. Only after that a student can try to practice engineering. The overall model has been to teach the foundations in the initial years, and only in final year the students may do full engineering projects in which they may build some systems. (Actually, in most cases, unfortunately even in final years decent engineering projects are not done.)

This model has been under challenge for some time, particularly in the west, as it does not allow students to experience the excitement of engineering, which comes from building useful systems that work, till very late. To address this, many institutions across the world have introduced project-based courses early to provide students some experience of building systems.

In IIIT-Delhi, very early we introduced two courses in the first year whose focus is on “hands on experience”. In the first semester, students do a course called “System Management” in which they work with laptops and mobile phones and their components, and learn what they can do with these machines, how they can manage them well, explore internals by opening them and seeing inside, etc.

In the second semester (by when they have learned programming as well as electronics in their first semester) we introduced an Intro to Engineering Design (IED) course, whose basic goal was to design a working physical system that included hardware and software (so software only projects are not permitted) to solve some problem. In IED the focus is on project – the lectures are to support the projects. So, the lectures provide an overview of the basic components that are widely used in such projects – a cheap but versatile platform like RasPI or Arduino, common sensors for vision, motion, proximity, etc, and some actuators like stepper motors, etc. They also learn a bit about workshop and tools.

Students form teams and start thinking about the project from the start of the semester. Each project team is given a budget to buy the components for their project – this exposes them to the process of buying components and markets, as well as about the basic engineering principle of cost control and delivering the project within budget. The completed projects are then demoed to all in an open house one day at the end of the semester.

This year also I visited the demos and interacted with at least 25 project groups. The course instructor was Alexander Fell, who is himself a fine system builder. I was amazed and highly impressed at the sophistication of the projects students had executed. Many of them were better than the final year projects in many engineering colleges and some of them, with extension and further development, could even be the final year project in IIIT-Delhi or an IIT.

To give a sense of the variety and complexity of projects undertaken, I am giving below a brief description of a few projects (I will keep adding to this list). It is worth remembering that these projects were executed by 2nd semester students (i.e. they have been out of class XII only for a few months), who were doing 4 other courses (at least two of them have their own programming/ lab assignments.)

These type of courses emphasize the fact that engineering is about solving problems of people by building systems and solutions using science, mathematics, and theories. Engineering is clearly not about theoretical understanding only in which problems are only solved on paper and tested in exams, or simple labs with defined experiments that are being repeated by students year after year.

Unfortunately, this is what engineering education in the country has degenerated to – most engineering institutions teach concepts (and that too not too well) with almost no exposure to actual engineering – mostly because the faculty does not have the necessary skills to guide such projects. As a result, we find engineering graduates who don’t have any real engineering or problem solving skills and are therefore not employable. And so a large number of these graduates proceed to do MBA where engineering skills are not important, and only conceptual understanding is needed to solve the problems in entrance tests.

This lacuna in engineering education is also contributing to the immature innovation-led ecosystem in our country to generate businesses offering new products and solutions. It has also led to an underdeveloped engineering industry. Thankfully, one is now seeing some examples of innovation resulting from deep understanding of the problem and technology and delivering solutions that can work to solve problems and scale – these are often led by teams that excel in engineering capabilities. Thankfully also, some leading engineering institutions including some IITs (e.g. IIT Delhi) are introducing project based courses early in their curriculum. These bode well for the future for engineering in the country.

 

Brief Description of Some of the Projects 

  • GardenBot. This bot is essentially a mobile cart with water, mechanical arm, camera, ultrasonic sensor, etc. It moves freely (choses the direction randomly), detects an object and if the object is a plant (done using image recognition library), checks the moisture of the pot, and adds water to the pot plant if the moisture content of the soil is low. It is integrated with the internet to check whether it has rained in the past few days to make a smarter decision for watering. As it moves autonomously, it can water all the pots in a garden – essentially doing the job of a smart gardner.
    • Components. Moisture Sensor, Ultrasonic Sensor, Webcam, five DC motors (four for wheels and one for water pump), One servo motor (for arm), H-Bridge for controlling DC motor
    • Platform and Code. Raspberry Pi, with about 500 LOC of Python.
    • Team. Akshat Singh, Apoorv Khattar, Harshit Chaudhary, Raghav Sood

 

  • SmartMirror. It’s a smart assistant (like siri) which you can put on your wall and it looks like a mirror. It’s powered by a Raspberry PI, and has a monitor with a one-way mirror sheet on it so it looks like a mirror on which things can be superimposed / projected also. User interacts with voice commands to get news, maps, etc., which the mirror intelligently displays by getting the information from internet using API calls.
    • Components: Mic, Camera (presence detection), a flat monitor (with one way mirror sheet posted on it), Speakers; a case was made to hold all components and make the monitor look like a mirror.
    • Platform, Code. Raspberry PI 3B, About 4000 Lines of Python and JavaScript.
    • Team: Peeyush Kushwaha, Madhur Tandon, Mudit Garg, Siddhant Singh

 

  • Faux Arm. A robotic arm that wirelessly mimics the arm movement of the operator. The Faux Arm is a robotic arm with three points of movement, simulating the operator’s elbow joint, wrist joint and two fingers for grabbing and picking things up. We also built the Sensor Sleeve, a sleeve with sensors that can be worn by the operator on his/her arm, serving as a wireless input to the robotic arm.
    • Sensors: ADXL335 x2, accelerometer (to sense the angle of the arm wrt ground);
    • Actuators: MG996R Servo; MG995 Servo; FS90 Servo
    • Microcontroller and code: Arduino Uno (two) with XBee Module (two); Appx  800 Lines of C.
    • Mechanical components used:  Self-designed 3D printed structure of robotic arm; Self-designed aluminum grabber; Elastic, Velcro and a glove for sensor sleeve.
    • Names of the team members: Shivin Dass; Anvit Mangal; Taejas Gupta; Aditya Singh.

 

  • Robotic humanoid hand. In our project we had constructed a robotic humanoid hand. The 3D model of hand was open source and easily available on Inmoov. Our project used 3 types of control functions i.e. glove control using flex sensors for remote control of the robot, voice commands using the voice sensors, and direct muscle controls using the myoware muscle sensors. This hand can be used by amputees and physically challenged (using muscle sensor or voice control), for exploring inhospitable areas (by glove or voice control), etc.
    • Sensors: Myoware muscle sensor V3; Electrohouse Voice recognition sensor; Flex sensors (4×5” and 1×2.5”)
    • Actuators: 5 x mg995 towerpro servo motor.
    • Mechanical Components: 3D – printed human hand and its assembly (we printed it).
    • Platform and Code: Arduino; About 300 lines of C code; open source libraries for Voice recognition module.
    • Team: Shreedhar Govil, Siddharth Dhawan, Tanish Gupta, Vishal Singh Rajput

 

  • ShadowBot. Despite the technology today, large parts of the world remain inaccessible due to the inability of the humans to survive in harsh conditions. This can be changed by using robots. However, AI is not yet developed enough to allow robots to react accurately in delicate situations. Our project aims to improve the ability of a human to control a robot, by allowing it to mimic the user’s actions! Project Demo on YouTube.
    • Sensors: Microsoft Kinect v1.8
    • Actuators: S3003 Futaba Servos (ten for different joints and degrees of freedom);
    • Mechanical Components: Oblique servo brackets; Long U-shaped servo brackets; Short U-shaped servo brackets; L clamps; Nuts and bolts
    • Power Source: Turnigy 2200mAh Lipo Pack
    • Microcontroller: Arduino Mega with HC-05 Bluetooth Module; About 400 Lines of C# code for Kinect, and 150 Lines of C for Arduino.
    • Team: Aditya Chetan, Anant Sharma, Shwetank Shrey, Siddharth Yadav (mentored by PhD student Manoj Gulati)

 

  • Ambhibian BOT:   It is a remotely controlled (through the Ardiuno RC controller, configured for Bluetooth) amphibian robot which has the capability to travel through varied tough terrains, including water bodies (antenna and camera remain outside the water), to provide video feed. It comes with an emergency propeller which can be used in case the directional motors fail. Entire functionality is controlled via Bluetooth connectivity, and a live video feed is given by the camera attached at level height of the robot to the phone.
    • Sensors: Night vision camera, HC05 – Bluetooth chip for Arduino.
      Actuators: Geared DC motors (300 rpm, Quantity-5 (4-wheels + 1-propeller)), Lithium ion batteries (Quantity-2, each battery-3V), L298N motor driver (Quantity-2).
    • Platform and Code: Arduino mega, 50 lines of C code.
    • Mechanical components: 7.5 cm diameter multi-terrain tyres, light weight plastic box, M-seal and hot-glue (insulation purposes)
    • Team: Ashutosh Sharma, Arshan Zaman, Yash Tomar, Vineet Kumar Rana.

 

  • DrawBot. An automated arm that drew pictures given to it with a pen on a paper. The input was an image file. From the grey scale image of the file, we extracted edges and lines (using Sobel edge detection algorithm) in the picture, and then drew these lines using the DrawBot arm. For drawing, movement was controlled by two stepper motors. The Drawbot worked by making use of the nearest salesman algorithm that moved the arm in the direction of nearest pixel, by drawing small segments of lines using the slope and coordinates.
    • Components: Stepper Motor, Voltage Level Shifter, Gear Belts, Channels (to make arms), H-Bridge
    • Platform and Code: Ras Pi 3B, about 200 lines of Python
    • Team: Simran Deol, Navneet Anand Shah, Aditya Tanwar, Naman Kumar

 

  • iDabba. Our​ ​ project,​ ​ named​ ​ “iDabba”​ ​ is​ ​ a​ ​ smart​ ​ container​ ​ which​ ​ identifies​ ​ what​ fruit / vegetable / item​ ​ is kept​ ​ in​ ​ it​ ​ (using computer vision techniques; the​ ​ item​ ​ has​ ​ to​ ​ be​ ​ one​ ​ of​ ​ those​ ​ trained​ ​earlier), ​the​ ​ temperature and humidity​ ​ of​ ​ the​ ​ box,​ ​ and​ ​ the​ ​ weight of the items. All​ ​ this​ ​ information​ ​ is​ ​ visible​ ​ to​ ​ the​ ​ user​ ​ via​ ​ a web​ ​ app. ​ We​ ​ were​ ​ motivated​ ​ to​ ​ design this​ ​ ​ ​ to​ ​ ​ ​ solve​ ​ every day​ ​ hassles​ ​ in​ ​ kitchens​ ​ and​ ​ households​ ​ regarding​ ​ spoilage​ ​ and infestation.​ ​ It​ ​ can​ ​ ​ ​ be​ ​ scaled​ ​to​ ​ meet​ the​ needs​ ​ of​ ​ farmers​ ​ and​ ​ storage companies​ ​ for​ ​ smart​ ​ storing​ ​ options​ ​ and​ ​ act​ ​ as​ ​ a​ ​ small-scale​ ​ sil,. It can be enhanced to add the age of the items kept – then more intelligent decisions can be taken.
    • Sensors​ : Humidity​ ​ Sensor (DHT11​), Temperature​ ​ Sensor DS18B20, ​ Load​ ​ Cell to measure weight, HX711​ ​ ADC​ ​ Module ​ ​ to convert; ​ ​ Wifi​ ​ Module ESP8266​;
    • Platform and code: Arduino​ ​ Duemilanove, Raspberry​ ​ Pi​ ​ 3 (for computer vision); 180 lines of C code for Arduino; Appx 250 Lines of Python​ ​with​ ​ Open CV​, Microsoft​ ​ Vision​ ​ API ​ and​ ​ Flask​ ​ for​ ​ backend​. Front End​ ​ using​ ​ HTML/Javascrip ​ -​ ​ approx​ ​ 150​ ​ lines
    • Team. Viresh​ ​ Gupta​, Brihi​ ​ Joshi, Zoha​ ​ Hamid, Shravika​ ​ Mittal​.

 

  • SmartCart: We made an automated cart which follows the user based on a tag which the user wears. When placing the product in the cart, the product’s barcode is scanned and the bill prepared automatically in the app on the mobile phone. By using such a cart, a store owners can reduce their manpower for checkout, and also reduce the waiting times for customers.
    • Components: Ultrasonic Transmitters and Receivers (made the circuit for using these), 2x 12V DC Motors, 2100mAh Lipo Battery, Wheels.
    • Platform and Code: Arduino, Android phone. About 90 lines of C code, and about 640 lines of Java code (for the App), about 200 LOC of PHP on the server (mimicking the inventory of the store).
    • Team: Aakash Sehrawat, Anmol Prasad, Nilay Sanghvi, Saksham Vohra

 

  • Plant Watering System. This project provides water (which may contain other essential nutrients) to multiple plants based on their respective moisture sensor readings. The frequency to check the moisture reading depends on the temperature and humidity readings given by the temperature sensor. A GSM module timely informs the owner through SMS about the water level of the tank, and when the plants are watered. (A few teams did project of this type).
    • Sensors. YL 69 Soil Moisture Sensor; DHT11 Temperature and humidity Sensor
    • Actuators . Micro (3-6V) Submersible Pumps
    • Mechanical Components.  Piping system to water the plants.
    • Platform and code. Arduino, Appx 200 Lines of C code
    • Team1: Raghav Bhatia, Jai Mahajan, Kanha Srivastav, Shashank Kataria
    • Team2: Ashish Kanojia Dilnawaz Ashraf Dushyant Jangra Rishin Lal

Enhancing Autonomy in our Higher Education Institutions

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This is a somewhat longer version of the article that recently appeared in Times of India Editorial Page – e-paper link, regular TOI link.

Autonomy of higher educational institutions/universities (HEIs) is now widely acknowledged as a necessity for excellence and improvement, particularly for those HEIs that engage in research as well as education.  In India we hear about the need for more autonomy in newspapers and debates. Most discussions and articles talk about autonomy as a broad concept and its desirability or how it can help improve the level of education and research.  What specifically needs to be done to improve autonomy is rarely discussed. This note discusses a few issues, which I believe are most important for autonomy of our HEIs, and without which  autonomy, and therefore aspiration for excellence, will not come about.

Recognizing the importance of autonomy in HEIs, the EU had started an autonomy scorecard for its member countries. The framework for autonomy had these four key dimensions:

  • Academic
  • Organizational
  • Financial
  • Staffing

Academic autonomy has been sometimes in the news, largely due to the requirements imposed by key regulators (UGC and AICTE) on the HEIs. While it is important, I believe, that many Act created HEIs (e.g. IITs, IIMs, IIITs, many Universities etc.) can exercise due control in this sphere. In any case, it is a topic for discussion on its own. (Perhaps a future note will discuss this.) in this note I will focus on two fundamental issues in Organizational and Financial dimensions.

First issue relates to the organizational dimension. Organizational autonomy starts with how autonomous are the HEIs in appointing their Chief Executive – i.e. the Director or the Vice Chancellor. This is the most important aspect of Organizational autonomy, as it impacts all other organizational issues. In most western countries, this selection is generally done by the bodies of the university – the Board, Senate, a Board of Trustees appointed search committee, etc. (though the selection may sometimes be subject to approval, which is usually a formality).

In our country, the Chief Executive is selected by the Government or the Ministry, though there is generally a selection committee to recommend a set of names from which the final choice is made. If the final decision of the Head of the Institution is left to the Government, the same person(s) will be doing the selection for all the HEIs of the state/center. Hence, it may be perceived by potential candidates that being in the “good books” of the person(s) is important. This creates distortions – from some good candidates not applying to some lobbying for posts. This has created a general perception that factors other than merit influence these decisions.

Suppose each HEI was to select its own Chief Executive through a documented and transparent process that involves the stakeholders from the HEI, as is done in many countries. With selections/appointments distributed, there is no single authority that needs to be convinced, thereby giving candidates multiple opportunities of assessment by committees of different HEIS. Furthermore, in selection by a single authority, the selected person is more indebted to that authority rather than the HEI for selection. If the HEI was to select the Chief Executive using its stakeholders, then the answerability of the Chief Executive is naturally to the HEI and its stakeholders.

This single change of having each HEI select its own Head through an approved and open process can bring about a great deal of autonomy in our HEIs. Thankfully, the authorities seem to appreciate this and there are signs that this is beginning to happen – one hears that in the IIM Bill, this autonomy has been granted. Hopefully, as a next step, this change will be made for institutions like IITs, and reputed Central Universities.

The second main area in need for autonomy is financial. As long as there is financial dependence of HEIs on the government, autonomy will always be compromised. Yet, public HEIs need support from the government, to provide affordable education to citizens. So, how can one achieve autonomy while still seeking public funds. A simple method, which now many countries use, is to have the funding be based on some parameters by applying some formula. E.g. funding may depend on the total number of students, faculty, R&D projects, consultancy, etc, and the support level is decided through a defined formula. Given that different HEIs have evolved in different manner and may have different needs, the formula need not be same for all types of HEIs. For example, a business school may be given little or no support for education, while an Engineering Institution may be provided limited support per student for education, and a humanities oriented institution may be provided a higher level of support per student.

A formula based funding makes the HEI “independent” of its equations with the Government of the day. The formula provides predictability of funding, and the HEI can count on it and focus its energies on its academics and more efficient use of this public funding. This enhances the autonomy of HEI autonomous, while still retaining the public character.

While these can improve the autonomy of HEIs substantially, there is a need to also ensure that HEIs, particularly those who are taking public funds, are discharging their responsibilities to the society properly.

How does one ensure accountability? This is important as without this, autonomy can lead to inward looking HEIs which are not responsive to societal needs. The responsibility of an HEI is mostly around expanding its educational opportunities, and to align its research towards national goals or needs. (Responsibility in terms of access is already built-in through reservation laws.) Both of these can be easily achieved through financial models. E.g. if funding is tied to the number of students studying (as is the case in Australia), then there is an incentive for the HEI to increase its student strength. Similarly, research direction is often influenced by providing research projects and grants in specific areas/types of work – an approach taken by most countries, including India.

With organizational autonomy, there is also a need for internal systems of the HEI to have proper checks and balances. For this, it is imperative that the system being followed is where the approving authority is different than the recommending authority. This is most important in faculty appointments –  if these appointments are not done properly and with rigorous processes, it can lead to substandard faculty, which takes an HEI down a path from which it takes decades to recover, as faculty stay in the system for even three decades. For this, the system followed in institutions like IITs is very sound – the recommendation for faculty selection is made by a selection committee which is chaired by the Director. But the recommendations are accepted by the Chairman of the Board on behalf of the Board of Governors. However, an alternate method, which is seriously flawed, is also followed in many universities in India, in which the Vice Chancellor chairs the selection committee, as well as the Board of the University, thereby making the recommending and approving authority as the same. This must be corrected to ensure that the autonomy does not get misused.

There are many factors that impact autonomy, many of them not covered in this note. This note focused on two most important issues for autonomy: (1) the selection of the Chief Executive should be done by the HEI itself through transparent and well defined process that takes inputs from the stakeholders of HEI, and  (ii) funding of each HEI should be formula-based dependent on some important parameters like R&D output, number of students, etc. so the HEI is clear about what level of support to expect. If these two can be done, we can possibly see an unleashing of trapped energy in some of the HEIs which can take them to path of excellence and global ranking/standing.

 

Australian Universities – Some Observations and Lessons for India

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Note: These are some observations based on a visit to about half dozen universities in a few different cities. Some of them were the G-8 universities (top universities identified by the Australian Government), and rest just below them. The observations in this note are based on discussions largely in CS/IT schools and the broad numbers that were indicated mentioned these discussions – hence only broad statements are being made. This is not a detailed study of any university or the University system in Australia.

Size

Main Australian universities are quite large – most with more than 50,000 students and over 1,500 full time, regular faculty. They are generally organized as Faculties, and within them are Schools (which are like Departments in US or India), which may have disciplines within them. Universities also have focused research centers, which have funding of their own, but faculty mostly come from Schools. CS/IT is often a school of its own and generally one of the largest (and is heavily in demand). Most large universities are catering to it by expanding their offerings in it.

The overall administrative staff is appx of the same size as the size of faculty, though in each department the number is smaller than the faculty.

In CS/IT, in many of these large universities the faculty strength for regular, tenure-track/tenured faculty is about 30 to 40.

In size, main Australian universities are similar to the US public universities (there are only a couple of private universities in Australia – the rest are all public universities, supported by the Government.)

UG Education

Many have multiple programs at the UG level – in CS, IT, Sw Engg, etc.  A program may have an average intake of a few hundred students every year, and overall UG population can be a few thousands. Foreign students ratio may be about 10-20%.

Most UG degrees are 3 year programs. However, many of them add one year to give an honors degree. Those CS/IT degrees that are in engg, are normally of 4 years. Altogether, the school of CS/IT may have about 1000+ UG students.

UG students do mostly 4 courses (units) per semester. First year is usually a common set of courses. There is a strong focus on professional skills development in courses.

Masters Program

The Masters is commonly by course work only, and is normally of 2 years duration. The intake may be as large as 300 or 400 every year. Masters has a large number of overseas students – often more than half, sometimes even two-thirds. Most of the overseas students are from Asia – China and India being the largest. Smaller number is from Africa.

Masters is a completely a paid program. There is no scholarship/fellowship. And the fee is normally higher than the UG fee.

PhD Program

PhD program may be around 200 students in CS/IT – generally between 3 to 4 students per regular faculty. All PhD students are given scholarship/fellowship (tax free, of around $28K). PhD students may get paid a top-up from research grants (of about $10K). They are often paid extra for TA work or for being tutors. Tuition fee is waived for about 3.5 to 4 years, and the scholarship is also often limited to this duration.

Often for each PhD student, the university will give some budget (of about $5K), which can be used for laptop, conference travel (by the student or the adviser), etc.

Teaching/Instruction

A regular course may have 2 hours of lecture, and 2 hours of lab, and/or an hour of tutorial. The instructor gives the lectures, and also takes some sessions of tutorials (to get the pulse of the students). Tutors are generally not allowed to take lectures.

Courses for UGs and PGs are mostly separated – however, many times courses are dual numbered and the same lecture may be used for both the courses, with some special assignments or work for the PG students.

Course syllabus is often standardized, including the nature and number of assignments or labs or projects.

Lectures classes are often large – most with around 200 students. For first year courses, the size of a lecture may be around 500. For a large class, there may be two sections (say of 200 each, or 500 each for the 1st year course), and there may be two instructors for it – who will collaborate.

While the lectures sessions are large, there are tutorials and labs for courses. These are usually in small groups of around 30 each. Problem solving as well as lab help is provided in these sessions.

In a course there is often a feedback from students early on during the semester – to help the instructor make  any changes in how the course is being taught. There is a feedback at the end of the course. Moderation of grades is often done (i.e. some committee looks at grading patterns in the courses.)

There are facilities to tape the lectures, which are uploaded almost immediately after the class is over. Students can watch it later.  Most universities are exploring ways to leverage technology to reduce faculty requirement. E.g. in one students can enrol in web-delivery mode also (though very few students opt for it).

Student Faculty Ratio and Teaching-Research Balance

If entire UG students in the programs and the Masters students are taken, in most universities, in CS/IT the ratio may be of the order of 40:1. Some CS/IT schools have about 35:1, but some even have a ratio as large as 70:1. (Overall student to faculty ratio in a university also seems to be around 35:1.)

However, the faculty are well supported by Tutors and TAs, which are largely PhD students or casual faculty hired for this purpose. In some universities, senior UG students are also hired to help in TA work, particularly in labs (mostly honors students may be taken for this.) Part-time faculty from industry are also used for teaching. There may also be a small number of teaching-focused faculty to reduce the load of regular faculty.

There is a good balance between teaching and research. Many universities mentioned the 40-40-20 formula – a faculty member is expected to spend about 40% effort in teaching, about 40% in research, and 20% in service/administration.

Teaching load of a faculty varies from 2.5 to 4 courses per year. Adjustment based on research and administrative load is permitted and there are rules for this.

In teaching approach and student-faculty ratio, Australian universities differs from their US counterparts. The course load for students is a little lower, more support is provided through labs and tutorials, and the student-faculty ratio is considerably higher (in US many of the prominent state universities like UC system or GaTech have a student-faculty ratio of about 20:1.)

Research and Research Grants

Australian Research Council (ARC) is the main body. It usually gives larger grants. Many faculty may not get grants. Small grants may be provided by the University also.

Grants cover PostDocs, other research staff and top-up to students, and also travel and other such expenses. They don’t need to cover for PhD students.

There is a culture of postdoc developing and people with grants will have them. Generally, research is done by faculty, post docs, and PhD students.

There is an emphasis on applied research – sometimes coming from industry, and sometimes derived from some direct application.

Fees, and Economics

For domestic students, the UG fee is around $15K per year. The intake of students is not controlled, and a university is free to admit as many as it wants. However, the fee for domestic students is controlled – i.e. the Govt has fixed it.

Of the fee for domestic students, the student has to cover about one-fourth to half, for which he can take a loan, which is to be paid later as additional tax, but only after the student’s earning crosses some threshold. The rest of the fee is the subsidy by the Govt. The university gets the full fee from the Government directly, and the Government recovers the money from the student. (There is also some option to pre-pay the fee at some discount…)

MS fee is usually higher. Govt does not provide subsidy for this. (Not fully sure)

Overall, the university gets a funding from the Federal Govt based on the number of students, i.e. fees times the number of students in the university. Due to this, there is an intense competition to get good students and there is an inherent motivation to grow – that is why most Australian universities are large in student enrollments. Note that even state created universities will get this grant from the Federal Govt.

Government also gives some grant for research which is also based on a formula which takes as input the impact, the research funds raised by the university from corporations and other sources, etc.

Except ANU and one or two others, there is no other grant from the government for teaching. Government may also give some special grants for infrastructure or special purposes every now and then – for which universities have to make proposals.

For foreign students, the fee as well as the numbers a university can take, is not regulated. The Government provides no subsidy for foreign students. The fee for foreign students is about $30+ K per year. So, the fee from foreign students cover part of the cost of education for domestic students, and also supports research expenditure of the university (as research projects do not cover the full cost of research.) Due to this, there is a strong incentive to recruit foreign students.  Australia has actively promoted itself as an education destination – high quality education in English, with the possibility of migration as well. (After 2 years of study, an overseas student is eligible to work in Australia.) By some accounts, education is the second (or third) largest forex earner for Australia.

A university may have a budget of about $1Billion (AUD). Broadly, the main income sources for a university are:

  • Tuition fee from domestic students given by federal Govt – about 70%
  • Research grant from the Federal Government – about 5%
  • Tuition fee from overseas students – about 15% (higher in some)
  • Research grants – about 10% (higher in more research places, lower in others)

There may be special grants, which arise from time to time – for construction, for some initiative of the Govt, etc.

So, funding approach for Australian universities seems to be formula based, and seems different from their US counterparts.

Autonomy

Universities are fully autonomous and are governed very well with a strong administrative set up and often visionary leaders. The Government has minimal role in university administration. There are some reps in the Board, and there are reporting requirements by the Government (e.g. to make sure that finances are in good shape), but govt does not play a role in appointing anyone, including the President. It seems that any interference in selection of President/Chancellor may be taken in very bad light even by public.

And most funding is formula-based. This allows a university to plan its own growth and finances, and there is predictability of funding from the Government. In other words, relationships with the government do not play any role in funding levels.

Some Lessons for Indian Research Universities

There are clearly some lessons for institutions like IITs, some IIITs, etc., which have a strong focus on research and have a vibrant undergraduate program, as well as for other research-led higher education institutions which give strong emphasis to research and education both.

  • Explore ways to enhance student faculty ratio – there is clear scope to do this so the benefit of the high quality faculty in these institutions can be made available to larger number of students. This will require, improving the PhD program, enhancing TA training programs, leveraging technology, use more internet delivered courses, have a program like Teaching Fellow, in which the teaching fellow is recruited and trained to handle tutorials and labs, and in the process get trained to become instructors in colleges. Extra revenue obtained by increasing the students at UG level, can be used to fund the PhD students.
  • Improve TA training and work culture – this is essential as the a higher number of students per faculty can only be supported if the TA help improves so TAs can handle most of the labs, tutorials, grading, etc. Besides training, this will need good guidelines for TAs for grading, handling students, etc, improved feedback and assessment of TA work, establishing awards and recognition for TA work, etc
  • Use senior UG students as TAs – they have been found to be very good TAs for undergraduate courses – this is partly due to the fact that the senior UG student has done the course in the same university, thereby has a better understanding of the course approach and teaching style etc. This may require giving them training, more respect and honor, stipend..
  • Expand the PhD program –  have about 3 to 4 PhD students per faculty. Make the PhD program more attractive – develop schemes for top-up (e.g. from projects for RAs, and extra support for TAs after they have done the mandatory 2 semesters of TA work), provide more facilities, support for conference travel,…
  • For expanding the PhD program, ACITE can consider stopping scholarships for MTech – these provide little value and world over scholarships for Masters are getting eliminated – and use the funds to instead provide PhD scholarships.
  • Enhance supervised labs in core courses so students can build strong practical skills – this is important for building professional skills. Must provide more support in the lab so students can be guided.
  • Enhance tutorials for developing problem solving skills – will require good training for tutors so they don’t make it a lecture, but applying concepts from lectures to problem solving.
  • Expanding the MTech program overseas – there is good possibility here and being a 2 year program where mature students come, least risky. If the courses are mostly exclusively graduate, then it is relatively easier to do this. The fee can be kept a little lower than fee levels in places like Australia, as it still be very cost effective due to lower cost of living. Initial focus can be on Asia and Africa.
  • Improve the use of technology – in infrastructure as well as in education (e.g. taping of lectures and putting them online asap, use of technology for tutorials, etc.)

Interdisciplinary Programs with Computer Science/IT

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Computer Science/IT is a young discipline. However, with easy and cheap availability computing power, its use has become ubiquitous – there is hardly any discipline or any sphere of life which is not directly affected by IT. That is why computing (I will use computing, IT, and CS interchangeably in this note) is sometimes considered as the “new physics” – it is useful in all disciplines and its basic knowledge is essential. Today, in every discipline, knowledge of computing is an asset, and there is a demand for professionals in various disciplines who also have decent knowledge of computing.

CS is in some ways a simpler discipline. It is fundamentally about software and systems (many of which are themselves software). Hence, education programs in CS focus on these. For software, there are courses like programming, data structures, algorithms, theory behind these, software engineering, etc. And for systems, there are courses like architecture, operating systems, compilers, networks, etc. Generally a subset of these topics form the core (or compulsory) part of a BTech program. In the rest of the program, a student often does advances in these areas, as well as developments special systems like databases, run time systems, etc, or application areas like computer vision, gaming, image processing, etc. This allows for a relatively small CS core in an education program.

Contrast this with an older discipline like Electrical Engineering. Even covering the foundations will require multiple courses in basic sub-areas like circuits, signal processing, communications, controls, power system, etc. And to become an engineer who can apply concepts of these, one will have to do many more advanced courses, and labs and projects.

This ability to have a small core to teach decent amount of computing to a student which he/she can apply, renders CS easily for interdisciplinary programs which combine CS basics with knowledge of other disciplines. And given the need for the knowledge of computing in many disciplines, having an interdisciplinary program with computing makes a lot of sense, particularly since further progress in many disciplines is highly dependent on good application of computing. A good example is biology – earlier it was considered an experimental discipline. But now, without the use of computing, many aspects can simply not be done (e.g. anything to do with genomics requires huge amounts of computing.)

In fact many senior computing academics have argued that while computing as a discipline must evolve, computing must get more tightly integrated with some disciplines to have more impact of computing for society and other sciences. This is another reason for having interdisciplinary programs with CS/IT.

At IIIT-Delhi, we are taking this thinking as a key approach for growth. While we will continue focusing on Computer Science and Engineering (CSE) as a discipline, and also Electronics and Communications Engineering (ECE), instead of adding more regular programs in traditional disciplines, we will add interdisciplinary programs with CS/IT in carefully selected areas which have a natural affinity to CS/IT and where combining them together brings advantages.

Last year IIIT-Delhi launched a program in CS and Applied maths. The basic motivation behind this program was that for solving problems for complex systems as well as for big data, both mathematics and computing tools and techniques need to be applied. Hence, an engineer with training in both will be better prepared to handle such problems. In addition, at research and foundational level also there are many connections between CS and Maths (in fact, many computer scientists consider themselves as mathematicians also), making mathematics a natural discipline for an interdisciplinary program with CS.

This year we are adding two new interdisciplinary programs. First is the BTech in Computer Science and Design program, which aims to develop graduates that are not only well versed with computing approaches, tools, and technologies, but are also experienced with Design approaches and new Media technologies and uses. The program will prepare students to work in the IT industry as well as digital media industry like gaming, animation, virtual/augmented reality, etc. The program will also allow students, who want to pursue higher studies, to take up higher studies in CS/IT or in Design. The program aims to develop capabilities in CS as well as Design and Digital Media. Along with this, we are also starting a center for Design and New Media, which will conduct research in these areas.

The second program is in BTech in IT and Social Sciences. Going forward we are likely to see more convergence of IT with social systems (e.g. social media) and the role social sciences will play in technology solutions and the role IT will play in addressing society’s and people’s problems, will increase. This will lead to an increase in demand for IT engineers who are also well versed with social sciences. This unique program aims to develop IT engineers with strong understanding of relevant social science disciplines as well as their methodologies. It may be an ideal program for those students who are not sure if they want to pursue engineering careers and would like to explore the possibility of going for social sciences later, but want to be ready to take an IT career if desired. Along with the program we are also establishing a research Center on IT and Society, which will research the interplay between IT and society and impact one has on the other – an area which is highly under researched in India.

Typically, in any such interdisciplinary program, a student will do a few foundation courses in first semester. Then in the next few semesters, he/she will do about 6 to 8 core (compulsory) courses in each of the two disciplines, which will provide him/her grounding in the two disciplines. In the last two years, the student will chose 4 to 6 electives from each of the disciplines, as well as do other courses that can help his/her career.  (There are usually some other requirements, like HSS, and possibilities like Open Electives in the last years.) Broadly, such an interdisciplinary program satisfies requirements of a BTech in CS/IT, as well as requirements of a BA/BSc program in the second discipline. This is feasible to achieve in a 4 year program, particularly since BA/BSc are 3 year programs, and if disciplines are chosen strategically, there can be many courses which are common and hence can be counted for both disciplines. Such programs allow a student to pursue an exciting career in the intersection of the two disciplines, but also prepares the student to pursue high studies and career in one of the two disciplines, as decent knowledge of both disciplines is provided in these programs. As it is a 4 year program, it also allows students to pursue higher study programs that require 4 year college education.

Many thinkers believe that interdisciplinary approaches for problem solving is where the future lies, as silo approaches of individual disciplines are limiting and often unable to take a broader view of the problem and its context. Such interdisciplinary programs should help develop manpower which has the capabilities of at least two disciplines for problem solving.

Normalizing Class XII Marks

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Recently it was reported in newspapers that CBSE moderates its marks by effectively increasing them – largely to “compete” with other Boards. It was also reported recently that some of the top colleges in Delhi have a majority of students from one Board in south, and a large number from one school.

Both of these anomalies are due to one reason – admission being based on Board percentage without normalizing the marks of different Boards. Due to this, Boards realize that their students will benefit if they have a higher percentage – so there is a race to give more marks. Besides distorting the admission process, this race is unhealthy for education and learning and gives a false sense of achievement to students.

Of course the natural course of action is to normalize marks from different Boards. Normalization across Boards can be easily done – all it requires is a little extra information from each Board. For some strange reason, it has not become regular practice and Boards do not provide sufficient information for normalization.

Let us first understand the normalization problem. Each Board gives marks between 0-100%. Normalization requires that marks between 0-100 given by different Boards be converted to a “normalized score”, also between 0 and 100, which provides a common reference where X marks mean the same, regardless of whether the Board was “tough” or “easy” in its marking.

One approach to normalize, which CBSE also used for JEE, is to base it on the percentile of a student in the Board. The percentile score of a student reflects what percentage of students in the Board have marks below that of the student. I.e. a student with 90 percentile means that 90% of the students have received marks that are below this student’s marks. To convert marks to percentile score, students are ordered in the order of marks they received, and then divided in 100 equal groups – the top 1% students fall in 99-percentile, the next 1% fall in 98-percentile, etc. (This can, of course, be done at 0.1 or 0.01 percentile granularity for finer resolution.) Once percentile is given, then there are ways to normalize, with the assumption that top N% of the students in a Board are essentially similar to top N% students in another Board, i.e., a 99 percentile student in one Board can be considered similar to a 99 percentile student of another Board. (If this assumption cannot be made, then it will require calibrating different Boards – an exercise that is unlikely to be undertaken, and if initiated, unlikely to culminate in an acceptable calibration.)

With a percentile score, one way to normalize across Boards is simply to use the percentile score. In this case, a student with 99.5 percentile (from any Board) will be ranked higher than a student in 99.3 percentile (from any Board). The percentile score can have finer granularity, if desired, and within each percentile, there can be tie-breaking rule.

The ranking with percentile is sufficient if the decision of admission is based only on class XII score, i.e. one needs to rank or order students only on class XII score. However, if admission is based on sum of multiple scores, in which one of them is the class XII marks (as was the case in JEE, where 60 marks came from JEE exam and 40 from class XII), then the situation is more complex and percentile will have to converted to a normalized score to be added to the other scores.

There are techniques to convert the percentile score to a normalized score. For this conversion, a desired target distribution is needed, which gives what fraction of students should be at each mark in the normalized marks between 0-100. The target distribution for normalized marks is a choice to be made, and any reasonable distribution can be chosen – the preferred distribution for exams is Normal Distribution, in which the largest fraction of students is at the mean and then the fraction at each mark reduces as we move on the two sides of the mean. If the target distribution is taken to be Normal Distribution with mean of 50 and the standard deviation (a statistical attribute indicating the variability in scores) of 15, then 99 percentile will translate to 85 normalized marks, 98 percentile to 81 marks, 95 percentile to 75 marks, 90 percentile to 69 marks. There are standard tables available for this conversion. (This conversion will be different if a different mean and/or standard deviation are selected.)

It should be clear that with percentile based normalization, inflating marks in a board does not help students – the top 1 % students of all boards will be mapped to the same normalized marks. So, in a Board which has inflated marks such that a large fraction of its students get above 90% marks, only the top 1% students will get the same normalized score (99 percentile, or 85 marks in the above example), which will be same as the top 1% students from a Board which has a much smaller fraction of students above 90%.

Overall, normalization can be done easily and transparently if information about percentile of a student is provided by the Boards.  If Boards provide the percentile, normalization is straightforward.

Normalization is not possible if Boards only give the percentage marks to students, as they do now. Though determining percentile is trivial and Boards can easily do it, for some reason, it is not being done. Perhaps because just with marks a Board can have as many students above 90% as it wants and let the students and their parents feel good. With percentile only 10% of the students can be in the 90 percentile – which will give a clear picture to the student about his/her relative standing in the Board. Given this situation, probably MHRD will have to mandate that percentile information must also be provided to the students. And to support this move, all universities that use class XII marks for admission can declare that they will normalize marks of different Boards and will therefore not admit students from a Board unless the percentile scores are also made available – if this is done all Boards will have to provide this information.

If normalization is done, besides fairness in admissions, it will also lead to curtailing of the unhealthy exercise of marks inflation that the boards seem to have gotten into. If normalization is not done, given the publicity received about DU’s admission this year, we will see an unhealthy race between Boards to give easy marks, resulting in a complete failure of merit based admissions, with less deserving students from some Boards getting admission into the best colleges in the country at the cost of more deserving students from some other Boards being denied admission.

Widen the Entrance Criteria in Higher Education Institutions

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It is well established that good quality higher education is the best way to open doors to a variety of opportunities – that is why world over students vie to get into the best universities and colleges. Due to this, while school education is meant to lay the foundation for a broad development of the individual, the single most important goal of school education becomes getting admission in a high quality higher education institutions (HEI).

Admission to our HEIs is based almost exclusively on performance in exams – class XII or entrance test. Most engineering institutes admit students through entrance test, though now class XII marks are also given weight, and most universities like Delhi University give admission based on class XII marks (though have some seats for sports etc). So, regardless of what educationists may like to see, students, parents, and teachers all eventually align to a single goal as outcome of school education – doing well in class XII exams and competitive entrance tests. As nothing else matters for achieving the important goal of getting into a high quality HEI, other aspects of development that the school education is supposed to provide, are mostly ignored.

As a result of  this exclusive focus on exams, a student who does innovative projects in schools demonstrating innate talent and interest for engineering is precisely the one who may not make it to the best engineering institutions as he/she “wasted” time doing these projects – time which could have been more optimally used in coaching classes. Similarly, a student who does internship in some company and writes a report on the economics of a sector – perhaps the ideal candidate for an economics program – may not be able to get into a good economics program as others who spent all the time preparing for exams get higher marks. Similarly, students who engage in school debates, participate in social work, sports, or other activities that can broaden their development and horizons, are often at a disadvantage for getting admitted to HEIs as compared to those who spend their time preparing for tests. This uni-focus on attaining high test scores also inevitably leads to shallow learning styles which maximize performance in tests but prevent deep understanding of subjects.

This focus on exams cannot be changed just by exhortation or changing the pattern of the exam or bemoaning the state of affairs. We have to squarely accept the fact that the most important goal for a student is indeed getting admission into best colleges, and if we want students to have wider development in schools, we have to widen the criteria for admission to include achievements and efforts outside tests.

One direct approach can be to assign some marks (say 20 out of 100) for achievement in other spheres while the remaining 80 can remain based on results of class XII and entrance test. With this, the problem reduces to developing sound procedures for assigning marks out of 20 for achievement in other spheres. This will be a challenge but not one that is unsurmountable – PG/MBA programs or public service exams routinely do this, by having an interview and assigning some weight to it.

IIIT-Delhi has been following another approach for the last few years for this. In IIIT-Delhi, for admission in BTech program, up to 10 bonus marks (on a base of 100) are given for achievements in various spheres, through a published criteria. For example, bonus marks are given to students who reach final stages of various Olympiads, participate in national school games, have Chess FIDE rating, get an award in the INSPIRE or IGNITE program, win prize in programming contests, have ministry of culture’s scholarship for talent, etc. The program was slow to start, but in the previous two batches, over 10% of the students admitted are ones who have received bonus marks.

We have also done some analysis of how these students perform in our Institute. As we had anticipated, the first year performance in the Institute of the students who had received bonus marks was significantly better than the performance of students without bonus marks (the average CGPA was higher by more than 1.) This clearly demonstrated that students with broader base are likely to be better prepared for higher education.

Most US universities, while giving a considerable weight to SAT scores and performance in high school, consider a host of other factors and achievements for admission. In fact, in top universities it is now known that just good grades and SAT scores are not sufficient, and students must show other achievements. This hugely motivates families to develop other aspects of a students’ personality – sports, culture, social work, volunteering, etc. If we start incorporating achievements and contributions in other spheres in admission to most of our top HEIs, we may also see an increase in motivation and drive to undertake such activities in school – this can only be good for our students and their development.

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