Bengaluru The Indian Institute of Science (IISc), often in the top 200 global university rankings, was praised by president Pranab Mukherjee on Wednesday for advancing research in science and technology.
“Alumni and faculty of IISc have played and continue to play a strong role in leading national science and technology institutions and in various advisory or administrative roles in the government,” said Mukherjee, the IISc’s Visitor, at its annual convocation here .
Noting that IISc maintained its reputation of being a premier institute of higher education and research, he said its academic stature as the country’s best university was confirmed by the National Institutional Rankings Framework.
“Over the century-old institute has laid emphasis on the pursuit of basic knowledge in science and engineering, as well as on the application of its research findings for industrial and social benefit,” said Mukherjee in his convocation address.
The institute was set up in 1909 through a private-partnership between Jamsetji Nusserwanji Tata, the Maharaja of Mysore and the government.
Deviating from the speech text, the president told the graduating students and the faculty that he was happy to be at the institute that made the country proud.
“One of my inspirations when I entered the teaching profession was the institute’s director JC Ghosh in the 1940s, who later became the first director of the Indian Institute of Technology (IIT) at Khargapur in West Bengal,” he recalled.
The institute is recognised globally and ranked among the world’s top 200 universities.
Observing that the country had 760 universities and 38,500 colleges across the country, the President said the massive expansion of the higher education sector had led to resource constraints and dearth of quality teachers.
“If our institutions have to become world-class, they will have to adopt best practices in academic management and excel in whatever they do, as the spheres of intervention are many,” he said.
Mukherjee also urged the institutions to provide best amenities to the academic community, as state-of-the-art laboratories would enable quality experiments.
He honoured 677 students, including post-doctoral research scholars, post-graduates and graduates passing out from the institute with awards and medals at the ceremony, held at the JN Tata Auditorium on campus.
Karnataka governor Vajubhai R Vala and chief minister Siddaramaiah were present on the occasion with other dignitaries and invitees.
Uttar Pradesh Chief Minister Yogi Adityanath on Saturday lamented India’s “poor performance” in the field of science and technology despite being the largest democracy.
“Despite being the largest democracy and market, India is lagging behind in the field of technology…we have lost our place in the field of science… those who used to follow us are being followed by us today,” he said at a function in Gorakhpur.
“We will have to bring a change in our mindset according to the changing times,” he said.
He said it was a matter of concern that none of the cities in eastern UP featured in the Centre’s Smart Cities list.
Stressing the need for reviving sugar mills in the region through new techniques, the chief minister asked the research institutes to do the needful in this direction.
He said research done for meeting local requirements was more important than that for international needs.
On the deteriorating standard of education, the priest-turned-politician said there were some 660 private engineering colleges in the state, but these were hardly getting any admission.
He said the college owners were now converting the institutes into marriage halls and malls.
“It is a matter of concern that the standard of education is falling,” he added.
Afew classic studies help to define the way we think about the science of learning. A classic study isn’t classic just because it uncovered a new fact, but because it neatly demonstrates a profound truth about how we learn – often at the same time showing up our unjustified assumptions about how our minds work.
A classic study defines where research will go next – whether to confirm, disprove or qualify the original finding – and helps us to reorganise our learning to be more effective.
I’m a psychologist, so you won’t be surprised that my choice of classic studies concern the mental processes rather than the social processes involved in learning. Other people might pick a different five studies, but these are mine.
1. Bartlett’s ‘War of the Ghosts’
Frederick Bartlett was a Cambridge psychologist who used a native American folk story called War of the Ghosts to show something fundamental about our memories. The story, and the research study he used it in, are related in his 1932 book Remembering.
The War of the Ghosts is a tale of two young men on a hunting expedition that goes wrong, with one of them becoming involved in a raid on another village in the company of some ghosts. The tale has some familiar elements (the men are hunting seals, they go in a canoe, at one point they hide behind a log, that sort of thing), but it also has some aspects which are, frankly, a bit unusual in western culture: ghosts, a mortal wound that doesn’t hurt, and one of the men dying after “something black” comes out of his mouth.
Bartlett had people read the story and then he tested their recall over intervals varying between 15 minutes and 10 years later. He found, of course, that the longer the delay before testing, the less accurate people were. But the most important result concerned the nature of people’s inaccuracies. Bartlett saw how the memory errors people made tended to focus around the unfamiliar elements. People’s recall was better for things they had a good model of (such as the hunting expedition), but bad for things that they didn’t have a model for (such as the ghosts or the strange wound one of the men receives). These elements got dropped, or distorted in their memories, so as to fit with reasonable expectations. The canoes became boats, for example, or the mortal wound was immediately recognised as fatal.
Bartlett’s studies showed that memory is a constructive process, not something like a video recorder, but a web of associations from which accurate memories – and plausible false memories – are rebuilt as they are needed.
The moral for learning is that you can’t just slot new memories in like writing files to a computer disk. You need to integrate them into what you already know, making connections between old and new information if you’re going to successfully recall them.
2. Skinner’s rats and pigeons
BF Skinner is famous as the father of behaviourism, the school of psychology known for training behaviours in pigeons and rats. To this day, the rat cage with a lever and a food pellet tray is called a Skinner box. His great achievement was to show how schedules of reinforcement, such as the delivery of food pellets to hungry rats, could condition behaviour.
One of Skinner’s key claims was that with the right practice conditions – meaning that correct behaviour is appropriately rewarded – any task can be learned using simple associations. This means anything that can form simple associations, even a pigeon, can learn many complex tasks.
The team that, in 1995, taught pigeons to discriminate between Picasso and Monet paintings were intellectual descendants of Skinner. Like him, they believed that we underestimate the power of practice and reward in shaping behaviour. After just a few weeks’ training, their pigeons could not only tell a Picasso from a Monet – indicated by pecks on a designated button – but could generalise their learning to discriminate cubist from impressionist works in general.
For a behaviourist, the moral is that even complex learning is supported by fundamental principles of association, practice and reward. It also shows that you can train a pigeon to tell a Renoir from a Matisse, but that doesn’t mean it knows a lot about art.
3. Dissociable memory systems
We say “it’s like riding a bike” precisely because this kind of memory seems different from the kinds of things we easily forget, like names. What is now indisputable is that different memories are supported by different anatomical areas of the brain.
Pioneering work led by Larry Squire showed that amnesic patients who had trouble remembering episodes of their lives had no trouble performing a new skill they had learned. Brain imaging has confirmed the basic division of labour between so-called declarative memory, aka explicit memory (facts and events), and procedural memory, aka implicit memory (habits and skills).
The neuroscience allows us to understand the frustrating fact that you have the insight into what you are learning without yet having acquired the skill, or you can have the skill without the insight. In any complex task, you’ll need both. Maybe the next hundred years of the neuroscience of memory will tell us how to coordinate them.
4. Inside the mind of the chess masters
Lab studies of learning tend to ask people to learn something new. Another approach is to take existing experts and look at how they do what they do so well.
Adriaan de Groot was a Dutch chess master as well as a psychologist. His studies of how chess experts think began the modern study of expertise. One of his findings was that chess masters have an amazing memory for patterns on the chess board – able to recall the positions of all the pieces after only a brief glance. Follow-up work showed that they only have this ability if the patterns conform to possible positions in a legal game of chess. When pieces are positioned on the board randomly, however, chess grandmasters have as poor memories as anyone else.
The result confirms the idea that knowledge is a web of associations – when you have a large existing store of knowledge it is easy to spot patterns and so remember the positions of all the pieces. This also helps us to recognise what is wrong with the idea of brain training. Our skills and memories aren’t like muscles. You don’t get better at remembering faces by practicing remembering digits, and even if you train to become a world-class chess master you won’t necessarily develop a better memory in other areas of your life.
5. Ericsson’s 10,000 hours of deliberate practice
Anders Ericsson is famous for claiming that all world-class performers have in common is that they have all invested at least 10,000 in deliberate practice. Deliberate practice means effortful, structured practice focusing on reducing your failings and errors, constantly pushing yourself to improve.
Deliberate practice isn’t much fun, but whether the domain is figure skating or chess, the thing that distinguished the best of the best from the runners-up was the way they had arranged their lives to prioritise practice. As well as underlining the golden rule of learning – you have to practice – Ericsson’s idea also has a strong egalitarian air. Don’t worry about innate talent, just find a way to put the hours in.
No study is perfect. Even without flaws, there are caveats to how they should be applied, and distortions in how they have been interpreted, but for better or worse these studies define how psychologists think about learning.
The Government’s Science and Technology Committee published its latest report, ‘The big data dilemma’ on 12th February. The report states there is a drastic skills shortage in the digital market. This is not a new problem and the industry has been talking about it for a long time. Go On UK, a charity set up to promote digital skills, last year found that over 12 million people and a million small businesses in the UK do not have the skills to prosper in the digital era. The government’s report highlights that the issue is not going away and needs to be addressed urgently.
However, as we delve deeper into the report, it becomes clear that the government’s emphasis may significantly limit how we overcome the digital skills shortage issue. While the report does mention that infrastructure is required for data warehousing and curation, it places a much greater emphasis on ‘analytics.’ Yet to identify our digital skills gap as simply ‘analytics’ demonstrates a weak understanding of ‘big data’ and the underlying technologies required to harvest data before any analytics can be applied. Analysing data can only be done once the right information has been collected, processed and extracted.
The way that this can be addressed is by making sure that we are developing talent across the data supply chain, not on a narrow piece of it. Those studying for a career in the burgeoning data industry must be exposed to a broad range of topics that will give them the ability to appreciate and contribute across the whole data spectrum. This is not just about providing training in analytics, but also about developing software and hardware engineering talent for data warehousing, tech-savvy legal expertise for crafting policy and regulation and thoughtful perspectives for understanding an increasingly complex cloud of social issues.
As we delve deeper into the report, it becomes clear that the government’s emphasis may significantly limit how we overcome the digital skills shortage issue
This is not going to happen if the Government itself does not truly understand what big data is and where to focus education, but at least the report is a move in the right direction. That the Government has blind spots is to be expected; data is a far more vast and complex area than it was ten, or even two, years ago. Companies and governmental organisations now produce astronomical amounts of information from a range of sectors and harnessing it can be very difficult.
The government should be looking to work with a range of institutions to help them grasp this landscape. King’s, as an example, is working hard to address the education issues for the next generation of data scientists, by developing and delivering materials to a cross-disciplinary cohort of students through a collaboration of seven different academic departments. This means not just providing the technical skills, but also the understanding of how to apply those skills in particular real-world domain contexts for particular applications.
King’s is also seeking to help public sector organisations, schools and businesses alike understand what is needed as they operate in today’s data intensive world. Until we do this, Britain runs the risk of creating a marketplace of people with technical skills focussed on a narrow subset of those required and abilities restricted to datasets that are limited in scope. Education is the route forward, extending the UK’s ability beyond ‘just’ analytics and shaping the future of data science.