Applying IBM’s Watson to Big Data Analytics in Education

‘A smarter planet is built on smarter analytics’

Anyone who has watched Jeopardy! for the last twenty odd years knows Watson as the computer genius who won against Ken Jennings on the show. Despite super intelligence, Watson’s cognitive software did not answer every question correctly. In fact during the second round contestants (human and AI) were stumped with this little known fact…Category? US Cities please. Its largest airport was named for a World War II hero; its second largest, for a World War II battle.

Watson, the artificial intelligence computer designed by IBM was programmed to get most rapidly-fired questions correct, with the exception of a few trick contextual answers. Ironically, one of the system’s biggest flaws was deciphering pesty language idiosyncrasies. For example, English anomalies; idioms, conundrums, euphemisms, semantic woes and punctuation malfunctions. To resolve the slight hiccup, IBM designers focused on natural language processing to pick up on inconsistencies and ambiguities. (See Major tasks in NLP)

So with only ten seconds to answer the gameshow’s million-dollar question, how does a computer examine over 4TB or 200 million wiki sources? Did Watson use algorithms to sift through the data? This all led me to wonder, what role does big data and analytics play in the world today?

Putting Watson to Work chiefly explains research expansion in areas of finance, healthcare, mobile communication devices and engagement, or better customer relationships. It has huge potential in cross-industry disciplines. Imagine what Watson can do to drive better data analytics in education if we apply some of these principles:

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Transform education through predictive analytics
Learn from software, improving outcomes for individual students
Align vision with data
Anticipate trends that shape the future
Act on decisions that optimize results

The Jeopardy answer was Chicago. I’m sorry Watson, but Toronto is not the US city we were looking for. If you only paid attention to context clues and punctuation: semicolons and syntax; the text directly following it.

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