I'm a data geek. A data nerd. I think about data and I think about how to analyze data. So much so, that my kids are starting to pick up my habit, or at least answer me in a logical, structured way.
Driving to school yesterday with my 10 year old daughter London, we started discussing her upcoming research project. Her school has a project that is done in groups every year from first grade on, and now she is at the level where she gets to do one by herself, on a topic that means a lot to her.
There are 3 things she likes, and one of them is math. Numbers. She loves them. Stats, she understands them. Calculations, she does them for fun. You get the idea.
The question she wants to research: "Are girls better at math than boys?"
I stepped lightly into this (potential) minefield of a discussion, mind you, and began the Socratic method.
Dad:"What do you think?"
London:"I don't know."
D:"How could you find out?"
L:"I could ask a bunch of girls and a bunch of boys."
D:"Would that be objective, or subjective?"
L:"Probably subjective"
D:"How could you get objective data?"
This went on until we determined there are probably some data sets somewhere she can get to analyze the performance of students in math. Google becomes your best friend in these situations, right? The world is full of data waiting to be analyzed. Data that's been collected that is just that, collected data. What we need is to turn that data into information we can use to communicate our finding.
Driving to school yesterday with my 10 year old daughter London, we started discussing her upcoming research project. Her school has a project that is done in groups every year from first grade on, and now she is at the level where she gets to do one by herself, on a topic that means a lot to her.
There are 3 things she likes, and one of them is math. Numbers. She loves them. Stats, she understands them. Calculations, she does them for fun. You get the idea.
The question she wants to research: "Are girls better at math than boys?"
I stepped lightly into this (potential) minefield of a discussion, mind you, and began the Socratic method.
Dad:"What do you think?"
London:"I don't know."
D:"How could you find out?"
L:"I could ask a bunch of girls and a bunch of boys."
D:"Would that be objective, or subjective?"
L:"Probably subjective"
D:"How could you get objective data?"
This went on until we determined there are probably some data sets somewhere she can get to analyze the performance of students in math. Google becomes your best friend in these situations, right? The world is full of data waiting to be analyzed. Data that's been collected that is just that, collected data. What we need is to turn that data into information we can use to communicate our finding.
This when got me thinking of another problem: How am I going to teach data analysis to a (smart) 10 year old? Something I've spent my career learning to effectively do? Where do I start? Spreadsheets? A stats program like SPSS?
London is lucky in a few ways. 1. She is good at asking questions. 2. She knows how to use a web browser. 3. She can upload a file.
Because of this, her research analysis just became a lot easier (for both of us). I helped London create her own IBM ID, the only other prerequisite other than the 3 above that is needed to get started immediately with Watson Analytics. The videos explain step by step how to upload data and begin analysis right away. The best part? She can use her inquisitive mind to ask Watson questions and Watson will give her answers. It's so easy, so easy that a 10 year old can get value out of using cognitive technologies to learn.
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