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Re: So much hot air so little accuracy from Dartmouth
While not fully developed, the idea behind the app has potential. I think to apply it to businesses, we'd need to consider each person and their working preferences. Some employees might need to interact with colleagues more to be productive while others can stay at their desks. I like working in coffee shops, for example, but doubt an app would say my 6 hours in Starbucks were well-spent.
Re: Dartmouth Predicts GPA Based on Phone Tracking App
@david: you read my mind! You must have your google ESP headphones on today!
Re: So much hot air so little accuracy from Dartmouth
@impactnow- Well, this isn't linear. In fact, it measures a lot of factors that have nothing to do with sitting in one place (sleep, fitness) and yes, I agree certain jobs need to stay more connected. So an app would have to be altered for different jobs.
No one is saying this is perfect now. But it represents an interesting step forward in course correcting and intervening with people when the advice counts as opposed to when it is too late.
No one is saying this is perfect now. But it represents an interesting step forward in course correcting and intervening with people when the advice counts as opposed to when it is too late.
Re: Dartmouth Predicts GPA Based on Phone Tracking App
@vnewman2- I think you'd break the Google Glasses app because it would get tired of constantly reporting that the kids were just "checking out the hot classmates." :)
Re: So much hot air so little accuracy from Dartmouth
@asksqn- It isn't that simple. It can work out what you are doing in a lot of places. Besides, it isn't just study time in the library it is using for measures of success. It measures sleep time, social time, physical activity, stress and a bunch of other factors for success. For instance, one of the interesting aspects of the research behind th decision is a stress curve. Successful students see a rise in stress early and a decline as the semester goes on (I assume that is because they find their footing but it doesn't say way). If the app doesn't see a stress curve liek that in the student, it knows it is time to intervene before it is too late.
In my experience, the number one reason people fail is that they don't correct their behavior in time. In a college student's case, I can imagine that means not going to class and then as the semester ends trying to "pull it all together." Often, we're not aware of the little things that add up to make us fail. We are going along just fine in our minds and we don't realize that we're just spending a little less time doing what we should or taking care of ourselves and by the time we realize it is too late.
In my experience, the number one reason people fail is that they don't correct their behavior in time. In a college student's case, I can imagine that means not going to class and then as the semester ends trying to "pull it all together." Often, we're not aware of the little things that add up to make us fail. We are going along just fine in our minds and we don't realize that we're just spending a little less time doing what we should or taking care of ourselves and by the time we realize it is too late.
Application on the enterprise
So imagine if some business leaders start believing that this process is really credible and they implement it in the organization, what havoc it'd create. You'd start to be monitored on the number of hours you spend on the computer and what time at each file. How many restroom breaks you take and how long do you have your lunch for. That'd really make the idea of look-busy-do-nothing be useful in this case.
Re: So much hot air so little accuracy from Dartmouth
"If they used a bunch of enthusiastic students it's not hard to see that the entire sample might not have deviated much more that .17 of a point."
@progman2000: I agree. The data gathered can be very skewed and misleading. The sample has to take into account a lot of factors such as time, location, nature of students, circumstances etc. Only then you can base an argument. I don't think there'd be any real co-relation though.
@progman2000: I agree. The data gathered can be very skewed and misleading. The sample has to take into account a lot of factors such as time, location, nature of students, circumstances etc. Only then you can base an argument. I don't think there'd be any real co-relation though.
Re: So much hot air so little accuracy from Dartmouth
I think the app would have to be tested in a broader sample group at multiple institutions to assure its accuracy. Once student entered data is used in conjunction with gps data the results get muddy. In the workplace I think it would be a night mare people have different working habits based on their jobs and their working style. I sometimes got more done talking to someone in the hallway than I ever could have done on the phone or email. There is a factor of efficiency that can't be measure with linear technology.
Re: So much hot air so little accuracy from Dartmouth
@asksqn - yep, I'm with you - sounds like a load of crap. And the video says it relies on a bunch of student reported data as well as what the phone collects. So it sounds like the phone makes assumptions on study/party habits based on where you've been and asks you to input a bunch of questions that if factors in. Plus they don't say what the sample range of their respondants were. If they used a bunch of enthusiastic students it's not hard to see that the entire sample might not have deviated much more that .17 of a point.
Yawn - have them give us the next Angry Birds and then we'll talk.
Yawn - have them give us the next Angry Birds and then we'll talk.
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6/1/2015 | 5:35:37 PM