I just experienced a great example of why retrospective protocols are fraught with error. I was walking down the hall and asked a colleague how he was doing. I thought he said "hot" but I wasn't sure. I asked him what he said. He had no idea. He guessed that he said "I'm fine thank you." Clearly, this could not have been it - it sounds nothing like "hot."
What he did, according to retrospective protocol studies, is search his schema for a logical or typical way to answer the question, rather than his memory of what he really said. This happens a lot in retrospective protocols. Instead of reported what they were thinking at the time, users develop rational explanations that often do not correspond with reality. Often, what they were really thinking is not logical or easy to articulate. And also hard to remember, even soon after.
Tuesday, July 18, 2006
Wednesday, July 12, 2006
Cleanflicks
Wow, two in one day. Are you guys lucky!!!
I just read about a Federal Court decision that ruled against Cleanflicks et al. They are no longer allowed to edit DVDs of movies to remove the sex and violence. One of the key issues was whether the modified movies were transformative (added in value) or derivative (just different). The court found that removing content can not add value.
From a Human Factors point of view, I find these totally against everything I know. How many web sites have you improved by removing clutter, outdated content, superfluous animation or graphics, etc? The judges need a good HF course!!!!
I just read about a Federal Court decision that ruled against Cleanflicks et al. They are no longer allowed to edit DVDs of movies to remove the sex and violence. One of the key issues was whether the modified movies were transformative (added in value) or derivative (just different). The court found that removing content can not add value.
From a Human Factors point of view, I find these totally against everything I know. How many web sites have you improved by removing clutter, outdated content, superfluous animation or graphics, etc? The judges need a good HF course!!!!
RFID for bartenders
Sorry I have been away for so long, but I was waiting for something good to discuss. Boy did I find it.
There is a new RFID device that attaches to liquor bottles. By measuring the angle and duration of each pour, it measures how much was added to a drink. It is connected to the cash register, so it actually knows which drinks are being poured too. It can determine if bartenders are under or over pouring and it even has a warning message for consistent errors. The warning is just a beep, so they need to work on the human factors of this. But talk about instant feedback!!!!
There is some good math behind the device for those of you in doubt. It knows what the shape and size of the bottle is, so it can change its predictions based on how much has been poured from the bottle so far. And when the bottle is empty, it can recalibrate its estimates to increase accuracy even more - although this info can only be used for long term modeling of bartenders, not the immediate feedback (unless the whole bottle is poured at once).
From a HF point of view, this is cool in terms of instant feedback. To learn, telling bartender once a month that he/she overpours doesn't help. But telling him/her that he just overpoured the Creme de Menthe bottle is much more useful, because he/she can adjust the way he/she pours that particular bottle shape.
From an IE point of view, this is cool in terms of real time performance measurement and feedback - with the goal of improvement. It also adds some security because the bartender can't pour free drinks for friends (unless there is a button for that on the cash register).
I would have never thought of this one - what will they come up with next!!!
There is a new RFID device that attaches to liquor bottles. By measuring the angle and duration of each pour, it measures how much was added to a drink. It is connected to the cash register, so it actually knows which drinks are being poured too. It can determine if bartenders are under or over pouring and it even has a warning message for consistent errors. The warning is just a beep, so they need to work on the human factors of this. But talk about instant feedback!!!!
There is some good math behind the device for those of you in doubt. It knows what the shape and size of the bottle is, so it can change its predictions based on how much has been poured from the bottle so far. And when the bottle is empty, it can recalibrate its estimates to increase accuracy even more - although this info can only be used for long term modeling of bartenders, not the immediate feedback (unless the whole bottle is poured at once).
From a HF point of view, this is cool in terms of instant feedback. To learn, telling bartender once a month that he/she overpours doesn't help. But telling him/her that he just overpoured the Creme de Menthe bottle is much more useful, because he/she can adjust the way he/she pours that particular bottle shape.
From an IE point of view, this is cool in terms of real time performance measurement and feedback - with the goal of improvement. It also adds some security because the bartender can't pour free drinks for friends (unless there is a button for that on the cash register).
I would have never thought of this one - what will they come up with next!!!
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