Summary
Ch8 - An Obsolete Culture
The author criticizes the distance between visual designers and program developers in software citing that this is amajor problem for the end user. He specifically takes several shots at Microsoft, specifically citing their Explorapedia project. He feels that programmers are incapable of designing correctly because they take too many short cuts that save them time instead of focusing on the end user. Also, because of Microsoft's success, others will try to implement it.
He also cites Sagent Technology as problem riddled company. Each person in the company tends to think the general customer is like the ones they interact with. Product management people think general customers need hand holding, senior developers think general customers are seasoned vets, etc. It's like the 3 blind men and the elephant story.
He goes on to say that the mentalities of today's programmers are obsolete as well, with focus on putting little strain on the processor at expense of the user not taking into account the vast advances in technology in the last few decades.
Part IV - Interaction Design is Good Business
Ch9 - Designing for Pleasure
In his company he implements a new way of thinking. He has his teams think up personas for a typical end user. They imagine everything about the person and then design the software with them in mind calling them hypothetical archetypes. His view is that logic would tell us to design broadly to accomodate as many users as possible and that "Logic is wrong. You will have far greater success by designing for a single person." He states that software should be like cars in that there are several models of the same thing and the user picks which fits them best.
Also, we're to realize that no single user fits the "average" user definition or fits snuggly into categories of users. (ex. no one is really completely tech illiterate). Also, designing for a specific user puts an end to discussion about what features should or should not be implemented.
Projects should cater to fixed set of personas with one person being the main focus of the personas and having his needs take precedence over the others.
The case study was of Sony Trans Com's P@ssport which was an In-Flight Entertainment product that brought Video on Demand to TV's in the back of the seat in front of passengers. The interface required 6 clicks to get to a movie and then if you decided you didn't want it, it would require 6 clicks to get back up. Touch screen was an intuitive solution because the screen was at arms length but constant clicking and tapping would make the person in front of you angry with incessant tapping on the back of their head.
They created 4 passenger personas and 6 airline worker personas. The old crotchety passenger became their primary persona. As a result, a physical turn knob was instantiated that resembled a radio knob and was intuitive for Clevis.
Ch10 - Designing for Power
"The essence of good interaction design is to devise interactions that let users
achieve their practical goals without violating their personal goals."
Basically, don't make the user feel stupid. Also, don't confuse tasks and goals. If your goal is to rest, you must first finish all your homework. Goal is rest, task is homework. Goals stay the same, but tasks change with technology. Ex. getting home is the goal. In 1850 you would bring a gun and a wagon. In 2010 you get on a plane and leave the gun. For both the goal is to get home, the tasks change. Goal is the end, task is the means.
The author pushes for goal directed design over task directed design. Also, strive to satisfy personal goals before practical goals. Having the user not feel stupid and get a lot done should take precedence over providing the user with tons of features.
He differs between Personal goals(goals of the end user), Coporate goals(goals of the company), Practical goals(goals that bridge this gap), and False goals(goals that shouldn't be considered(easing software creation, saving memory, speed up data entry, etc).
Software should function somewhat like a human should toward other humans. It should be friendly and polite meaning that it should be forgiving of errors and serve when possible, demanding minimal sacrifice from the user.
Some examples are below:
Polite software is interested in me
Polite software is deferential to me
Polite software is forthcoming
Polite software has common sense
Polite software anticipates my needs
Polite software is responsive
Polite software is taciturn about its personal problems
Polite software is well informed
Polite software is perceptive
Polite software is self-confident
Polite software stays focused
Polite software is fudgable
Polite software gives instant gratification
Polite software is trustworthy
The case study for this chapter was Elemental Drumbeat, a software for creating dynamic, databased-back websites. The problem was that their target audience was composed of two completely different personas, one that was very artsy and one that was techy. As a result, the coders tended to code towards the techy guy's needs. Only a few companies had targeted the artsy type so the solution was to provide more power for the artsy type than they were familiar with, but this only meant that the artsy type would be more dependent on the techy type which was a turn off. With advances in the web, it was necessary for both to work together so the program had two interfaces, one for the artsy webmaster and one for the techy programmer.
Ch11 - Designing for People
scenario - concise description of a persona using a software-based product to achieve a goal.
Scenarios
daily use - frequently performed
necessary use - must be performed but not frequently
edge case - anomalies(can usually be ignored but a lot of times isn't)
inflecting the interface - a technique for making a program easier to use but not sacrificing functionality
- offering only the functions that are necessary when they are necessary
perpetual intermediates - most people are not beginners or experts but are perpetually in between
Part V - Getting Back into the Driver's Seat
Ch12 - Desperately Seeking Usability
Ch13 - A Managed Process
Ch14 - Power and Pleasure
Tuesday, March 23, 2010
Monday, March 22, 2010
Scratch Input: Creating Large, Inexpensive, Unpowered and Mobile Finger Input Surfaces
Authors
Participants were shown how to use the scratch input system and then participants used a program which told them which gesture to produce. Each participant repeated each gesture 5 times for a total of 30 trials per participants(15 participants).
The results are shown in the above box. The results were sufficient for a proof of concept for the use of scratch as a source of input for computers.
Discussion
At first I was incredibly skeptical about this research. I thought about how ridiculous it would be for people to scratch things in order to manipulate their computers. However, the video definitely sold me on the concept. Installing just a few of these cheap microphones around your house could transform nearly every surface into a computer input console. Every wall, desk, or even your car's dashboard or steering wheel could be used as an input device. I will say though that the success rates will probably need to be much higher for introduction into the mass market. Having a gesture wrongly categorized 1 out of every 5 or 10 times is not satisfactory for any mass distribution.
Chris Harrison Scott E. Hudson
Human-Computer Interaction Institute
Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213
{chris.harrison, scott.hudson}@cs.cmu.edu
Summary
Scratch as a computer input has never really been exploited on a mass scale before. Scratching a surface such as wood, paint, or fabric produces a high frequency sound that is actually unique to the gesture that it corresponds with.
These sounds are better propagated through the material itself rather than the air. For instance, if you scratch the surface of your desk you will be able to hear it audibly with some clarity just as you would hear someone next to you talking. However, if you put your ear to the surface of the desk the sound becomes amplified and the effects of outside noise is minimal in the sound that you hear. Because sound is preserved so well in dense materials, gestures from several meters away can be accurately recognized.
Using a microphone attached to a stethoscope and a high pass filter to remove noise, the frequency graph of the sound input can be constructed and categorized using any decision making tree. These gestures can then correspond to specific actions in a computing environment such launching and exit programs, silencing music players, increasing/decreasing volume, etc. Nearly every dense surface could be turned into an input device including cell phones, tables, and walls.
Participants were shown how to use the scratch input system and then participants used a program which told them which gesture to produce. Each participant repeated each gesture 5 times for a total of 30 trials per participants(15 participants).
The results are shown in the above box. The results were sufficient for a proof of concept for the use of scratch as a source of input for computers.
Discussion
At first I was incredibly skeptical about this research. I thought about how ridiculous it would be for people to scratch things in order to manipulate their computers. However, the video definitely sold me on the concept. Installing just a few of these cheap microphones around your house could transform nearly every surface into a computer input console. Every wall, desk, or even your car's dashboard or steering wheel could be used as an input device. I will say though that the success rates will probably need to be much higher for introduction into the mass market. Having a gesture wrongly categorized 1 out of every 5 or 10 times is not satisfactory for any mass distribution.
Sunday, March 21, 2010
Predictive Text Input in a Mobile Shopping Assistant: Methods and Interface Design
Authors
Petteri Nurmi, Andreas Forsblom,
Patrik Floreen
Helsinki Institute for Information
Technology HIIT
Department of Computer Science, P.O. Box
68, FI-00014 University of Helsinki, Finland
firstname.lastname@cs.helsinki.fi
Peter Peltonen, Petri Saarikko
Helsinki Institute for Information
Technology HIIT
P.O. Box 9800, FI-02015 Helsinki
University of Technology TKK, Finland
firstname.lastname@hiit.fi
Summary
The usage of text predictions in creating shopping list was studied in this paper. They compiled an auto-generated list of 10K shopping lists to create their dictionary of suggestible words. They then implemented 8029 association rules assorted by their confidence. This alters the listing of the suggested words so that it fits the user rather than just listing them alphabetically. For instance, if the user types "cereal" and the user types the letter 'm', the program would suggest the word "milk" before listing the word "macaroni".
Petteri Nurmi, Andreas Forsblom,
Patrik Floreen
Helsinki Institute for Information
Technology HIIT
Department of Computer Science, P.O. Box
68, FI-00014 University of Helsinki, Finland
firstname.lastname@cs.helsinki.fi
Peter Peltonen, Petri Saarikko
Helsinki Institute for Information
Technology HIIT
P.O. Box 9800, FI-02015 Helsinki
University of Technology TKK, Finland
firstname.lastname@hiit.fi
Summary
The usage of text predictions in creating shopping list was studied in this paper. They compiled an auto-generated list of 10K shopping lists to create their dictionary of suggestible words. They then implemented 8029 association rules assorted by their confidence. This alters the listing of the suggested words so that it fits the user rather than just listing them alphabetically. For instance, if the user types "cereal" and the user types the letter 'm', the program would suggest the word "milk" before listing the word "macaroni".
The user study was done using mobile devices equipped with text prediction and without(the control group). Within these groups the users were also asks to complete entering their shopping lists with either both their hands or with only one hand. The participants were given candy for being in the study.
The results of the study showed that users would input words at about 5 wpm faster than without text prediction. This result was even faster for people typing with two hands.
Discussion
The user study in this paper was hilarious! They gave the participants candy? Really? Don't most studies actually pay their participants? Also, it said that one participant was removed from the study because of their "substantially high typing error rate". I don't really understand why they decided to test the difference between one handed and two handed typing. It seemed like an arbitrary test to create further useless information.
From Geek to Sleek: Integrating Task Learning Tools to Support End Users in Real-World Applications
Authors
Aaron Spaulding, Jim Blythe, Will Haines, Melinda Gervasio
Artificial Intelligence Center
SRI International
333 Ravenswood Ave.
Menlo Park, CA 94025
{spaulding, haines, gervasio}@ai.sri.com
USC Information Sciences Institute
4676 Admiralty Way
Marina del Rey, CA 90292
blythe@isi.edu
Summary
These researches combined forces to create ITL, an integrated task learning system. Basically it aims to provide a more user friendly script creation for the average end user. They wanted to make something that was not nit-picky as macro recorders as well.
They integrated their technology with two currently existing military software applications called LAPDOG and Tailor. Initial versions were disliked by users and the product was updated to adjust to their suggestions.In addition to letting users specify a particular set of scripted steps, the program let the users edit, copy, and paste scripts as well. In the end, they found that their product does in fact increase productivity because it automates repetitive tasks for the users.
Discussion
My favorite line was "this format was immediately derided as 'a bunch of geek [stuff]' by our users". I may have actually chuckled out loud a little to see those brackets in a scholarly paper. Also, considering the simplicity of the study's topic I understand why this was labeled under the "short" papers list.
Aaron Spaulding, Jim Blythe, Will Haines, Melinda Gervasio
Artificial Intelligence Center
SRI International
333 Ravenswood Ave.
Menlo Park, CA 94025
{spaulding, haines, gervasio}@ai.sri.com
USC Information Sciences Institute
4676 Admiralty Way
Marina del Rey, CA 90292
blythe@isi.edu
Summary
These researches combined forces to create ITL, an integrated task learning system. Basically it aims to provide a more user friendly script creation for the average end user. They wanted to make something that was not nit-picky as macro recorders as well.
They integrated their technology with two currently existing military software applications called LAPDOG and Tailor. Initial versions were disliked by users and the product was updated to adjust to their suggestions.In addition to letting users specify a particular set of scripted steps, the program let the users edit, copy, and paste scripts as well. In the end, they found that their product does in fact increase productivity because it automates repetitive tasks for the users.
Discussion
My favorite line was "this format was immediately derided as 'a bunch of geek [stuff]' by our users". I may have actually chuckled out loud a little to see those brackets in a scholarly paper. Also, considering the simplicity of the study's topic I understand why this was labeled under the "short" papers list.
Pulling Strings from a Tangle: Visualizing a Personal Music Listening History
Authors
Dominikus Baur
Media Informatics, University of Munich
Munich, Germany
dominikus.baur@ifi.lmu.de
Andreas Butz
Media Informatics, University of Munich
Munich, Germany
andreas.butz@ifi.lmu.de
Summary
Several methods for helping music listeners create a playlist are currently implemented. Most mp3 players utilize ID3 tags which contain album, artist, year, genre, etc information. While this information allows the user to quickly utilize and find particular songs, playlist creation requires intimate knowledge of the actual music that lies the behind the ID3 tags. Others such as Pandora, have utilized machine learning techniques to categorize songs and base future suggested songs off of the machine's recommendations. Still others, such as Last.fm, study past listening histories across thousands and thousands of users and based on the similarities between those and the user's listening history suggests future songs.
To obtain the data needed for the project, they used Audioscrobbler, Last.fm's tracking software. Using this data, they created three different types of visualizations. First is the Tangle, which is a global view of the listening history. Outer loops represent anomalies or songs that were listened to without correlations to other songs. Songs that are close to other songs are relatively similar and thickness of a line represents how often a particular sequence of song was listened to.
The second visualization algorithm is strings, which shows, in a very ordered and organized way, past listening sequences.
The third visualization is called knots and it shows the user which songs are present in several strings to give the user a better visualization of which songs they most listen to.
Users can then determine paths that their music should take along with specifying a "novelty" factor which determines how unusual the path between waypoints is.
Discussion
This sounds like it would be a really cool but novel idea for the music culture. It would be equivalent to the visualizations that iTunes and Windows Media Player offer. They're really cool to look at but no one really uses it more than a couple times. I could be wrong because I haven't exactly used it and unlike those visualizations offered by Windows and Apple, Tangle actually offers some practical usage. The 1,000 song limit is a bit of a problem though.
Dominikus Baur
Media Informatics, University of Munich
Munich, Germany
dominikus.baur@ifi.lmu.de
Andreas Butz
Media Informatics, University of Munich
Munich, Germany
andreas.butz@ifi.lmu.de
Summary
Several methods for helping music listeners create a playlist are currently implemented. Most mp3 players utilize ID3 tags which contain album, artist, year, genre, etc information. While this information allows the user to quickly utilize and find particular songs, playlist creation requires intimate knowledge of the actual music that lies the behind the ID3 tags. Others such as Pandora, have utilized machine learning techniques to categorize songs and base future suggested songs off of the machine's recommendations. Still others, such as Last.fm, study past listening histories across thousands and thousands of users and based on the similarities between those and the user's listening history suggests future songs.
To obtain the data needed for the project, they used Audioscrobbler, Last.fm's tracking software. Using this data, they created three different types of visualizations. First is the Tangle, which is a global view of the listening history. Outer loops represent anomalies or songs that were listened to without correlations to other songs. Songs that are close to other songs are relatively similar and thickness of a line represents how often a particular sequence of song was listened to.
The second visualization algorithm is strings, which shows, in a very ordered and organized way, past listening sequences.
The third visualization is called knots and it shows the user which songs are present in several strings to give the user a better visualization of which songs they most listen to.
Discussion
This sounds like it would be a really cool but novel idea for the music culture. It would be equivalent to the visualizations that iTunes and Windows Media Player offer. They're really cool to look at but no one really uses it more than a couple times. I could be wrong because I haven't exactly used it and unlike those visualizations offered by Windows and Apple, Tangle actually offers some practical usage. The 1,000 song limit is a bit of a problem though.
Parakeet: A Continuous Speech Recognition System for Mobile Touch-Screen Devices
Authors
Keith Vertanen and Per Ola Kristensson
Cavendish Laboratory, University of Cambridge
JJ Thomson Avenue, Cambridge, UK
{kv277, pok21}@cam.ac.uk
Summary
This paper explores the possibility of speech recognition as a way to input text on a touchscreen device. Speech recognition has generally been blocked from entering the mobile phone arena because of the processor resources required to effectively translate from speech to text. Not only does it normally require far more resources than the processor can spare, the result is usually very erroneous (ie Google Voice voicemail transcriptions). However, despite the setbacks speech to text is very attractive as a text input method because users are already familiar with speaking so no training is involved and users can typically speak up to 200 wpm which far surpasses even the best typists (especially mobile typists).
The researchers built Parakeet to address this issue. When designing it they followed 4 design principles. First, they were to avoid cascading errors involving phase offset. They did this by using a multi-modal speech interface. Second, they needed to exploit the speech recognition hypothesis space. They did this by offering the user several choices from several recognition hypotheses. Third, they must implement efficient and practical interaction by touch. They did this by implementing an interface that only required touch so that it could be used with or without a stylus. Lastly, the design should support fragmented interaction. In other words, the device should anticipate the ADD tendencies of its user. They did this by offering text predictions and alerting the user audibly that their speech is done translating to text.
Users used the device both while seated indoors and walking outdoors to test the effectiveness and mobility of their product. They were given a fixed set of sentences between 8 and 16 words in length to say in 30 minute trials. Once they said a sentence they were to try and correct the sentence using Parakeet's correction interface before moving on to the next sentence. On average, participants completed 41 sentences inside and 27 sentences outside during the 30 minute trials.
Results indicated that participants managed an average of 18 wpm indoors and 13 wpm outdoors while utilizing correction.
Discussion
I don't really know what the average typing speed of phone texters is but I would imagine that 18wpm is a little on the slow side for texters, especially those that text frequently. Obviously, this rate would be vastly improved if the translation algorithm was more accurate, but even the almighty Google is far from achieving that feat.
Keith Vertanen and Per Ola Kristensson
Cavendish Laboratory, University of Cambridge
JJ Thomson Avenue, Cambridge, UK
{kv277, pok21}@cam.ac.uk
Summary
This paper explores the possibility of speech recognition as a way to input text on a touchscreen device. Speech recognition has generally been blocked from entering the mobile phone arena because of the processor resources required to effectively translate from speech to text. Not only does it normally require far more resources than the processor can spare, the result is usually very erroneous (ie Google Voice voicemail transcriptions). However, despite the setbacks speech to text is very attractive as a text input method because users are already familiar with speaking so no training is involved and users can typically speak up to 200 wpm which far surpasses even the best typists (especially mobile typists).
The researchers built Parakeet to address this issue. When designing it they followed 4 design principles. First, they were to avoid cascading errors involving phase offset. They did this by using a multi-modal speech interface. Second, they needed to exploit the speech recognition hypothesis space. They did this by offering the user several choices from several recognition hypotheses. Third, they must implement efficient and practical interaction by touch. They did this by implementing an interface that only required touch so that it could be used with or without a stylus. Lastly, the design should support fragmented interaction. In other words, the device should anticipate the ADD tendencies of its user. They did this by offering text predictions and alerting the user audibly that their speech is done translating to text.
Users used the device both while seated indoors and walking outdoors to test the effectiveness and mobility of their product. They were given a fixed set of sentences between 8 and 16 words in length to say in 30 minute trials. Once they said a sentence they were to try and correct the sentence using Parakeet's correction interface before moving on to the next sentence. On average, participants completed 41 sentences inside and 27 sentences outside during the 30 minute trials.
Results indicated that participants managed an average of 18 wpm indoors and 13 wpm outdoors while utilizing correction.
Discussion
I don't really know what the average typing speed of phone texters is but I would imagine that 18wpm is a little on the slow side for texters, especially those that text frequently. Obviously, this rate would be vastly improved if the translation algorithm was more accurate, but even the almighty Google is far from achieving that feat.
“My Dating Site Thinks I’m a Loser”: Effects of Personal Photos and Presentation Intervals on Perceptions of Recommender Systems
Authors
Shailendra Rao
Stanford University
shailo@stanford.edu
Tom Hurlbutt
Stanford University/ Intuit
hurlbutt@cs.stanford.edu
Clifford Nass
Stanford University
nass@stanford.edu
Nundu JanakiRam
Stanford University/ Google
nundu@google.com
Summary
This study explores the effects that bad recommendations from recommender systems can have on the individuals that use those systems. For example, if someone's TiVo mistakenly thinks that they are gay and recommends television programs that would appeal to those that are gay, then the user might erroneously watch more "guy" programming to compensate for their miscategorization.
The situation that is explored in this paper is online dating. People will lie about themselves, omit information about themselves, or submit misleading pictures of themselves to present their "ideal" self. Giving false information like this only skews the system and matches users with people who differ substantially from what they were expecting. This leads to frustration for both parties involved and now the dating site cannot effectively carry out its purpose or end goal.
The study used a new algorithm called MetaMatch, which took the answers to a set of personal questions and used them to purposefully suggest undesirable matches. After receiving the matches, the participants rated their recommendations and answered a post questionnaire.
During the questionnaire, half of the participants had their submitted picture posted next to the questions as they answered them and the other half had no picture. Also, half of the participants were shown 4 possible (undesirable) matches after each set of 10 questions and the other half were only shown matches after they finished the entire questionnaire.
The results of the post questionnaire are represented in the graphs above. The study found that displaying a personal photo can have a stabilizing effect amongst participants. Having an element of self-reflection during the questionnaire tended to make the participants not change their answers to the questions to compensate for their bad matches. Also, intermediate recommendations tended to make the user change how much they approved of the bad match at the end of the questions.
Discussion
I thought this study was one of those studies that proves something that you already suspect. It would be interesting to see what online dating companies do with this information or with more indepth studies. I do feel like only testing 56 people was a bit small for the user study though. I would like to have seen a more exhaustive study that included thousands of participants.
Shailendra Rao
Stanford University
shailo@stanford.edu
Tom Hurlbutt
Stanford University/ Intuit
hurlbutt@cs.stanford.edu
Clifford Nass
Stanford University
nass@stanford.edu
Nundu JanakiRam
Stanford University/ Google
nundu@google.com
Summary
This study explores the effects that bad recommendations from recommender systems can have on the individuals that use those systems. For example, if someone's TiVo mistakenly thinks that they are gay and recommends television programs that would appeal to those that are gay, then the user might erroneously watch more "guy" programming to compensate for their miscategorization.
The situation that is explored in this paper is online dating. People will lie about themselves, omit information about themselves, or submit misleading pictures of themselves to present their "ideal" self. Giving false information like this only skews the system and matches users with people who differ substantially from what they were expecting. This leads to frustration for both parties involved and now the dating site cannot effectively carry out its purpose or end goal.
The study used a new algorithm called MetaMatch, which took the answers to a set of personal questions and used them to purposefully suggest undesirable matches. After receiving the matches, the participants rated their recommendations and answered a post questionnaire.
During the questionnaire, half of the participants had their submitted picture posted next to the questions as they answered them and the other half had no picture. Also, half of the participants were shown 4 possible (undesirable) matches after each set of 10 questions and the other half were only shown matches after they finished the entire questionnaire.
The results of the post questionnaire are represented in the graphs above. The study found that displaying a personal photo can have a stabilizing effect amongst participants. Having an element of self-reflection during the questionnaire tended to make the participants not change their answers to the questions to compensate for their bad matches. Also, intermediate recommendations tended to make the user change how much they approved of the bad match at the end of the questions.
Discussion
I thought this study was one of those studies that proves something that you already suspect. It would be interesting to see what online dating companies do with this information or with more indepth studies. I do feel like only testing 56 people was a bit small for the user study though. I would like to have seen a more exhaustive study that included thousands of participants.
The TeeBoard: an Education-Friendly Construction Platform for E-Textiles and Wearable Computing
Authors
Grace Ngai, Stephen C.F. Chan, Joey C.Y. Cheung, Winnie W.Y. Lau
{ csgngai, csschan, cscycheung, cswylau }@comp.polyu.edu.hk
Department of Computing
Hong Kong Polytechnic University
Kowloon, Hong Kong
Summary
Wearable computing and e-textiles is an emerging field in contemporary fashion. However, existing technology is so complex that it is neither affordable or feasible for the average hobbyist or consumer. The solution for this problem, presented by the above researchers, is the TeeBoard, a constructive platform that aims to "lower the floor" for e-textiles and explores the possibility of integrating the technology into the education field as a teachable tool.
For e-textile technology to be more widely adopted as an educational tool it should be robust for everyday use and rough handling, it should have large error tolerance, and a shallow learning curve. The current state of e-textile technology does not yet satisfy these requirements.
The researchers set out several goals for their project in addition to solving the above listed problems: 1) capabilities of the materials used should be as close to their electrical equivalents as possible, 2) the construction platform should be able to be used by users of all skill levels, and 3) the platform should be easily reconfigurable and debuggable.
The TeeBoard was the solution they came up with, a wearable breadboard that could easily configured to the user's wishes. The shirt uses a Arduino Lilypad microcontroller for processing of signals and a conductive thread instead of wires to achieve the robustness necessary for everyday wear and tear.
The shirts were used with several test groups. Groups were given simple tasks and then incrementally harder tasks to test the effectiveness of the product. The results showed that the TeeBoard did in fact meet its requirements and students were more interested in computational and electronic designs.
Discussion
This is an interesting concept for more interactive applications of electronic theory. I think the main problem with the A&M program is that application is not stressed in a tactile way. Granted we do use breadboards and circuits to illustrate concepts, but rarely are the concepts illustrated in a way that it would be used in the real world. I would love to see more interactive solutions such as the one in this paper in the educational system.
The only problem I saw with the user study was that it was tested amongst college classes that already had significant background in electronic theory. I would have liked to see them test this product amongst high school settings where students are not as familiar with electronic theory.
Grace Ngai, Stephen C.F. Chan, Joey C.Y. Cheung, Winnie W.Y. Lau
{ csgngai, csschan, cscycheung, cswylau }@comp.polyu.edu.hk
Department of Computing
Hong Kong Polytechnic University
Kowloon, Hong Kong
Summary
Wearable computing and e-textiles is an emerging field in contemporary fashion. However, existing technology is so complex that it is neither affordable or feasible for the average hobbyist or consumer. The solution for this problem, presented by the above researchers, is the TeeBoard, a constructive platform that aims to "lower the floor" for e-textiles and explores the possibility of integrating the technology into the education field as a teachable tool.
For e-textile technology to be more widely adopted as an educational tool it should be robust for everyday use and rough handling, it should have large error tolerance, and a shallow learning curve. The current state of e-textile technology does not yet satisfy these requirements.
The researchers set out several goals for their project in addition to solving the above listed problems: 1) capabilities of the materials used should be as close to their electrical equivalents as possible, 2) the construction platform should be able to be used by users of all skill levels, and 3) the platform should be easily reconfigurable and debuggable.
The TeeBoard was the solution they came up with, a wearable breadboard that could easily configured to the user's wishes. The shirt uses a Arduino Lilypad microcontroller for processing of signals and a conductive thread instead of wires to achieve the robustness necessary for everyday wear and tear.
The shirts were used with several test groups. Groups were given simple tasks and then incrementally harder tasks to test the effectiveness of the product. The results showed that the TeeBoard did in fact meet its requirements and students were more interested in computational and electronic designs.
Discussion
This is an interesting concept for more interactive applications of electronic theory. I think the main problem with the A&M program is that application is not stressed in a tactile way. Granted we do use breadboards and circuits to illustrate concepts, but rarely are the concepts illustrated in a way that it would be used in the real world. I would love to see more interactive solutions such as the one in this paper in the educational system.
The only problem I saw with the user study was that it was tested amongst college classes that already had significant background in electronic theory. I would have liked to see them test this product amongst high school settings where students are not as familiar with electronic theory.
PrintMarmoset: Redesigning the Print Button for Sustainability
Authors
Jun Xiao
Hewlett-Packard Laboratories
Palo Alto, CA USA
jun.xiao2@hp.com
Jian Fan
Hewlett-Packard Laboratories
Palo Alto, CA USA
jian.fan@hp.com
Summary
This paper focuses on Sustainable Interaction Design, design which aims to alleviate the problems associated with dwindling natural resources by shifting from production of new products to production of sustainable growth products. Specifically, they focus on redesigning the print button to minimize erroneous prints and other various paper wastes and in turn, promote sustainability.
Users in the study were studied to reveal what and how often they printed and the results were critically examined to draw conclusions. The found that users printed information that was digitally available because it saved time(in the case of printing a map vs using a GPS), it was easier to user(in the case of printing a pdf instead of viewing it on screen), it signified importance(in the case of printing a website instead of emailing a link), and the information was volatile and needed to be preserved(in the case of news articles being constantly updated). These cases were generalized to say that printing served four main functions: display, delivery, sharing, and storage.
While this paper did not aim to resolve these problems, it did attempt to minimize the problem of erroneous or unnecessary prints. People reported printing out webcontent because it was necessary but only to find their printout riddled with web advertisements or malformatting which rendered the printout useless and therefore thrown away as waste.
Their goal was to create a solution that required 1) require neither developers to modify existing web sites nor users to change existing print flow; 2) require the least amount of user input effort, if not zero; 3) offer flexibility that allows users to choose what to print in addition to pre-defined filter or template; 4) maintain a history of print activities for collecting and organizing web clips; 5) raise awareness of the tool among people and build a “green” community around it.
The resulting solution was PrintMarmoset, a Firefox extension that allowed the user to better select what needed to be printed. The user would click the icon for the extension, "stroke" through webcontent that was unnecessary, and then click the icon again to print what was selected.
People commented that PrintMarmoset is WYSIWYG and the UI was easy to use. The authors commented that the tool did not satisfy all users but that that was an impossible task to accomplish.
Discussion
This seems like an awesome idea to be honest. Many times have I wanted to print a website only to see that the advertisements have completely ruined the layout of the print or have offset the layout to produced unneeded blank pages with just the website printed at the bottom. These pages are then thrown away as a wasted print and paper is subsequently unnecessarily wasted. I'll have to try this extension out to see just how user friendly it is, but the concept itself seems hopeful.
Jun Xiao
Hewlett-Packard Laboratories
Palo Alto, CA USA
jun.xiao2@hp.com
Jian Fan
Hewlett-Packard Laboratories
Palo Alto, CA USA
jian.fan@hp.com
Summary
This paper focuses on Sustainable Interaction Design, design which aims to alleviate the problems associated with dwindling natural resources by shifting from production of new products to production of sustainable growth products. Specifically, they focus on redesigning the print button to minimize erroneous prints and other various paper wastes and in turn, promote sustainability.
Users in the study were studied to reveal what and how often they printed and the results were critically examined to draw conclusions. The found that users printed information that was digitally available because it saved time(in the case of printing a map vs using a GPS), it was easier to user(in the case of printing a pdf instead of viewing it on screen), it signified importance(in the case of printing a website instead of emailing a link), and the information was volatile and needed to be preserved(in the case of news articles being constantly updated). These cases were generalized to say that printing served four main functions: display, delivery, sharing, and storage.
While this paper did not aim to resolve these problems, it did attempt to minimize the problem of erroneous or unnecessary prints. People reported printing out webcontent because it was necessary but only to find their printout riddled with web advertisements or malformatting which rendered the printout useless and therefore thrown away as waste.
Their goal was to create a solution that required 1) require neither developers to modify existing web sites nor users to change existing print flow; 2) require the least amount of user input effort, if not zero; 3) offer flexibility that allows users to choose what to print in addition to pre-defined filter or template; 4) maintain a history of print activities for collecting and organizing web clips; 5) raise awareness of the tool among people and build a “green” community around it.
The resulting solution was PrintMarmoset, a Firefox extension that allowed the user to better select what needed to be printed. The user would click the icon for the extension, "stroke" through webcontent that was unnecessary, and then click the icon again to print what was selected.
People commented that PrintMarmoset is WYSIWYG and the UI was easy to use. The authors commented that the tool did not satisfy all users but that that was an impossible task to accomplish.
Discussion
This seems like an awesome idea to be honest. Many times have I wanted to print a website only to see that the advertisements have completely ruined the layout of the print or have offset the layout to produced unneeded blank pages with just the website printed at the bottom. These pages are then thrown away as a wasted print and paper is subsequently unnecessarily wasted. I'll have to try this extension out to see just how user friendly it is, but the concept itself seems hopeful.
Tuesday, March 2, 2010
Emotional Design
"The problem is that we still let logic make decisions for us"
Sentences like this in the prologue of the book kind of scared me going into it. However, I did enjoy this book more than his previous work. It gave more insight into why certain technologies succeed over others despite offering the same or even less capabilities than their competition. I also enjoyed how spelled out the processes of what was happening when a person is introduced to a new product.
Honestly, I left reading the book with one desire in mind: I'd love to visit this guy's house. He kept referencing all the little things he has in his house and i think it would be so cool to just get to mess with it all one day.
Sentences like this in the prologue of the book kind of scared me going into it. However, I did enjoy this book more than his previous work. It gave more insight into why certain technologies succeed over others despite offering the same or even less capabilities than their competition. I also enjoyed how spelled out the processes of what was happening when a person is introduced to a new product.
Honestly, I left reading the book with one desire in mind: I'd love to visit this guy's house. He kept referencing all the little things he has in his house and i think it would be so cool to just get to mess with it all one day.
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