Response: Beyond “Social Protocols”: Multi-User Coordination Policies for Co-located Groupware

Summary:

This paper primarily discussed the role of social conventions in interaction on shared digital tabletops. The authors observed several interactions on a variety of applications that employed a shared environment. From here, the authors argued that social conventions are almost necessary for design in order to avoid numerous negative social situations. This includes situations where individuals control group context or individuals intentionally (or otherwise) manipulate another users content. To solve these types of situations, the authors devised a coordination policy for conflicts, where conflict type is based on either global (affects the whole application) or whole-element (affects a single object). For each category, they then specify what can or can’t be done by users within a social context.

Response:

While I see the point of this paper, I had very mixed feelings to it. On the one hand, the territoriality aspects of an application are important (as are social protocols), but I think given the nature of how interactive a digital tabletop is, I think perhaps maybe some new protocols should be defined. To me, the point of a digital tabletop is to collaborate and to explore (and that includes all the negative aspects as well). By limiting the freedom, I think the tabletop loses its utility. Overall however, there is some utility in the coordination policy, depending on the circumstances. In an application designed for children, the policies would fail because children need freedom. On the flip side, the policies for a business environment or shared work environment are more fitting.

Summary Response Week 7: Territoriality

CPSC 601.25 Week 7 Part 2

Papers

In this response I will discuss a paper regarding territoriality in physical tabletop applications, territoriality in digital tabletops and how design techniques impact groupware that involves tabletops.

Traditional Territoriality

Any collaborative human work project involves territoriality and investigating how people interact on traditional tables, doing specific or general tasks, is a good source of theories to describe how they will interact with more modern tabletop applications. In the paper "Territoriality in Collaborative Tabletop Workspaces" the researchers studies a large group (n=18) interacting while playing various boardgames. They found people would opportunistically use the space made available for them, which is consistent with common sense expectations. The participants also seemed to partition an area 'for themselves' which would be expected as well. In another study they asked three groups to layout a room plan which is a more cognitively challenging task. They found that people divide these areas into storage areas, group territories and personal areas. They describe how these findings and some specific findings on how these interact should motivate designers of systems

Incorporating Tabletops into Groupware

In the last paper called "Three's Company", the researchers explored how tabletops could be incorporated into a groupware application, which had a shared work space (via the tables), video cameras to provide visual feedback of the other participators and audio feedback to aid communications. To communicate feedback on the tabletop itself, the internal cameras in the Surface were used to capture pictures of arm movements which were displayed semi-transparently. Using this setup the researchers evaluate the interaction of three spaces, person space, task space and reference space. In the first study they tried two configurations for three person interaction, same side and around-the-table. From this they found that each configuration has different advantages - basically that users seem to prefer same side but that that approach sometimes leads to confusion as the different arm shadows occlude each other. In the second study they used a orientation-free task and concluded that people did not really use 'person space' and did not often glance at the users outside the communication phase of the work. Which makes sense as people would likely be looking down and away from the cameras (or the people) if they were working together in real life.

When constructing applications that attempt to mimic or replace physical interactions, certain key properties of the activity are often lost. To minimize this we try to mimic the physical interactions closely, for example, many of the interaction styles on tabletops mimic interfaces that might exist in physical form. But when this copying is done we must observe carefully the physical interactions and make sure key elements aren't missing. Studies like those above attempt to capture this information and communicate to the designer.s

RE: Theory-Driven Design Strategies for Technologies that Support Behavior Change in Everyday Life

Summary

Consolvo et al, argued in their paper that designing, what they termed as 'persuasive technologies ' that target long-term discretionary use throughout everyday life is challenging, especially when those technologies attempt to help individuals change their everyday behaviours. According to their hypothesis, this task of instigating or motivating behaviour change often remains challenging even when the individual wants to change. In presenting their work, they rely mostly on previous research, which focuses on how human behaviour and social functioning can be shaped and influenced, based on the a better understanding of the psychological principles at play. Their research draws mostly from the Goal-Setting Theory as espoused by Locke et al (2002) and the

Transtheoretical Model of Behaviour Change as proposed by Prochaska et al (1992). Other important references they drew from were Festinger and Goffman, two foremost researchers in the field of human psychology and how it influences everyday behaviour.

Opinion

Let's talk about this in the realm of HCI technologies. I believe that all successful - or seemingly successful - HCI designs and applications that target behaviour change, and are successful in so doing, are the ones that rely in fundamental principles of human psychology. For example, Festinger posited that technologies that strive to encourage lifestyle behaviour change must support fundamental impression management needs (backstage and front stage theory). An obvious example is facebook , which is alive and well and thriving because it encourages the psychological behaviour of impression management. Same with Twitter - which probably explains why celebrities will readily take to twitter instead of speaking to a reporter. Because they hold the reigns (backstage), they control the information output( front stage). It is human nature and stagemanship at its best. Another twitter analysis is that of followers and leaders - a fundamental behavioural psychology. The mass influx and acceptability of the twitter interface might look like behavioural change in terms of creating a new social normal but it is only a successful design because it taps into well-established human nature of mass followership and the tendency of a few to lead.

Google is also in same category. It plays on the inherent insatiable curiosity of human nature to know, to investigate, to sniff around. I call it a psychological thriller. HCI technologies that have succeeded do not target behavioural change (in they obvious sense) - they target well entrenched behavioural patterns in human nature. New technologies relying on old concepts. It works.

An online dating website is a typical HCI which employs the principles of human psychology into the design of its user interface, and has successfully( seemingly so) changed the behaviour of its users. Gone are the days of romantic affiliations through chance face to face meetings, or introductions through friends. Nowadays it has been reduced to a few mouse clicks on an a HCI application. But it is based on the principles of stagemanship: human natures always tries to show itself from the best side. It also plays to the psychology of possession, taking advantage of a situation. The list of criteria on most dating websites make it easy to narrow down choices. Also, the psychological principles of stage control - back stage, front stage - are at play. People who ordinarily would not talk about dating in real life, brazenly post their stuff online and even women, actively and aggressively search for men. A behaviour that is still frowned up in real life.

One Size Does Not Fit All: Applying the Transtheoretical Model to Energy Feedback Technology

The intention of the paper is provide a model that can help in building Energy Feedback Technologies that can motivate people to develop a more sustainable energy behaviour.
The Transtheoretical Model is a process of change of human being from the psychological perspective. The model has the following 5 stages and a person should be motivated differently according to the stage of change she is at:
Pre-contemplation: At this stage a person is unaware of the situation and unwilling to change their behaviour to accommodate the situation. The paper recommends that at this stage benefits of energy sustainable behaviours should be highlighted according to personal preferences. Another recommendation is presenting it with relevance to social norms,  e.g 85 % people of the neighbourhood recycle.
Contemplation: At this stage people are aware, but not active in participation. Therefore, by providing the pros of sustainable behaviour with regards to the benefit to the individual can motivate him to be active. For e.g, by walking to the office you can loose weight. Moreover, tell them the environmental impact of their inactive behaviour. Provide encouragement to every little sustainable action performed, and show the environmental impact. For e.g By switching off the monitors last night, these many trees were saved. Provide means to get further information on energy saving and impact.
Preparation: At this stage people are ready to incorporate the change in their lives, however, need a gradual plan to achieve sustainable energy consumption. Therefore, provide choices of goals to commit to and make them difficult as they progress. Provide means to connect to real energy mentors.
Action: At this stage people are active and can relapse--reinforcement of motivation is required to stay on track. Therefore, positive performance feedback should be provided immediately. Feedback should be personalized, that is, a person who seeks monitory benefits from the energy savings, should be shown how much he saved.
Maintenance: People at this stage seldom fall into relapse and have developed a norm of performing energy saving actions. Therefore, feedback should become less and people at this stage should be asked to become energy saving mentors. There should be independent ways of keeping track of ones goals and viewing them in various ways(Graphs) and provide means to keep a journal.

My View: I feel that this paper was very interesting, however, as said in the conclusion of the paper that people don't fall in exactly one stage at a time and they may not be sequential. However, it does give us an insight into different levels of acceptance to change by people and how to motivate them towards that change.

Response: One Size Does Not Fit All: Applying the Transtheoretical Model to Energy Feedback Technology Design

Summary

The focus of the paper is to motivate change in individuals' behaviors to be more energy sustainable to help against Global Warming. However, the current techniques that available technologies employ to motivate such changes are heavily generalized, "one-size'fits-it-all", and only informs rather than motivate.

The paper defines motivation as an internal condition, such as needing or wanting, that activates or energizes behavior.

They use The Transtheoretical Model, TTM, to identify the different stages of how behavior change occurs. The stages are:

1. Precontemplation - a person does not have any knowledge to change behaviors.
2. Contemplation - a person acknowledges that their behavior is a problem but may not be committed into changing it yet.
3. Preparation - a person is committed to change and take action.
4. Action - a person modifies their behavior intently.
5. Maintenance, relapse, recycling - a person tries to maintain the action or relapses back to an earlier stage.

In conjunct to TTM, they use MI or Motivational Interviewing, a client-centered counseling style, to facilitate behavioral change.

From here, the paper talks about different persuasive energy feedback technology and how they design for general consumption and tend to persuade people in different stages of behavioral stage and thus are not so effective.

To solve this, they propose a motivational framework based on TTM and gives goals, recommendations, and rationale for each stage of behavior change.

Precontemplation - “Plant the seed” to acknowledge problematic unsustainable behaviors

Contemplation - “Tip the balance” in favor of change

Preparation - Develop a plan that is acceptable, accessible and effective.

Action - Positively reinforce sustainable action and develop intrinsic motivations

Maintenance - Maintain durable behavior change

They then discuss a scenario and how their framework handles it through the different stages of behavioral change.

Reflection

While I was reading the different types of stages TTM states, I was actually thinking "What if a person is actually in different stages?" Having tried to have change a behavior of mine, I believe that a person may actually be in different stages or may even skip some of them.

I was also thinking that they should use a different form of visualization rather than plain text.

Then the paper puts these in the discussion/future-work section.

I personally agree with this paper about how feedback techniques are so generalized that they may are do not affect anyone as much as they could. Having a system that meets needs in individual units to a certain degree as far more potential to be effective.

Summary Response Week 5: Motivating Change

CPSC 601.25 Week 5 Response Part 2

Papers

In this response I will discuss a paper regarding the trans-theoretical model of personal change and another paper applying that problem to motivating change in energy consumptuon

Models

Borrowing from the field of psychology, researchers in "Theory Driven Design Strategies" attempt to provide a set of design strategies to support persuasive technologies. These are technologies aim at supporting people to change behavior. This question invariably involves psychology because we need rigorous definitions of behavior, behavior patterns, motivations and other terms and ideas. The researchers employed two models, the "trans-theoretical model of behavior change" and the "presentation of self in everyday life". The former model describes a set of steps a person goes through before they change their behavior and the latter a discussion about how people present themselves to the world. These models are used when providing guidelines as a reference point, to make the design strategies consistent with theory.

Guidelines

The authors suggest that persuasive technologies be designed so as to have the following properties.

1. Abstract and reflexive - that the data collected by the system be abstracted so users are able to reflect on it easily.
2. Unobtrusive - so users are not annoyed by the system.
3. Public - so that data can be made public without causing embarrassment or discomfort.
4. Aesthetic - so that the system is not visibly ugly.
5. Positive - the system should present encouragement or correctives positively
6. Controllable - so that the user can remove and edit data if they feel the need.

Some of these guidelines are common sensical and obvious. Other suggests are not obvious, such as abstracting the data, many systems in this way present data in a raw or raw-ish manner. Another interesting guideline is that the data be structure in such a way that it could be made public, but this is a hard guideline to follow. How exactly would this work?

A Specific Case

These design guidelines are applied to a certain degree in the second paper, which focuses on feedback in a whole class of persuasive technologies. The "One Size Does Not Fit All" paper analyzes a set of applications which attempt to motivate or persuade users to follow green energy habits or behaviors. In this paper the authors focus in a look specifically at how feedback is handled in these systems and correlate them to different psychological theories of motivation. Several different recommendations are made and a explained using these motivation theories and the TTM. These recommendations involve providing personal feedback, connecting the feedback to social norms for people in the pre-contemplation stage or supporting individually set goals for people in the preparation stage.

This is all very straightforward and probably correct, in as much as the psychological theories are correct. The problem becomes how the software is going to be put before users if they are not in the stage already defined - a person in the pre-contemplation stage is unlikely to download software that nags them about energy use. In order to persuade, people must actively use the software, something that might fall off as the person falls behind their goals. Looking more closely at how to accomplish behavioral change in a clinical sense might provide more useful material for aiding these persuasive technologies. See Beeminder and 'The Breakdown of Will" for examples.

Response: The Data Driven Life

This article was very interesting because it had many examples of self-tracking and analysis.
Initially, the paper reminds us that we do a lot of data collection and analysis in our jobs. Therefore, it isn't so weird if we do some numeric data collection for ourselves. Moreover importantly, this numeric data can be manipulated to extract meaningful information for ourselves or others.
Another idea is that the human behaviour is a mystery, that was explored earlier by the means of  thinking deep about ourselves and then writing about it as literature. Since, today we have newer technology that help measure, such as weight scales, accelerometer to track a runner movements, headbands to monitor sleep etc, why not use these tracking devices to monitor human behaviour and discover irregularities. Moreover, numeric data represents clear comparable results.
The most significant point raised in the paper is that each person is different form the other, therefore the goal is to discover something about yourself and not human beings in genenral. For example, there is this person diagnosed of a disease, and  doctors treated him as a standard case because they had treatment for the standard case. However, with tracking he can determine whether he is a standard case or not.
In addition, the paper found that its just not the sub-concious we are not aware of, we forget are actions as well. We can focus our attention to one or two things that we need to do, but self tracking devices can keep a track about us and aid us in remembering our actions and represent them as clear numeric results.  
However, tracking devices are unemotional and display results that show some bad behaviour in an unemotional way. Therefore, adding human-like reassurances to the results can help us overcome this problem.
Finally, tracking devices look weird today, however when they become common it will be accepted as a norm, a good example is the mobile phone.

RE: The Data-Driven Life

A journal is respectable. A spreadsheet is creepy.

I think this summarizes the whole point of Gray Wolf’s piece in the New York Times. The original quote was in past tense but I have paraphrased in the present tense, because the sentiment is still valid in the present tense.

It is one thing to keep informal record of one’s actions and activities; but it is another matter to allow minutiae data-keeping to infiltrate every crevice of our personal. It borders on the creepy. There is a reason why we are humans and not machines.

This is not to say that tracking does not have its benefits. Perhaps a more problem-focused, goal-oriented approach to tracking does a better service than the everyday slog where some individuals can decide to track the entire gamut of their daily activities, picking apart their lives in ways that are not beneficial to them. Everything a person tracks requires time and energy and some things are probably not worth the effort. If people want to change specific aspects of their behaviour or habits and need to explore the pattern, that seems reasonable, but to track every aspect of one’s daily life, where is the enjoyment in that?

As Gary Wolf rightly mentioned in his article, the data-collectors claim that their ultimate goal is to increase efficiency – to improve their productivities – and to eliminate shortcomings. Perhaps this point of view is rather narrow, ambiguous and, perhaps, unfathomable. Efficiency should imply rapid progress toward a known and targeted goal. For many self-trackers, the goal is unknown. Although they may take up tracking with a specific question in mind, they continue because they believe their numbers hold secrets that they think they cannot afford to ignore, including answers to questions they have not yet thought to ask.

When it comes to data analysis, I am of the opinion that less is more. Before I embark on a data collection activity, I’ll have to ask myself the most important question: What is it for?

Summary Response Week 5: Self Experimentation

CPSC 601.25 Week 5 Response Part 1

Papers

In this response I will discuss one paper and one newspaper article, in which personal informatics and self experimentation are discussed.

Self Experimentation

The history of self experimentation in science long. Newtown formulated his theory of optics after painful experiments on his own eyes. More recently Barry Marshal won the Nobel prize for discovering the bacteria that cause stomach ulcers. He confirmed this result by drinking a test tube full of the bacteria and a year later, developed stomach ulcers himself. But self experimentation today is less common, science proceeds on a huge scale now, using defined and formulated methods. Researchers try to separate themselves, the subject, from what they study, the object. But this paper suggests that self experimentation is in fact more effective then traditional science which is a bold claim.

Claims

The author rests his claim on comparing his professional, peer reviewed research to his privately conducted self experimentation. Some of the reasons he poses for this are interesting and rational, such as how the incentive structure of academics forces plodding, low risk work to guarantee tenure. But other arguments, those of which take up the bulk of the paper, suggest that professors affect a faux aristocratic air by purposely conducting research that is useless - in the way that the idle rich might learn about yachting and fencing. This argument is much less convincing, since funding and grants follow researchers who produce results. The claim is then extended even more grandly into a 'theory of scientific progress', which involves power laws and log scaled measurements of 'scientific progress'. Here the author seems disturbingly comfortable quantifying things that are not quantifiable.

What can we salvage from this? That scientific research is weighed down by incentives for professors, ethics hassles and too much work validating timid hypothesis then bolding proposing new ones and then pursuing their falsification. That self experimentation succeeds when it frees researchers from these shackles, letting them generate interesting new hypothesis.

Validity & Science

But for people familiar with the philosophy of science, that is where the new theory of science must end. Science consists not in validating narrow theories but in falsifying broad, rich theories, the construction of which is half the work of good science. A self experimenter might propose many interesting hypothesis from their small scale tests, but these must be subjected to control groups and all the usual rigor afterwards.

Self Experimentation & Wider Personal Informatics

The second paper summarizes for a newspaper article the general trends in personal informatics. Starting with a few "ultrageeks" who recorded everything aspect of their lives, then moving slowly into the mainstream with techniques for tracking sleep and time and then finally large, well funded, mainstream tools like Mint and Nike+. The author briefly touches on self experimentation and discusses a women who tested tryptophan on herself to cure insomnia and improve focus. He suggests that this is a different sort of personal science, whose theories only reference a single person, an interesting idea that isn't given enough time or space. The author paints and interesting picture of a future where PI has gone mainstream, and personal tracking extended to many more variables, improving peoples health and letting them "self actualize" by more fulling living life ... through their refreshed memories. But more interesting then self actualizes quantified selfers, is all the data that this will produce and how much more easily researchers, if employing these tools, could validate and test hypothesis. That might be the actual, interesting, impact of PI.

Response to The Unreasonable Effectiveness of my Self-Experimentation

Summary

Seth Roberts outlines why self-experimentation can yield results that are better than the results from traditional scientific methods. The paper focuses both on the points in his self-experimentation where he was able to find good results to otherwise elusive problems (although the results themselves are not discussed particularly discussed). While the paper ranges on topics relating to the quality, sources and the social factors of research, the main point (for us at least) is how the personal tracking and personal informatics helped the research.

In particular the author mentions, in the formulation of his theory of the power relation of scientific research, how keeping records of every night's sleep were critical to determining what factors were important waking early. That even though the bulk of the records were not very meaningful (or at least were very consistent) having them available is still important to the process.

Discussion

In terms of personal informatics there seems to be two main points. As in our previous discussions the reflections from personal informatics still rely on collecting as much information as possible for as long as possible. Secondly here the personal informatics are not used directly for reflection, but are mostly used as  support to investigate hypotheses. In this case the apriori collection is the most important aspect of the pi systems used.

Response: The Data Driven Life

Summary:

Continuing with last week’s theme about personal informatics, this paper was heavily focused on learning about one’s self through personal tracking. The main argument of this paper was that in fields such as accounting or science, numbers mean everything. They allow us to see patterns and make predictions. Thus, the same reasoning can be applied to our personal lives as well by tracking numbers about what we do. Despite all the positives about personal tracking this paper lists, there were some drawbacks it mentioned briefly. Namely, that of crushing self-awareness due to “the numbers don't lie”. Overall however, the paper strongly implies that self-monitoring can have benefits in all areas of a persons’ life.

Response:

My initial response to the beginning of the paper was positive, as the arguments it made in regards to using numbers in other areas made sense. However, as it delved further into what it meant to do personal tracking, it became obvious to me this was not a simple task to do (and probably what its not as widely spread as the paper would have one to believe). Following this train of thought, I thought about last week’s paper 'Why Groupaware fails', and I think some of the lessons in that could apply here, particularly in regards to maintenance. Additionally, in tracking personal data, we ourselves become a collaborative system around our own data.

Response: Understanding my Data, Myself

Summary:

The purpose of this paper was to examine ways in which we view data about ourselves. The main result of asking this question was that as we grow individually, so does the data about ourselves and how we view it. In the paper, they describe this as a shift from the Discovery phase (where information is being discovered and there is an overall goal) to the Maintenance phase (where a goal in information seeking has been achieved and it is now a matter of maintaining it). Even with the phases, the paper also showed that our data is dynamic and we can switch in and out of phases constantly. This is shown by the study in which they noticed that different questions about our own data is asked at different times.

Response:

The examination of personal data in this paper was interesting, especially when framing it with ubicomp. However, while thinking about data itself, the question as to why would this need to be done becomes obvious to me. In my opinion, the visualization of the data itself becomes as important, if not more important than the phases themselves. Yes, collecting as much data as possible is important, but it is its visualization that can lead to shifts in the phases themselves. I would have liked to see a study ubicomp + visualization and the changes it can cause, perhaps to further support the discussion in this paper.

Response: Why Groupaware Fails

Summary:

The primary purpose of this paper was to highlight several major reasons (at least to the author), why groupaware software fails. The staple example it provides is that of an electronic calendar and the amount of work required for one group of users (those who schedule) vs. those who just view (those who simply view the schedule). From here, listed are problems such as additional work being required and design process failure due to non-realistic design (design is based upon users similar to designer and not real-world ones). Another important component of this paper was the distinctions made between Multi-user systems vs. Multi-user applications vs. Single-user Applications. With these distinctions, valuable points about organizational change, overall benefits and costs become apparent.

Response:

Overall, I thought this was a significant paper because it highlighted problems that STILL exist today. The staple electronic calendar problem is still a problem today. Although admittedly, Google Calendar has done a pretty good job for some of the problems.

To me however, the most important component of the paper were the distinctions between all the systems. Especially when framing the problems in that of a tabletop application, these problems are further enhanced in my view. In some regards, a tabletop application, with its inherently collaborative nature, can be all 3 of these at the same time, if not separately. Although I have not looked into it extensively, a more modern version of this paper could cover not just systems, but multi or single surface environments.

Response: Stage Model for Personal Informatics

Summary:

In this paper, the authors discuss about how to address problems that come across with people using Personal Informatics which are not fully understood or defined, and finding a way of setting up PI that patterns with what people typically do. To do so, they did a survey.

The survey focused on how difficult it is to collect personal data, what is the motivation for reflection, and what patterns were found during exploration of the information.

From the survey, they came out with different stages to PI: Preparation, Collection, Integration, Reflection, Action.

This staged-model improved on PI assessment; what current PI systems can improve on, and what future systems should have to be effective.

Reflection:

What I find interesting in this paper is that based on my personal experience with collecting personal data, the stages are quite real. However, some stages need not be linear. For example, when you are collecting data manually, you may actually skip integration and immediately do some reflection and action.

I believe each person will be able to learn something about their data in each stages so if we have PI systems that actually allow people to do each of the stages in a non-tedious way, people will get more from their personal data.

I also think that we should have a degree of automation and experience-sampling (manual) together in PI systems.

Response to Li's Stage Model for Personal Informatics

Problem: there is no comprehensive list of problems that users experience towards using personal informatics systems.

Motivation: memory is limited and PI allows a more true self reflection. But how can we step it up?

Approach:

They performed a survey:

· How difficult is it to collect personal information?

· What was the initial motivation to reflect on it?

· What patterns are found when exploring personal information?

Most important areas: Finance, journaling, exercise and health.

Reasons: curiosity, interest in data, discovery of new tools, suggestion and trigger event.

Stages:

· Preparation: motivation to collect personal information, what and how they will record it.

· Collection: observations and recording of the data.

· Integration: combining and putting together all the information.

· Reflection: observing the results of the data collected, short term or long term.

· Action: what they do after they see this data -> potential behavior changes.

Contributions:

(1) Problems across Personal Informatics tools.

(2) Model that improves diagnosis, assessment and prediction of PI systems.

(3) Recommendations about how to improve existing systems and build effective personal information systems.

Thoughts:

I actually found a lot of value in the different stages, mainly because I hadn’t thought of them before. These are all things that I did when I collected my data for my infovis class. The interesting is that I don’t think we’re necessarily aware that we do these stages, or at least I never noticed when I did them. The interesting question is “what data should be collected manually vs electronically?” and to what extent can we automate it? What stage do we actually learn more from? I actually think we do still gain insight from just collecting or integrating the data, and this happened to me in one of my visualizations.

Summary Response Week 4: Personal Informatics

CPSC 601.25 Week 4 Response Part 2

Papers

In this response I will discuss two papers relating to personal informatics, both of which present models which describe how users interact with the system.

Personal Informatics

In the past ten years a new class of application has arisen, personal informatics. As it has become easier to record data, the desire to process and analyze it has increased. The authors of both papers consider personal informatics to be a practice, not a tool, and if considered this way the practice is not old. Certain people, such as Ben Franklin, had the patience to record information pertaining to themselves for years and years and on. Technology changes the equation in two ways, making it easier (or even automatic) to record the data and improving the tools for analyzing it.

What? Why?

The underlying question behind personal informatics seems to be 'why?'. The stage based model paper discusses it only briefly, but suggests that reflection is the key. In a later work, the understand my data paper, they suggest that behavioral change is a key motivating factor. While creating models and workflows and interviewing users can shed some light on the tools people are using and their goals in using them, the cost benefit equation of personal informatics has not been completely decided. Does recording meals help people who are struggling to lose weight? Are people who struggle with conscientiousness, willpower or self control really likely to be diligent plodding collectors of data? It seems at first glance that a person who can't force themselves to abstain from pie cannot force themselves to record either. If the purpose of PI is to change behavior, then it can be evaluated like any other method in this role. So what then is PI for?

Self Experimentation

When the paper authors discuss reflection they make no real distinction between a user casually reflecting over events in a journal, old pictures and emails and those doing experiments and investigations. But the later is far more interesting then the former. For a user trying to determine why they can't sleep, a tool which tracks their sleep can provide a baseline while they experiment with other variables, such as caffeine, lighting and exercise.

Seeking Utility

While users do follow certain 'models' when they use PI tools, the models themselves might not be that important. Certainly users begin using a PI tool by evaluating it, recording data with it, and then reflecting on it ... but this is common sense and generalizing this doesn't solve a real problem. And categorizing the general types of PI tools as well is also interesting, but it doesn't solve the real utility. Perhaps users enjoy recording and visualizing data about themselves in it self but probably not most people. To extend PI applications into the mainstream they need to provide a more clear utility to actual users. PI researchers should push users to show what utility they really get out of these tools and derive ways to make them more useful.