Ready-to-hand

Update your Facebook status: social comparison and the availability heuristic

Over at Captology Notebook, the blog of the Stanford Persuasive Technology Lab, Enrique Allen considers features of Facebook that influence users to update their status. Among other things, he highlights how Facebook lowers barriers to updating by giving users a clear sense of something they can right (”What are you doing right now?”).

I’d like to add another part of the interface for consideration: the box in the left box of the home page that shows your current status update with the most recent updates of your friends.

This visual association of my status and the most recent status updates of my friends seems to do at least a couple things:

Influencing the frequency of updates. In this example, my status was updated a few days ago. On the other hand, the status updates from my friends were each updated under an hour ago. This juxtaposes my stale status with the fresh updates of my peers. This can prompt comparison between their frequency of updates and mine, encouraging me to update.

The choice of the most recent updates by my Facebook friends amplifies this effect. Through automatic application of the availability heuristic, this can make me overestimate how recently my friends have updated their status (and thus the frequency of status updates). For example, the Facebook friend who updated their status three minutes ago might have not updated to three weeks prior. Or many of my Facebook friends may not frequently update their status messages, but I only see (and thus have most available to mind) the most recent. This is social influence through enabling and encouraging biased social comparison with — in a sense — an imagined group of peers modeled on those with the most recent performances of the target behavior (i.e., updating status).

Influencing the content of updates. In his original post, Enrique mentions how Facebook ensures that users have the ability to update their status by giving them a question that they can answer. Similarly, this box also gives users examples from their peers to draw on.

Of course, this can all run up against trouble. If I have few Facebook friends, none of them update their status much, or those who do update their status are not well liked by me, this comparison may fail to achieve increased updates.

Consider this interface in comparison to one that either

• showed recent status updates by your closest Facebook friends, or
• showed recent status updates and the associated average period for updates of your Facebook friends that most frequently update their status.

[Update: While the screenshot above is from the "new version" of Facebook, since I captured it they have apparently removed other people's updates from this box on the home page, as Sasha pointed out in the comments. I'm not sure why they would do this, but here are couple ideas:

• make lower items in this sidebar (right column) more visable on the home page -- including the ad there
• emphasize the filter buttons at the top of the news feed (left column) as the means to seeing status updates.

Given the analysis in the original post, we can consider whether this change is worth it: does this decrease status updates? I wonder if Facebook did a A-B test of this: my money would be on this significantly reducing status updates from the home page, especially from users with friends who do update their status.]

6 comments July 29th, 2008

Naming this blog: Heidegger, Husserl, folk psychology, and HCI

The name of this blog, Ready-to-hand, is a translation of Heidegger’s term zuhanden, though interpreting Heidegger’s philosophy is not specifically a major interest of mine nor a focus here. Much has been made of the significance of phenomenology, most often Heidegger, for human-computer interaction (HCI) and interaction design (e.g., Winograd & Flores 1985, Dourish 2001). And I am generally pretty sympathetic to phenomenology as one inspiration for HCI research. I want to just note a bit about the term zuhanden and my choice of it in a larger context — of phenomenology, HCI, and a current research interest of mine: cues for assuming the intentional stance toward systems (more on this below).

The Lifeworld and ready-to-hand
Heidegger was a student of Edmund Husserl, and Heidegger’s Being and Time was to be dedicated to Husserl.¹ There is really no question of the huge influence of Husserl on Heidegger.

My major introduction to both Husserl and Heidegger was from Prof. Dagfinn Føllesdal. Føllesdal (1979) details the relationship between their philosophies. He argues for the value of seeing much of Heidegger’s philosophy “as a translation of Husserl’s”:

The key to this puzzle, and also, I think, the key to understanding what goes on in Heidegger’s philosophy, is that Heidegger’s philosophy is basically isomorphic to that of Husserl. Where Husserl speaks of the ego, Heidegger speaks of Dasein, where Husserl speaks of the noema, Heidegger speaks of the structure of Dasein’s Being-in-the-world and so on. Husserl also observed this. Several places in his copy of Being and Time Husserl wrote in the margin that Heidegger was just translating Husserl’s phenomenology into another terminology. Thus, for example, on page 13 Husserl wrote: “Heidegger transposes or transforms the constitutive phenomenological clarification of all realms of entities and universals, the total region World into the anthropological. The problematic is translation, to the ego corresponds Dasein etc. Thereby everything becomes deep-soundingly unclear, and philosophically it loses its value.” Similarly, on page 62, Husserl remarks: “What is said here is my own theory, but without a deeper justification.” (p. 369)

Heidegger and his terms have certainly been more popular and in wider use since then.

Føllesdal also highlights where the two philosophers diverge.² In particular, Heidegger gives a central role to the role of the body and action in constituting the world. While in his publications Husserl stuck to a focus on how perception constitutes the Lifeworld, Heidegger uses many examples from action.³ Our action in the world, including our skillfulness in action constitutes those objects we interact with for us.

Heidegger contrasts two modes of being (in addition to our own mode — being-in-the-world): present-at-hand and ready-to-hand (or alternatively, the occurant and the available (Dreyfus 1990)). The former is the mode of being consideration of an object as a physical thing present to us — or occurant, and Heidegger argues it constitutes the narrow focus of previous philosophical explorations of being. The latter is the stuff of every skilled action — available for action: the object becomes equipment, which can often be transparent in action, such that it becomes an extension of our body.

J.J. Gibson expresses this view in his proposal of an ecological psychology (in which perception and action are closely linked):

When in use, a tool is a sort of extension of the hand, almost an attachment to it or a part of the user’s own body, and thus is no longer a part of the environment of the user. [...] This capacity to attach something to the body suggests that the boundary between the animal and the environment is not fixed at the surface of the skin but can shift. More generally it suggests that the absolute duality of “objective” and “subjective” is false. When we consider the affordances of things, we escape this philosophical dichotomy. (1979, p. 41)

While there may be troubles ahead for this view, I think the passage captures well something we all can understand: when we use scissors, we feel the paper cutting; and when a blind person uses a cane to feel in front of them, they can directly perceive the layout of the surface in front of them.

Transparency, abstraction, opacity, intentionality
Research and design in HCI has sought at times to achieve this transparency, sometimes by drawing on our rich knowledge of and skill with the ordinary physical and social world. Metaphor in HCI (e.g., the desktop metaphor) can be seen as one widespread attempt at this (cf. Blackwell 2006). This kind of transparency does not throw abstraction out of the picture. Rather the two go hand-in-hand: the specific physical properties of the present-at-hand are abstracted away, with quickly perceived affordances for action in their place.

But other kinds of abstraction are in play in HCI as well. Interactive technologies can function as social actors and agents– with particular cues eliciting social responses that are normally applied to other people (Nass and Moon 2000, Fogg 2002). One kind of social response, not yet as widely considered in the HCI literature, is assuming the intentional stance — explanation in terms of beliefs, desires, hopes, fears, etc. — towards the system. This is a powerful, flexible, and easy predictive and explanatory strategy often also called folk psychology (Dennett 1987), which may be a tacit theory or a means of simulating other minds. We can explain other people based on what they believe and desire.

But we can also do the same for other things. To use one of Dennett’s classic examples, we can do the same for a thermostat: why did it turn the heat on? It wanted to keep the house at some level of warmth, it believed that it was becoming colder than desired, and it believed that it could make it warmer by turning on the heat. While in the case of the thermostat, this strategy doesn’t hide much complexity (we could explain it with other strategies without much trouble), it can be hugely useful when the system in question is complex or otherwise opaque to other kinds of description (e.g., it is a black box).

We might think then that perceived complexity and opacity should both be cues for adopting the intentional stance. But if the previous research on social responses to computers (not to mention the broader literature on heuristics and mindlessness) has taught us anything, it is that made objects such as computers can evoke unexpected responses through other simplier cues. Some big remaining questions that I hope to take up in future posts and research:

• What are these cues, both features of the system and situational factors?
• How can designers influence people to interpret and explain systems using folk psychology?
• What are the advantages and disadvantages of evoking the intentional stance in users?
• How should we measure the use of the intentional stance?
• How is assuming the intentional stance towards a thing different (or the same) as it having being-in-the-world as its mode of being?

1. But Husserl was Jewish, and Heidegger was himself a member of the Nazi party, so this did not happen in the first printing. [↩]
2. Dreyfus (1990) is an alternative view that takes the divergence as quite radical; he sees Føllesdal as hugely underestimating the originality of Heidegger’s thought. Instead Dreyfus characterizes Husserl as formulating so clearly the Cartesian worldview that Heidegger recognized its failings and was thus able to radically and successfully critique it. [↩]
3. It is worth noting that Husserl actually wrote about this as well, but in manuscripts, which Heidegger read years before writing Being and Time. [↩]

Add comment July 23rd, 2008

Expert users: agreement in focus from two threads of human-computer interaction research

Much of current human-computer interaction (HCI) research focuses on novice users in “walk-up and use” scenarios. I can think of three major causes for this:

1. A general shift from examining non-discretionary use to discretionary use
2. How much easier it is to find (and not train) study participants unfamiliar with a system than experts (especially with a system that is only a prototype)
3. The push from practitioners in the direction, especially with the advent of the Web, where new users just show up at your site, often deep-linked

This focus sometimes comes in for criticism, especially when #2 is taken as a main cause of the choice.

On the other hand, some research threads in HCI continue to focus on expert use. As I’ve been reading a lot of research on both human performance modeling and situated & embodied approaches to HCI, it has been interesting to note that both instead have (comparatively) a much bigger focus on the performance and experience of expert and skilled use.

Grudin’s “Three Faces of Human-Computer Interaction” does a good job of explaining the human performance modeling (HPM) side of this. HPM owes a lot to human factors historically, and while The Psychology of Human-Computer Interaction successfully brought engineering-oriented cognitive psychology to the field, it was human factors, said Stuart Card, “that we were trying to improve” (Grudin 2005, p. 7). And the focus of human factors, which arose from maximizing productivity in industrial settings like factories, has been non-discretionary use. Fundamentally, it is hard for HPM to exist without a focus on expert use because many of the differences — and thus research contributions through new interaction techniques — can only be identified and are only important for use by experts or at least trained users. Grudin notes:

A leading modeler discouraged publication of a 1984 study of a repetitive task that showed people preferred a pleasant but slower interaction technique—a result significant for discretionary use, but not for modeling aimed at maximizing performance.

Situated action and embodied interaction approaches to HCI, which Harrison, Tatar, and Senger (2007) have called the “third paradigm of HCI”, are a bit different story. While HPM research, like a good amount in traditional cognitive science generally, contributes to science and design by assimilating people to information processors with actuators, situated and embodied interaction research borrows a fundamental concern of ethnomethodology, focusing on how people actively make behaviors intelligible by assimilating them to social and rational action.

There are at least three ways this motivates the study of skilled and expert users:

1. Along with this research topic comes a methodological concern for studying behavior in context with the people who really do it. For example, to study publishing systems and technology, the existing practices of people working in such a setting of interest are of critical importance.
2. These approaches emphasize the skills we all have and the value of drawing on them for design. For example, Dourish (2001) emphasizes the skills with which we all navigate the physical and social world as a resource for design. This is not unrelated to the first way.
3. These approaches, like and through their relationships to the participatory design movement, have a political, social, and ethical interest in empowering those who will be impacted by technology, especially when otherwise its design — and the decision to adopt it — would be out of their control. Non-discretionary use in institutions is the paradigm prompting situation for this.

I don’t have a broad conclusion to make. Rather, I just find it of note and interesting that these two very different threads in HCI research stand out from much other work as similar in this regard. Some of my current research is connecting these two threads, so expect more on their relationship.

References
Dourish, P. (2001). Where the Action Is: The Foundations of Embodied Interaction. MIT Press.
Grudin, J. (2005). Three Faces of Human-Computer Interaction. IEEE Ann. Hist. Comput. 27, 4 (Oct. 2005), 46-62.
Harrison, S., Tatar, D., and Senger, P. (2007). The Three Paradigms of HCI. Extended Abstracts CHI 2007.

Add comment May 27th, 2008

Riskful decisions and riskful thinking: Donald Davidson and Cliff Nass

Two personal-professional narratives that I’ve been somewhat familiar with for a while have recently highlighted for me the significance of riskful decisions and thinking in academia. I think the stories are interesting on their own, but they also emphasize some questions and concerns for the functioning of scholarly inquiry.

The first is about the American philosopher Donald Davidson, whose work has long been of great interest to me (and was the topic of my undergraduate Honors thesis). The second is about Cliff Nass (Clifford Nass), Professor of Communication at Stanford, an advisor and collaborator. The major published source I draw on for each of these narratives is an interview: for Davidson’s story, it is an interview by Ernest Lepore (2004), a critic and expositor of Davidson’s philosophy; for Cliff Nass, it is an interview by Tamara Adlin (2007). After sharing these stories, I’ll discuss some similarities and briefly discuss risk-taking in decisions and thinking.

Donald Davidson is considered one of the most important and influential philosophers of the past 60 years, and he is my personal favorite. Davidson is often described as a highly systematic philosopher — uncharacteristically so for 20th century philosophy, in that his contributions to several areas of philosophy (philosophy of language, mind, and action, semantics, and epistemology) are deeply connected in their method and the proposed theories. He is the paradigmatic programmatic philosopher of the 20th century.

Despite this, Davidson’s philosophical program did not emerge until relatively late in his career. The same is true of his publications in general. Only after accepting a tenure track position at Stanford in 1951 (which was then still up-and-coming, though quickly, in philosophy) did he begin to publish (nothing was even in the “pipeline” previous to this). This began under the wing of the younger Patrick Suppes, with whom Davidson co-authored a book (1957) on decision theory. His first philosophical article appears in 1963 (which he authored alone only through an unexpected death). As Davidson puts it in an interview with Ernest Lepore, “I was very inhibited so far as publication was concerned” and was worried “that the minute I actually published something, everyone was going to jump on me” (Davidson 2004).

Then Davidson published “Actions, Reasons and Causes” (1963), twelve years after joining the Stanford faculty. It argues against the late-Wittgensteinian dogma that reasons are not also causes. It is only with this paper that there was a publication by Davidson that drew significant attention from the community (beginning with a presentation of the paper at a meeting of the American Philosophical Association). This paper has been hugely influential and alone identified Davidson as an important thinker in the field, though he was surprised the reception was not as overwhelming as he had thought: “I didn’t realize that if you publish, as far as I can tell, no one was going to pay any attention.” Many responses, both positive and critical, did eventually come, and Davidson went on to publish many highly influential papers, reaching the height of his immense scholarly influence in the 1970s and 1980s.

Clifford Nass is widely known researcher in the psychology of human-computer interaction (HCI). With Byron Reeves, he wrote The Media Equation (1996), which presents research carried out at Stanford University on how people respond in mediated interactions (e.g. with computers and televisions) by overextending social rules normally applied to other people. This hints at the (here simplified) straight, bold line of Nass’s research program: take a finding from social psychology, replace the second human with a computer, see if you get the same results. This exact strategy has been modified and expanded from, but the general consistency of Nass’s program over many years is striking for HCI: unlike in psychology, for example, in HCI there are many investigators seeking low-hanging fruit and quickly moving on to new projects.

Nass likes to refer to his “accidental PhD”, as he hadn’t intended to get a PhD in sociology. After working for a year at Intel, he was planning to matriculate in a electrical engineering PhD program, but an unexpected death postponed that. “[J]ust to bide my time and to have some flexibility, I ended up doing a sociology degree,” says Nass. He did his dissertation on the role of pre-processing jobs in labor, taking an approach that was radical in its elimination of a role for people and that connected with contemporary research by social science outsiders doing “sociocybernetics”. With such a dissertation topic (and the dissertation itself unfinished), finding a job did not seem easy at the outset: “It’s a nutty topic. I was going to be in trouble getting jobs. I had published stuff and was doing work and all that, but my dissertation was so weird” (Adlin 2007).

There was, however, a bit of luck, well taken advantage of by Nass: the Stanford Communication Department was under construction and looking to hire some folks doing weird work. So when Nass interviewed, impressing both them and the Sociology Department, he got the job, despite knowing nothing about Communication as a discipline and having been to no conferences in the field. After beginning at Stanford, Nass was seeking a research program, as clearly there was something wrong, at least when it came to getting it accepted for academic publication, with his previous work: “I was having a terrible time getting my work accepted. In fact, to this day I’ve still never published anything off my dissertation, 20-odd years later. Because again, no field could figure out who owned the material. I got reviews like, ‘This work is offensive.’”

But Nass couldn’t settle on any normal research program. He wanted to examine how people might treat computers socially. Getting funding for this work wouldn’t have been easy, but he got a grant that the grant administrator described as the 1 of 35 given that they chose to give to the “weirdest project that was proposed”. It wasn’t all easy from there, of course. For example, it took some time to design and carry out successful experiments in this program — and even longer to get the results published. But this risk-taking in distributing this grant helped enable the work to continue.
Cliff Nass is very clear about the role riskful decisions, in admissions, hiring, and funding, played in his success:

I was very lucky. I fear that those times are gone. I really do fear to a tremendous degree that the risk-taking these people were willing to do for me, to give me an opportunity, are gone. I try to remember that. [...]

I benefited from the willingness of people to say, “We’re just going to roll the dice here.”

Of course, it isn’t just Cliff who got lucky; in a sense we all did. His work has been an important influence in HCI and has contributed to our stores of both generalizable knowledge and new lenses for approaching how we get on in the world.

What does it mean for academic research, and science generally, if this choice and ability to take these risks evaporates? There is incredible competition for academic positions now, more so in some fields than others. And the best tool in getting a job is a whole list of publications accepted in important, mainstream journals in the field. There is a lot written about the competition for academic jobs and criteria for wading through applicants to sometimes a safe option. There are case studies of families of disciplines; for example, a study of the biosciences argues that market forces are failing to create sufficient job prospects for young investigators (Freeman et al. 2001).

I won’t review them all here. Instead I suggest an article for general readers from The New York Times about state and regional colleges’ use of non-tenure track positions, which has an impact of the institutions’ bottom line and flexibility (Finder 2007). This is part of a wider trend in how tenure is used that also impacts the academic freedom and resources that scholars have to pursue new research (Richardson 1999).

Enabling riskful thinking
Hans Ulrich Gumbrecht argues that “riskful thinking” is central to the value of the humanities and arts in academia. He defines riskful thinking as investigation that can’t be expected to produce results interpretable as easy answers, but that instead is likely to produce or highlight complex and confusing phenomena and problems. But I think that this is more broadly true. Riskful thinking is critical to interdisciplinary and pre-paradigmatic sciences, or disciplines long doing normal science but in need of a shake-up. These are situations where compelling phenomena can become paradigmatic cases for study and powerful vocabularies can allow formulating new problems and theories.

What threatens riskful thinking, and how can we enable it? What is so great about riskful thinking anyway, and what makes some riskful thinking so successful, while much of it is likely to fail? At Nokia Research Center in Palo Alto, our lab head John Shen champions the importance of risk taking in industry research, but also argues that risk-taking is often misunderstood and that it is only some kinds of risk-taking that are most important to cultivate in industry research.
—
Finally, a list of Davidson-Nass similarities, just for fun:

• Both were hired to tenure track positions at Stanford, where they first did and published highly influential work
• Both are easily and widely seen as highly programmatic, having defined a clear research program challenging to currently popular approaches and beliefs in their fields
• Both had great difficulty finding early, publishable success with their research programs, even after ceasing their early work (Davidson: Plato, empirical decision theory; Nass: information processing models of the labor force)
• Both had other draws and distractions (Davidson: business school, teaching plane identification in WWII; Nass: being a professional magician, working at Intel)
• Both produced dissertations viewed by others in the discipline as odd (Davison: Quine “was a little mystified by my writing on this. He never talked to me about it.”; Nass: “my PhD thesis was so bizarre”)

References
Adlin, T. (2007). An interview with Cliff Nass. UX Pioneers. http://www.adlininc.com/uxpioneers/home_popular_row_2/interview_cliff_nass
Davidson, D. (1963). Actions, Reasons, and Causes. Journal of Philosophy, 60(23), 685-700.
Davidson, D., & Suppes, P. (1957). Decision Making: An Experimental Approach. Stanford University Press.
Finder, A. (2007, November 20). Decline of the Tenure Track Raises Concerns. The New York Times.
Freeman, R., Weinstein, E., Marincola, E., Rosenbaum, J., & Solomon, F. (2001). Careers: Competition and Careers in Biosciences. Science, 294(5550), 2293-2294.
Lepore, E. (2004). Interview with Donald Davidson. In Problems of Rationality, Oxford University Press, 2004, pp. 231-266.
Nass, C., Steuer, J., & Tauber, E. R. (1994). Computers are social actors. In Proc. of CHI 1994. ACM Press.
Reeves, B., & Nass, C. (1996). The media equation: how people treat computers, television, and new media like real people and places. Cambridge University Press.
Richardson, J. T. (1999). Tenure in the New Millenium. National Forum, 79(1), 19-23.
Sanford, J. (2000, November 17). ‘Elementary pleasures’ and ‘riskful thinking’ matter to Gumbrecht. Stanford Report.

Add comment April 29th, 2008

Definitions of unconscious processing in cognitive and social psychology

John Bargh, Professor of Psychology at Yale, and his ACME (Automaticity in Cognition, Motivation, and Emotion) Lab are doing very exciting work. I had read some articles by Bargh some time ago (e.g. Bargh & McKenna 2004) and encountered his work in the context of debates about how objects can automatically activate attitudes that apply to them. But it hasn’t been until recently (following a discussion with James Breckenridge) that I’ve begun to really engage with the larger body of research Bargh and his collaborators have produced — and the interesting reflections and arguments found in the reviews of this and related work that he and his collaborators have written.

I expect I’ll be writing more about this work, but in this and some follow-up posts I want to just say a little bit about the general character of the research and, more specifically, how this work engages with and employs definitions of ‘unconscious’ and ‘unconscious processing‘.

Bargh & Morsella (2008, in press, page numbers are to this version) highlights how cognitive psychology and social psychology have operated with different definitions and different emphasis in investigating what they call “unconscious”. For cognitive psychology, “subliminal information processing – [...] extracting meaning from stimuli of which one is not consciously aware” – has been paradigmatic of the unconscious (p. 1). That is, its study of unconscious processing is the study of the processing of stimuli of which one is unaware. On the other hand, for mainstream social psychology research, including work with priming, “the traditional focus has been on mental processes of which the individual is unaware, not on stimuli of which one is unaware” (Ibid.).

This is a striking difference that, as Bargh & Morsella illustrate, has consequences for how “dumb” or “smart” and “limited” or “pervasive” unconscious processing is. If unconscious processing is limited to processing of subliminal stimuli, then it doesn’t have much to go on. But the social psychology definition — the liberal, process-awareness definition — allows us to call a lot more things unconscious processing.

I recognize shortcomings with the cognitive psychology definition — the narrow, stimulus-awareness definition. And Bargh and Morsella’s statement of the process-awareness definition does enable them to say some striking things (e.g. about automatic activation of motivations).

But I also wonder whether this redefined term can bear much theoretical weight. Specifically, I have two concerns:

1. this definition makes what is unconscious depend on each person’s knowledge of the causes of their actions — and this can get tricky in unintuitive and highly individual ways
2. this definition seems to count on having good identity conditions for the kinds of objects to which ‘unconscious’ is supposed to apply (e.g. events, processes), but identity conditions (which are often hard to come by in general) are tricky for this domain in particular.

These are familiar problems in philosophy of mind, and they deserve consideration when designing theoretically useful definitions of unconscious processing. I aim to take up each of these issues in more detail in another post.

Bargh, J.A., & Morsella, E. (2008, in press). The unconscious mind. Perspectives on Psychological Science.

Bargh, J.A., & McKenna, K.Y.A. (2004). The Internet and social life. Annual review of psychology, 55, 573-590.

Add comment March 6th, 2008

Taxonomy of diary research methods

Diary studies are widely used in human-computer interaction research, but also in user experience research as practiced in product R&D groups. Bolger, Davis, & Rafaeli (2003) is a good review of diary research methods from a Psychology perspective. It gives practical guidance in what research questions are suited to these methods, design decisions, tools, and analysis.

Though it covers state-of-the-art technology used for these methods, I think the argument below for the taxonomy of methods used in this paper needs revision in light of new diary methods, e.g. those made possible by using context-aware devices for signaling participants. Here is the argument for the two-way taxonomy (p. 588):

Diary studies have often been classified into the three categories of interval-, signal-, and event-contingent protocols (e.g., Wheeler & Reis 1991). The interval-contingent design, the oldest method of daily event recording, requires participants to report on their experiences at regular, predetermined intervals. Signal-contingent designs rely on some signaling device to prompt participants to provide diary reports at fixed, random, or a combination of fixed and random intervals. Event-contingent studies, arguably the most distinct design strategy, require participants to provide a self-report each time the event in question occurs. This design enables the assessment of rare or specialized occurrences that would not necessarily be captured by fixed or random interval assessments.

As we see it, diary studies serve one of two major purposes: the investigation of phenomena as they unfold over time, or the focused examination of specific, and often rare, phenomena. It appears to us that the three-way classification blends this conceptual distinction with the technological issue of signaling. Instead, we incorporate interval- and signal-contingent designs into a single category, which we call time-based designs.

This argument to collapse the taxonomy does not account for methods in which participants are signaled based on factors other than time. For example, diary studies can include signaling participants to create an entry based on events that are automatically detected by the system: this occurs when the system is immediately aware of the event because it is an interaction with the system (e.g. the participant has just completed a phone call) or because it can infer an appropriate change in state (e.g. the participant has just moved from one place to another, as detected by readings from GPS).

Add comment January 9th, 2008