Behavior/Experience Reading W2

Readings Week 2
Design for Behavior & Experience

“Chapter 1 Living with Technology” Technology as Experience. J. McCarthy & P. Wright, 2007.

  • “We don’t just use or admire technology, we live with it.”
  • “The old computing was about what computers could do; the new computing is about what users can do.” -Ben Shneideman
  • Mobile technologies (and the texting, mailing apps therein) have experienced success because then enable what humans like to do: communicate.
  • Teenagers have a unique experience with short messages of digital communication (email, chats, messengers, texts) in that they put time and thought into their composition and content, taking into consideration into designing the conversation to be understood by the recipient.
  • In computing and technology, the terminology for a person has progressed from “cog in the machine” to “source of error” to “user” and now, to “consumer.”
  • “For many everyday tasks, goals and intentions are not well specified: they are opportunistic rather than planned. Opportunistic actions are those in which the behavior takes advantage of the circumstances. Rather than engage in extensive planning and analysis, the person goes about the day’s activities and performs the intended actions if the relevant opportunity arises.” – Donald Normam, 1988.
  • “The user experience development process is all about ensuring that no aspect of the user’s experience with your site happens without your conscious, explicit intent. […] That neat, tidy experience actually results from a whole set of decisions-some small, some large-about how the site looks, how it behaves and what it allows you to do.” – Garrett (2002)
  • A set of design implications cannot create a user experience, and it is often business momentum that pushes this agenda when it is least appropriate.
  • Consumers are not passive, they are emotional, social actors who actively complete an experience for themselves via interactive technologies and products.
  • The experience of the user is recognized by many companies and manufacturers, but the understanding (and thus use) of experience is limited.
  • People generally enjoy overhearing conversations, but not solely one side of a conversation.
  • For pragmatists, knowing/doing/feeling/making-sense are inseparable.

Dewey, a pragmatist, surmises that the relationship between the object and the self is the experience. Actions with these objects are situated and creative. Action is therefore emotional, volitional, and imaginative; experience is the process of sense-making.

  • “When we attempt to pragmatically conceptualize people’s experiences with technology, we are concerned with inquiring into what pragmatism has to offer towards enriching those experiences, even to the point of imaging what a rich experience of technology could be.”
  • Scientific study is often to concerned with backward-looking goals, that of explaining or making sense of what has already happened. Representational or reflective theorizing only makes sense when the world is relatively stable; however, it is more common to design products and artifacts that mediate action because the world is more chaotic.
  1. Technology has a wide range of influences that extended beyond its shell or interface; the relationships between people and technology should be described in “felt” life and “felt” emotional quality of action and interaction.
  2. Look to social and physical circumstances of actions and interactions (rather than exclusively cognitive models) for informed understanding, designing, and interpreting these actions/interactions.
  3. It is difficult to develop accounts of felt experience with technology, because we are present in its ever-moving flow. Its richness is elusive, as “we can never step out of [it] and look up at it in a detached way.”
  4. Models of action and meaning-making encompass felt life and emotional components of action and interaction.
  5. Importance to the emotional-volitional aspect of actions/interactions proves importance upon the aesthetic form in crafting experience.
  6. A revisionary theory of pragmatism, that by doing new form can derive, helps to clarify the nature of experiencing technology and design.

“Chapter 4 Embedded Gear” Digital Ground: Architecture, Pervasive Computing, and Environmental Knowing. M. McCullough, 2005.

  • “What are the essential components [of technologies], and what are the contextual design implications of the components?”
  • “The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” – Mark Weiser
  • The PC is an outdated ideal for personal computing. Graphical interfaces are now too crowded by the need for the potential, rather than aiding common tasks.
  • Design for experience often comes after the software engineers’ role, and thusly it is too late. A consumer will receive what an engineer thinks is the necessary functions for that year. Also a problem described as feature accumulation. -Alan Cooper
  • Pervasive computing, or embedded computing, that has a purpose to physical space, has the chance to begin anew (with interfaces, with user-interaction, etc.)
  • “We face limits to how much we care to do or will consider doing with any one device in one place. More subtly, we also face limits to how much a device can do without better information about its context.”
  • The desktop OS was made to store and perform tasks locally. The internet age assumes connectivity was universal. If the internet of things is to become no less baggy than its DOS relatives, then they must enact situational protocols.

“We have been very good a putting computers into the environment, but we have been very bad at getting them out of the way.” -Mark Weiser

  • Ambient interfaces allow monitoring of potentially relevant information; haptic/tangible interfaces allow latent use of intuitive physics.
  • Specialized technologies become ad hoc networks of things in a contextual space. Interoperability is critical. How to design these connections and make them invisible is a valid question for design.
  • Local networks (compared to universal networks) do not require high-level models of software and are less subject to monitoring of third parties. Properties of scale, discovery, protocol, configuration, and tuning become essential.

“The goal of the perceptual intelligence approach is not to create computers with the logical powers envisioned in most AI research, […] because most of the tasks we want performed do no seem to require complex reasoning or a god’s-eye view of the situation.” The HCI world has begun to value how people play situations, rather than specific outcomes.

Building blocks of technology-embedded space:

  1. Sites and devices are embedded with microprocessors.
  2. Sensors detect action.
  3. Communication links form ad hoc networks of devices.
  4. Tags identify actors.
  5. Actuators close the loop.
  6. Controls make it participatory.
  7. Display spreads out.
  8. Fixed locations track mobile positions.
  9. Software models situations.
  10. Tuning overcomes rigidity.
  • more than 95% of devices with microprocessors embedded in them do not present as “computers” (Intel)
  • sensors intrinsically serve a logic device, reporting if a change (or set of changes) has happened or hasn’t happened
  • pervasive computing depends on unplanned communication, connections only opening when necessary
  • tags are a way to embed information or instructions for other devices to attach to a person or an actor, making the technology conform to the context that the addition of the actor will manifest
  • “The physical environment abounds with opportunities for improving commodity, firmness, and delight through the application of intelligent feedback systems.”
  • “Know when to eliminate an obsolete ‘legacy’ operation, when to automate, and when to assist and action. Know how to empower, not overwhelm.”
  • Representing scenes and situations becomes the challenge of software creation, or people, actors, and things in contexts.
  • Tuning (or tweaking) is incremental adjustments that come as orders from a qualitative, top-level reading of performance. Even when engineers balance complex systems with mathematical models, some tuning still needs to be done.
  • “Location and type have to matter (to new technologies). Otherwise, with everything possible all the time, mostly chaos will result.”

 

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Project:Thesis Readings 1

Embodiment in Data Sculpture: A Model of the Physical Visualization of Information
Jack Zhao and Andrew Vande Moere (2006)

“With human’s inherent proficiency in comprehending the physical affordances present in the real world, some researchers and designers are investigating how meaningful insights can be conveyed by way of sculpting data” (Zhao & Moere, 1).

  • Data sculpture is (1) created from data, (2) exists in space or is physical, (3) possesses both artistic and functional qualities, and (4) an attempt to make obvious the insights and relevance of the data.
  • How data is best presented to inform, educate non-expert audiences, capture attention, and maintain curiosity is largely subjective and contextual.
  • Interpretation of physical objects come from their affordances, something digital media and digital space does not inherently carry.
  • Data sculpture has the potential to communicate information to a mass, lay audience through touch, exploration, and possession. This externalization of data will now have functional and artistic qualities.

 

“Embodiment is based on the measurement of the distance between metaphor and data and between metaphor and reality” (Zhao & Moere, 2).

  • Qualities data sculpture can take on: physical property of depth and perspective, materiality, and nuance.
  • Data sculpture belongs to design subfields of information aesthetics, artistic visualization, or casual visualization.
  • A predecessor of data sculpture, ambient displays transform architectural space by implicating interfaces for stimulating audience’s attention where none was previously warranted.

“In data sculpture, embodiment describes the expression of abstract data in physical representation through the process of data mapping. In information visualization, and by extension, in data sculptures, data mapping describes the process of translating data values to representations using metaphors. In such processes, metaphors become manifested in representations and draw associations between the abstract data and the perceiver’s prior knowledge or experiences. Metaphor is defined as a concept that is regarded as representative or symbolic to another concept. The primary function of a metaphor is to help people conceive an unfamiliar domain in terms of another familiar domain through drawing connections of similarity between the two” (Zhao & Moere, 3).

  • In the field of tangible computing, the research into the use of metaphor has been based on the theory that users naturally relate what they are experiencing to what they already know. Stronger metaphors exist when they reference a specific mental image, afford the intended interaction and have a place in a mass audiences’ realm of familiarity.

zhao_model.JPG.png

“A more precise definition of data sculpture has emerged from the domain model: a data sculpture is a highly data-oriented physical form, possessing both artistic and functional qualities, to augment facilitates an audience’s understanding of the underlying data and issues” (Zhao & Moere, 4).

“Our model relies on following three axioms:

1. Data sculpture is a system of physical representation and abstract data coupled by a relationship called embodiment.

2. Metaphor is a contributing factor to embodiment and can be gauged by metaphorical distances from the data and reality.

3. Different modes of embodiment determined by different metaphorical distances in data sculpture can affect the informative value.”

Data Stories: Data Sculpture

Data Stores Podcast: Episode 17

Data Sculpture
01/29/2013

State of the Art: Part 1

State of the Art: Prior Works Research
Part 1

Thesis key words: Physical data visualization, data installation, data materiality, participatory data visualization

(1) Glue Society – “BT – Longterm Investor”

A series of (TV/digital media) spots using light sculpture to present estimates of investment data.

BT Financial ‘Superannuation’ from The Glue Society on Vimeo.

Materiality: Light

Architecture: digital, sloping, flat

Interaction: None, but animated

Pros: Metaphor equating light with idea and positivity and the future intact; narration clear; mood and graphics align with intended audience

Cons: Numbers not present until the end & their scale is small; light field is essentially flat, no conceivable reason for sloping plane; low resolution data

(2) Bryan Ku – “MB15 Minos”

An interactive installation for Moving Brands that visualized staff members as codified three-dimension, brightly patterned geometric solids based on office location, department, and other facts about the employees.

Materiality: none, digital

Architecture: Operating podium, projection

Interaction: Leap System, hand movements as a signal

Pros: Design of application provided approachability to party-goers; codified system of making able to be discovered (some hints found on side of operating podium); metaphors for socialization strong; integrated live stream of party goers tweets and instagrams

Cons: Lacks materiality; spatial presence brought about by utility; installation competes with experience of party

(3) Bryan Ku – “WIM•BLE•DON”

Flipbook data visualization that operates with a pair of users alternating page turns for the final game of a Wimbledon championship match.

Materiality: Paper, bound book

Architecture: none, mostly flat

Interaction: user-operated, chronological animation

Pros: metaphor in interaction between opponents; sleek visual design; excellent source of storytelling; user-operated creates controlled experience

Cons: unsure how unguided operation would begin; lack of relationship to body or space; experience heightened greatly by video track; assumes knowledge of rules of tennis to communicate story

(4) Doug McCune – “San Francisco Housing Prices

A 3D-printed data sculpture that abstractlyd displays average price per square foot for housing in the San Francisco area.

img_94543

Physicality: 3D-printed plastic

Architecture: non, ~12″ tall

Interaction: None, static

Pros: Form takes on powerful metaphor of ripping apart; content well-researched and clearly discerned from sculpture; excellent craftsmanship; process well-documented

Cons: No sense of data scale; lack of relation to human body or architecture

Rules for Animated Infographics

Thesis/Research

Information Animated Infographics
Editors T. Finke & S Manger (2012)

“Well-made animated information graphics are based on clear decisions about what matters and what should be left out.” – Stefan Fichtel (in Finke & Manger, 8)

“By comparing different data sets and visualizations of the data and embedding them in a context, the view sees the result in the form of a narration with the help of illustrations” (Finke & Manger, 21).

The Pros and Cons of “passive, animated information graphics that have a linear structure:”

 

finke_manger_pro

Finke_Manger_Con.JPG

 

In sculptural, interactive works…

Time Sequences
…if time is represented, interactivity may permit atemporality.

Directing the Viewer
…the viewer cannot experience events in a predetermined order.

Changing Perspective
…emphasis should not be encoded in perspective.

Viewing Time
…the viewer is permitted to spend as much time as needed (or desired) for perception of content.

Linearity
…the information presented may be perceived in various orders, and will permit different outcomes depending on the viewer.

Complexity
…the statistical content must balance between rich and generalized visualizations, understanding experience can cease upon exhaust of attention.

Manipulation
…the viewer is permitted to ask questions or examine the data in detail.

 

Combinations of Visualization Techniques in Animation:

Schematic Diagrams
A way to view structure of an object, connections (of objects), or abstract processes (temporal connections of objects). Drawings of the object should be only as detailed as necessary to communicate understanding. Cross sections should be carefully cut (and visualized) so that inside and outside distinctions can be made and the form as as whole is still readily perceived. In charts of process, if the process is abstract, consider employing visuals that offer interest-piquing metaphor.

When making process graphics, it is helpful to recognize an overall image, a sequence of images, and the feature graphic. The overall image should lead the eye through the whole, often helpful to read top-left to bottom-right. Any visualization of the process must be distinct from the elements or actors, as such the elements and actors must be perceptually grouped/organized to show relationships. Feature graphics or elements must be introduced early in sequences, so that the rest of the sequence can animate the process and relationships.

Maps
Cartographic information pertaining to event space should be placed in context, with appropriate amounts of labels for bordering lands or geographic features (like bodies of water). Thematic maps provide a spatial distribution of one or more phenomena; in these cases geographic data is linked to statistical data. Codifying the map with symbols or iconography is often necessary, but in the course of an animation the legend should not be present the entire time (labels or voice-over work can suffice), so clear metaphors for visual encoding must be established. Moving images of maps need not a title, because tracking and eye back and forth from title to map (or legend to map) costs time.

“A good information graphic makes its content, or its essence, as accessible as possible in a brief period of time” (Finke & Manger, 109).

Finke_Manger_Workflow.JPG

Process & Pitfalls: Writing in InfoVis

Process and Pitfalls in Writing Information Visualization Research Papers
Tamara Munzner (2008)

Applied Reading 1

Patrick J. O’Donnel

Munzner begins her meta-research paper, or model paper, supported by her involvement as Posters and Papers Chair of the IEEE Symposium on Information Visualization, by recognizing common pitfalls witnessed in research writing for the information visualization community.

“A good way to begin a research project is consider where you want it to end” (Munzner, 2). This advice, as logical as it may sound, gives a false sense of applicability with its proverb-like brevity. It is my interpretation that Munzner wishes to espouses is one of a researcher’s awareness of a sound argument during the project’s conception. If taken too literally, one could bias any creative effort to eschew undesired form. Instead, she most likely supports her later categorizations of papers as having validation methods unique unto themselves. Breaking ground on a new research topic without these validation methods in mind could prove fruitless, despite richness of content and discovery.

Non-Exclusive Categories of Research Papers

(1) Technique Paper

The main contribution of a technique paper is a novel algorithm or implementation. The validation methods are beyond the scope of my thesis work at this time.

(2) Design Study

New visual representations in context of a problem are the contributions of Design Studies. In order to accurately justify the visual encodings utilized, one must include brief and relevant contextual history of the problem as well as any requirements obtained through task analysis, so that the appropriateness of the solution can be appraised. Furthermore, a researcher can also conduct and include case studies, scenarios of use, or evidence of adoption by a target audience to help support their solution’s approach. This style of paper is well within my personal technical abilities and theoretical scope for my thesis.

(3) Systems Paper

A Systems Paper evaluates the use of infrastructure, framework or toolkits in software or applications. These types of papers consider choices in structure rather than visual encodings. These types of papers are not within the scope of my abilities to author with my current thesis.

(4) Evaluation Paper

Information Visualization systems and techniques are examined in use by some target population in any Evaluation Paper. Both laboratory studies of abstracted tests, and real-world behavioral field studies fall under the umbrella of this category of research paper. The lines between Evaluation Papers, Design Studies, and Ethnography can be blurry and often co-exist. This style of research is within my capabilities, but does not exclusively match the creation-of-works approach of my thesis.

(5) Model (Meta-Research) Paper

A Model Paper is considered a Meta-Research Paper because it presents formalisms and abstractions about the nature of work, production, and process. Taxonomy models seek to detail the space of some topic (such as categorization of other works). A Formalism model provides new terminology and methods by which to analyze past (and future) works. Commentary models craft an argument for a position relating to the field, much like an opinion column or advice but supported by observation, reflection and prediction. Some parts of my thesis will likely lean towards a Formalism Model paper, as it will detail my conceptual model for working with material, space, and interaction simultaneously.

Pitfalls in writing research papers come in many forms during all stages of researching and writing. Munzner suggests that many researchers fail to connect their contributions to either technique (algorithmic) or design. In a well-drafted design study paper, a well-versed information visualization professional must know how to “clearly state the problem” that can be addressed through visualization techniques, know those very techniques, and justify the technique used against other techniques in existence. When writing a paper that exists in more than one of these categories, understand which category is guiding your writing structure most, and which categories are secondary—and how to properly embed them not to distract from the primary purpose.

Justifying visual encoding and interaction methods is a necessary consideration for design study papers; do not skip discussing task analysis. Similarly, any kind of technique proposed that does not discuss who or when it might be used is hardly useful. Specificity of use case is not a requirement, but at least abstractions of tasks in domains is advised to be included in research documentation.

Visualizations in three-dimensions are often necessary when the mental model of the content must be mapped less abstractly to afford quick understanding.  When working with 3D spatial data, consider occlusion and interactivity that permits navigation of perspective. But do not assume this to be solved, as human memory is limited to make judgments from a current viewpoint to a previous viewpoint.

Research papers should not read like a manual or a journal entry; they are not exhaustive of your process, rather they are tailored and designed to make an argument. The scope of your research (and thus paper) should be self-contained and not so dense as to cover too many topics. A proper research paper should present the amount of material necessary to make your point and be able to be reproduced. To avoid missing details or including unnecessary details, consider using a sentence such as “My contribution is…” near the end of the Introduction and ensure your writings address that contribution thoroughly.

“What can we do that wasn’t possible before? How can we do something better than before? What do we know that was unknown or unclear before?” (Munzner, 12).

Convince the reader of your paper that your contributions are unique by detailing how your work differs from the established work of the intellectual community past and present. Do not simply cite previous work, explain in what ways does it not solve the problem you’ve identified. Consider grouping previous works into categories to systematically carry out analysis of each work and it’s limitations. No assertion should go unattributed. If a fact is presented as justification and no source is cited (such as “general knowledge” or “conventional wisdom”) consider deleting it, making a different justification, or searching for research on that topic. Research papers that fail to disclose reflection on their own weaknesses, limitations, or implications are seen as unfinished.

When comparing your results to other work, compare with the most up-to-date work possible. Choosing data sets to test with use-cases should be indicative of the data sets actual users would come across. Tasks used to epitomize results should be justified, in that actual users would come across the need for this procedure. Cherry-picking tasks that showcase your solutions strengths (or worse, hides its weaknesses) dilutes your results with bias.

Writing a research paper requires a calculated style that aims to produce understanding in the audience. It is often helpful to present solution descriptions in the order of what it is, why you chose it, and then how it satisfies the problem. Captions should be written in full-sentence, paragraph form so that a chart, diagram, or image could justifiably stand alone, and flipping through the paper would allow an overview via the images only. When comparing visual techniques to others, it is helpful to do so side-by-side, rather than relying on the capacity of human memory.

Behavior/Experience Readings W1

Readings Week 1
Design for Behavior & Experience

“Chapter 7 Hurried Ethnography for the Harried Ethnographer” Ethnography: A way of Seeing. Wolcott, 2008.

  • What is the minimum or maximum time needed to be spent in the field to claim ethnographic validity? The researcher’s belief that enough time will produce guaranteed outcomes is at odd with the realist’s understanding that it’s impossible to exhaust any topic of inquiry.
  • “Ethnographic accommodation” is a researcher’s limitations of time that are put upon an study that employs ethnographic means.
  • How should a researcher handle time? As a scarce resource. Plan out time and set limits to fieldwork that take into account the other parts of the project.
    • When field work is not yielding any new or novel insights, it may be time to start writing.
    • Writing while still having time set aside for field work permits an initial analysis that a researcher can use to focus the remaining observation time.
    • Begin writing as soon as you think you might not be able to get it all. Do not put off writing by waiting to be a more astute observer.
    • Once you begin to review collected data in your head, start writing. Begin with the comfortable or well-synthesized ideas, and the writing should guide the remaining time you set aside for field work.
    • Start writing if half of your total time is remaining. Writing and organizing data often takes more time than observations themselves.
    • “People do writing this fashion [fieldwork first, then writing last] but this is one reason why so many monographs are uninspired.” Rosalie Wax
  • Writing about your thoughts before fieldwork can help to focus your observations on its ultimate purpose, and to organize your final account.
  • In subfields of anthropology, rapid fieldwork has become common but should not be dismissed. Common surveys, questionnaires, targeted interventions are not rushed as much as they are repetitive and formalized. Ethnographers are then considered data sources for teams conducting anthropological appraisals.
  • Anthropological appraisals may use common interviewing techniques, or even group interviews (focus groups), where an ethnographer would partake in a less structures interview/conversation and potentially identify a key informant.

“[…] Much stands to be gained for any researcher who pauses long enough to have a look around, with the intention of putting an inquiry into some broader perspective.”

Ethnographic Reconnaissance

  • –an ethnography precursor, permitting an initial survey or examination which is followed by a more detailed inquiry.
  • A windshield survey–or a survey of a community from a drive around town–is a rapid appraisal technique that can lead to valuable observations for further examination.
  • Ethnographic reconnaissance does not carry the notion that it must be done quickly, only that time must be set aside for getting one’s bearings in a new situation.
  • Do not disregard intuitive feelings about what is going on in a project, even if you’re part of a team performing pre-selected rapid assessments. Reconnaissance and getting one’s bearings should aware remain forefront while doing fieldwork.
  • Advice for initiating fieldwork to realize maximum return on ethnographic reconnaissance:
    • ethnographic reconnaissance develops organized common sense, free from inappropriate professionalism. don’t stick to overly scientific methods for observing the nuance complexity of human activity.
    • a researcher conducting ethnographic reconnaissance should try not assume a tourist or poll-taker or professional researcher identity, rather an interested human being. All of those identities could hinder natural conversation.
    • do not feel pressured to “sample” the population in any certain way. There will always be “gate keepers” of the community and they are worth your time as well.
    • write up notes quickly thereafter a reconnaissance effort. Initial opinions, anticipated problems, observations that go against your conceived notions are often fleeting once removed from the field.
    • keep in mind you are there to learn how those in this setting make sense of their world; if they can’t answer a question, it’s not part of their world. an idealistic goal for interviewing is to get them to talk with the fewest direct questions. ask questions as they come to you.
    • know what information is already out there (community history, maps) and do not feel obligated to reproduce it, but consider its biases and affordances carefully before inclusion in your reconnaissance or ethnography.

Systematic Research

  • Systematic research doesn’t always describe the existence of a community in ethnography. Care should be taken to understand when and how to count what needs to be counted, and measure what needs to be measured.
  • Problems and questions that are defined or redefined in terms of computational capabilities shift the researcher further away from orienting traditions of ethnography.
  • Photography, videography, and systematic research should not become ethnography–they are tools, not philosophies.
  • Stepwise research should not go against timing, but instead inform it. Dedicate chunks of times to different topics over the course of the fieldwork, and observe what changes and what doesn’t.
  • long-term fieldwork by ethnographers can provide “finer distinctions between change efforts and changed results, or between change and rhetoric of change.”

 

The Interpretation of Cultures “Chapter 1 Thick Description: Toward an Interprettive Theory of Culture” C. Geertz, 1973.

“To try to find the figure in the carpet of one’s writings can be as chilling as trying to find it in one’s life; to weave, post facto, a figure in —”this is what I meant to say”—is an intense temptation.

  • New ideas take hold of the intellectual community with vigor. It is applied to many problems and many situations. The community applied is where it is applicable and desists where it cannot be extended. What is does explain is now brought into focus, and the pseudoscience falls away.

“The concept of culture I espouse […] is essentially a semiotic one. [M]an is an animal suspended in webs of significance he himself has spun, I take culture to be those webs, and the analysis of it to be therefore not an experimental science in search of law but an interpretive one in search of meaning.”

  • If you want to understand science, look at what practicing scientists do. If you want to understand anthropology, look at ethnography.
  • Ethnography is more than just establishing rapport, selecting informations, transcribing texts, etc. It is an intellectual effort called “thick description” by Gilbert Ryle.
    • “Thick Description” is both thinking and reflecting, as well as thinking of thoughts.
    • A “thin” description of events merely records actions or direct observations, but a “thick” description finds a hierarchy of meaningful structures that leads to the actions. Where was this action learned? What was the intention behind the action? What is the context of the action? What is the action codifying?
  • Ethnography is a collection of data that is really a “construction of other people’s constructions of what they and their compatriots are up to. [I]t does lead to a view of anthropological research as rather more of a observational and rather less of an interpretive activity that it really is.” Analysis is sorting out the structures of signification.

“What the ethnographer is in fact faced with […] is a multiplicity of complex conceptual structures, many of them superimposed upon or knotted into one another, which are at once strange, irregular, and inexplicit, and which he must contrive somehow first to grasp and then to render.”

  • Human behavior as symbolic action has a significance. The communication by an action’s agency is of significance. With this componential analysis of culture, “culture is composed of psychological structures by means of which individuals or groups of individuals guide their behavior.”

“The cognitive fallacy—that culture consists of ‘mental phenomena which can [should] be analyzed by formal methods similar to those of mathematics and logic’—is as destructive of an effective use of the concept as are the behaviorist and idealist fallacies to which it is a misdrawn correction.”

  • Ethnographers seek to speak to and with individuals, not for them.

“Culture is not a power, something to which social events, behaviors, institutions, or processes can be causally attributed; it is a context, something within which they can be intelligibly—that is, thickly—described.”

  • Behaviors are the vehicle for culture. Behaviors’ relationships to each other is intrinsic, but it’s their role in patterns of life that give them meaning.
  • Inspecting events his how we interpret symbols and symbol systems, not by setting them up and organizing them into our own patterns.
  • Searching for sound, overarching order in cultural proceedings discredits analysis; do not divorce interpretations of events from the events themselves.

“If anthropological interpretation is constructing a reading of what happens, then to divorce it from what happens—from what, in this time or that place, specific people say, what they do, what is done to them, from the whole vast business of the world—is to divorce it from its applications and render it vacant. A good interpretation of anything—a poem, a person, a history, a ritual, an institution, a society—takes us into the heart of that of which it is the interpretation. When it does not do that, but leads us instead somewhere else—into an admiration of its own elegance, of its author’s cleverness, or of the beauties of Euclidean order—it may have its intrinsic charms; but it is something else than what the task at hand—figuring out what all that rigamarole with the sheep is about—calls for.”

  • There is a distinction being speaking and writing. An informant speaks; speaking is the event.  An ethnographer writes (inscribes); writing is the thought of speaking… or the meaning of the speaking.
  • Cultural analysis is guessing at meanings and assessments of such guesses; it is not all-encompassing or robust, rather its nuanced and situational.
  • Ethnographic descriptions are…
    1. …interpretive.
    2. …interpretive of the flow of social discourse.
    3. …attempts to rescue the “said” of discourse from ephemerality.
    4. …microscopic by nature.
  • Any larger, broader implications or abstractions of culture are often from extended acquaintances with extremely small matters, not a wide variety.
  • “To regard [ethnographic findings] as anything more (or anything less) than [particular] distorts both them and their implications, which are far profounder than mere primitivity, for social theory.”
  • This methodological critique of the microscopic nature of ethnography is valid, yet not to be resolved by considering the events as an actual microcosm, but resolved by “realizing social actions are comments” on society, with no bounds nor guarantee where the interpretation can go.
  • Generality of cultural theory grows from the “delicacy of its distinctions, not the sweep of its abstractions.”
  • Cultural analysis does not build on other analysis; it “plunges deeper into the same things” and enriches the understanding of both analyses.
  • Cultural theory is not predictive. It guides the lens to which we can view past events, and potentially anticipate future occurrences of the event.

“In ethnography, the office of theory is to provide a vocabulary in which what symbolic action has to say about itself—that is, about the role of culture in human life—can be expressed.”

  • Cultural analysis is, by definition, incomplete. They are sustained by continued debate and discussion. Yet, the more narrow the details, the less complete they become.

“The danger that cultural analysis, in search of all-too-deep-lying turtles*, will lose touch with the hard surfaces of life-with the political, economic, stratificatory realities within which men are everywhere contained-and with the biological and physical necessities on which those surfaces rest, is an ever-present one. The only defense against it, and against, thus, turning cultural analysis into a kind of sociological aestheticism, is to train such analysis on such realities and such necessities in the first place.”

*An old Indian story goes: The world rests upon a platter that is on the back of an elephant and that elephant stands on the shell of a turtle. Each turtle, in turn, rests on another turtle.

“Ethnography” in The Encyclopedia of Human-Computer Interaction, 2nd Ed. D. Randall and M. Rouncefield.

What is Ethnography?

  • “Ethnography is a qualitative orientation to research that emphasizes the detailed observation of people in naturally occurring settings.”

Why use Ethnography?

  • “Perhaps the main virtue of ethnography is its ability to make visible the ‘real world’ sociality of a setting through detailed descriptions of the ‘workaday’ activities of social actors within specific contexts.”
  • Ethnography seeks to observe and record activies as social actions embedded in a socially organized domain.

Doing Ethnography – Relying on the Kindness of Strangers

  • The social world ethnographers plunge into is often not organized in the way researchers expect to find it.
  • Recording the richness of everyday activities is often difficult because of its commonplaceness.
  • Ethnography does not take immense amounts of training, nor is its goal to search for hard-to-find things; nor is it simply hanging around or experiencing another community. It is listening and watching to the guiding principles that structure others’ activities.

What does an Ethnographer do?

  • An ethnographer does not need to go look for data; they look for communities and actions within these contexts to observe, the data is then presented to them in that context.

“The point of fieldwork is to understand the social organization of activities within the setting.”

Collecting Data

  • “In terms of what the fieldworker collects by way of data, […] it will be dictated not by strategic methodological considerations, but by the flow of activity within the social setting.”
  • Everything an ethnographer experiences or witnesses or observes is data. There is no sense in having all the data, but nevertheless your record of it should far exceed your use of it.
  • Ethnography is “the deliberate attempt to generate more data than the investigator is aware of at the time of collection” (quoted in Dourish (n.d.: 2). Mass amounts of data collection tends to happen as a consequence of the ethnographer’s immersion in a setting. Recording things often comes naturally as a foreigner in a new country wants to document everything they don’t understand.

Readings for Sept 13

ARTG 6310: Designing for Behavior and Experience, Week 0

 

“The Design of Waits” Chapter from Don Norman’s Living with Complexity (2011)

Quotes

  • “Unexplained waits are annoying; unfair waits can be anger inducing.”
  • “There will be waits whenever one system has to send items or information to another. It doesn’t matter whether the interaction is between two organizations, two people, two machines, or a person and a machine or organization.”

The Psychology of Waiting

  • “[A] person in line soon develops a long list of questions about efficiency, fairness, and even the nature of the line itself.”

Design Principles for Waiting

  • 1. Provide a conceptual model.
    • “For the model to be effective, there must be ample feedback. Uncertainty is a prime cause of emotional irritation: a good model coupled with proper feedback removes this source of anxiety.”
    • “The goal is to minimize uncertainty by providing reassurances and evidence of care.”
  • 2. Make the wait seem appropriate.
    • “The perception of appropriateness ultimately derives from a combination of information about the situation and the conceptual model.” The cause, duration, and provider response should all be perceived as appropriate.
  • 3. Meet or exceed expectations.
    • “Experience shows that the time should always be overestimated: if the actual waiting time is shorter than the expected time, people are likely to be pleasantly surprised.”
  • 4. Keep people occupied.
    • “[P]hysical time and distance can be precisely specified and measured, but people’s perceptions of distance and time are governed by psychology, not physics.”
  • 5. Be fair.
    • “Emotion is heavily influenced by perceived causal agents. If the wait seems reasonable, with nobody to blame, it will not necessarily trigger a strong negative emotion. The emotion comes when there is something to blame, even if it isn’t true. Thus, if the line appears to be arbitrary, unpredictable, and worst of all, unfair, emotions rise.”
  • 6. End strong, start strong.
    • “But if everything is relatively homogeneous (such as the act of waiting in line, from entering through leaving), then the most important influence on memory is the ending, the beginning, and the middle, in that order. This is called the serial position effect.”

Design Solutions for Waiting

  • “A form of the double buffering principle can be seen in the design of a two-sided cash register. Here, the cashier is in front of a cash register with customers on both sides—the right and left”
  • Supermarkets, Coffee Shops and Drive-Thru restaurants all currently use some form of temporal (linear) double bufferings, allowing customers to start part of the experience of getting coffee before the prior customers’ services are completed.

Designing the Lines

  • “Customers far prefer the perceived fairness of a single line feeding multiple servers rather than individual lines in front of each server.”
  • “The electronic variants [of number assignment queues] have the virtue of giving people more freedom to wander, but they eliminate the feedback that comes from being able to observe the length of a line or the current number being served.”
  • “One way to minimize the trauma of waiting lines is through reservations. But this has to be done in a way that seems fair and reasonable, even to those without reservations. […] A modification of a reservation system is to provide each person with an admissions ticket with a guaranteed time, even if it is for some time in the future.”

Memory Is More Important than Reality

  • “The memory of the whole experience is more important than the experiences of the separate parts.”
  • “Some waits at the start of an activity are beneficial, allowing us time to prepare [or decide].”
  • “[T]hrough the psychological mechanism known as ‘cognitive dissonance,’ the suffering actually enhances the enjoyment of the later event. Although the dissonance reduction is subconscious, think of it as the subconscious mind deciding that ‘any event that requires so much effort to enter must really be important and wonderful.'”

When Waiting is Handled Properly

  • “Note too that you cannot assess the strength of the negative feelings just by asking those who are waiting to be served. The people with the strongest negative reactions may have stopped attending altogether.”

Designing the Experience

  • “When we’re in a positive mood, minor difficulties or confusions are considered minor, not a major problem. But when we’re anxious or irritable, the same minor setback can become a major event.”

Takeaways

  1. Waiting is a product of systems interacting.
  2. Computations of efficiency, fairness of waiting are necessary while designing lest they exclude the human element of experience.
  3. “Conceptual models can transform confusing products and services [and waiting lines] into coherent and understandable ones.”
  4. Feedback and explanation are tools to help users wait less frustrations, informing them why they are waiting and that its reasonable to do so.
  5. Different cultures are accustomed to different structures of waiting, and therefore also different experiences while waiting.
  6. After an event outcome, the memories of the event dominate the memories preceding the event only if the unpleasantness (of boredom and frustration and anxiety) is outweighed by the reward or desired outcome of the event itself.

 

“The Psychology of Waiting Lines” by David H. Maister (1985)

Quotes

  • “Waiting is frustrating, demoralizing, agonizing, aggravating, annoying, time consuming and incredibly expensive.” –Federal Express Advertisement: Fortune, 28 July 1980, p. 10
  • “Once we are being served, our transaction with the service organization may be efficient, courteous and complete: but the bitter taste of how long it took to get attention pollutes the overall judgments that we make about the quality of service .”
  • “S = P – E. In this formulation, ‘S’ stands for satisfaction, ‘P’ for perception and ‘E’ for expectation. […] The point, of course, is that both the perception and the expectation are psychological phenomena.”
  • “I would hypothesize that people waiting to make their first human contact with the service organization are much more impatient than those who have ‘begun’: in other words, preprocess waits are perceived as longer than in-process waits.”
  • “Ask yourself what customers might be worrying abut (rationally or irrationally), and find ways to remove the worry.”
  • “[A] customer with an appointment has been given a specific expectation about waiting times, and a failure to deliver on this premise makes the wait seem longer than if no appointment had been made. […] It should be recognized, however, that an appointment defines an expectation that must be met.”
  • “Waiting in ignorance creates a feeling of powerlessness, which frequently results in visible irritation and rudeness on the part of customers as they harass serving personnel in an attempt to reclaim their status as paying clients. In turn, this behavior makes it difficult for the serving personnel to maintain their equanimity.”
  • “[T]he customer’s sense of equity is not always obvious, and needs to be explicitly managed. Whatever priority rules apply, the service provider must make vigorous efforts to ensure that these rules match with the customer’s sense of equity, either by adjusting the rules or by actively convincing the client that the rules are indeed appropriate.”
  • “[A user’s] tolerance for waiting depends upon the perceived value of that for which [they] wait.”

Takeaways

  1. When addressing the concerns of waiting (with research and design), the objective reality of the systems has been favored over emotional experience brought about by the systems.
  2. Occupied time feels shorter than unoccupied time.
  3. Service-related waiting can give the illusion that service has begun, which lessens the negatives effects of waiting.
  4. If a user must wait, it is preferable that the waits are expected/justified, known, equitable and finite. Any deviation from this could cause anxiety, dissatisfaction, or perceived temporal lengthening.
  5. “By learning to research and understand the psychological context of their own waiting lines, managers can have a significant impact upon their customers’ satisfaction with the service encounter. “

 

“The End of Reflection: Future Tense” by Teddy Wayne (June 11, 2016 – New Yorker Times)

Quotes

  • “Finding moments to engage in contemplative thinking has always been a challenge, since we’re distractible,” said Nicholas Carr, author of “The Shallows.” “But now that we’re carrying these powerful media devices around with us all day long, those opportunities become even less frequent, for the simple reason that we have this ability to distract ourselves constantly.”
  • “It seems counterintuitive to say that we are entering an unreflective cultural phase, as our time tends to be criticized for its self-absorption. But our solipsism is frequently given outward expression rather than inward exploration, with more emphasis than ever before on images. When there is text, new media such as Instagram commonly sideline the role of language.”
  • “As our technologies increase the intensity of stimulation and the flow of new things, we adapt to that pace. We become less patient.”

Takeaways

  1. The immediacy of information (as well as ubiquitous access) has led to the “loss of the contemplative mind,” and questions that don’t have simple, search-friendly answers become inefficient and not worth consideration.
  2. The outward expression of the digital media age is related to the lack of reflection and contemplation in the new society. Expressing a thought, an idea, an opinion, a tweet has less restrictions and hurdles than ever before.
  3. The human brain is easily distractible and mobile media devices permit distraction. The distraction is from the rumination and contemplation that previous generations have used to craft, edit, consider, and empathize viewpoints.