SAP DESIGN GUILD

UI Design Blinks (2012)

By Gerd Waloszek, SAP AG, SAP User Experience – Updated: April 25, 2012

Gerd Waloszek Welcome to a new column of brief, blog-like articles about various UI design topics – inspired by my daily work, conference visits, books, or just everyday life experiences.

As in a blog roll, the articles will be listed in reverse chronological order – and if the roll becomes too long, I will start a new one.

Please note that I will not be able to maintain the initial publishing speed! The articles will appear at irregular intervals as time permits and inspiration comes...

GoSee also an overview of 2010 Blinks • overview of 2011 Blinks

 

April 18, 2012: A Sneak Preview of Wearable Computing

At the recent "Interaction 2012" conference in Dublin, Ireland, I attended a keynote by Amber Case. Case calls herself a "cyborg anthropologist" (and user experience designer) and started her keynote with a definition of cyborgs: A cyborg is an organism "to which exogenous components have been added for the purpose of adapting to new ambient spaces". The Wikipedia definition of cyborgs is perhaps a little easier to understand: "A cyborg, short for cybernetic organism, is a being with both biological and artificial (e.g. electronic, mechanical or robotic) parts. Case presented Steve Mann (from MIT) as a prototypical example of a cyborg. . In 1981, he began wearing computers on his body to augment reality through a view-piece, called a "wearcam", strapped around his left eye (see Figure 1). According to Case, this may have been one of the first examples of an extension to our mental selves (but see Mann's history starting with wearable abacuses and wrist watches...).

Steve Mann 1981

Figure 1: Steve Mann in 1981 (photo of Amber Case's slides)

Case remarked that while technology has advanced since the 1980s, our perception of cyborgs is still influenced by the augmentation of the physical. Nevertheless, the progression of physical to mental augmentation is reflected in today's devices, which are unstable, change, and are proclaimed (by Mark Weiser and Don Norman, for example) to become invisible in the end. This is reflected in Steve Mann's "evolution" and his state today (see Figures 2-3):

Evolution of prosthesis     Present-day Steve mann

Figures 2-3: The evolution of prosthesis, demonstrated by Steve Mann (photos of Amber Case's slides)

I tell this story here, because yesterday, Mads Soegaard, editor of the HCI encyclopedia at interaction-design.org, notified me of a new sneak preview for SAP Design Guild readers: a chapter written by Steve Mann entitled, Wearable Computing: www.interaction-design.org/encyclopedia/wearable_computing.html?p=b248. "Oh, it's a small world", I said to myself...

I learned about wearable computing many years ago at the CHI 2002 conference (see my CHI 2002 report CHI 2002 – Changing the World, Changing Ourselves), but at that time I thought it was just a flash in the pan. Shortly afterwards, the links to manufacturers of smart clothing no longer worked. And, admittedly, despite all the fuss about ubiquitous computing, I have not heard a great deal about wearable computing since.

Kevin Warwick on video

Figure 4: Kevin Warwick appeared via QuickTime video and cell phone

At the CHI 2002 conference in Minneapolis, I also attended a remote interview with Kevin Warwick, who was then exploring transplants that connect the nervous system to electronic circuits, which command electronic devices. It was interesting for me to learn that Steve Mann includes both implantable and portable devices like smartphones in his definition of "wearable", or as he prefers to say, "bearable" or "body-borne" computing.

Once again, the encyclopedia chapter is accompanied by several commentaries. I would like to recommend reading the commentary by Woodrow and Jessica Barfield as an introduction to Mann's chapter. They write:

"Steve Mann has written a comprehensive and informative chapter on the general topic of wearable computing (which Steve describes as miniature body-borne computational and sensory devices). We use the phrase – "general topic" because Steve expands his discussion of wearable computing to include the more expansive term, "bearable" computing (essentially wearable computing technology that is on or in the body). In the chapter, Steve also discusses how wearable computers may be used to augment, mediate, or diminish reality. ... While much of Steve's current chapter is historical in content, he also discusses many of the wearable computing applications he has created, often with Steve's insight as to the rationale behind his inventions."

I could not have provided a better description. Finally, I would like to point you to some buzz words in the area of wearable computing that might help you extend your vocabulary:

Enough said. Now it's your turn to put on your glasses (if you neede them and which, by the way, are a very old analog wearable computing device) and delve into Mann's chapter and the commentaries.

References

March 27, 2012: A Sneak Preview of Visual Aesthetics

When I was a student, a fellow student of architecture told me that he attended a lecture about "numeric aesthetics". I was surprised that such a topic existed at all and asked him to provide me with the lecture notes. When I looked at the notes, I was surprised again to encounter stuff that was familiar to me as a physics student: Numeric aesthetics has a lot in common with thermodynamics, and as I found out later, also with information theory (which made perfect sense to me). In my simple words, this approach was measuring order and disorder in visual scenes. This reminds me of my own behavior when placing objects on tables and shelves: I cannot stand when they lie around in an irregular, "chaotic" fashion (see the figures below).

Chaotic table   More orderly table

Figures 1-2: Chaotic vs. more orderly desk at work – I prefer the more orderly version on the right (lower entropy)

In his new HCI Encyclopedia chapter Visual Aesthetics, a term that refers to the "beauty or the pleasing appearance of things", Noam Tractinsky surveys the field of visual aesthetics in HCI and in the course of it also touches on the issue of measuring aesthetics in the context of interactive systems (and potentially providing guidelines or heuristics for creating aesthetically pleasing designs). Interestingly, this has been a research topic in the HCI domain for only about 15 years. Tractinsky actually co-established this research field within HCI, and in his chapter provides an overview of the current state of affairs. He discusses, among others, the following questions:

By the way, attentive readers will already have noticed that another new chapter of the HCI encyclopedia is about to appear. Indeed Mads Soegaard, editor of the encyclopedia, has provided one more sneak preview for SAP Design Guild readers: www.interaction-design.org/encyclopedia/visual_aesthetics.html?p=b248.

Let me return to the new chapter. The theme of my introduction refers to the first question. One might be tempted to assume that formal, objective attributes of the visual scene determine people's aesthetic judgments. And indeed, according to Tractinsky, "some researchers argue for the prospect of identifying formal, objective, attributes that determine aesthetic judgment." These "will ultimately lead to automatic composition or checks of displays such as Web pages." However, as the third question suggests, formal attributes are only part of the story. Tractinsky cautions his readers that "this approach has been criticized on the grounds that aesthetic laws engrained in the object as 'universal' would not survive individual, cultural and context differences." He comes to the more pessimistic conclusion that "the problem of finding universal visual aesthetic guidelines and laws is further exacerbated in the field of HCI because of the variety of applications and products and the uniqueness of so many use contexts. In addition, the dynamic nature of contemporary society and fashion-like approach to the design of many interactive devices and applications make aesthetics a moving and often unpredictable target."

By the way, two of my colleagues at SAP User Experience are investigating this field, and they do it from the "objective" point of view: At the Mensch & Computer 2011 conference in Chemnitz, Germany, Chris Lafleur and Bernard Rummel won the Best Paper Award (Research Award) for their paper Predicting Perceived Screen Clutter By Feature Congestion. They had evaluated an algorithm which calculates a measure of visual clutter from screenshots, called feature congestion. In a nutshell, the algorithm predicts how hard it is for an item in a picture to stand out by its visual features so a viewer can actually find it.

Let me conclude this UI Design Blink with two interesting topics that I found in Tractinsky's chapter. Firstly, according to Tractinsky, research in HCI primarily views the value of visual aesthetics as a mediating force between perceived attributes of the product: For example, visual appeal has been demonstrated to have positive effects on perceived usability (particularly, in the case of low usability) and performance (Norman: "attractive things work better"). He concludes that "there is empirical evidence that aesthetic design of interactive technology increases users' pleasure and engagement. Consequently, we expect pleasurable interactions to make us happier and thus to improve our well-being. Furthermore, they may make us more tolerable of other design imperfections and improve our task performance under certain conditions." But before you rush to focus on visual design be warned: A closer look at the chapter reveals that the studies provide "mixed results" and that the preconditions of positive effects are largely unknown.

Secondly, Tractinsky discusses the "(dis)connect between designers and users", which in his opinion has yet to receive attention as a research topic in HCI. He writes: "In other design disciplines, studies have found significant differences in aesthetic evaluation between lay people and designers. In HCI such differences were found between designers and software engineering students in assessments of Website design trends. Similarly, authors found that the minimalist design recommendations for charts made by Tufte's (1983) influential critique of "chartjunk" practices do not resonate with people's actual preference of chart types." I assume that every designer has faced this disconnect in his or her professional life. I found that there is often a huge difference between what professionals like and what lay people prefer.

In this UI Design Blink, I picked only a tiny bit of what Tractinsky discusses in his HCI encyclopedia chapter about visual aesthetics, but I hope I have, once again, whetted readers' appetites. As always, the chapter is accompanied by a number of commentaries from researchers, regrettably not from design practitioners. Personally, I found the commentary by Alistair Sutcliffe most useful, and I also like Mark Hassenzahl's remarks about the aspect of authority in our aesthetic judgments. He states: "It is not an immediately perceivable inherent quality that distinguishes a design classic from any other object. It is the very fact that accepted authorities announce it to be a design classic – through exhibiting, reviewing, and giving away precious awards – which counts." Hassenzahl illustrates his remark with two striking examples, and I suggest that you read them in the HCI encyclopedia, because I will not disclose the puchline here... All in all, I think that this chapter is, once again, a useful read for HCI professionals. While Tractinsky's chapter focuses on research, I found unexpectedly many connections to my daily work in it.

References

March 13, 2012: Two More Sneak Previews into the HCI Encyclopedia

Last Friday, Mads Soegaard from interaction-design.org notified me that there is another sneak preview on the HCI encyclopedia available for SAP Design Guild readers, namely Victor Kaptelinin's chapter on Activity Theory. Shortly thereafter, Mads announced another one, namely Albrecht Schmidt's chapter on Context-Aware Computing, and we agreed to feature the two previews in one combined UI Design Blink that would be published at the beginning of the following week. This implied, however, that I had to write the article on the weekend and that I had to tell my wife and my friends I would be busy that weekend writing it. And then I started trembling: If they would ask me what the article and the HCI encyclopedia chapters are about, how would I explain it to them? My solution was to write this article as an attempt to answer their potential questions.

Albrecht Schmidt's chapter about context-aware computing looked like the easier task to me, so "easy" things first. Although the term itself might frighten people, context-aware systems are, as Schmidt points out, ubiquitous and therefore familiar to us. In his chapter, he presents simple examples of such systems and assures his readers that these already "outline the basic principle of a context-aware system". One of his examples is the exterior lighting of houses. Here, two sensors come into play which detect the state of the environment, more scientifically called "context": a light sensor for detecting darkness and a motion sensor for detecting moving people (which sometimes also detects the neighbors' cats or cars that pass by). When it is dark outside, the light switches on when it detects a movement, switches off again after a period of time if no more motion is detected. The system's "computing" is based on analog circuitry, or at least it could be – no "digital computing" is required.

Now it is my turn to find examples. A very simple and primitive context-aware system comes to mind: the light inside a refrigerator. It switches on when we open the fridge and off when we close it (at least we hope it is switched off). This is not even a "computing" system, but a mechanical one, including the "sensor". My laptop is another example of a context-aware system: It has several sensors that help it accommodate the state of its environment. One of them detects when I close the lid to send the laptop into sleep mode. When I open the lid, the laptop wakes up again (well, most of the time anyway). This sounds like another fridge door example, but the "lid behavior" is "computed" and actually more complex: When the lid is closed and I connect a second monitor and a power supply to the laptop (see Figure 1), the laptop wakes up again to be used like a desktop computer (it took me quite a while to figure out how to get this to work).

Figure 1: My laptop is an example of a context-aware system – although the lid is closed, the laptop is "awake", because a monitor and a power supply are connected to it

And then there are zillions of so-called location-aware systems such as trip computers for cars, bicycles, and even walkers that use GPS data and other information sources. Everyone seems to have one – except me. Just mentioning these devices should therefore suffice. To sum up, context-aware computing basically is about a couple of sensors connected to a device plus some algorithms to process the sensors' data. That's how I will explain it to my family and friends. But you as a reader of this UI Design Blink should now be ready and eager to digest Schmidt's chapter. You will find out that there is a lot more to context-aware computing than I have mentioned so far: for example, (hierarchical) feature spaces, the User-Context Perception Model (UCPM), the notion of an awareness mismatch, and a lot more. You will also learn that designing context-aware systems is a difficult task. Some systems work flawlessly – while others fail miserably… Moreover, UI design becomes much more complex than in the good old days of desktop computing because you have to design for multiple usage contexts and to decide effectively (depending on location, time, movement, presence and many more factors) which context is present and when.

Now to the second sneak preview, the one on Victor Kaptelinin's chapter Activity Theory, which Mads announced to me with the words "We're happy to give you and your readers at your UI Design Blinks blog some real brain gymnastics". He was right and after having read parts of the chapter, I wrote to Mads: "I am just trying to read the Activity Theory chapter. Hard stuff for me as a physicist! I have problems when people "formalize" vague ideas... I need well founded mathematical formulas or algorithms to understand the effects... And sometimes, I would call the effects of the "object" on the "subject" simply learning... Have to read on…" As a consolation, Mads replied: "I know exactly what you mean. I spent *ages* trying to understand activity theory. And I still don't fully understand it. But it keeps popping up everywhere and all the time, so I force myself to read up on it every once in a while. But yes, really complicated stuff." Oh dear, how can I explain such a theory to my wife and my friends?

First of all, when I try to talk with other people about my profession and the related scientific background, they tell me that they knew that all along and ask me why science only confirms what we already know. I believe this is the key to explaining, or better introducing, activity theory to other people: Tell them what they already know. Even Victor Kaptelinin states in his chapter: "Most people have an intuitive understanding of what activities are. Is there any need for a theory here?" So, what's the issue? One of the issues is probably how activity theory is presented. Kaptelinin states: "A common problem with interpreting Leontiev's [the original author of activity theory] texts is that they often reflect the unfolding logic of his conceptual explorations rather than provide a systematic overview of the logical structure of the framework as a whole." Together with Bonnie Nardi, he translated Leontiev's framework, as it is described in his texts, into a structured set of distinct principles, which can be found in his chapter. But I have to make it much simpler for my friends. Here is an attempt:

I am far from believing that I have even touched the gist of activity theory with this example, but perhaps it helps readers lose their fear of this theory and makes them curious about Kaptelinin's chapter – which is a precondition for reading it. Will this example also work for my wife? I will check this even if she doesn't not ask what my article is about.

References

March 1, 2012: More Experiments with Skyline Graphs

My previous UI Design Blink about skyline graphs inspired a response and also a question from a reader. He sent me a 3D column chart and asked me my opinion about it. Because the graph contained the values for the columns, I was able to recreate the graph in Excel so that we are not confined to the original chart and its specific characteristics for the discussion here:

3D column chart   3D column chart with round columns

Figure 1-2: Two variants of 3D column charts for the same data set (created in Excel: Click images for larger versions)

One thing is obvious to me: It is hard to estimate the lengths of columns that are not located along the grids (of course, I could use a ruler, but that's not the intention of graphs). Comparisons are also difficult, partly because the columns start at different heights. The creators of the original graph indirectly conceded this point by adding values to the columns. That, however, made the graph even more illegible... At the end of the day, I still prefer the simple multiple column chart (see Figure 3) to its fancy siblings. And, with this chart type, there's no need to add numbers to the columns.

Multiple column chart

Figure 3: 2D multiple column chart using the same data (created in Excel: Click image for larger version)

You can find information about problems with charts in Recommendations for Charts and Graphics in the Goodies section on this site ("Problems with Charts" page).

I then turned my attention to skyline graphs, although, based on what I already knew of the, I ran into a serious issue straight away: Namely, that you can only compare two data sets at a time. The example above, however, contains three data sets. Therefore, in my initial attempt, I took the obvious approach and created two skyline graphs – using the "College students" data as a measure of comparison:

 

Figure 4-5: Relative changes and skyline graphs for younger vs. college students (left) and older vs. college students (right) (click images for larger versions)

As always, it took me some time to get familiar with the skyline graphs. But, having overcome my initial state of confusion, I could easily see that the younger students eat a lot less chocolate than the college students, and that they more or less shun two particular brands. The older students, on the other hand, do not differ much in their overall chocolate consumption from the college students, but their preferences are different. They have also accepted the two brands that the younger students do not like...

And then I asked myself: "Why not combine the two skyline charts into one?" So, I now proudly present the first result of my own experiments (I have never encountered such a graph, but someone else has probably tried it somewhere already):

Dual skyline graph

Figure 6: Combined skyline chart with college students as a reference (click image for larger version)

"Oh dear!" you might think, "What is this weird graph trying to tell me?" I will leave it to you to answer this question and to decide whether or not you like the graph. As a consolation, I will divulge one small secret: The blue-bordered boxes indicate the changes for the older students and the magenta-bordered boxes the changes for the younger students. I hope this helps at least a little...

References

February 21, 2012: Skyline Graphs – New Insights on the Horizon...

Sorry for the obvious title of this UI Design Blink, which was inspired by a paper presentation that I missed, entitled "Telling the Data Comparison Story Using A Skyline Graph (Instead of Two Pies)". Bill Caemmerer gave the presentation at the Interaction 2012 conference in Dublin in early February this year and introduced it with: "Just like every picture, every graph tells a story, or it should. Frequently the story we want to tell is a comparison to the past or to our plans, a 'what happened' story. Do we have the best tools to tell this story visually, in graphs?" He believes that traditional graphs do no tell the whole story and offers a new graph type that does – the skyline graph. While I had missed Caemmerer's message, a former colleague told me at the conference that he had attended the presentation and made me curious about skyline graphs. I searched for Caemmerer's slides and found them on the Internet. In the following I will briefly disclose what I have learned from them and from searching the Web. I will also present some results of my own programming exercises in skyline graphs using once again Processing, a programming language for designers.

The Starting Point

Let's assume that you have two sets of data and want to make a "Before-After" (or an "After-Before") comparison:

Data
1
2
3
4
5
6
Before
10
20
30
15
15
10
After
15
15
20
20
23
7

Table 1: Two data sets for comparison

The data in Table 1 might represent categorical item values, for example, the yearly spending for different budget items (for two different years). In this particular example, each data row totals to 100 so that the data might be treated as percentages, but this is not relevant here. This data can be presented visually, as the title of Caemmerer's presentation suggests, as two pie charts:

Chart 1 (before)
Figure 1: "Before" pie chart (created in Excel) Figure 2: "After" pie chart (created in Excel)

It can also be presented using a horizontal bar graph with two columns for each item and each column representing one data row:

Dual horizontal bar chart

Figure 3: Bar graph with "Before" and "After" bars (created in Excel)

According to Caemmerer, and I agree completely, the following questions are hard to answer from these charts: Questions on...

A Proposal

Because these graph types do not "tell the story behind the data", we need a better graph that makes relative as well as absolute changes visible. Caemmerer regards a skyline as a good approach to this, and the following slide from his presentation illustrates the basic idea behind the skyline chart:

Skyline

Figure 4: Deriving the idea of skyline graphs (from Caemmerer's slides)

The horizon provides a reference and standard of comparison (it can be the 0% or 100% percent line, depending on how you scale your data). Relative changes are made visible through the height of the buildings/bars relative to the horizon, while absolute changes are made visible through the areas of the buildings/bars. 

I searched the Internet for further references to the skyline graph, and encountered the RENOIR Website from 2003 (University of Augsburg, Germany; it seems to have had only a short "active" life). There, I found some useful explanations (slightly modified by me):

Explorations with Processing

Inspired by the RENOIR Website, I will now derive the skyline graph in three steps using my "old friend" Processing for programming the charts. My first chart (Figure 5) allows us to compare relative changes using height only – all the columns have the same width. The colors indicate positive (green) and negative (red) changes with regard to the "before" data (= 0%; I might have chosen to do this the other way round as well).

Skyline Graph

Figure 5: Graph indicating relative changes (relative to "before") (created with Processing)

In the second step (Figure 6), I also look at absolute changes, employing area (height x width) as an indicator. The red and green areas depict absolute changes, and the color and direction show whether the change was positive or negative with regard to the "Before" data. Again, the heights of the columns depict relative changes.

Skyline graph (RENOIR)

Figure 6: Skyline graph indicating relative (height) and absolute (areas) changes (relative to "before") (created with Processing)

In step three (Figure 7) I finally move from the RENOIR version of the skyline graph to Caemmerer's version by changing the standard of comparison from 0% to 100% and extending the columns down to 0% so that not only absolute changes but also absolute values are shown. The areas between 0% and 100% represent the absolute values of the "Before" data set. Like in the version above, red and green areas depict absolute changes, while the heights of the red and green columns depict relative changes.

Skyline graph
Figure 7: Skyline graph indicating also absolute values (areas between 0% and 100%, "Before" = 100%) (created with Processing)

The chart in Figure 7 looks similar to one that Caemmerer presents in his slides ("Spending vs. Budget"). It may be a little bit confusing, though, that the "Before" data is represented either as yellow or as yellow+red columns, while the "After" data is represented either as yellow+green or yellow columns. Caemmerer uses different visualizations to solve this dilemma (see his slides). Although humans have more difficulties with comparing areas than with comparing heights, you can clearly see in the chart that large relative changes alone may not tell the whole story, because they can be connected with comparably small absolute and thus not so important changes.

There are many variations in the look of skyline graphs (see, for example, Caemmerer's slides) and many possible uses for them. This UI Design Blink was just meant as an appetizer for the readers. For more information, see the references below and search the Web.

Note: Above, I present charts that use the "Before" data as standard of comparison (100%). Click here to see charts for both "Before-After" and "After-Before" comparisons.

References

February 15, 2012: Sneak Preview Number Five into interaction-design.org

It's only February, yet Mads Soegaard, editor of the HCI encyclopedia, has already announced the second sneak preview into interaction-design.org for this year (and the fifth altogether). Mads writes: "We've hit a major milestone with our free educational materials: Our newest chapter is written by NY Times bestseller and Harvard professor Clayton Christensen." While he forgot to mention that the new chapter is entitled "Disruptive Innovation", he did not forget to send us the link to the sneak preview. Here it is: www.interaction-design.org/encyclopedia/disruptive_innovation.html?p=b248.

Interestingly, I just returned from the "Interaction 2012" conference at Dublin, where Luke Williams held the opening keynote on disruptive design, entitled, "The Disruptive Age: Thriving in an Era of Constant Change". I assume that his keynote was more or less the essence of his new book "Disrupt: Think the Unthinkable to Spark Transformation in Your Business". The same is true for the new chapter by Christensen: It is based on his book "The Innovator's Solution", which was published in 2003 as the successor to his original book "The Innovator's Dilemma" from 1997. Therefore, and as Don Norman points out, many of the examples are already dated (Table 2 of the Appendix in particular). He leaves "the analysis of today's relevance of the companies to the points of the article as an exercise for the reader." This might indeed be an interesting and insightful exercise for the readers.

The new chapter is accompanied by commentaries from Don Norman, Mark Steen, and Paul Hekkert. For a change, I will not introduce the new chapter with Mads' ideas; instead, I will cite some of the commentaries (some of the emphasis is mine). Steen provides a very useful summary of the new chapter in his introduction:

Thus, Steen found a niche that designers might be able to fill. Hekkert builds on this and points to the fact that the words "design" and "designer" do not appear in the new chapter (I found a few occurrences but these are not specifically related to the topic of "design"):

In the remainder of Hekkert's commentary, he investigates if he can fit designers in somewhere.

And then, there is the commentary by Norman, which is actually the first of the three. Since I already cited Norman above, I will close with just a remark from the end of his commentary:

I hope that I have whetted the appetite of the readers, and that they will rush to read the sneak preview of the new chapter "Disruptive Innovation" and the three commentaries.

References

January 11, 2012: Sneak Preview Number Four into interaction-design.org

It looks as if the new year 2012 will start the same way as 2011 ended – with new additions to the HCI encyclopedia at interaction-design.org. Having returned from the holiday season, I found already a fresh e-mail in my inbox, in which Mads Soegaard, editor of the HCI encyclopedia, announced that they are preparing the publication of a new chapter, entitled "Affective Computing". And once again, they offer SAP Design Guild readers a sneak preview into the new chapter, which took Kristina (or Kia for short) Höök from Stockholm University, Sweden, 18 months to write. It includes four HD videos and four commentaries by notable designers, such as Rosalind Picard from MIT, whose presentation I attended at the CHI 2003 conference (read my report). I came across Kia Höök more often, particularly at Interact 2009 in Uppsala, Sweden (read my report), and at DIS 2010 in Aarhus, Denmark (read my report). At both conferences, she was a highly visible participant.

Thus, for the fourth time, SAP Design Guild readers are a few days ahead of the crowd and can already take a look at the HCI encyclopedia's new content (www.interaction-design.org/encyclopedia/affective_computing.html?p=b248).

And, as with previous sneak previews, Mads has provided us with some backstage photos (which you will find in the sneak preview as well):

Interviewing Kias Höök - Setting up the equipment

Interviewing Kia Höök – Setting up the equipment

  

Interviewing Kias Höök - Setting up the equipment

Interviewing Kia Höök – Setting up the equipment

Interviewing Kia Höök

Interviewing Kia Höök

    

 

 

And, just like for the previous previews, Mads has sent us his thoughts about the new chapter (to which I have added a few words):

Höök presents three approaches to research on emotions: "affective computing", "affective interaction" (which is the approach that she pursues), and "technology as experience". As the commentaries show, her view of the approaches may not be universally shared by other researchers. Therefore, I would like to encourage you to also read the commentaries on the chapter by Rosalind Picard, Paul Hekkert, Egon van den Broek, and Joyce Westerink. In particular, Picard, a pioneer and proponent of the "affective computing" approach, objects to Höök's view that "affective computing" is "cognitivistic".

References

 

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