Els Rogier

Gerrit C Van Der Veer

Laura Benvenuti

Teresa Consiglio

Perception or Pixels -Designing a Visual world from the User's Point of View

User centered design would benefit from a dedicated environment, where the designer can focus on the application domain. Our current main domain is design for adult learning. We show how user centered interaction design may require a flexibility that often is not supported in commercially available digital learning environment. Based on design ideas that emerged during observing our students, supporting their needs for learning resources and our actual teaching we developed prototype learning facilities that fit the "human size".

Introduction: Designers build bridges between worlds

Designers use their professional expertise to apply it on the domain they are designing for. The next section will elaborate on this for our case. Designers need tools and a design environment, in order to implement their design decisions. If these are not available, designers have to invest in additional types of expertise, or they have to cope with a suboptimal context.

Applying design to the domain of adult and distance learning requires a choice for a design paradigm. Designing electronic learning support may be approached from two sides: 1. Choosing or adapting an (existing) learning environment or building one based, based on a general view on what is the best way to support learning (as intended by the "client of design", which could be an educational authority, or the intended the learners). The actual learning content may subsequently be inserted and its presentation format and the related interaction possibilities will have to fit the functionality provided by the environment. 2. Analyzing the multiple types of learning activities that the intended learners might want to perform. How to enable or support these will depend on each learner"s individual background regarding knowledge in the learning domain, preferences for presentation and interaction, and the actual context of learning that includes location (e.g., at home, in a bus), time available (a day, 10 minutes), and available resources (books at hand, a peer in the same room). Based on this analysis design patterns may be found or developed that support the activities. In this case the next step will be to identify or develop an electronic learning environment that facilitates the provision of these patterns. We decided to choose for adaptation to the individual and momentary needs and the learning context of the learners (symbolized by "perception" in our title, rather than for the application of standard commercially available learning environments and their rigid templates (the "pixels" in our title). That is what the main section of this chapter is about for our case, where visualizing our design ideas is the main challenge. We will not aim at a complete overview of all possible learning activities and all possible ways of presentation and interaction. We will choose a sample of activities that we often encounter in our teaching practice in the domain of interaction design, and show various ways of supporting them in our practice of blended learning that we discovered useful for our adult students. So far we did not aim at a complete set of guidelines. What we are developing in the first place are design patterns for support of individual learning activities of adult learners in blended learning situations in specific context.

In this chapter we will first discuss the multidisciplinary character of user centered design, followed by a description of our students and the content domain of learning. Next we will discuss the commercially available electronic learning environments that were available in our teaching context.

For our research approach we choose action research. We will argue for this choice and describe the process.

Next we will provide examples of learning activities, and the various ways to support these, that we analyzed, tried, and assessed. Finally we will provide conclusions and point to a research agenda.

User centered design is a multidisciplinary expertise

User centered design requires theoretical understanding, knowledge of techniques, experience with tools, and general design skills, in the domain of application. If the application is user-system interaction, the domain requires expertise from: Cognitive Psychology, Software Engineering, Industrial/Interaction Design and, depending on the context of use, Cultural Anthropology, Ethnography, or Organizational Design. In an ideal world designing is team work where the team owns all different types of expertise.

Our current case considers the domain of adult learning: we teach our students the various aspects of theory, concepts, tools and techniques of human-centered design, and we ourselves practice the expertise of designing Internet based learning resources. This allows students, independent of location, context, or time, to find and use learning resources. These resources need to optimally fit unpredictable learning situations. Learners might need their learning activities to be supported, context dependent for different types of devices (smart phones, laptops, Wii, wall size screens, e-book-readers [2], [3]) communicating through many different modalities, e.g.:  The system output to the learner through spoken or readable text (in some cases with voice over), still pictures (2D, 3D), video (sound could be synchronous and authentic to the video, or an expert"s comment to the video, or a studio audience"s reaction to the video, or a suggested learner"s reaction, ….) etc.  The learner"s input to the system through voice, pointing in 2D or 3D, typing and mouse handling, body movements, … The current state of technical opportunities that are available for our students mainly consists of some kind of computer (most of the time mobile) with a screen, and internet availability depending on the context. Consequently, we focus on visual design with pointing and gestures and sound as the common available basics.

Learners should be able to interact with these supporting systems in a way that fits the "human size". This includes supporting human ways of reading, scanning, pointing, and a system"s way of reacting to learner behavior that is "naturally" perceivable, noticeable, and acceptable. And these aspects require a system behavior that should fit both: human perception, and culturally determined expectations and meaning (of colors, turn taking, location, reading direction, etc.).

Our students and their learning topics

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Their background, or the official label of their curriculum varies between Cognitive psychology, Ergonomics, Computer science, Information sciences, User system interaction, Artificial intelligence, or Architecture and design.

Many are at the age of "traditional" university students, some are adults, often in a University that focuses on adult education. In general, the courses we teach are taken by students who are genuinely interested. Consequently, hardly anybody ends with a "fail", though some (max 10%) decide to withdraw. From our experience, all our student groups should be considered "adult" as far as learning intention and behavior is concerned.

, Design for cultural heritage, etc.

In all cases, we provide an introduction to the domain of the course and discuss just a sample of the relevant concepts, techniques or tools, after which we require our students to each study several or the remaining items in these categories, and teach these to each other. After each student presentation we provide a reflection on the presentation, mainly underscoring the good points, and, whenever needed, providing additional information (e.g., things we missed from the student"s presentation). We record all presentations, put our own (portioned in 10-minute mini courses) on a dedicated YouTube channel, and provide the students" ones on website that is open only for the current student group. All our courses include as a main part real hands on experience of the approach, the techniques and tools. In each case we ask them to analyze and design for a real live need of a real (local) client in that we carefully select based on size and content of the project and on possibility of the client to be available for the students during the course.

Commercially available platforms are conservative

We teach for students that we cannot supervise "full time", because we are traveling teachers and many of our students are not living close to the location where we happen to deliver our tuition. Our learning situation can be characterized by the concept of "blended learning" where we sometimes have face to face meetings, sometimes teach through the internet, and frequently provide learning opportunities through electronic learning environments.

A blended learning approach combines face to face classroom methods with computer-mediated activities to form an integrated instructional approach. In the past, digital materials have served in a supplementary role, helping to support face to face instruction. For example, a blended approach to a traditional, face to face course

might mean that the class meets once per week instead of the usual three-session format. Learning activities that otherwise would have taken place during classroom time can be moved online. There is no consensus on a single agree-upon definition for blended learning and, in addition, the terms "blended," "hybrid," and "mixed-mode" are used interchangeably in current research literature [START_REF] Torrisi-Steele | This thing called blended learninga definition and planning approach[END_REF]. Pennsylvania State University defines blended learning as a combination of face to face classroom methods with computer-mediated activities to form an integrated instructional approach [20].

Most of the universities where we provide our courses do in fact have their preferred or prescribed electronic learning environment. We discovered that four rather divers learning environments were regularly used:  Blackboard [5]commonly used to provide lecture presentations, exercises for homework, and exams, to upload homework in a dropbox, and to form student discussion groups, and a chat facility can be provided. Streaming video can be added through mashup-modules.  Elluminate Live [16]a communication tool that includes integrated voice over IP and teleconferencing, chat, quizzes and polls, and the use of multiple webcams. There are visualization tools and shared whiteboard facilities for uploading documents and controlled sharing of writing rights. The teacher can plan as well as record the meeting.  Adobe Connect [1]based on Adobe Flash, this environment supports video meetings where multiple webcams can be used, presentations may be given, and documents can be uploaded and shared with controllable writing rights. Like the previous environment, sessions can be recorded. Different from, Elluminate there is no tool for planning and no requirement to have the teacher fix meeting times in advance, so each participant can enter the environment and work there whenever needed.  Smartschool [START_REF] Smartschool | [END_REF] a learning environment that is developed, and extensively used, in Belgium (Flemish) educational institutes. It is mainly focused on administrative management of education and exchange between institutes and teachers, and it contains an electronic learning environment that allows exchange of learning content. We were supposed to use these and we tried. We found ourselves confronted with rules, requirements, restrictions, and impossibilities that made us stop spoiling our time.

We decided to build our own learning environments, mainly in a Moodle environment, which allows us to provide open access and with a Creative Commons license well as to use (with appropriate attribution) others' resources under that license. Creative Commons (CC) is a nonprofit organization that enables the sharing and use of creativity and knowledge through free legal tools. The CC copyright licenses provide a simple, standardized way to give the public permission to share and use creative work -on conditions of the user's choice. CC licenses allow easy change of copyright terms from the default of -all rights reserved‖ to -some rights reserved.‖ Creative Commons licenses are not an alternative to copyright. They work alongside copyright and enable you to modify your copyright terms to best suit your needs [13].

Moodle is a Course Management System (CMS), also known as a Learning Management System (LMS) or a Virtual Learning Environment (VLE). It is a Free web application that educators can use to create effective online learning sites [START_REF] Rice | [END_REF].

Action research

The development of our electronic learning environments is based on growing understanding during practical use. We aim at supporting our students" authentic learning needs.

For our research approach we choose for action research, which, according to the British Open University [START_REF] Coats | Action research, a guide for associate lecturers[END_REF] is characterized as -Any research into practice undertaken by those involved in that practice, with an aim to change and improve it. It is therefore, a process of enquiry by you as a practitioner (an OU tutor in this case) into the effectiveness of your own teaching and your students' learning. Action research is about both ‗action' and ‗research' and the links between the two. It is quite possible to take action without research or to do research without taking action, but the unique combination of the two is what distinguishes action research from other forms of enquiry.‖

According to Carr and Kemmis [START_REF] Carr | Becoming Critical. Education, knowledge and action research[END_REF] action research is simply a form of selfreflective enquiry undertaken by participants in social situations in order to improve the rationality and justice of their own practices, their understanding of these practices, and the situations in which the practices are carried out. Bogdan and Biklen [START_REF] Bogdan | Qualitative Research For Education[END_REF] define action research as the systematic collection of information that is designed to bring about social change.

According to Ferrance [START_REF] Ferrance | Action research. Themes in education[END_REF] there are numerous reasons to choose Action research as the basic paradigm for investigations in practical educational context:  it allows, and in fact requires a focus on school issue, problem, or area of collective interest;  it naturally includes a form of teacher professional development;  it is based on, as well as stimulates, collegial interactions;  it provides participants the potential to impact school change;  it is based on reflection on own practice;  it supports improved communication on the phenomena investigated. We decided on joining this choice.

Examples

Adult learners might want to perform a multitude of different types of activities. We will in this chapter only describe a sample that illustrates those that are most common in the learning domain that we consider, e.g.:  Get a definition;  Get an explanation;  Get theoretical background material related to a definition;  Get a well prepared example;  Construct their own example;  Practice a skill;  Attach a personal note to received or constructed material  Highlight parts of material  Attach a note to be shared with other learners;  Attach a note intended to share with a teacher or expert;  Discuss a topic with one or more others (synchronously or asynchronously).

With our electronic learning environment we intend to support this type of activities. In many cases the activities are to be expected, though we are regularly prompted by our students. Based on our experience in teaching we design support and we provide this during the next course where we expect it would be appreciated. Our observation of the resulting student behavior, the learning results, and the students" comments (unsolicited as well as triggered) teaches use what to keep and what to adapt. That is how we learn. The current chapter provides an overview of work in progress.

For the above illustrative set of basic learning activities that we need to support we will show examples of how to support these. If relevant we also discuss the context for which alternative representations seem to work best.

Get a definition

Students will, and do need definitions of concepts. They will ask for this during face to face lectures, and they turn out to look for them in their electronic learning environment. Depending on the context (being in a quiet home or in a noisy bus) they might prefer a different presentation mode. Figure 1 shows a video capture of a lecture. The definition is visible on the screen where a PowerPoint slide is displayed. The professor is standing next to the screen explaining the definition. We found that students preferred this representation in the learning environment in case they had attended the actual class previously: they reported it helped them to remember and supported a more thorough understanding.

Figure 1. Definition as given by a teacher using a slide and life discussion Figure 2 shows and alternative where the definition is presented (silently) in a scrollable text that is followed by a more elaborated explanation of the definition. This kind of representation can be easily accessed from either a regular computer or a (smaller) mobile device. Some students that did not attend an actual class preferred this in order to study in depth and make notes.

Figure 3 is from an online course on human information processing [START_REF] Oppelaar | Human information processing[END_REF]. The definition of working memory is displayed within a text. Extra information about the definition is available in different ways: in following pages, as well as in pointers to "external" sources that will pop up in a new window. This visual structure will work best on a laptop or PC screen, though it allows for scattered short learning periods like the other alternatives: a student can mark for each page if he considers he studied this page or not. This pattern is preferred by students who take a course and at their own pace without any face to face meetings. They will often return to the text later and go to additional resources Finally, figure 4 shows a slide that was used during a face-to-face lecture where the teacher explains in greater detail. The slide does not formally state it as a definition but is one nonetheless. This type of slides can also be used as stand-alone learning material or can be accompanied by voice over. Some students use this to refresh their understanding and in that case, the voice over explanation may provide additional support if needed and if the use of sound is feasible in the actual context. 2. Get an explanation Explanations, in our learning domain, are mostly about a concept (most of our students in fact appreciate to be able to have both, a definition, and an explanation of concepts that are core in the learning domain), a phenomena, or a tool. . Figure 5 is a screenshot from a website on task analysis and design [START_REF] Consiglio | Task analysis and design[END_REF]. It shows the screen at the moment that the mouse is moved over the square labelled "Distributed cognition", at which event a rectangle pops up that explains the goal for which the labelled tool or technique could be used. Different concepts (tools and techniques for task analysis) are presented on the right side and when hovering over them with the mouse a short explanation is shown. This allows quick scanning a structure of unfamiliar terms, as indicated by the labels that group the concepts: Knowledge sources; Analysis orientation; Sketching; Phenomena of use; and Negotiation. As the structure itself is relevant for comparison and choice, a relatively large part of the screen is needed to display this.

If, after orientation based on the short explanation, a learner wants to learn about the details, a click on the rectangle makes the pop-up screen changes to provide a choice of 5 tabs that allow information to be studied in detail: the type of problem that could be solved by applying the tool or technique; how to apply this; examples of the use; an exercise to trying out; and pointers to more information.

Learners will choose which tab(s) to open depending on how they estimate the information to be relevant for their actual aim in studying the material. If they will come back to a concept later they have different possibilities to refresh their understanding. Re-reading examples might help them most since this refers to application in a realistic case. If this strengthens the applicability for the actual moment, they might subsequently go to the "how" tab that provides them with detailed guidelines. Tools and techniques, in our domain of interaction design, are never used in isolation. Their applicability in relation to the phase of design, the context, and the type of problem to be solved, need explanation as well. As an example we refer to the open source website created by Tassi [START_REF] Tassi | Service design tools[END_REF]. This site is a learning resource for service design, intended to be used stand alone, though we have actually used it extensively in blended learning courses. We discovered it does help learners to explain the system and structure of the tools and techniques in relation to the process and context, as well as to have learners work through an actual design process (designing for a real client). We discovered it makes sense to support the process by providing an explanation of the use of this website, to which end we used a presentation in a face to face session of which figure 6 shows the main slide.

This slide in fact combines two layers of explanation: the original representation is taken from the service design tool collection [START_REF] Tassi | Service design tools[END_REF], where the text of the main page itself gives an explanation of what the website is about. In our lectures, as well as in our website for each course on service design, we showed this slide that (in dynamic red graphics) highlights and a shortly explains, our suggestion for using the resources in that website. A voice over is an option for the individual student who cannot attend class.

From our online course on Human Information Processing, that is supposed to be studied in a free time schedule and without any contact with a teacher or with peer students, figure 7 presents how students get an explanation on why they should bother about perceptions. The explanation is supported by a relevant picture, as it turned out to make the phenomenon much more easy to understand and remember. Learners in general commented that this worked just fine for them. The amount of explanation was considered just enough to understand without any other support or possibilities to discuss with others during the actual reading. Still, for who would ever wants more, we provide a possibility to "find out more" which will bring the learner to additional explanations from sources that differ from the actual lecture. 4. Get a well prepared example Definitions, explanations, and additional pointers, often are not enough for some, or even most, of the learners. Examples allow them to reason about the concept, the phenomenon, or the technique, and try out their understanding by interpretation in practice. In a physical classroom or laboratory, examples may well be samples of the actual phenomenon. Students can be walked through a process (a design, an experiment, the observation of behaviour) and experience the process in real time accompanied by explanations and by questions that trigger understanding. In an electronic environment we may provide a simulation or suggest the experience by a proxy. Figure 9. An example that is experienced as a game, illustrating the issue Figure 9 is a screenshot from the online course of human information processing. On the right side in the blue box is a section "Try it". This is a well prepared example illustrating the text on the centre stage. In this example the user can do a test that allows to understand the written material better. The phenomenon to be understood is attention, the test in "Try it" is a case where the actual attention is manipulated by the text "you must count how many times this red ball bounces on the 4 ides of the container". When the learner hits the button "I"m ready, let"s go" several balls with different colours start to bounce along with the red one. That one is, obviously, rather easy to follow and the bounces may be counted. However, after a few seconds a figure of a brown monkey, with the same size as the balls, appears and starts bouncing as well. After the monkey disappears (after 15 seconds) the test stops in 5 seconds. The number of bounces is asked and then the learner is asked about the monkey. 9 out of 10 students did not see it at all. Now they are suggested to repeat the test, at which occasion everybody notices the monkey, and they all understand the phenomenon of selective attention that has been discussed in the main page.

Another well prepared example from the same online course is illustrated in figure 10. The main text is about the domain of Cognitive Psychology, and the "Try it" examples are developed to show remarkable phenomena that can be described and understood in this domain. The student can do several experiments that allow to understand the reason for going into dept regarding the theoretical part of the domain.

The experiment in this figure illustrates the "Stroop" effect that shows that several dimensions of an incoming stimulus may trigger different and conflicting responses. In the original Stroop test there is a page with individual words that are printed in various colors. The reader has to mention the colors of the words as quickly as possible. The next page contains color names, printed in different colors that are inconsistent with the work. The time needed to name the printing colors suffers considerably, illustrating the effect of conflicting input dimensions on information processing. In our version of the Stroop effect we use only words printed in black, and ask the reader to mention the number of letters. Our second page only contains words that label a number ("one", "two", three, "six", etc.), which allows the learner to experience the same phenomenon without violating copyright rules. Figure 10. An example that simulates a laboratory proof of the phenomena Finally, we present an example of a concept from a visual design pattern collection. Figure 11 shows how a pattern is applied. The example contains pictures, text and links to find out more about the example. The way to browse the pattern examples and to explore the knowledge on them is in fact analogous to the concept explanation pattern that we illustrated in figure 5: hovering over the pattern icon reveals only a visual representation of the pattern, clicking on the icon provides the pop-up as shown in figure 11 where the learner, by choosing one of the tabs, may find the basics of the visual design pattern; an elaborated example from a real website; the forces in the current design space that would support or discourage the use of this pattern; how the pattern may be applied, and a systematic overview of when and why to apply it.

Construct my own example

For many learners the construction of their own example is the ultimate proof of understanding. In this case, some feedback is almost always needed. In courses with face-to-face possibilities, this can be scheduled or provided on request.

Figure 12. Two pictures from a student"s presentation to show changes in design

Figure 12 shows two pictures that a student made during a course in Italy. The student presented his work to the teacher and other students in a slide presentation. A picture of the prototype that the student designed was drawn in a natural context to explain the new prototype and the changes from the previous design. The first of the student"s pictures illustrates how users of a current type of remote control might have problems reading the labels of the multiple buttons and needed time to discover what button to press. The second picture shows a new prototype remote control with only a few (considerably larger and shaped) buttons that would allow quick scanning and quick user action.

Obviously, learners may develop this type of examples wherever they are and any time that fits them. However, we found in practice that they mostly want to have feedback from someone who would understand, like a peer learner or a teacher. Consequently, we try to support this need even for blended learning situations. Figure 13 In a recent case where we taught this course, the (Chinese) students triggered a new development for their learning environment, requesting the possibility to upload their intended presentations well before the face-to-face meeting in order to collect feedback from their peers prior to "submitting" it to the teacher"s comments. to officially presenting it to the teacher 6. Practice a skill Students need, and want, to demonstrate their knowledge. Even though this is not a main goal in any of the courses we teach, nor a main goal of any of the learners that visit our electronic learning environments. A fact, however, is that students differ regarding their competence and we discover they are happy to try themselves and to learn from each other. A teacher may be of help in this case.

In order to aim at systematically improving presentations (whenever needed, depending on the culture and level of the students) we have developed a process of selecting those student presentations that we consider exemplary for the quality, structure, content, or even performance. We publish a short list of "remarkable" presentations and we suggest students to especially consider the video recordings of these and we give each student team in the course the assignment to write a brief report on those selected recordings stating why each of these is excellent.

In the slides in Figure 14 the exercise is explained. Students are encouraged to learn from each other and therefore are asked to look at good examples of fellow students. On purpose we ask them to view the presentation videos on a small screen, in order to avoid the viewers to focus on content details. We generally experience a striking improvement on the aspects that we aim at and mention in the exercise. Figure 14. Suggested peer presentations to improve presentation skills Occasionally students are unable to attend. A student that was unable to physically attend the class on the day of the presentation asked, and received permission, to do his presentation at home in front of a video camera. His presentation was highly rated by his peers as well as by the teacher.

But face-to-face meetings are also taken as an opportunity to practice relevant skills. Figure 15 shows a picture from a Chinese student who really wanted to learn how to present the work he prepared. He developed his own ideas to do so, combining a prepared slide show on the screen with notes and schedules drawn on a flipchart during his presentation. He wanted the presentation to be videotaped so that people could give feedback and allow him to learn from it. Other students or the teacher who receives this could be triggered to respond to in the same way. Figure 16) shows an example, where both the student and the teacher (that is the one who is answering in this example) need to be aware whether the conversation is private between the two of them, or between a well specified design team, or open for reading as well as reacting by the whole course group. Our learning environments now allow each of these, and we find in most cases the students choose the "open for the whole class" mode.

Highlight parts of the material

When learning material has to be structured and the structure is complex, it may often only fit on large screens (laptops, PCs). In that case learners tend to read in their "normal" reading habite.g., from left to right and from top to bottom in European and Chinese current cultures. Any complex (e.g. 2D) representations might make the student miss some relevant features. Figure 17 is an example of a visual pattern wizard [START_REF] De Moel | Visual design patterns, patternwizard.nl/pattern/wizard[END_REF] for website design. o Photo journals? Each time a learner answers a question in the left side box, or deletes an answer (which makes the question unanswered) (Figure 17 top), an arrow towards the right side box dynamically starts to appear and move, and some patterns lighten up (Figure 17 middle part). After that a back arrow (Figure 17 bottom) indicates that the changing configuration of feasible patterns is in fact related to the answers of the questions that the user just gave, and which may be revised. The moving arrows in the previous example turned out to help notice that something new has appeared on the right side as a result of what is going on by the learner"s tentative choices at the left.

In the courses that we build ourselves, we may apply any highlighting technique that fits the purpose. However, we will often use relevant and open source available learning recourses if they fit our students" needs. During a course where cultural diversity [START_REF] Van Der Veer | Culture Centered Design[END_REF] was an issue, we wanted to explain how to use the website from Hofstede [START_REF] Hofstede | National culture dimensions, geerthofstede.com/dimensions.html[END_REF] and what kind of information you could find on it. Therefore, in preparing a lecture, the teachers connected live to the website and used these for a demonstration while his screen and his comments were recorded. The mouse pointer is highlighted to allow the viewer to see what elements the teacher is attending to and pointing at. This dynamic representation (figure 18) supported learners to follow the teacher"s attention and to understand the actual use as demonstrated. Viewing a recorded video capture of the session turned out to be appreciated as well as providing the intended learning. In a course on design for cultural heritage, pictures are shown of personal item that are considered family heritage. The type of pictures, in this case, do not match well with dynamic visualisation of attention support, and require careful study without disturbance of esthetic aspects. In a discussion on such an item one or more specific parts may need to be considered, like the year 1883, or the name indication MAK (in this case the name of the young women who embroidered this in the indicated year) in the example of figure 19. Trying out in practice showed us that the temporary indication of which part we are referring to by using a not confusing shape and color (in this case a red circle) helps to clearly focus attention. When that is reached the attention support can be removed and the meaning of the detail may be discussed, experienced, and appreciated. In this case, dynamics turn out not to be needed (and even to be considered irritating) to draw attention. Figure 19. Simple static way to draw attention to a detail that could easily be missed.

After attention has been established, the pointer should be removed to allow acceptable experiencing of the esthetics.

In our courses there are often various different elements and phenomena that occasionally require attention to be drawn. The previous examples show, respectively, how to support attention to the effect of student actions (as discussed with Figure 17) and how to focus attention of students to join the teacher"s focus. However, there are many situations in electronic learning environments where there are opportunities that learners might miss. Screens often cannot be just plain and simple, and multiple options for interaction need to be provided at the same time. In that case reactions to mouse over may help the learner find out (or remember) there are interaction possibilities available. Figure 20 shows 2 phases from interaction with the design pattern wizard [START_REF] De Moel | Visual design patterns, patternwizard.nl/pattern/wizard[END_REF] where attention to relevant parts is triggered by dynamic highlighting on mouse over, through a red exclamation mark and a thought cloud.

Attach a note to be shared with other learners

Sharing ideas with peers is common practice in face-to-face learning situations. In the Moodle learning environment that that we often use as a platform for our design there is an option for a learner to share work, ideas and materials with others. The result is posted in a discussion topic. Other students and teachers can read and reply on the message. Obviously, this facility needs to be known and triggered, like Figure 21 illustrates, where our learning environment administrator fount out there was a need to alert students. She posted a message that started the actual use that was apparently not obvious for a new class of students. Figure 21. A triggering message to show students how to upload and share notes Once students are aware of this functionality they turn out to use it and they want others to receive the message, to react and to collaborate. In fact students in a group will use the board for purely social purposes as well. Figure 22 is a snapshot from the creation of a topic "Pictures" on a discussion board used during a course we gave in China. A student wanted to share pictures taken during the last class with the rest of her classmates. She adds a note telling people what to do in case they cannot open the file. As you may read, the teacher was triggered to react as well, with a personal not to thank for the nice initiative. Figure 22. A personal note and some help in case the zip file cannot be opened 10. Attach a note intended to share with well defined others In some cases our students wanted to be very precise on whom to share their notes with. Sometimes our courses draw over 100 students and in such a case the teacher is supported by tutors, about 1 per 30 students. Tutors support the students in providing facilities, additional learning resources, and when there are communications problems with uploading homework or preparing presentations because English is not the first language of the students, tutors are available even when the teacher is only present at scheduled times (e.g., 2 day during each fortnight. In teaching such relatively large groups, we found out there may well be a wish for several levels of intimacy. Students feel the need to share some communications only with the teacher or tutor; or only between their design team, or between the team and the tutor, or with the whole class.

Figure 23 shows a design sketch, not yet implemented, of a web environment for this type of context [START_REF] Blanco | Design Guidelines for Self-Assessment Support for Adult Academic Distance Learning[END_REF]. The "sticky notes" suggest informal messages the student can choose to keep private or to share. With the create group button, a person or new group of people can be added. In the current example, each student can choose to keep the notes private or make them general or share them with "UtrechtSC", his group of computer science students at the University of Utrecht. Also, the sketch indicates that each note can have a PDF attached, allowing the sharing of documents that have a more formal state compared to a sticky note.

Discuss a topic with one or more others

Students often ask for possibilities to discuss issues with their peers beyond the possibilities in the face-to-face meetings. If privacy is not considered an issue (which we found out is clearly culture dependent), Moodle allows acceptable functionality. Figure 24 shows how we are able to provide this in our Moodle based electronic learning environments. On the right side of the screen several discussion topics are listed. Students and teachers can react on these topics or start a new discussion topic. Design requires a supporting environment After design follows implementation, for which different types of expertise are needed to implement an actual product or service. A design team should be aware of the characteristics, possibilities and restrictions that the design environment is providing. The current commercially available products that we were supposed to use (e.g., Blackboard, Elluminate, Smartschool, and Adobe Connect) present us with problems. The guiding principles and concepts for visual design in these electronic learning environments are a mismatch to our learner centered didactic approach and to or students" learning objectives. In contrast, open source environments like Moodle offer more flexibility and allow us to develop our own extensions, to profit from the creations of our colleagues and to combine successful ideas. In practice, many educational institutes have yet to learn to trust and rely on open source solutions where an active community is replacing the commercial business model for managing risks. This means we are confronted with limitations in the visual facilities of digital learning environment that hinder the support of learners in a way that fits the "human size" of this type of user. In many cases the system imposes, by design, restrictions to who is the boss of a screen"s real estate: where can we put a question, a video, a button to press, or how can we specify our own animation. On the other hand, most designers of learning support are not eager to focus on pixels and to reinvent a wheel for which they do not have the expertise.

Commercially provided learning environments should be re-developed to allow designers to do their job in a proper way, possibly by freely applying Open Source based solutions. On the other hand, Open Source environments should (be developed to) acquire a state of acceptability for educational institutes that allow both designers and learners access to state of the art solutions.

Conclusions

Our experiences and the ideas we developed are based on supporting blended learning, for adult students in many countries, in the domain of interaction design. Our students are highly motivated and well aware of the restricted opportunities and time available for them.

We base our teaching, as well as the design of our learning environments, on what we learned during teaching. Our adult learners turn out to set their own learning goals. In addition, they are learning in a large and unpredictable variety of contexts and time slots. They will try to learn wherever they can access learning resources, and they choose to aim at learning goals that fit the availability of time.

Our design knowledge is developing during practice; hence we choose action research as our paradigm. Experiments for our type of learners and our type of learning domain are not possible and would not make too much sense.

In order to optimally support learning, we started by identifying learning activities, trying out how to support them, assessing the result in practice as far as practice allows assessment. In many cases the assessment is subjective: students let us know, or do not complain, and if we were lucky half of them answered short questionnaires.

We are in a situation where we are allowed to teach our courses in different settings and different educational cultures in many countries as far apart as Europe and China. This helps us to find out what our growing understanding is worth. Still we are currently in the process of identifying design patterns to support a growing set of learning activities, taking the context (location, available time, opportunities to contact peers and teacher, available hardware and platform) as well as the individual learner"s state (educational background, domain knowledge, actual need) into account.

We are working on it. The current chapter provides the examples that help us to consider further research, where we are aware of the need to combine our action research with the experiences of our colleagues, who, hopefully, be as open as we try to be in sharing.

Figure 2 .Figure 3 .

 23 Figure 2. Definition followed by explanation, in a scrollable text that fits on PC screens as well as on mobile phones

Figure 4 .

 4 Figure 4. Slide with definition, originally used in class, and subsequently provided as standalone definition resource with optional voice over explanation

Figure 5 .

 5 Figure 5. Explanation of concepts can be found by hovering a concept and then clicking on it.

Figure 6 .

 6 Figure 6. Slide showing Roberta Tassi"s website [22] overlaid with a dynamic visual representation on how to find relevant tools

Figure 7 .

 7 Figure 7. Explanation with words and a picture3. Get theoretical background material related to a definitionEven if a definition seems enough (or is considered so in a certain context by a teacher) individual students might well feel a need to know more. Especially in the case of fully stand alone online courses, learners appreciate the possibilities to find additional material which may well stem from other websites.

Figure 8

 8 Figure 8 is a screenshot from the online course of human information processing, where the definition of a concept (Working memory) is provided. The figure shows the screen after the learner just hit the blue box at the right hand side that says "Find out more". At this event, in the blue box there appears a section in which the student can find background links from other locations related to the definition presented on the central stage. In this case these are additional definitions and theoretical background on them from different trusted sources, i.e., from the "Memory" site of the Cognitive Psychology department of the University of Amsterdam, and the Computing classes site of Georgia Tech.Clicking on these URLs will open a new window that displays the relevant material on those sites. Learners will often first look at what material might be available for further reading and only in a second round come back and go to these resources.

Figure 8 .

 8 Figure 8. Find out more through pointers to additional resources that will appear in a new window.

Figure 11 .

 11 Figure 11. A visual design pattern example.

  is from the learning environment of a course on service design. We actually trigger students to develop their own examples and provided facilities to upload these. A list of presentations with examples students made themselves are displayed at the relevant place in the course website. Participants in the course can review how other students in their class made their presentation and view the examples they constructed.

Figure 13 .

 13 Figure 13. Students developed presentations to share with each other, sometimes prior to officially presenting it to the teacher

Figure 15 .

 15 Figure 15. Voluntary trial presentation intended to collect feedback7. Attach a personal note to received or constructed materialIn our blended learning courses students are frequently asked to upload material.

Figure 16 .

 16 Figure 16. Personal notes may well be part of a learning environment

Figure 17 .

 17 Figure 17. Successive views of a dynamic support to attention to new information on the right hand side that is the result of checking options at the left.

Figure 18 .

 18 Figure 18. Dynamic highlighting of the teacher"s pointer, combined with a voice over explanation

Figure 20

 20 Figure 20 dynamic highlighting to draw attention to possibilities

Figure 23 .

 23 Figure 23. Prototype (not implemented yet) of note sharing facilities with a specified audience

  Through different questions the learner may explore what visual patterns could be suitable for the website they are designing. At the left hand students may, first of all, choose for one of four different design space categories, each with multiple variables:  Page descriptions, which allow, but not enforce, choices between o Purpose of the site: information or entertainment?

	o Tasks that need a sequence of subtasks?
	 Categorisation of the site structure
	o Meaningful sections?
	o Hierarchy of depth more than 2?
	o Icons to support categorization?
	o Content continuous with categorization?
	 User characteristics
	o Mainly experienced internet users?
	o More than ten events a year interesting for users?
	o Desktop only or mobile use as well?
	o Are there user polls or review questions to be answered by users?
	 Page elements
	o Icons used for menus in the pages?
	o (Large) tables?

o Size of text to read (long or short)? o Number of pages of the site (more than 30 pages or not)? o Number of pages with actual content (15 or less)? o Interaction tasks other than navigation (e.g., form filling, file upload)?


Johann Schrammel
email: schrammel@cure.at

Manfred Tscheligi

Patterns in the Clouds -The Effects of Clustered Presentation on Tag Cloud Interaction

Tag clouds have become a frequently used interaction technique in web-based systems. Recently, different clustered presentation approaches have been suggested to improve usability and utility of tag clouds. In this paper we describe a modified layout strategy for clustered tag clouds and report the findings of an empirical evaluation of automatically clustered tag clouds with 22 participants for both specific and general search tasks. The evaluation showed that automatically clustered presentation performs as well as alphabetic layouts in specific search tasks and that clustered presentation is an improvement over random layout for general search tasks. Clustered tag cloud presentation also was preferred by a majority of users for general search tasks. High quality of the clustering was mentioned as key variable for usefulness of the approach in the qualitative interviews with the users.

Introduction

Since the first introduction of tag clouds different means to further enhance their usefulness have been proposed. Suggestions for modifications were directed towards the utilization of additional display properties for encoding more data dimensions [START_REF] Waldner | Exploring Tag Clouds for Multi-Dimensional Data[END_REF], the optimization of the layout algorithms [START_REF] Kaser | Tag-Cloud Drawing: Algorithms for Cloud Visualization[END_REF], adaptation of sorting strategies (e.g. alphabetically versus importance-based) [START_REF] Sinclair | The Folksonomy Tag Cloud: When is it Useful[END_REF], or the combination of tags with graphical elements [START_REF] Kuo | Tag clouds for summarizing web search results[END_REF]. A specifically popular direction of research has been along the lines of clustering and displaying tags along their semantic meaning, and different approaches have been suggested [START_REF] Berlocher | TopicRank: bringing insight to users[END_REF][START_REF] Fujimura | Topigraphy: visualization for large-scale tag clouds[END_REF][START_REF] Hassan-Montero | Improving tagclouds as visual information retrieval interfaces[END_REF].

Only few empirical evaluations exist assessing the expected advantages, and were they are available they did find no or only minor advantages [START_REF] Lohmann | Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration[END_REF][START_REF] Schrammel | Semantically structured tag clouds: an empirical evaluation of clustered presentation approaches[END_REF]. We think that these rather discouraging results are partly due to shortcomings in the used clustering methods and presentation approaches of semantically clustered tag clouds. Typically the used methods are not optimized for the most relevant tasks and context situations.

Another critical element regarding the usefulness of clustering approaches for use in tag cloud display is the quality of the automatically calculated clusters. Evaluations of human-made clusters based on hand-picked data have shown very promising results for usage of clustered approaches [START_REF] Lohmann | Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration[END_REF]. Results for methods that use automated clustering however have been much less convincing [START_REF] Schrammel | Semantically structured tag clouds: an empirical evaluation of clustered presentation approaches[END_REF]. The quality of the clustering algorithm and whether the resulting clusters are understandable for humans seem to be of major importance with regard to the usefulness of clustered presentation approaches.

Also, the type of task a user is working on has been shown to be a main influence on whether an interface solution is perceived well by users or not [START_REF] Sinclair | The Folksonomy Tag Cloud: When is it Useful[END_REF]. Therefore in our work we address both specific and general search tasks.

In our work we want to answer the question whether similar results as with handmade clusters could be achieved with realistic data and state-of-the-art clustering algorithms. We developed a rectangular clustered layout approach and evaluated it in the context of specific and general search tasks. In the next sections we present related work, the study design and the evaluation results.

Related Work

Visual features of tag clouds

The importance of visual features of tags within tag clouds for attention has been researched recently, and results from different authors [START_REF] Bateman | Seeing things in the clouds: the effect of visual features on tag cloud selections[END_REF][START_REF] Rivadeneira | Getting our head in the clouds: toward evaluation studies of tagclouds[END_REF] show that font size, font weight and intensity prove to be the most important variables. Regarding the importance of tag position reported empirical findings are not as concise. Whereas [START_REF] Bateman | Seeing things in the clouds: the effect of visual features on tag cloud selections[END_REF] found no influence of tag position other researchers [START_REF] Lohmann | Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration[END_REF][START_REF] Rivadeneira | Getting our head in the clouds: toward evaluation studies of tagclouds[END_REF][START_REF] Schrammel | Semantically structured tag clouds: an empirical evaluation of clustered presentation approaches[END_REF] report that tags in the upper-left quadrant receive more attention than tags in the lower-right quadrant. Tag clouds and information seeking tasks Sinclair et al. [START_REF] Sinclair | The Folksonomy Tag Cloud: When is it Useful[END_REF] compared the usefulness of tag clouds against search interfaces for general and specific information seeking tasks and concluded that tag clouds are especially useful for non-specific information discovery as they can provide a helpful visual summary of the available contents and its relevance. Similarly, comparing the visualization of search results using tag clouds in contrast to hierarchical textual descriptions Kuo et al. [START_REF] Kuo | Tag clouds for summarizing web search results[END_REF] found that users were able to answer overall questions better when using tag clouds. Regarding specific search tasks however both studies showed disadvantages for tag clouds. Using eye tracking data to analyze the effect of introducing search results overview in the form of a tag cloud Gwizdka and Cole [START_REF] Gwizdka | Does interactive search results overview help?: an eye tracking study[END_REF] found that a results overview in form of a tag cloud helps a user to become faster and more efficient.

Layout of tag clouds

Halvey and Keane [START_REF] Halvey | An assessment of tag presentation techniques[END_REF] investigated the effects of different tag cloud and list arrangements comparing the performance for searching specific items. The setup included random and alphabetically ordered lists and tag clouds. Clustered presentation was not part of their setup. They found that respondents were able to more easily and quickly find tags in alphabetical orders (both in lists and clouds).

Rivadeneira et al. [START_REF] Rivadeneira | Getting our head in the clouds: toward evaluation studies of tagclouds[END_REF] compared the recognition of single tags in alphabetical, sequential-frequency (most important tag at the left-upper side), spatially packed (arranged with Feinberg's algorithm, for more information see www.wordle.net) and list-frequency layouts (most important tag at the beginning of a vertical list of tags). Results did not show any significant disparity in recognition of tags. However, respondents could better recognize the overall categories presented when confronted with the vertical list of tags ordered by frequency.

Hearst and Rosner [68] discuss the organization of tag clouds. One important disadvantage of tag cloud layouts they mention is that items with similar meaning may lie far apart, and so meaningful associates may be missed.

Semantic tag clouds

Hasan-Montero and Herrero-Solana [START_REF] Hassan-Montero | Improving tagclouds as visual information retrieval interfaces[END_REF] proposed an algorithm using tag similarity to group and arrange tag clouds. They calculate tag similarity by means of relative cooccurrence between tags. Likewise, Fujimura et al. [START_REF] Fujimura | Topigraphy: visualization for large-scale tag clouds[END_REF] use the cosine similarity of tag feature vectors (terms and their weight generated from a set of tagged documents) to measure tag similarity. Based on this similarity they calculate a tag layout, where distance between tags represents semantic relatedness. Another very similar approach is proposed by [START_REF] Berlocher | TopicRank: bringing insight to users[END_REF].

Semantic approaches have been evaluated recently by different researchers. Schrammel et al. [START_REF] Schrammel | Semantically structured tag clouds: an empirical evaluation of clustered presentation approaches[END_REF][START_REF] Schrammel | The Visual Perception of Tag Clouds -Results from an Eye Tracking Study[END_REF] evaluated a semantic layout approach that places related tags together but does not explicitly calculate and present groups of tags. They report that semantic layouts can provide minor advantages, and that it was difficult for users to identify and understand the layout strategy.

Lohman et al. [START_REF] Lohmann | Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration[END_REF] studied a clustered layout were groups of similar tags were placed together and indicated by border lines and background shading. They report advantages of the clustered layout for general search tasks. However, as they used a manually constructed tag corpus and provide no details on how the clustering was calculated the question remains whether these results can be replicated with realistic data and unsupervised clustering algorithms.

Research Questions

In detail we wanted to answer the questions how automatically clustered tag layouts affects search time, the perception of tag clouds as well as the subjective satisfaction of the users after interacting with the tag clouds both when searching for a specific tag and when performing searches for tags that belong to a specific topic. We compare three layout strategies: alphabetic (the currently most used approach), random (to be able to see if clustered presentation provides any improvement over no structure at all) and automatically clustered.

Study Materials and Participants

Tag Corpora. As a basis for our work we decided to use data from del.icio.us, as this site allows everybody to tag and that the site employs a blind tagging process i.e. the users cannot see which tags where used by other users during the tagging process. In detail our work is based on a large data sample that was downloaded from 'del.icio.us' by Yusef Hassan-Montero, who thankfully provided us with the data. The data originally was collected for research described in detail in [START_REF] Hassan-Montero | Improving tagclouds as visual information retrieval interfaces[END_REF]. Data was crawled by means of an automatic crawler during October 2005 and contains 218,063 URLs tagged with 242,349 tags by 111,234 users.

Clustering.

To calculate tag similarity we used a well proven method known as Jaccard coefficient. Similarity between tags is measured by the intersection divided by the union of the sample set. Based on this similarity measure clusters of tags where calculated using the bisecting k-means approach. For a discussion of different clustering approaches and their pros and cons see Steinbach et al. [START_REF] Steinbach | A comparison of document clustering techniques[END_REF]. The clusters were calculated using the CLUTO-Toolkit provided and described by [START_REF] Karypis | CLUTO -a clustering toolkit[END_REF]. Basically the N-dimensional similarity matrix of tags was used as an input for the clustering algorithm. The target number of clusters to calculate was specified as 20. This number was chosen to form clusters of about five tags, which informal pre-test showed to be a good size for clusters.

Tag selection for test content. Six different tag content sets were needed to guarantee that participants worked with a new content set in every condition. To construct the different tag content sets the 600 most useful tags according to the improved selection mechanism described by [START_REF] Hassan-Montero | Improving tagclouds as visual information retrieval interfaces[END_REF] were chosen from the delicious data set. Tags where then divided into three groups according to their frequency of use. This later one is used to decide on the size of the item in the tag clouds. The three different groups were not of equal size, as this would result in an unaesthetic and inefficient use of tag clouds.

Tag cloud composition. Next, each of these three tag collections was divided into groups of six items to form the basis for the different needed tag clouds. Tags where assigned to groups starting from the tags with the highest value for usefulness continuing to the lower values (again based on [START_REF] Hassan-Montero | Improving tagclouds as visual information retrieval interfaces[END_REF]). Then the tags of these groups were assigned randomly to the six test content sets. With this procedure we could ensure both that a) all tag clouds have the same number of big, medium and small tags and that b) the items of the different tag clouds are of similar quality and usefulness.

Tag cloud design. In contrast to [START_REF] Hassan-Montero | Improving tagclouds as visual information retrieval interfaces[END_REF] who place each cluster in a new line or [3] who translate semantic distance into screen distances we decided to keep the typically used rectangular layout of tag clouds. The reason for this approach is its efficiency with regard to screen real estate, and the advantages regarding readability and scanability. Furthermore this design layout eases implementation.

Figure 1. Example content displayed in alphabetic and clustered layout condition

To mark the different clusters color-coding was used: each tag within a cluster was underlined with the same color. To avoid disconnecting clusters spatially in case of line-breaks tags were placed in the tag cloud in a zig-zag-manner (i.e. one line was filled in the normal reading direction left-to-right with tags, and the next from right to left). Clusters were also separated from each other by additional blank space to enhance immediate perceptibility of clusters. The placement approach also reflects the similarity between clusters and not only between tags. Clusters that are placed near each other are more similar than clusters with great distance between them. Figure 1 (b) shows an example from the set of constructed clustered tag clouds.

Participants. 22 user (17 male, 5 female) participated in the evaluation. Average age of participants was 31.9 years (Min: 25, Max: 53). All of them had normal or corrected to normal vision. All participants had a technical background (because of the used tag corpora from delicious which contains many technical terms) and were intense users of web technologies.

Experiment One: Finding Specific Tags

The first experiment was designed to test how clustered tag layout influences search time and subjective evaluation of task difficulty when searching for a specific tag within a tag cloud. The task for the test participants was to find a predefined tag within a tag cloud as fast and accurately as possible.

The tag to be found was shown on the screen, on clicking 'Next' a tag cloud containing the target word appeared on the screen. The target word was also shown below the tag cloud. After locating the target tag participants had to click on it to proceed to the next task. Search time and clicked tag was logged.

For each layout condition twelve search tasks for different targets within the same tag cloud where performed. Target tags where evenly distributed across the three font sizes. We controlled for evenly distributed target position across the four quadrants of the clouds used in each condition, as prior research showed that tag position can have relevant influence [START_REF] Lohmann | Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration[END_REF][START_REF] Rivadeneira | Getting our head in the clouds: toward evaluation studies of tagclouds[END_REF]. Presentation order of layout during the test procedure was systematically varied to counterbalance possible order effects.

Effects of tag cloud layout on search time.

Repeated Measures Analysis of Variance showed a significant influence of the layout condition on search time (F 2,42 =61.48, p<0.000). Post-hoc analysis using paired-samples t-tests with Bonferroni-corrected alpha levels showed that the alphabetic layout is significantly faster than random (t 21 =-12.4, p<0.000) or clustered (t 21 =-10.3, p<0.000) layout. There is no significant difference between random and clustered layout (t 21 =.0, p=0.33). Average search times are shown in Table 1 below.

Experiment Two: Finding Tags Related To A Specific Topic

In the second part of the study the task of the participants was to find a specific tag that belongs to a pre-defined category. The categories were selected manually by the researchers. Special care was given that only unambiguous categories were used. Table 2 below provides examples of tasks for the selected categories for the tag cloud shown in Figure 1. All categories were verified by informal testing with colleagues of the authors with regard to their understandability and unambiguousness.

For every tag cloud three categorical search tasks were defined that contained multiple (two or three) relevant tags that were grouped together by the clustering algorithm into one cluster. Similarly, two categorical search tasks were defined that also contained two tags, but where the clustering algorithm had placed these tags into different clusters. Furthermore ten tasks were specified, where only one correct target tag existed. Again special care was given that these target tags where evenly distributed across all quadrants in the alphabetic, random and in the grouped tag cloud layout. Table 2 below shows example tasks for all three task categories. Repeated Measures Analysis of Variance showed a significant influence of the layout condition on search time (F 2,42 =3.37, p=0.044). Post-hoc analysis using pairedsamples t-tests with Bonferroni-corrected alpha levels showed that the clustered layout is significantly faster than the random layout (t 21 =2.6, p=0.017). Even though mean search time for clustered layout is 1.5 seconds faster than for alphabetic this difference is not statistically significant (t 21 =0.96, p=0.349). Based on information from the qualitative interviews we think this is due to the very high variation in the data which is caused by cases were test persons did overlook a tag and had to scan the tag cloud for very long time.

User Preferences

After conduction of the experiment users were asked to state their preference for a layout strategy both when searching for a specific tag and when trying to achieve an overview on a web page. All except one participant preferred alphabetic layout for the specific search. For gaining orientation and overview a majority of users preferred the clustered layout (15) over alphabetic (4) or random (3) layout strategies.

Qualitative Comments of Users

After each experiment users were briefly interviewed regarding their subjective impression regarding the clustered presentation approach. The general impression can be summarized as positive. Most participants really liked the approach for orientation tasks and general searches. Almost everyone also mentioned having been irritated and confused by some arbitrary looking clusters or 'wrong' placements of tags. Another negative aspect mentioned was the additional cognitive cost for understanding the meaning of a cluster. Few participants were irritated by the colors used to mark the clusters.

Discussion and Conclusion

Clustered tag cloud layouts seem to have the potential to improve search performance and satisfaction for general search tasks. However, our results (especially from the qualitative interviews) also show that state-of-the-art clustering mechanisms still produce artifacts that are difficult to understand by the users, and that counteract the possible usefulness of the approach. Application of clustered approaches therefore is only recommended in case sufficient quality of the clustering can be ensured. Results for specific searches show -as expected -that clustered presentation is only suited for application contexts were the main goal of the users is to gain an overview, and were searching for specific contents is secondary.

We could show that clustering tags in tag clouds is feasible in realistic settings i.e. using real data and applying state-of-the art clustering algorithms, and produces satisfactory results that are welcomed by users for general searches.

In future we plan to work on tackling the problems arising from suboptimal clusters. We want to explore the effects of only marking clusters with high internal homogeneity, and to use machine learning based categorization approaches to be able to also label found clusters.

Table 1 : Mean search times in seconds for the three layout strategies for specific searches (Experiment One) and general searches (Experiment Two)

 1

		Alphabetic	Clustered	Random
	Specific Search (Exp. One)	3.7 sec	13.3 sec	14.6 sec
	General Search (Exp. Two)	18.6 sec	17.1 sec	22.0 sec

Table 2 : Example tasks for general search in Experiment Two

 2

	Category	Task	Solution
	Multiple tags in same cluster	City in the USA	seattle, sanfrancisco
	Multiple tags in different clusters IT-Enterprise	sun, apple, ebay
	Only one target	Name of a Continent	Europe
	Effects

of tag cloud layout on search time.