by christina.volckmar -

#4 Chrissis Weg zur Character Animation – Step 2: Der Adobe Character Animator

Trigger Warnung: Ich habe meine Adobe Programme alle auf Deutsch eingestellt. Wer sich hierdurch getriggert fühlt sollte diesen Blogbeitrag nicht lesen.

Tu ich mir mit Tutorials schwer, weil die alle auf Englisch sind und ich beim Nachbauen dann erst mal Effekte übersetzen gehen kann, um sie anzufinden? Ja, sehr. Kann ich mich dazu überwinden die Programme nach all den Jahren endlich einmal umzustellen? Nein. Don`t judge me.

Auf meinem Weg hin mehr über Character Animation zu lernen lud ich mir den Adobe Character Animatior herunter. Wer das Programm nicht kennt: Es ist – wie der Name schon verrät – darauf ausgelegt Charaktere damit zu animieren. Was das Programm dabei aber von Animate oder After Effects abhebt: Der Character Animator kann mit deinem über z.B. Photoshop gebautem Charakter gefüttert werden und animiert diesen dann automatisch und in Echtzeit auf deine eigenen Bewegungen, die du mit der Computer-Cam aufnimmst. Dein digitaler Charakter ahmt dich sozusagen nach. Dies funktioniert besonders mit Facial Expressions.

Man kann sofort reinstarten, denn der Character Animator hat eine große Auswahl an bereits vorgefertigten Charakteren. Teils nur Gesichter, teils mit ganzem Körper.

Hier im Screenshot zu sehen ist das Arbeitsfeld mit einem vorgefertigten Charakter. Rechts zu sehen ist meine Kameraaufnahme. Das Programm erkennt meine Gesichtszüge bei einigermaßen guten Lichtverhältnissen wirklich gut und wendet diese sofort auf den Charakter an. Selbiges funktioniert mit Mundbewegungen beim Sprechen. Rechts im Feld zu sehen sind voreingestellte Steuerungen – Posen, die ich den Charakter machen lassen kann. Möchte ich z.B. ein Erklärvideo mit dem Charakter machen, würde ich auf record drücken, den Erklärtext runtersprechen und wenn ich mich danach fühle auf die verschiedenen Posen zugreifen, die der Charakter mit nur einem Klick nachmacht.

Funktioniert alles super einfach – wenn der Charakter bereits da ist.

Möchte man einen eigenen Charakter in das Programm einschleusen schaut die Welt nicht mehr ganz so rosig aus. Denn jede Pose und jede Mundstellung muss einzeln gezeichnet und korrekt gelayert werden.

Hier als Screenshot zu sehen sind die verschiedenen Sprechlaute des Charakters – sogar in zwei Ausführungen: sad und happy. Fast jeder der Laute hat dann auch noch einmal Unter-Layer. Character „Lucy“ ist jedoch im Vergleich zu den anderen vorgebauten Charakteren eher auf der aufwendigen Seite. Dafür hat sie auch viele Animationsmöglichkeiten.

Was praktisch zum Erstellen des eigenen Charakters ist: Character Animator gibt einen klaren Überblick und Anweisungen bzw. Empfehlungen, welche Facial Expressions für eine nahtlose Sprech-Animation benötigt werden und listet diese mit kleinen Symbolen auf, die man dann mit eigenen Zeichnungen füttern kann. Natürlich ist es auch möglich, wenn man nicht so einen aufwendigen Charakter wie Lucy zeichnen will, nicht alle Laute zu verwenden. Kreiert man z.B. eine sprechende Ente (wer auch immer so etwas Verrücktes tu würde…), reicht vielleicht ein einfaches Mund (Schnabel) – auf und zu.

Neben der Aufzeichnung der Gesichtszüge und Sprache haben manche der voreingestellten Charaktere auch ein Body Rig. Jene Charaktere ahmen dann auch Arm- und Beinbewegungen nach. Wichtig: Immer zuerst in neutraler Pose kalibrieren! Das funktioniert auch sehr einfach: Unter der Kamera zuerst den Body-Tracker aktivieren, dann auf den Kalibrierungs-Button drücken. Man hat dann, anders als bei der Gesichts-Kalibrierung 5 Sekunden Zeit schnell an die andere Seite des Raumes zu rennen und sich in T-Pose hinzustellen.

Die Intensität sämtlichen Verhaltens des Charakters kann zudem auch bestimmt werden, sodass im Aufnahmeprozess keine Bewegung ungewollt erscheint.

Wer sich mehr mit der Materie auseinandersetzen will, kann in dieses Video reinschauen. Hier werden Schritt für Schritt sämtliche Funktionen des Programmes erklärt, natürlich viel detaillierter, als ich es in einem Blogpost machen kann.

In einem weiteren Blogpost werde ich versuchen meinen eigenen Charakter zu animieren – der muss hierfür aber erst einmal erstellt werden.

Mein vorläufiges Fazit von Adobe Character Animator:

Man kommt sehr leicht rein und hat nach kürzester Zeit schon ein Erfolgsgefühl, wenn man mit einem bereits vorhandenen Charakter animiert. Durch die vielen schon geriggten Puppen kann man sofort reinstarten und das Programm kennenlernen. Ich kann mir sehr gut vorstellen, dass Character Animator besonders für Erklärvideos exzellent geeignet ist – also für Videos, in denen man einen statisch auf dem Platz stehenden Character hat, der ab und an eine Hand bewegt und die meiste Bewegung im Gesicht beim Sprechen stattfindet. Aus dem oben verlinkten Video habe ich auch herausgefunden, dass dich diese Puppets in andere Adobe Programme, wie After Effects integrieren lassen. Bis jetzt bin ich von den Funktionen und der Flexibilität positiv überrascht. Mal sehen, wie es mir geht wenn ich versuche meinen eigenen Charakter zu riggen…

by Indigo Tschurtschenthaler -

Testing my prototype in class

Design & Research 2 with Birgit Bachler

During our last session with Birgit Bachler we performed some usability tests of our prototypes. 

My aim was to find out if the reporting game was understandable and engaging. The reporting minigame does not have a VR function yet and I supposed that this could have created a difference between how I imagined the prototype and how it was perceived by others. Since the testing happened during broad daylight in a classroom, I suspected that users would not have understood that the minigame is meant to be used at night to send a useful report. For this reason I prepared some pictures of the sky to simulate different observations. 

I measured these parameters:

  • Time spent on tasks
  • Number of trials until the participants succeeded in completing the task (if they did)
  • Task completion — whether the task was completed in way I intended it

The method used was the “thinking aloud” one. Users should speak while they perform the test and tell the interviewer their thoughts and feelings.

These were the tasks that I gave my participants:

  1. Play the game without lying or pretending
  2. Play the game in this situation (picture of clear sky)
  3. Play the game in this situation (picture of cloudy sky)
  4. Play the game in this situation (picture of polluted sky)
  5. Imagine you are seeing a clear sky but you cannot find that constellation
  6. You already know where the constellation is and want to jump straight to reporting

The questions I asked them at the end were the following:

  1. Did anything create frustration or confusion (text, icon, something in the flow)?
  2. How would you explain the main goal of the game to a friend?
  3. What was your favourite part?
  4. If you could add a feature, what would it be?
  5. What do you think about the visual style and aesthetics?

Three people participated in the test, including two students and one professor. I called them P1, P2 and P3. I did not ask them all of the questions, instead I selected different ones every time to keep the test shorter.

The results of the tests are summed up in this table:

These are the pictures I showed my participants for task 2, 3 and 4:

Clear sky
Suburban sky
Cloudy and polluted sky
Cloudy sky
Polluted sky

Some other observations are summed up in the following table:

This is how the participants answered the questions:

Did anything create frustration or confusion (text, icon, something in the flow)?

P1: I would say that in the beginning I wasn’t quite sure what I’m supposed to do, but maybe also because I did not read the text fully in the beginning, so I wasn’t quite sure whether you can only report when it’s night. I didn’t quite get that at the moment and was confused because I could not see anything, but I should have seen something. Yeah, then maybe the hint, but I already said that about the northern hemisphere, when you give a hint that something is supposed to be there, that there’s some sort of hint about which direction to look and maybe also how high or maybe if there’s another star that you would recognise that you can take as a reference point or something. Then I think you can make it quicker. Also, in the beginning I didn’t know what this button meant, I would have had to test it out to see what it does and also the exit button didn’t go to the start, but it went back to the star constellation, so maybe from exit I would expect that it would let me exit. I think maybe in the beginning it could be a little more clear what to do and more help, and maybe that the stars could be a little bigger or further apart. The smaller ones are a challenge to click.

P2: A lot of stuff generates confusion, like when I started I didn’t even know how to report. It said “locate this star” and I don’t even know what that is, so it was really frustrating, like what exactly I have to find? So I just randomly tapped here and there and found out. The most frustrating part was that everything is designed for a person who knows about this.

P3: The finger (the tapping on stars feature) – didn’t realise that at the start.

How would you explain the main goal of the game to a friend?

P1: I would say: identify constellations and also report about light pollution in different areas based on what stars are visible with the eye in the sky. 

P2: The main goal of this game is to locate the stars and report them.

P3: Reporting to what extent a constellation is visible from a certain location, and perhaps including metadata as well – or did that come later? Yeah, that would be cool, because you’d say, ‘I can’ ’t see it, and then you can say, ‘Why not?’ I reckon one reason is that I’m too daft to find the star, and the other is that it’s too light-polluted, so I think you have to… But since it’s just a game, you can simply track light pollution and constellations.

What was your favourite part? 

P1: I think clicking the constellations, like the selection of the stars I could see.  

P2: When I can see the clear sky and I’m like “yeah maybe I am doing something” and also I really like that there’s a hint option, it gave me a little bit of information.

P3: I think the writing is a good start, ‘Help me’ and so on.

If you could add a feature, what would it be?

P1: Maybe more constellations? And also I had an app on my phone when I was stargazing and it showed the entire night sky. Every star is supposed to be there. Maybe it could also be nice to have an overview of all the constellations that should be in the sky and if you could kind of see on the phone and then compare it to what you actually see. I think it might also be easier to find a constellation. Like, okay, I found this constellation and if I turn a little more up then I can find more constellations and get a better understanding of what is where in the sky.  

P2: I would really like the feature to be really using the current sky, like having a region of it. That could be really cool. 

P3: Maybe the step where you have to look for the constellation in the sky or check if it’s visible. It’d also be cool to have a location, just like with those apps, so you know that’d be the next feature – and at the same time you’d be learning about the constellations, so you could pick up on that sort of mythological stuff on the side as well – that mix of astronomy and astrology.

What do you think about the visual style and aesthetics?

P1: It is very nice, very clean, very easy. Also it’s like the theme of the stars, black-and-white. Also, I think the constellation with the outline of the animal and then the stars inside is good because then you also learn a little more about the constellations, because sometimes in the sky if you only have the stars it’s hard to see the animal or whatever that’s supposed to depict. I think the style was very nice.

P2: The night vision, I really liked it. I think it’s a good direction. 

P3: Simple and neat.

After analysing the recordings of the tests, I concluded that:

  • It was not clear to the participants that you are supposed to play the game at night and tell the game if it is daytime; I could have specified that in the introduction (“this game should be played at night”)
  • Sometimes when the stars are not visible, participants would still send a report; I could make a first screen that asks a yes/no question to filter out reports that are not valid
  • Constellations are not always a concept known by everyone; I should explain what they are at the beginning
  • There were issues with orientation and localisation of the constellation; the VR feature with compass sensor and GPS that other applications use would help with that
  • Users tried to tap on the stars on the first screen; it should be clear that they are not tappable or they should be tappable right from the start
  • Exit buttons were not working properly; I should check them
  • The stars were a challenge to tap on; maybe the tappable area could be bigger or there should be a zoom/swipe feature
  • The option to tap on the stars was appreciated; I can keep working with that
  • There was some confusion about what was reported at the end; I should specify it
  • The black and white theme with the constellation illustrations was appreciated

For the next testing, I need to remind myself to:

  • explain the product and what we are doing with it
  • ask some introductory questions to understand the participant’s knowledge of the topic
  • ask everyone the same questions to compare results better
by christina.volckmar -

#3 Chrissis Weg zur Character Animation – Step 1: Wie funktioniert Rigging?

Da ich nun den Entschluss gefasst habe mich in Character Animation auszuprobieren, stellte ich mir nun die Frage: Wo fange ich an?

Meine Kenntnisse in (Character-)Animation sind limitiert. So tat ich das, was jede Person tun würde, die mehr Wissen und Know-How zu einem Thema haben will: Ich leistete umfängliche Recherchearbeit in der Bibliothek.

Und mit Bibliothek meine ich YouTube. Und um spezifischer zu werden: Ich gab in die YouTube Suchleiste den Begriff „Character Animation After Effects“ ein und sah mir das erste Video an. „How to get started with Character Animation in After Effects 2023” schien mir ein zielführender Titel zu sein.

Der Hauptinhalt des Videos ist das Rigging von Charakteren. Kurzer Exkurs hierzu (für die 1%, die noch nie was von Rigging gehört haben):

Character Rigging ist der Prozess ein digitales Skelett an einen digital erstellten Charakter zu binden, um diesen so bewegen zu können. Dies funktioniert sowohl für 2D, als auch für 3D Animationen. Je nachdem wie aufwendig die Animationen am Ende sein sollen, wird entweder nur ein grobes Skelett für die Extremitäten, oder ein feines Skelett für z.B. Facial Rigging erstellt. Was der große Vorteil von Rigging gegenüber Frame by Frame Animation ist: Man wendet einmal Aufwand für das Bauen des Rigs auf und kann danach den Charakter wie eine Puppe steuern, ohne jede Bewegung einzeln animieren zu müssen. (1)

Da 3D Animation ein gruseliges Kapitel ist, bleibe ich also bei 2D und probiere mich in After Effects aus. Für das Character Rigging gibt es mehrere Tools, die man in After Effects verwenden kann. Ich habe mich hier (2) ein bisschen schlau gemacht:

  1. Puppet Pin Tool: Dieses ist bereits in After Effects inkludiert. Das ist einmal ein großer Vorteil. Jedoch eignet sich dieses Tool nicht für komplexere und cleane Animationen. Es kann Deformierungen erzeugen und ist manchmal schwer zu kontrollieren. Für einfache Bewegungen kann es jedoch sehr nützlich sein. Ich habe es bereits mehrmals verwendet, wenn ein Objekt etwas bouncen soll oder leicht hin und her schwankt.
  2. Duik Bassel: Dieses Tool steht zum Gratis-Download verfügbar. Es scheint auch das am weitesten verbreitete und meist genutzte zu sein. In einem Artikel finde ich sogar den Satz: „If you learn only one Character Rigging tool for After Effects, it should be Duik.” Das ist mal ne Ansage. Duik hat sehr viele features, darunter Auto-Rig, Icon-Based Controllers und Automatisiertes Parenting. Durch diese Vielfalt ist die Lernkurve aber auch etwas flach.
  3. Duik Ángela: Dies ist die neuere Version von Duik Bassel und bietet erweiterte Rigging- und Animationsfunktionen.
  4. Rubberhose 2: Dieses Tool macht Rigging super easy. Es wurde extra dafür entwickelt eine einfache und schnelle Alternative zu anderen Tools zu sein. Finde ich, hört sich sehr ansprechend an. Die 45$ Kosten sind eher weniger ansprechend…
  5. Limber: Macht Rigging auch einfacher als mit Duik, kostet jedoch auch. Hier gibt es aber eine lite Version, die Gratis ist. Natürlich sind hier nicht alle Funktionen freigeschalten, jedoch ist es zum Erstellen einer einfachen Animation ausreichend. Wer noch nie gerigged hat (ich, lol) könnte hier beginnen. Stand heute (05.07.2026) ist die lite Version jedoch nicht mehr zum Download verfügbar. ☹
  6. Joysticks’n Sliders: Hier inkludiert, was der Name Schon sagt: Joysticks und Sliders. Diese dienen bei dem Tool zum Steuern des Charakters. Vor allem wird es in der Charakter Animation zur Rotation z.B. von Kopf, Augen und Körper verwendet. Kostet 39$.
  7. Adobe Charakter Animator: Dieses Programm fällt ein bisschen aus der Auflistung, da es ja kein Tool in After Effects ist, sondern eine eigene Applikation. Eine der Funktionen, die ich hier am spannendsten finde ist, dass Bewegungen und Mundpositionen automatisch animiert werden, basierend auf Videos. Man kann einen Charakter bauen, die Frontkamera des eigenen Computers anschalten und jene Bewegungen durchführen, die der Charakter nachmachen soll. Alles ganz automatisch.

Nach meiner mehr oder weniger umfassenden Recherche stechen für mich zwei Programme bzw. Tools hervor, die ich weiterverwenden möchte. Erstens Duik Ángela – ansprechend hierbei natürlich, dass es Gratis ist und so viele Funktionen verspricht. Außerdem möchte ich den Adobe Charakter Animator für Sprach-Animationen ausprobieren. Leider gibt es Limber lite nicht mehr zum Download, sonst hätte ich mir auch dieses Tool geholt.

An all jene, die sich diesen Blogpost durchlesen (also Roman): Mich würde sehr interessieren, mit welchen Programmen und Tools ihr die besten Erfahrungen in Character Rigging gemacht habt.

Quellen:

1. Mimic Productions (3.10.2025): Character Rigging: How, Why, and Where You Can Use It. In: Mimic Procutions, https://www.mimicproductions.com/post/character-rigging (zuletzt abgerufen am 05.07.2026)

2. Joe Camarata (o.D.): Character Rigging Tools for After Effects. A List of the Best Character Rigging Tools for After Effects. In: School of Motion, https://www.schoolofmotion.com/blog/character-rigging-tools-after-effects (zuletzt abgerufen am 05.07.2026)

by christina.volckmar -

#2 Komplettes Verwerfen des Konzeptes und Vorstellung einer neuen Idee

Nachdem ich einen unveröffentlichten Blogbeitrag über Ionenpumpen geschrieben habe, für den ich akribisch in meinen alten Biologie-Büchern recherchierte, habe ich mich nun dazu entschlossen das Konzept zu verwerfen. Monate sind vergangen seit der Veröffentlichung meines letzten Blogbeitrages und was soll ich sagen… Ich bin von meiner anfänglichen Idee abgewichen und verfolge nun ein anderes Konzept, das in eine andere Richtung geht. Nicht in die komplett andere Richtung aber sagen wir mal… ich mache eine seichte Kurve.

Mir ist – wie so oft – beim Fahrradfahren ein Licht aufgegangen. Ich weiß nicht, ob das eine gemeingefährliche Eigenschaft von mir ist mich mitten im Straßenverkehr in Gedanken zu vertiefen, doch ich schwöre: Während ich auf gefährlichen Bundesstraßen versuche nicht von großen LKWs überfahren zu werden, kommen mir die besten Ideen.

Nun, meine treue Leser:innenschaft (die whs eh nur aus Roman besteht; Hi Roman), nun möchte ich euch feierlich meine Idee für die Masterarbeit präsentieren und daran anlehnend was ich für DesRes machen möchte:

Im Wintersemester 25/26 schrieb ich einen Blogpost über den Bechdel-Test der Erklärvideos und nannte ihn den „Volckmar-Test“. Darin bewertete ich die Geschlechterdarstellung in geschlechterspezifischen Erklärvideos, wie etwa zum Thema „Aufbau des menschlichen Körpers“. Mit Erschrecken (naja, eigentlich habe ich es nicht anders erwartet) musste ich feststellen, dass gar im medizinisch-biologischem Umfeld, wo es doch um korrekte, naturgetreue Darstellung von Fakten geht, der, männliche Körper als Norm angesehen wird. Kam eine Frau in den Videos vor, dann meist nur zum Zwecke der Darstellung ihrer geschlechterspezifischen Körperregionen. Von intergeschlechtlichen oder transgeschlechtlichen Personen war zudem niemals die Rede.

Meine Masterarbeit soll sich diesem Thema widmen. Zudem entwerfe ich den Volckmar-Test und entwickle Parameter, für sensible, realistische und faire Geschlechterdarstellung in Erklärvideos. Mein Werkstück wird wahrscheinlich solch ein Erklärvideo.

Mein Plan für DesRes ist es nun einen Charakter zu erstellen und mich in Charakteranimation auszuprobieren. Das war eigentlich eh mein ursprünglicher Gedanke, doch nun zu einem anderen Thema.

Ich habe noch keine exakte Vorstellung, wie das Endprodukt aussehen wird, mein Ziel ist es einfach mich auszuprobieren mit Walk-Cycles, Lip Sync etc.

Zudem werde ich einen oder mehrere Charaktere entwerfen, die es dann vielleicht in meine Masterarbeit schaffen.

by martina.monterisi -

#3: From literature gaps and sketches to a clear direction

In the previous post I sketched three possible directions for the prototyping phase of the research, with the promise of developing one of them further. This one will start from openings left by the literature review draft of my ongoing thesis and it will explain its possible applicative idea.

Summarising gaps

Reviewing the literature made one absence particularly clear. A considerable amount has been written about how artificial intelligence could, or should, be integrated into the creative process and into data-driven storytelling. Yet, much less has been written about how practitioners actually behave when they sit down and use these tools in their everyday work. The theory on good integration of AI in our work is a lot, but the empirical picture of real habits in the storytelling and data-driven design practices field is almost inexistent.

Sierra Shell makes a related observation in The Human Touch(point), where she notes that understanding the current state of how people use AI features and how they give feedback on them is still an open area for research, rather than settled knowledge. Additionally, the recent surveys on data-driven storytelling and visualization point in a similar direction, treating a human-centred account of the process as an unresolved question rather than as an established one. In other words, before proposing how designers should work with AI, it would be much more useful to document how they are already doing.

Building the idea

To effectively address this empirical gap, there is the need to collect firsthand data. The thesis, therefore, opens up to the need of a survey aimed at students, workers, and experts across communication design, storytelling, and data visualization, with the aim of collecting data and make them later available for further studies and fellow researchers as open source.

The instinctive move would be to reach for a common survey platform. Yet, I would rather build a different tool for ensuring having open data together with the possibility of taking the survey, with also the opportunity of having always updated data in real time. A generic form provider tends to lock results away in a private account, whereas the aim here is the opposite, making the collected evidence a shared and accessible resource.

For the survey section, the priority is currently to define how the tool works and which steps it moves through, not to finalize every question. What remains fixed is the intent: to capture habits of AI usage together with a basic professional profile of who is answering. As for the open data hub, once results begin to accumulate, they will be presented in an aggregated and anonymized form that anyone can consult, without having to complete the survey first and keeping sensitive data out of this public layer.

Encouraging personal reflection

Both parts in this idea, in the end, serve the same purpose, which is to encourage reflection on our behaviours. For the respondent, answering the survey is already a small prompt to consider one’s own reliance on these tools. For a visitor to the open hub, seeing collective patterns laid out invites a comparison with their own practice. The intention is not to lecture nor to attach a score of guilt to anyone’s choices, but to make current habits visible enough to become the source for discussion.

The full bibliography of the thesis will be attached to this documentation, for anyone who wishes to follow the sources behind the literature review.

Thesis’ BibliographyDownload
by julia🐨razumovskaia -

PROTOTYPING – Design & Research II (Birgit) – 5/6

Continuing my research on the topic of “Slowness”from last semester, I will be doing further work on this topic as part of the Design & Research II course with Birgit Bachler PhD.

For the final assignment, I will need to record a 2-minute video of the final prototype — in my case, I plan to use prototyping in Figma, which each of you will be able to test. The research will again focus more on contextual analysis, as well as user testing, bibliography, and heuristic evaluation.

Comparing default routes and experience-based routes 🛣️

For this post, I decided to conduct a small practical experiment and compare a standard navigation route with one that more closely resembles the concept behind my future app. I chose the same route: from my current location to Hauptplatz in Graz. It was important to me to look not only at the time and distance, but also at how the walking experience itself changes.

On Google Maps [1], the standard route looks very straightforward and functional. The app suggests the fastest option: 35 minutes, 2.6 km, mostly along Annenstraße. This is convenient if the goal is simply to get to your destination. But with this option, the walk feels more like a task: follow the line, don’t get distracted, and reach your destination.

Then I manually created a second route in Google Maps and added stops: BILLA PLUS, Volksgarten, and Gelateria Italiana by Luis, and only then—Hauptplatz. The time increased to 42 minutes, but the route itself became completely different. It’s no longer just a path from point A to point B, but a little walking itinerary: pop into a store, walk through the park, buy some ice cream, and only then head to the center.

I also ran the comparison on Mapy.cz [2]. The direct route is shown there as 43 minutes, 2.6 km, while the route with additional stops is about 50 minutes, 3 km. What I especially liked about Mapy.cz is that the urban environment itself is much easier to make out. You can see parks, green spaces, paths, the terrain, the river, and the neighborhood’s layout. The map looks more detailed and “outdoor-oriented.” Visually, it’s not as minimalist as Google Maps, but for my purposes, that’s actually a plus because it helps me not just walk, but understand the space around me.

This experiment helped me better understand the concept behind my app. I don’t just want to make routes longer. The idea is for users to be able to choose not only their destination but also the type of route: fast, leisurely, green, adventurous, social, or with short stops.

In the next prototype, I want to develop this logic further. For example, if a user selects a “slow route,” the app could automatically suggest a path through a park, a quiet street, a café, or a spot for a short stop. In other words, the map becomes not just a navigation tool, but also a tool for planning a walk.

This test showed me one simple thing: navigation doesn’t have to be just about the shortest route. Sometimes an extra 5–10 minutes can make a route much more enjoyable, personal, and memorable.

Sources 🛈

[1] Google Maps. Google LLC. Available at: https://www.google.com/maps

[2] Mapy.cz. Seznam.cz, a.s. Available at: https://mapy.cz

by Hannah Wasserfaller -

Science Communication and Dissemination

While I am busy with creating further visual content that is related to science and have been starting to put out some of my creations, I still wanted to continue my research about the world of science communication. From an exercise in the design and research class, I came up with a number of relevant key words for my research which I wanted to explore further. And one term in particular has crossed my path in both the research process and in “real life”, which is why I would like to dedicate this blogpost to the topic of dissemination. In the world of science, dissemination is a term that one will frequently come across – and one that I would define as closely related to the field of science communication.

Dissemination in the context of science essentially means transferring knowledge to a targeted audience because that audience will either use it, be impacted by it or influence the use of the evidence. In short: dissemination is all about getting information to the right people so that they can make use of that knowledge. To name one example – knowledge that concerns health care could be communicated to policy makers, patients or healthcare practitioners. It is a core component in translating knowledge strategically in order to adopt and implement new practices.

There are various frameworks and translation models that include elements of dissemination, however, dissemination is often regarded as a single step at some point towards the end of a research project rather than spanning over its entire running time which in turn contributes to a translational gap between what is evidence is being generated and what actually impacts policies and practices. This furthermore has also the potential to represent poor return on investment to research funders.

Dissemination is a complex topic that demands strategic use and while many models exist, researchers struggle to select the fitting resources for their dissemination strategy and lack guidance in terms of which activities to implement at the subsequent steps of the dissemination process. 

So, to sum up: while there are strategies and models, implementing them effectively poses a big challenge, which is why it would be important to develop a framework that is accessible and clear to everyone. 

While my previous posts and my general approach was more on the non-scientific community as a target group for my topic and also the little projects I have been working on, it was quite interesting to see that proper science communication is a struggle that is not only related to (public) education but maybe even more relevant for the scientific community,  incredibly important in order to translate scientific findings for decision makers or audiences that concretely benefit from certain knowledge. 

While communication to the public and offering ways of easily accessible information that are intended to raise the overall knowledge within the population is a large part of what caught my interest in the matter and is also something I want to pursue further, the importance of that other side of science communication was not as evident to me before.

Therefore, I think it could be interesting to also follow the topic from this other side. To look at the ways  scientists currently frame and communicate their work to respective target groups and then find the issues and new (design supported) approaches to make for better knowledge transfer.

The way of communication research has been changing, especially due to digital possibilities.

And while traditional formats such as scholarly journals and books can be found online, their functions and formats have remained similar throughout that time of change. 

Therefore, online media such as blogs and social media platforms offer new possibilities for scientists to use. Blogs and wikis have risen to popularity with something called „open notebook science“, professional academic networks like ResearchGate or Academia.edu have millions of users, and for interaction with the wider public, online formats such as TED talks that are being streamed via YouTube have become very popular. 

Digital technologies allow scientists to not only communicate with their primary dissemination targets (such as other scholars, policy makers or similar) but to actively involve people that otherwise would not have had access to this information.

The potential of adopting new methods is promising, as new cross-disciplinary collaborations could emerge which in turn could support publications, funding and new research opportunities.

Overall, there has been a noticeable push towards making science and research known to the greater public since the 1980s and the inclusion of non-scientific audiences which in turn has caused new forms of dissemination to emerge. Examples for this would be sciences shows or magazines and in more recent years, new event types such as science slams or open lab days. New participatory spaces such as science cafés or hackerspaces emerged which influence both research production and dissemination  processes, and powerful trends that strive for the globalization of research, responsible research, and inclusion of previously excluded audiences are reshaping the scope and purposes of dissemination. 

The issue here is, that while these new emerging approaches are viewed as fundamental constituents of open science, researchers tend to still focus on traditional outputs such as journal articles, speaking at conferences or publishing books. 

Innovative dissemination would, in turn, mean dissemination that exceeds traditional academic publishing and meeting practices and aims to spread the research findings to a more widespread audience.

I feel like this is the part I would like to find out more about in the future because that is also where the power of (media) design can play a vital role. 

For the next blogpost, I plan on diving a little bit deeper into (innovative) dissemination practices in order to find out more about the possibilities and challenges in that regard.

Sources used in this blogpost:

First part: Scott, Sion, Bethany Atkins, Thomas D’Costa, Claire Rendle, Katherine Murphy, David Taylor, Caroline Smith, Ian Kellar, Andrew Briggs, Alys Griffiths, Rebekah Hornak, Anne Spinewine, Wade Thompson, Ross Tsuyuki, and Debi Bhattacharya. “Development of the Guide to Disseminating Research (GuiDiR): A Consolidated Framework.” Research in Social and Administrative Pharmacy 20, no. 11 (2024): 1047–57. https://doi.org/10.1016/j.sapharm.2024.07.007.

Second part: Ross-Hellauer, Tony, Jonathan P. Tennant, Viltė Banelytė, Edit Gorogh, Daniela Luzi, Peter Kraker, Lucio Pisacane, Roberta Ruggieri, Electra Sifacaki, and Michela Vignoli. “Ten Simple Rules for Innovative Dissemination of Research.” PLOS Computational Biology 16, no. 4 (2020): e1007704. https://doi.org/10.1371/journal.pcbi.1007704.

by Indigo Tschurtschenthaler -

Testing my second prototype

Design & Research 2 with Birgit Bachler

Sketching

After doing the context review and the material studies, I decided to work on my prototype again. I focused on our lecturer’s question “what is the smallest prototype you can create that still touches the issue?”. A specific issue came to my mind: according to A review of invasive species reporting apps for citizen science and opportunities for innovation by Howard, van Rees, Dahlquist, Luikart, and Hand, gamification is not sufficiently used in citizen science apps. With the intention of creating something quick, fun, and gamified, I looked at my initial analogue prototype and the app prototype I created with Ahmed Turk for our app design course. I decided I wanted to focus only on the reporting flow of the app and create a minigame. By focusing on its core feature, I wanted to make it as interesting and seamless as possible. This way, the reporting platform could benefit from a higher engagement.

I started my second version of the prototype by sketching a storyboard. Then, I highlighted some scenes that in my opinion are the foundation for the MVP. After that, I sketched some screens and created them on Figma.

Heuristic evaluation

I then went through Jacob Nielsen’s 10 Usability Heuristics for User Interface Design to further refine the prototype. Here you can read my evaluation:

  1. Visibility of system status. At the top of the screen, you can see the progress through the game (0/2); I do not know if it should start with 0/2 or with 1/2.
  2. Match between System and the Real World. The constellation has the same shape and proportions as the one in the sky. The brightness of the stars also mirrors reality. As the app does not use GPS and the gyro sensor yet, the constellation is not rotated in the same direction as it appears in the sky. This could also be a challenge factor that makes the game a little harder. No technical jargon is used, only commonly used words.
  3. User Control and Freedom. There is an emergency exit (X) to exit the game and a back arrow to return to the previous step
  4. Consistency and Standards. The back arrow is located at the top left corner (iOS standard), while the X is at the top right. The latter should ideally also be positioned in the top left corner, but that space was already occupied. The main action is in the white button, while secondary actions are in all-caps. All clickable text is in all-caps.
  5. Error Prevention. If the sky is not visible, there are various options that can be selected, which open tips for better observation. This prevents false reports. In the future, once sensors are incorporated, the app should recognise whether you are pointing your phone at the right constellation, to prevent mistakes.
  6. Recognition Rather Than Recall. The name of the constellation is repeated on every screen of the reporting game.
  7. Flexibility and Efficiency of Use. For expert users that already know constellations, there is an option to jump straight to the report and skip the constellation hunting part.
  8. Aesthetic and Minimalist Design. I tried to keep everything minimal; the only thing that could be simplified is the bear illustration and maybe the copy, but in my defense it is intended to have a relatable tone that brings the audience a little closer to a complex topic.
  9. Recognize, Diagnose and Recover from Errors. Error messages are written in a simple language and suggest a solution for a wide variety of issues.
  10. Help and Documentation. If the constellation cannot be located, there is the option to receive a hint.

Here are some screens of the minigame. After hitting “play”, the user needs to find a certain constellation in the night sky. Then, they can report the visibility of its stars by tapping on them.

If the user cannot see the app, they can tap on “I can’t see it” and select why. This leads to different tips based on the answer.

These videos illustrate two possible flows:

Possible improvements

  • Fun facts about the constellation at the end of reporting
  • Getting a badge on your profile
  • Changing tasks
  • Seeing what kind of report you submitted

by anja.kljajic -

D&R2 BIRGIT – The Human Element 5/6

TESTING
COMPARISON
UX/UI DESIGN

For my final post I’d like to talk about the preparation for the guerrilla testing session, as well as the results.

The prime target for this was a dedicated webpage for Resellers on the sprinters.at website. My story from the introductory post was actually based on this outcome. I was already working on some complex interfaces behind the scenes that would be utilised for this feature, such as a completely new address system for multiple recipients. However, when it comes to the informational webpage that serves as the sign-up hub for this feature, a completely AI-generated design was used without my knowledge.

Prototyping

Since my topic is all about how workflows change with the advent of AI, I decided to actually work with the situation instead of wallowing in it. The primary focus of this redesign was to simply use the existing design system and corporate design.

What was a new experience to me about this prototyping session was that I worked with the AI-generated design, keeping the overall structure and content as inspiration but rewording what I thought was necessary as well as keeping the design philosophy in mind. I still made everything from scratch, but used the design as heavy inspiration.

Guerrilla Testing

To test this, I took both the AI-generated and the human-redesigned version and presented them. The test happened with two participants and consisted of simple questions about brand context, visual consistency and a more personal “is this ready to ship?” question.

1. The Brand Context & Transition Feel

When going from the landing page to the reseller page, Participant 1 noted that the AI version felt “cramped and crowded” in the hero section, while the human-redesigned version felt more “clean and organised”. Participant 2 agreed with this, saying that the AI version had “no personality” and was “more business”, while the human one felt “more similar and personal”.

2. Visual Consistency

This question was aimed more at looking more closely at individual components and elements (such as icons, buttons and images). Jakob Nielsen fourth heuristic, Consistency and Standards, describes the need for recurring elements in a user interface like language, icons, symbolism to be consistent across different tasks [1]. This was the biggest blunder of the AI design.

When talking about the AI version, both participants pointed out that “the icons don’t go with it“, “the images don’t look intentional“ and that “spacing was different from the homepage and cramped to the border“. One participant also noticed that the “buttons are rounded, when they’re more square on the main page“. This participant also mentioned that the icons in the human version are “great, because the colours are the same as the brand“.

One thing Participant 1 also mentioned on the machine-translated version of the AI version, was that the texts “tell you to do it, but not what it is“, while Participant 2 said that the text feels generic.

3. Ready to ship?

When the participants were asked if they would consider this as ready to ship as part of the same product (if they were the UX/UI designer responsible), they gave dividing responses. Participant 1 gave a hard “NO!”, pointing to the inconsistent spacing and icons, and added: “Why put something bad online when could can give me some time to improve it?”

Participant 2 gave a more nuanced answer, stating that “if the priority is to ship, then yes, its functional and still intuitive, but not the same brand”. They said they would “feel bad as a designer”, because the first impact of the brand is the most important.

Conclusion/Reflection

In conclusion, I gathered some data on what stands out to designers from two other designers. I particularly found the comments about the “texts telling you what to do, but not what it is” interesting, and for further testing I’m definitely going to take care to provide English versions of my prototype as well so this could be compared. I worked on the Reseller feature for weeks, so I had to understand it myself by asking multiple people within the company. AI didn’t have this simple human advantage, and thus the end result was what it was.

However, this isn’t about “AI being bad”, and I’d like to wrap up my research journey for this semester with this quote from IDEO (the design agency which developed design thinking):

How many things were meant to be great big breakthroughs, but they just don’t work because they don’t take into account what humans want from the technology? […] AI is far too important to leave just to the technologists—human-centered design is a crucial part of it. [2]

References