The REMOTE conference at ASU, Arizona State University, was my second fully virtual conference. It impressed me. Although many things could be better, this is —I think—, so far, state of the art. In the following video, you’ll get a few impressions.
What this conference did very well
Most talks were done by two people plus a moderator. It’s much more lively than when someone is on their own.
Every session was synchronous, had a timeslot and was recorded.
A few minutes after a session the recordings were online.
There were many different chatrooms. The participants were listed and could be reached by chat or mail.
Schedules could be saved and downloaded to one’s calendar.
You could get into a session a few minutes in advance and have a look at the handouts.
You could watch sessions simultaneously (if you were brave).
The chat and the Q&A (informal and formal communication) in every session were separate channels. If you had a real question or if you needed help, you could write into the Q&A.
If I’m not mistaken, it was organised using the product by inxpo. The price tag is quite impressive. But maybe it’s worth it. Let’s look at the pros and cons of virtual conferences in general!
Content/parts/sessions can be asynchronous (pre- or post-recorded)
It’s much easier and comfortable for shy people. 😉
Ther are no additional travel and accomodation costs.
It’s time efficient.
You can switch between rooms/sessions (if something’s boring).
It’s possible to attend conferences around the world.
Participants attend from all over the world. (Diversity, equity,…)
Discipline to attend may lack! It’s hard if work is just in another window on your computer.
It’s tiring to sit a few hours in front of the screen. (Some conferences offer ‚Chair Yoga‘ sessions once or twice a day!)
Although possible, it’s harder to connect to other people.
If there are many participants all writing in a chat, it is IMPOSSIBLE to read what’s going on.
Anything we should add to the list? Please drop me a line!
Tagung vom 16. & 17. Januar 2020, Collegium Helveticum
Serious Games for Ethics Training in Medicine
Summary in German; Report in English
Das ‚Institute of Biomedical Ethics and History of Medicine‘ der UZH hat ein ‚Serious Moral Game‘ entwickelt, um die Sensitivität der Medizinstudierenden in ethischen Fragestellungen zu erhöhen. Ob dies gelingt, ist noch nicht geklärt; weitere Studien folgen. Nach einer ausführlichen Einführung zum Spiel ‚uMed‘ durften wir es selber spielen.
Der untenstehende Bericht (auf Englisch), besteht aus den Beiträgen von Celia Hodent und beinhaltet Spannendes zu unserem Hirn, unserem Denken, ‚Dark Patterns‘ und was ein Lernspiel im Vergleich zu anderen Spielen zusätzlich benötigt.
First the basics! Our human brain is wonderful but:
Perception is subjective
Attention is scarce
Memory is fallible
Because of this, we can be fooled very easily. (The internet is full of videos where this is shown over and over again. Or think of optical illusions!)
It is very important for designers to be aware of our brain limitations. For example, they cannot overuse our attention span. They cannot assume that we will see something while we are focussed on something else. And so on.
In UX Design two main topics are important: Usability and Engage-ability.
Regarding usability, of the seven topics Celia Hodent identified two are the most important ones:
Signs & Feedback
Form Follows Function
Error Prevention / Recovery
The motto of game design on usability is: Where is the challenge? Make everything else as simple as possible!
Make everything else as simple as possible! Really! If the challenge of the game is not spatial or memory training, help the players with additional cues (to find out where they are), provide mini-maps and more.
Thinking, Fast and Slow is a best-selling book published in 2011 by Nobel Memorial Prize in Economic Sciences laureate Daniel Kahneman.It was the 2012 winner of the National Academies Communication Award for best creative work that helps the public u…
[Fast thinking] works automatically and quickly, largely effortlessly, and without deliberate control.
[Slow thinking] is attention-controlled and carries out strenuous and complicated mental operations in orderly steps, which are controlled consciously.
To reach engagement on parts of the player, watch out for the following three areas:
Motivation is of primary importance and can be achieved through making the players feel competent, giving them autonomy, and creating a sense of progression. The content, goal or focus of the game should be relatable and have meaning.
Dark Patterns & Nudges
Sometimes players don’t do what the designers want them to do. In many games (and in many other contexts) dark patterns are used to trick or force the players in doing or buying something they don‘t necessarily want.
UX is against dark patterns because they are good for commercial reasons but not for the user.
Dark patterns make use of the scarcity of our attention and our many cognitive biases.
Examples of dark patterns:
FOMO (Fear of missing out)
Pay to win / Pay to remove friction
Lootboxes tied to monetization
As an example, Snapchat ruthlessly punishes disengagement through social obligations. It‘s scary.
Nudges are much better than dark patterns. Nudges also make us do things we may not do without a nudge but for our own good. Examples are seatbelts and smoking bans. They are (just) milder versions of dark patterns and very paternalistic! So, nudges should only be used based on consent of the community and population. See „Examples of engineering of the environment“ below for more examples and fun nudges.
Dark Patterns are tricks used in websites and apps that make you buy or sign up for things that you didn’t mean to. The purpose of this site is to spread awareness and to shame companies that use them.
Implicit Biases & Inclusion
Because of slow and fast thinking, because of our limited energy, because of our cognitive biases, we have blindspots. And: We are blind to our blindness. This is a very difficult position to be in. This is also the reason why we don’t think about diversity if it is not around us.
Group dynamics, specifically group pressure, —remember the Ash experiment— and cognitive dissonance relate to many biases. Bandwagon effect, groupthink, and herd behavior are biases related to group dynamics. „Three cognitive biases are components of dissonance theory. The bias that one does not have any biases, the bias that one is ‚better, kinder, smarter, more moral and nicer than average‘ and confirmation bias.“
It’s very uncomfortable for us to accept that we are biased (because we’re human). So, don’t point fingers; people don’t want to feel discomfort. It will backfire if you do!
In a study (not mentioned) an added reflection task made the results worse (no change in comparison to positive change). Reflection may be a problematic task especially if done in groups, and it is —if we’re honest— mostly uncomfortable for us.
If you want to change behavior,…
Engineering (of the environment; more fun, easier, etc.)
Examples of Engineering of the Environment
Checklists and standardized forms for the hiring process
Blind auditions for orchestra. (The scientists didn’t get it right immediately. They had to add a carpet to the setting because the sound of high heels was recognized.)
Engineering is the most efficient and the fastest!
Memory is fallible. Attention is scarce. Perception is subjective and is influenced by so many things (anchoring, language choice, group pressure,…). We have to accept that we are biased and find out what to do to change the system.
For an educational game, you need one more ingredient (than for a ’normal‘ game)! On top of usability and engage-ability, you need to have at least some kind of transfer of the learning content. It is a pity that most educational games may train skills but don’t offer transfer tasks.
Take-away message: Usable, motivational and transferable.
AI and Bias
Some people think that we should use AI (Artificial Intelligence) in many contexts, like law or education. They think, because AI is a machine, that it will not be biased. Let’s see about that!
Let’s translate the phrase ‚He is a doctor‘ and ‚She is a doctor‘ with Google Translate into Turkish:
O bir doktor
The Turkish language doesn’t have gender pronouns, and that is why both sentences are the same. In English, this sentence should be translated as „This/that person is a doctor“ to be more or less accurate. Now, some time ago, translating the Turkish sentence back into English with Google Translate you would get ‚He is a doctor‘ and if you did the same with ’nurse‘, you would get ‚She is a nurse.‘ That is a flagrant bias.
The point here is that AI uses human data. Human data is biased, and AI may well have the power to perpetuate and reinforce biases. Fortunately, some people are sensitive to the topic and correct biases. Nowadays, Google Translate will show you both translations. (Google hasn’t learned French yet. The sentence „C’est son pull“ translates into „It’s his sweater“ although it could just as well mean „It’s her sweater“.)
Take away message: Change the environment, design it!