Monday, December 04, 2017

More ideas for activating students, and: should we do that?

Today I had the second installment of the course Flipping the Classroom by Ine Noben of the University of Groningen. It gave me a lot more ideas for activating my students, but also stimulated some interesting thoughts about how we organize our education.
getting creative with lesson design


First, in terms of the ideas: we started with an interesting activity called "concept map", in which you draw a concept map about a topic (in this case the previous lecture), which was a good way to see what we remembered about the previous meeting. We then retrieved even more memories of the previous meeting by "crowdsourcing", in which we walked up to another person in the class, explained the maps to each other, and then exchanged them. When we received them, we scored them on a scale from one to five, and moved on to another person with the new map we got. We continued this a few times and got to see quite a few concept maps. Quite a fun activity!

Another thing we learnt was that it's important to think about how to engage *all* students. That made me realize that when I have some students give presentations, then the others typically disengage and start to play with their phones (or even enter the lecture late). I came up with the idea of asking students to draw a concept map of the presentation and hand it back to me as an 'exit ticket' at the end of class (added benefit: you get a reading of who is present in the class at the same time). Alternatively, I could ask students to write down comments, or things that are incorrect about the presentation, or I could ask them to come up with an exam question about the presentation. Lots of interesting options!

A third interesting activity is having students engage in a debate, where they are randomly assigned to diametrically opposite positions. They have to write a paper about the topic before the class (so they come prepared), and then a subset of students are chosen to debate in class. Of course you have to make sure that all students engage, so you could switch out students at random moment (I can imagine you can make this pretty fun with some weird bell to indicate it's switching time!).

Rink Hoekstra came to share his experiences with the flipped classroom, which he started with the critical note that the flipped classroom is really nothing new, just a repackaging of the older concept of "active learning." He had been experimenting with the flipped classroom (or active learning) and made the interesting observation that students tended to skip the lectures once he provided pre-recorded video lectures because they felt they already knew the information from the video lecture (so what's the point of coming to class?).

We also had some good discussions about whether these active learning forms are not too much like high school. And do they not play too much into the students' extrinsic motivation? On the other hand, how else do you get most students to engage from week 1? An interesting observation by another colleague in this respect was that students really like to see progress, so giving them some form of feedback is crucial.

Finally, we learnt about how video can be a cool tool in the classroom. I am not too excited about recording myself for video lectures, but two things can be very helpful. First, there is a tool called

Monday, November 27, 2017

Invisible scientists and the messiness of science: a dicsussion about open science

Today we hosted a visit of Rosanne Hertzberger with the Young Academy of Groningen. The theme of the afternoon was "open science", and I heard some soundbites that were too good not to share. Rosanne is a very passionate and courageous person who decided to pioneer being a freelance scientist. She started by saying that we as scientists at the university are unaware of how invisible we are. Why? Because we write lots of stuff, that gets put in journals behind a paywall, we talk about our science at conferences that only scientists go to, and we tend to not talk to the public (because we're too busy writing our papers). Good point. Sometimes I feel like the university considers me to be a little hamster running faster and faster in the paper-producing wheel.

She also talked about how science is the only profession where it is not possible to do it as an amateur--you have to be the equivalent of an olympic athlete, or not at all. But why do you have to fully dedicate yourself to science, why is it frowned upon if you have a significant other interest (in her case: writing articles, books and columns). I sometimes feel like that too: why do people think it is so crazy to be a serious amateur ballet dancer as well as a scientist? (see the inspiring quantum physicist Merritt Moore, or my own attempts at dancing and sciencing here). We had a discussion about the extent to which "everyone" can do science (cf. the citizen science movement), but Rosanne retorted that there are so many people who get a PhD and do not get the opportunity to continue in science because there are so few jobs. And another person said: are we even that special as scientists...

Probably one of the most important discussions revolved around the issue of invisibility. Rosanne said "it's very disappointing to see how little openness social media has brought to science. Why is live-tweeting a conference talk still a thing?" In other words, why do scientists not share their talks on youtube? (see for one example to the contrary Richard Morey's periscope broadcasts or the Lab Scribbles open lab notebook). Why don't scientists share their intermediate results on twitter? (while we do see pictures of their kids or cats). We discussed about the benefits of peer review, of which Rosanne posited that it holds us back, because there is too little communication between scientists in the heat of the process about things that work and things that don't. This means that progress is very slow, which is particularly problematic in the case of diseases and epidemics.





I think one other very important point was that in the communication to the public, and in our textbooks, science all looks very clean and shiny, while it is quite messy in the midst of it. Why don't we share our mess online? Rosanne: "it should be standard procedure to overshare. There is no such thing as TMI in science". There was some debate about how this may result in us all drowning in information, but Rosanne argued that a mechanism like reddit would easily allow us to manage this.

A final remark that I really liked was "aren't we reproducing each other's work all the time? It's called scooping." Good point. We ended also discussed quite a bit about incentives in science. Sharing results and materials takes quite a lot of time, for little reward. But this is what will make science progress much more. There is probably also a lot of things we can learn by talking to people from other fields, because in our discussion we learnt that for example in informatics producing reproducible code was standard practice, while sharing event questionnaires is not standard in psychology.

In short: a lot of work needs to be done, and sharing more of our science messiness, materials, intermediate data and so on would probably be a good idea. To be continued!

Monday, November 20, 2017

Activating students: some more tools

Today I took a course about flipping the classroom. Flipping the classroom refers to the idea that students listen to video lectures before class while the teacher helps them with exercises during class (instead of the lecture being spent delivering a lecture while students have to do their homework at home). The most important idea here is that flipping the classroom allows the students to be more active and allows the teacher to help the students where they need help most: to elucidate misunderstandings. In a course by Ine Noben I got some of the following ideas:
Another way to activate students practised for hundreds of years in Tibetan monasteries: requiring them to debate  in pairs while peers are looking on and with large physical gestures.
  1. Get everyone active with 1-2-4-all: students think about a question first alone, then share in pairs, then they share insights with a neighbouring pair and finally you discuss it in the big classroom. Another colleague mentioned that when students are forced to discuss in groups of 4, almost all of them will do some work (because there will always be some active students in the group), especially if you walk around to check on them.
  2. It is important to focus your lecture well, because as H. Simon said "a wealth of information creates a poverty of attention"
  3. A nice blog about peer instruction, with among others a nice series of blogs on why flipped classrooms fail. One thing that can make your flipped classroom fail is if you require students to do all kinds of work, but do not actually give feedback about this work. Another thing that can make your flipped classroom fail is when there are no consequences when students do not do the work, or when students are not clear on what their and your responsiblities are in the classroom. Useful case in point: it's helpful to spell out what you mean by "active participation" in the classroom. I will definitely try this out in my classroom.
  4. Nice platforms for creating online course content: FutureLearn and Google Classrooms. Both allow you to create very nice-looking course materials. Google classroom has the advantage it nicely integrates with googledocs for marking up assignments and things like that. Google classroom also makes it easy to grade with a rubric.
  5. A nice empirical investigation of the flipped classroom: article
  6. Tools for doing online voting: Socrative (allows you to also setup competitions in which teams try to answer as many quiz questions together as possible), mentimeter (allows you to easily vote on single questions and display the results interactively)
  7. A website with active activities: https://compass.itcilo.org as well as a book with game-like activities: Game Storming
  8. If you make quizzes for students to do before class, make sure you give useful feedback, e.g., "go back to section 11.3 of the book"
  9. Tools to make videos: for making screencasts: https://screencast-o-matic.com (e.g., to explain using some data analysis software), or to make cool animated videos/cartoons: https://www.powtoon.com/home/
  10. Another cool tool is "ticket to class"--make sure students do some activity beforehand to earn their ticket to class. One tool I like a lot is Perusall, in which students collaboratively read textbooks or articles. You could also use an exit ticket in which students can only exit the room if they hand in a piece of paper with the answer to a question such as: what is the question still remaining after this class? Name three things that can improve science? Etc (if you require students to add their name to this you immediately have a handy tool to keep attendance).
  11. A very effective tool to get students who are doing poorly back engaged is to find out who is not engaged with learning analytics (checking Blackboard for example) and then sending them a personal e-mail asking why they are not submitting assignments/not showing up etc.
  12. Nice database with exercises for physics, math etc: sowiso
  13. Tool to allow students to make collages of course-relevant information and comment on that (like a kind of instagram): padlet

Sunday, August 27, 2017

Pondering work and meditation

Some reflections from my stay at Ngari Institute of Buddhist Dialectics in Saboo, Ladakh.
Morning story: I woke up to run with the kids at 5:30. Since I wasn't sure where to go, I ran up to what I later found out to be the monk's quarters. Two of the institute dogs came with me. When there was nowhere to go, they guided me back below to where the kids were running. I joined some of them. Together we struggled up the hilll, panting for breath, looking at the beautiful views together, meeting yaks and people on our way. What a beautiful fresh way to start the day!\\
Contemplation:
From Andrew Harvey--''A journey in Ladakh'': ``Those who reject the materialism of the West, who despise it and separate themselves from it, are in danger of refusing to look at it, they are in danger of not being responsible to the facts of life as it is lived, and must be lived, now. We must find a way to work within the world, within science, within industry, even within politics; we cannot simply pretend a superiority to those things, for they are the forces that largely shape mankind. To work within the world we will have to be strong, and in the world our inner strengths will be greatly tested. But that is good. That will dissolve any pride we may have, any sense of virtuous invulnerability. It will take away from us any sense that we are "special'', that we deserve "special treatment'', that we are "unique.''
My continuous struggle is to figure out how to be living a "vita contemplativa.'' What does it mean to be a scientist and yet to also live a spiritual life such that the life and the science are not wasted, but are in fact of benefit to both myself and others. It seems from this writing that what is truly crucial is humility: to just work without expecting anything in return, without any recognition. And also, to drop any thought of being special but just focus on being of help. It is difficult to really live this, because in the West and especially in a career in a competitive profession we are conditioned to continually try to prove we have the best and we deserve recognition. So how can we resist that? Maybe one way would be to contemplate again and again on how we are interdependent with everything. Everything we do cannot be done without the kind help of many others (if only for the food we eat, the electricity we use, and so many more things).
Another helpful quote from the same book: "Be quietly detached from what you do and dedicate it to the good of all created beings, and you will be safe from disillusion or vanity.'' Every time when I go on retreat I realise how important it is to dedicate time in silence. Even just being here, I can see my automatic tendency to ditch meditation in favor of "something useful''--typically processing some information like reading a paper. It is hard sometimes to see the true value of meditation, yet this is the only way we can remain detached from what we do and put it into perspective. And only when we do that can we remain joyful in the face of difficulties, because we see there is so much else that is involved in all of our successes and failures.

Saturday, August 19, 2017

Science at the monastery gets real


I just returned from another study visit to Sera Jey Monastery in Bylakuppe, India. We are studying the effects of monastic debate and analytical meditation on emotion and cognition. Since this was already the fourth visit of the project, it was time to get real and get down on scientific rigour. In our EEG study, instead of just exploring different types of debate, we now developed a procedure in which each pair of debaters debated the same topic (a text on bodhicitta), got some chance to refresh their memory before the debate by studying the text for 15 minutes, and we used a standard classification for the triggers that the observing monks were using to score the debate. We even asked our observers to give the debates a grade, so we can in the future see whether the quality of the debate is related to some patterns of brain activity. In addition, the most interesting new feature of our EEG studies was more related to the frequent power outages: we bought a big car battery to run our EEG system off of!
We also took major strides in standardizing the behavioral tasks that we have been running by filming one of the monks explaining it while demonstrating on a tablet, and then showing this same video to all of our participants. The video demonstrations nicely combine standardization of explanation with a hands-on demonstration.
Monks pouring over a computer running JASP in stats class


In addition to spending time on standardizing experiments, we also spent quite a bit of time making predictions with the monks. This was a significant challenge, because obviously monks do not have the same space of possibilities in their heads that we Western scientists do (e.g., things either differ in their magnitude or there is a linear or non-linear relation between them). The monks found it a challenge to make predictions--maybe because guessing is not really encouraged in monastic debate you are drilled to be absolutely certain of what you are talking about (and in predictions you can never be). Nevertheless, we managed to get some predictions, and at least some of the EEG predictions were actually borne out! This is always a major happy moment for a scientist.

monks getting ready for EEG
Of course predictions are not always borne out, and we are also still sorting through a lot of confusing data that we still have to make sense of. Actually, the hard part of doing psychological science is that when you present a person with a task, quite often do they behave in quite a different way than we expected. This is mostly because the tasks we use to learn about the mind are really mostly geared towards Western college students (see this paper for a great discussion of that issue). As we slowly see all these interpretations of the tasks happen, we develop more appropriate instructions, and hopefully in the future also new tasks that are made more for our target population. As a first step in preparing for this, we held a methods and statistics class, which was actually met with tremendous enthusiasm: almost the whole monastic core team showed up voluntarily for this class on their free day! We had a lot of fun talking about t-tests, anovas and different kinds of variables, and we even played around with Bayes Factors in JASP!

This trip also was one of lots and lots of discussions. Actually one of the things that became obvious to me this time around is that the most insightful discussions actually happen when you are working one-on-one, not when having a large group discussion. For example, I spent a good amount of time sitting with my monk-colleagues to translate the debates (well, they translated, I wrote down the translations). In the course of this process I learnt a lot of tricks that happen while debating, such as interpreting a question differently when you do not know the answer to this question.
behavioural testing in action

This time we also met for the first time some Western monks studying at Sera Jey. Both with them, and with some members of our monastic collaborator team who studied in the West, I had some really interesting conversations about how monastic university training differs from Western university training. One thing that differs is the extent to which it actually informs how one practises and lives one's life. In addition, the debate training is a tool that is very confrontational: if you do not know something in great detail then there is no place to hide. This has as a result that you learn to really understand things in depth, but probably also that you build up quite an emotional resilience to being continually challenged. In short, it was a very illuminating visit, and such a precious chance to get to hang out in the peaceful monastery environment and the amazing group of monastic collaborators!
Last but not least: our study was featured in the Times of India!

Sunday, August 13, 2017

Where meditation meets reasoning: analytical meditation


Over the course of the last two years or so I have been studying, with several American colleagues, the practices of monastic debate and analytical meditation. As I am writing this I am once again in India for that study. It is a tremendous gift to be able to spend time in India working with a fantastic group of monks in the context of my work. During this visit, we had a short panel at the monastery on analytical meditation in which I shared some words about how we measure the brain with EEG, but most interestingly, two very bright monastic scholars shared textual and practical information about analytical meditation and debate. To ensure that I do not forget it, I decided to share it here on my blog (doing my best not to misrepresent what I have heard).

While analytical meditation (Tib. che gom) can be traced back to the historical Buddha (described for example in the King of Concentration sutra), and even Hindu saints before that time, it really became popular with the Buddhist saint Tsongkhapa. Tsongkhapa was the founder of the Geluk school of Tibetan Buddhism which has a strong focus on study and reasoning. Apparently there is also the criticism from other schools in Tibetan Buddhism that say that analytical meditation is just fake meditation invented by Tsongkhapa. Analytical meditation is complemented by stabilizing meditation, in which the mind is placed on an object and tries to stay there without moving. This stabilizing meditation is more well-known in the West, where meditating on the breath is a quite popular component of many mindfulness courses and interventions. However, it is said that such calm abiding does not really help to transform suffering in the long term--it can only give calm in the short term. Analytical meditation seeks to investigate the true causes of phenomena and thereby can lead to wisdom and new insight into the nature of phenomena.

However, neither type of meditation can exist without the other ones. Without stabilizing meditation, the analytical meditation cannot really thoroughly accomplished, because the mind is just too wild. Without analytical meditation, stabilizing meditation is just a brief respite from our crazy monkey mind (if we manage to get it quiet). Also interesting: in this tradition, meditation is referred to as familiarization (see also Dreyfus (2015) for an excellent discussion)--meditation is becoming thoroughly familiar with its object (such as the breath) by bringing your attention to it again and again.


Analytical and stabilizing meditation differ on various dimensions. As I mentioned above, the results of analytical meditation are more stable than the results of stabilizing meditation. While stabilizing meditation is only practised individually, analytical meditation can also be practised in smaller or larger groups, such as in the debates that we have been recording in the lab. While in stabilizing meditation, the body should remain still, in analytical meditation, it can also move (as it does in monastic debate).

This movement dimension is also the feature of analytical meditation that is fascinating to me, given my experience in dance. It seems like a genius way to make meditation palatable to young men in a monastery that have lots of physical energy: meditation in action! Analytical meditation is characterized by a continuous questioning of the topic at hand, looking at it from all directions and asking "why" and "how"? These questions then allow the practitioner to become more familiar with the topic at hand (traditional topics include concepts such as impermanence and interdependence) by thoroughly investigating it. Debating in the physical way that is used in the monastery (see this clip for an example makes it more interesting than just sitting down. In addition, the monks say that standing makes your thinking quicker and more clear. It brings all the senses together. Through a repeated investigation of concepts like impermanence, but also negative emotions like anger, slowly your mental patterns start to change, such that eventually thoughts of impermanence or patience come up more automatically in daily life, and in situations where you are about to become angry.

It seems to me that analytical meditation is worthy of more attention by contemplative neuroscientists. We have begun to do the first EEG studies and behavioral experiments. This surely is a slow process, frought with dangers of misunderstanding, but I think it is well worth our while. It is important not only because of potential applications in education or in therapeutic interventions to manage maladaptive thought patterns, but surely also because there is so much interest in science in the monastic community as well. I hope to be able to share some preliminary results in this space in the near future.

Monday, July 10, 2017

What I learnt about research on human trust

Last week I went to the Air Force Academy in Colorado Springs, United States to learn about research that is being done on trust. Mostly for the benefit of my future self, I will make an attempt at summarizing what I learnt about this somewhat foreign (to me) area of research. Trust is actually measured in lots of different ways, ranging from tightly controlled lab conditions to the messiness of the real world and foreign cultures. Trust models come larger from Roger Mayer. Fundamental components of trust appear to be ability, benevolence and integrity. In other words, you trust someone when you believe they can do things (ability), when you think they are meaing well (benevolence) and when you believe they act with integrity. Trust is most crucial in situations of risk, and when you are together with someone you trust, you are more willing to take risks in this relationship. Mei-Hua Lin discussed that trust depends on the amount of interaction you have had with a person, the similarity, affect, status, as well as situational factors. Mayer mentioned an interesting experiment to measure trust in a person, is to ask people how likely they would give ths person a project that is important to them when you cannot monitor them. Across the world, the integrity dimension appears to be the most important predictor of trust. Although mostly trust is considered to be positive, Alan Wagner is studying situations in which people overtrust. Most frequently people use Mayer's questionnaire for measuring trust, but another possibility is Rotter's Interpersonal Trust Questionnaire.


Trust in the laboratory can be related to confidence. It has been known for some time that confident testimony has greater influence, especially when it comes from people that also calibrate their confidence to their probability of being correct (Tenney et al., 2007). As such, you can examine trust in the laboratory by looking at how people take the advice of advisor that vary in how confident their advice is (see some cool new work by Yeung and Shea). It is apparently even possible to create computer models of trust, which update trust in an opponent on the basis of previous experiences (Juvinaet al., 2015). One interesting context in which these models were used were in peer-assisted learning of paired associates, in which your partner can inform your answers to the paired associates. In a slightly less cognitive lab setting, trust can be assessed by looking at people's facial expressions as they perform a task collaboratively (Social BART task). Even more, humans can extract trust from body odors, although this effect is modulated by gender. Extraction of social information from smell is also disrupted in people suffering from autism spectrum disorder.

Another dimension of trust occurs in teams of humans and robots collaborating. Antonio Chella thinks about whether recovery of trust can occur when we let a robot say "sorry". You can also look at how humans trust automation (e.g., in a factory) and look how often they notice failures of this automation, such as in the AF-MATB task. Apparently errors by the automated system can even elicit an error-related negativity ("oERN"). As the machine/factory makes more errors, people evidently trust it less. So in fact the reliability of one artificial agent affects how reliable we think another agent is: trust calibration.

On the other hand, do humans consider machines in the same ways as other humans? Jonathan Gratch looks at what aspects of robot behavior make us treat the robots like humans vs machines. Appararently the relevant dimensions are a sense of agency and displays of emotion--together he calls that mind perception. Humans treat robots unfairly and exhibit different emotions when they feel they are just machines. When you add emotions to the robot, people start to treat it more human-like. Apparently you can even decode from human brain activity whether people think they are dealing with humans versus machines. Also gaze is an important cue that humans use to decide whether to trust a robot. Angelo Cangelosi uses investment games to study how much people trust robots, and observed that people invest more in nice than in nasty naos. Amazingly enough, even rats prefer helpful robots over non-helpful robots! Also team interactions can be modelled with ACT-R, as Chris Myers' work on synthetic team mates shows.

Slightly less related to trust, but more to influence was work from Matt Lieberman, who showed that activity in the mPFC could predict behavior change in many contexts such as smoking cessation, wearing suncreen and more. Now what happens between two people are they are succesfully influenced? In experiments at Mount Jordan, Matt Lieberman showed that people's brains are more synchronized when they are watching a video together and are engaged and share a common reality. Also synchrony in speech (speech entrainment) can create social connectedness, because it is associated with increased positive feelings. However, this is not a simple phenomenon, because apparently it's not just more entrainment is better; rather, more variation in entrainment is better. The amount of speech entrainment seems to even affect whether people take advice from an avatar, although that is again a messy process. Less biological ways to measure connectedness include a questionnaire of social presence, which Kerstin Daubenhahn found to be sensitive to whether robots synchronized to the interaction with humans or not.

Other very interesting work by Clara Pretus looked at what is different in the brains of people who are wlling to fight and die for sacred values compared to people who don't. The main difference seemed to be less reliance on the dorsolateral prefrontal cortex for making these kinds of decisions. On a more positive note, very interesting work by Daniel Fessler showed how watching brief videos of prosocial behavior promotes real-world prosocial behavior (donations). The emotion of elevation appeared to be driving this real-world behavior. An important determinant in video content appeared to be reciprocation between the actors. Other happy news is a study by Adam Cohen who showed that when you ask people what kind of fictitious characters they would friend on Facebook, they trust Muslims and Christians equally, and the people they find most trustworthy are those who engage in costly religious practices (such as adhering to a kosher diet).

On a larger scale influence can be measured on twitter. People such as Vlad Barash have been developing network methods to study social contagion on this social media platform. Tim Weninger showed that social rating systems have a huge influence on how much other people like images/posts: to the extent that people are very poor at predicting what image will be more popular on social media, and popularity ratings are driven primarily by other users' ratings. In short, trust and influence are highly complex topics, on which very multidisciplinary research is done from many angles and perspectives.

Some useful tools I learnt about: