Blog parade “AI for Common Welfare?”

(Deutsche Version unten)

@algoethik is running a blog parade “AI for common welfare?”. I tried to respond to their questions.
Logo of @algoethik

  1. To what extent are ethical and Common Welfare aspects of AI already covered by the key points paper?
  2. Which relevant common welfare aspects are missing in the key points paper?
  3. A look outside: What have other countries done better in their strategies?
  4. What concrete measures should be included in the German AI strategy so that algorithms and AI are used for the benefit of society and for the benefit of all?

#1: The paper relentlessly mentions ethics and an ethics commission; it adds clauses like “taking into consideration…”, and so on. There are many honorable declarations of intent. I particularly like the “traceability” of algorithms. This is fine.

But (#2) I wonder if this intent can be sustained once the economic pressure grows and the jobs become scarce.

I do not believe that the change on the labour market only means that we will have different jobs (such that employees just need more education). We must not kid ourselves. The small number of new jobs for programmers and algorithm supervisors, or for managers with the much heralded new kind of soft-skills, cannot outweigh the jobs lost to the cognitive automation, IMHO. Understanding what AI can do now, we will no longer underestimate their competitive power on the labour market. (And there are even voices who say that today, humans themselves strive to become more machine-like — i.e., even easier to replace.)

The paper speaks of a “basis of justified trust and acceptability for users” (sectiion 3.9), and this needs, IMHO, a palpable guarantee (#4) and commitment for jobs. Not job security for existing jobs, but for sufficient jobs. And not just welfare (in a reservation where AI keep us benevolently as well-fed pets?), but sufficient gainful employmnet.

The paper sets the ambitious goal that Germany shall become a worldwide leading location for AI. If workers have a worldwide leading, justified, trust in their security, this may well happen, because then they will embrace the development rather than procrastinating and resisting it. Perhaps the time has come that an enforceable ‘right of work’ finally enters into the laws. For example, for every Euro of revenue, x Cents must be paid as wages — with these obligations being tradeable, of course. Otherwise, I think, Luddism will be inevitable, when workers feel like the Silesian weavers when the mechanical loom was introduced.

The horror scenario would be that algorithms are employed to administer the shortage of jobs. Any administration of shortages done by AI will be intolerable. Even if there was traceability of the algorithms. I also doubt that this traceability can really be achieved, except in simpler cases. After all, trial-and-error plays a big role in machine learning, doesn’t it? And if we hope that we can still supervise the algorithms, we must not forget the fatigue effect which inevitably occurs when 98 % of the AI decisions are reasonable. Perhaps a criterion for the admission of an algorithm would be that if it cannot be traced it must not administer shortages.

(Re question #3, I don’t know enough about others, but Finland seems to have thought about labour market aspects: see here.)


@algoethik veranstaltet eine Blogparade. Ich versuche, die Fragen zu beantworten:

  • Inwieweit werden ethische Gesichtspunkte und Gemeinwohl-Aspekte von KI durch das Eckpunktepapier bereits abgedeckt?
  • Welche relevanten Gemeinwohl-Aspekte fehlen im Eckpunktepapier?
  • Der Blick nach draußen: Was haben andere Länder in ihren Strategien besser gemacht?
  • Welche konkreten Maßnahmen sollten in der deutschen KI-Strategie auftauchen, damit Algorithmen und KI in den Dienst der Gesellschaft und zum Wohle aller eingesetzt werden?


(1.) Das Papier erwähnt unablässig Ethik und eine Ethikkommission; es enthält Klauseln wie “unter Berücksichtigung von…”, usw. Es gibt viele ehrenwerte Absichtsbekundungen. Besonders gefällt mir die “Nachvollziehbarkeit” von Algorithmen. Das ist gut.

Aber (2.) ich frage mich: können diese Absichten aufrecht erhalten werden, wenn der ökonomische Druck steigt und die Arbeitsplätze knapp werden?

Ich glaube nicht dass der Wandel auf dem Arbeitsmarkt nur bedeutet, dass wir andere Jobs haben werden (so dass Arbeitnehmer nur mehr Weiterbildung brauchen). Wir dürfen uns nichts vormachen. Die wenigen neuen Arbeitsplätze für Programmierer und Algorithmen-Supervisoren, oder für Manager mit der vielbeschworenen neuen Art von Soft-Skills, können nicht die Verluste ausgleichen, die durch die Kognitive Automation entstehen, denke ich. Wenn wir verstehen, zu was KI jetzt fähig ist, können wir ihre Wettbewerbsposition auf dem Arbeitsmarkt nicht mehr unterschätzen. (Und manche Stimmen sagen, dass der Mensch selbst ehrgeizig immer maschinenähnlicher wird, also noch leichter zu ersetzen.)

Das Papier spricht von einer “Grundlage für berechtigtes Vertrauen und Akzeptanz für Nutzerinnen und Nutzer” (Abschnitt 3.9), und diese braucht m.E. eine greifbare, konkrete Garantie (4.) für Arbeitsplätze. Keine Garantie für die derzeitigen Stellen, aber für ausreichende Stellen. Und nicht nur Gemeinwohl im Sinne von Wohlfahrt (in einem Reservat, wo uns die gutwilligen KIs halten wie wohlgenährte Haustiere?), sondern ausreichend Erwerbsarbeit.

Das Papier setzt sich das ehrgeizige Ziel, dass Deutschland der weltweit führende Standort für KI werden soll. Wenn die Arbeitnehmer ein weltweit führendes, berechtigtes Vertrauen in ihre Sicherheit haben, kann das Ziel durchaus realistisch werden, denn dann können sie die Entwicklung bereitwillig annehmen, statt Verschleppug und Widerstand zu zeigen. Vielleicht ist nun die Zeit gekommen, dass letztendlich ein einklagbares “Recht auf Arbeit” in die Gesetzgebung einziehen muss. Etwa, von jedem Euro Umsatz müssen x Cent als Löhne aufgewendet werden — wobei diese Obligationen natürlich gehandelt werden können. Andernfalls, glaube ich, wird zwangsläufig eine Maschinenfeindlichkeit entstehen, wenn sich die Arbeitnehmer fühlen wie die schlesischen Weber, als der mechanische Webstuhl eingeführt wurde.

Das Horrorszenario wäre, dass Algorithmen die Mangelverwaltung für Arbeitsplätze übernehmen. Jede Mangelverwaltung durch KI wäre unerträglich. Sogar mit Nachvollziehbarkeit der Algorithmen. Ich bezweifle auch dass diese Nachvollziehbarkeit wirklich erreicht werden kann, außer in ganz einfachen Fällen. Schließlich spielt Trial-and-Error doch eine große Rolle baim maschinellen Lernen? Und wenn wir hoffen, dass wir die Algorithmen ja noch überwachen könnten, dürfen wir nicht den Ermüdungseffekt vergessen, der sich zwangsläufig einstellt wenn 98 % der KI-Entscheidungen vernünftig sind. Vielleicht wäre es ein Kriterium für die Zulassung eines Algorithmus, dass er keine Mangelverwaltung betreiben darf wenn er nicht nachvollziehbar ist.

(Zu 3. weiß ich zu wenig über andere, aber Finnland scheint schon über Aspekte des Arbeitsmarktes nachzudenken, siehe hier.)


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Cmaps and the “Split Attention Effect”

A big benefit of Concept Maps is that similar concepts are spatially close to each other — even those that are not explicitly connected by lines, become coherent by the gestalt principles. But what if you need more text to explain your ideas, such that the closeness gets lost? As Stephen Downes recently observed about concept maps:

“they’re the sort of thing that I think has never really made the transition to digital media. I think they just need bigger screens.”

It is hard to swallow that despite all the urge for digitalization, exactly this tool is left behind which might so optimally support networked thinking.

It seems that instructional designers traditionally shy at the “Split Attention Effect” that was described in 1992 by Chandler and Sweller. Which says that the cognitive load is increased if an annotation is not immediately next to the item it refers to.

I wonder if this is still as true as it was 1992 in a paper world, where the annotations had to be found somewhere in the linear text. Today, it is possible to catch annotations with an eye saccade movement if it appears always at the same location — such as the preview pane in the “coordinated views” technique used by ordinary email clients.

An eye saccade works extremely fast and effortless because the jump is ballistic (like a missile), i.e. the target fixation is determined at the start and it cannot be changed later (I learned this from S. P. Ballstaedt, on p. 20 of his German lecture notes).

In my experience, this works much better than a popup annotation which is commonly used as the digital equivalent of the callouts bubble in a diagram of the paper era.

Now this is the effect that is the basis of my own think tool — so I would love to hear your feedback!

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Guesses about wisdom

Recently, the term ‘wisdom’ caught my eye multiple times, so I tried to clarify for myself what it means to me (and so I’m extending my old DIK post of 2005 to DIKW).

The term occurred in diverse contexts and senses:

  • as opposed to knowledge here on Mastodon,
  • as a gift which, like wealth and other powers, calls for moral accountability, here on Halfanhour,
  • as insight into the deepest structures and shapes of the universe, here by McGilchrist,
  • and as ‘wisdom of crowds’ here in a nice new ‘explorable explanation’.

1. In the Mastodon discussion, some definitions of wisdom seemed to me like just a higher level of knowledge, or like ‘meta’ knowledge, which I would rather call ‘critical literacies’: they depicted knowledge as simply knowing a googleable fact, and wisdom as something that is beyond that. But if this were true, everybody would have to be wise in the future — or else they would be displaced by artifical intelligences. Emergent knowledge based on long experience and intuition, will become more necessary but IMHO, it is not already wisdom.

Also, if knowledge cannot be transferred, or ‘told’, it is not already wisdom. Of course, wisdom cannot be told, but can it at least be taught? If teaching is Downes’s “to model and demonstrate”, this is certainly a useful prerequisite for developing wisdom, since we can sometimes recognize wisdom in other people even if we cannot describe it. But an important connotation of the term is, IMHO, that it takes a long time to develop wisdom. So, it is not for impatient teachers who expect an instant impact of their interventions.

In my understanding, wisdom grows very slowly, and it is often about what is really important, or actually, what is not important. For example, all the grumbling by the ‘wise’ wisenheimers who criticize everything but don’t offer an alternate solution — gradually becomes unimpressive.

2. By contrast, people who are wise enough to perceive their wisdom as a gift (and not as result of hard work that needs compensation), see their responsiblity.

3. McGilchrist, in turn, talks about the ‘path to wisdom’. And he likens it to how the hunter behaves (who “is careful, quiet, listening, attentive”). While this does not yet sound ‘left-brained’ to me, ‘Be a hunter of wisdom‘ (here) seems a bit misleading, because wisdom is not a target that can be shot, no more than happiness should be hunted for.

Furthermore, “insight into the deepest structures and shapes of the universe” is certainly a great thing, but it is so much entangled with fighting for truths about unknowable things, that I am not sure how important it should be to me. (Notwithstanding McGilchrist’s deep insight into the two modes of the brain, which are as important and fundamental to me as the flexors and extensors of the mind, i.e. relevant throughout everyday life.)

Another project of deep insight is currently undertaken by Dave Gray here (although he does not speak of ‘wisdom’ but of ‘level two’). His emphasis on ‘purpose’ can be seen as complemetary to the above ‘structures and shapes’, and while the latter might be seen as rather ‘right-brained’, the former is very ‘left-brained’. For me, wisdom seems more balanced.

A diagram showing 5 players, a button for launching the next match.

Screenshot of

4. In wisdom of crowds, finally, it is the aggregated knowledge of the many that creates the higher level, that cannot quickly be attained by a single human. And in a twin simulation here, it is the aggregation of many iterations of a trust game that leads a wise behavior — which, again, points to the long time that wisdom needs to be built.

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Myths, semi-myths etc.

I bought Clark Quinn’s new book about training myths, semi-myths and misconceptions, and I can whole-heartedly recommend this exciting, in-depth, clinical and precise work.

Continue reading

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Zooming is overrated

For the last release of my thought condensr tool, I had to think a lot about zooming. Besides text zooming — which was certainly important — the question was: Should I try to zoom the map, i.e., offer to edit the visual overview on different zoom levels?

Many people are enthusiastic about the ‘Big Picture’ attitude. Some even quote Dyson’s distinction between birds (who “fly high”) and frogs (who “live in the mud”).

A boss flying above a landscape, and some frogs sitting near the bottom.Photo credit: Flickr user youdid2, cc-by-nc-sa.

But I am sceptical, and I doubt that such a detached view of a ‘Big’ picture can be the necessary rich picture. It must leave out a lot, and usually there is a predetermined hierarchy that controls what to show and what to hide.

A geographical map, for example, needs some cartographic generalisation for zooming out: the labels of the big towns must be bigger than the others, and the smaller towns are gradually omitted, just as the smaller rivers and streets vanish. Otherwise there would be no orientation possible on the larger area. (This is why Google maps are becoming unusable: because the locations of the advertisers cause ever more clutter.) And this hierarchy may have distorted the rich picture already.

In my tool, there is no pre-existing hierarchy. On the contrary: it tries to facilitate an overview without premature hierarchy-building and pigeon-holing. And it has a different approach to handling the relationship between overview and detail: all the overview on the (visual) left pane, all details on the right (text) pane.

So, my new ‘bird’s eye view’ is just for making long-distance moves easier — not for withdrawn attitudes.

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Time: Back or forward?

Many people were confused about whether the clock would be switched forward or back today. This is a nice opportunity to visualize how unintuitive our abstract concepts can be, even if they seem so natural all year long. Why do we hesitate to accept that we have to forward “the time” ? Because it seems that in reality, it is being switched back: sunset is delayed.

A landscape with the sun being pushed back, and an overlaying clock-face showing the spring time switching.

It is a similar effect as the confusion about how a document on the screen should be moved when we want to proceed to the later sections: Scroll down, or pan or swipe upwards? We’ve got accustomed to ignore the reality of the paper, and use the scroll bar as a tool of abstraction. But now ever more user interfaces want it the other way around.

In McGilchrist’s terms, the abstraction tools such as the scroll bar or the clock, belong to the “emissary” mode of thinking, while the ‘real world’ such as the sun or the paper, belong to the “master”. (Actually, he talks about two hemispheres seeing the world differently. But for me, thinking of my brain as two separate “seeing” entities, is rather unintuitive, too. I prefer to think of their difference in much more mundane and elementary ways, as the flexors and extensors of the mind.)

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Mike Caulfield has a thoughtful blog post whose title alone is a nailing formula:

“Media Literacy Is About Where To Spend Your Trust. But You Have To Spend It Somewhere.”

This may seem to contradict Stephen Downes’s advice excerpted here:

“First rule: Trust no one. […] Don’t even trust me. Read this article sceptically. […] Did we see a tiger in the bush, or just black and orange stripes? It’s easy to jump to conclusions through bias and prejudice.

Take your time. Don’t jump to conclusions; evaluate the evidence.”

Tiger and magnifier

Picture credit (tiger): Bjørn Christian Tørrissen, CC-BY-SA

I think there is no contradiction, just another example of how our limited time and resources prohibit too much double-checking.

I like Caulfield’s term of ‘spending’ because this hints at the idea that trust is not (only) an idealistic concept from removed dreamers or verbose humanities scholars, but it can even be an economic idea: in our knowledge economy, it saves resources if I can trust someone’s information or judgment, rather than fetching external evidence. Or if a superior trusts me (rather than trying to check everything on his own).

And there is so much more connected to the idea of trust.

Early social bookmarking and blogging networks helped not only guarantee the validity but also the relevance of the recommended posts — before the cloaca of the ‘stream’ generated such a mess that everyone is now dependant on the platforms’ patronizing algorithms, whether we trust them or not.

Also the topic of my last post (see also Jenny Mackness’ covering), pedagogies of harmony and hope, which derived from a discussion on pedagogy of small and slow, can be related to trust which is, IMHO, an important ingredient of the described settings.

And finally, trust is distinctively human and cannot be learned by robots, since it grows from the early gaze ‘conversations’ where a baby learns about the world through the eyes of their mother (see here).

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Expectations make the difference

In a discussion about the ‘Pedagogy of Harmony’, Stephen Downes and Laura Ritchie addressed something that highlights the importance of expectations.

“I think that learning is the process of adjusting our expectations to align with experience so we are not taken by surprise and thrown off balance by what comes next.” (Downes, December 13, 2017)

Depending on what usually comes next, the very same event may be experienced in very different ways.

This can also be beautifully demonstrated with musical chords. While Laura (as a music expert) has much more to say about this and draws much wider connections, for me (as an absolute amateur) already a small example was very impressing:

When a chord with a ‘nonharmonic tone’ is played out of context, it sounds awful, but when we hear it as a ‘passing tone’ or as a ‘neighbor tone’, we don’t notice the dissonance — because we expect that it will immediately be resolved.



Thanks Laura for the explanation and for the link to Tim Poulin’s video whose intervals I used for my smaller example.

The role of expectations was even more fascinating for me since Downes’s recent writing about the brain as a ‘prediction machine’ (here and here) and the short-term memory’s role of making temporal perceptions similar to spatial perceptions (here and here).


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Stephen Downes’s big article “Consciousness” is an incredibly rich resource. I have not yet understood everything, but I need to organize my notes. Inspired by Heylighen’s glossary which can be organized into a nice picture, I tried to arrange some quotations (and a bit of glue text in italics) in a similar way, see below.

The greatest takeaway so far was the explanation of the mysterious ‘suddenness’ through recognition, see the last entry of my list.


“Consciousness seems to be mysterious to most people.” (01)

Absolute qualitative difference:

It is difficult “‘to explain away an absolute qualitative difference — such as that between third-person physical events and first-person consciousness'” (19, quoting Hart) This contributes to the mysteriousnness.

First person vantage:

“what might be called the ‘first person vantage‘ is pretty much an irreducible. It is not something I derive or infer from other things; it is something of which I have an immediate awareness. … ‘willing to deny … the actual existence, of the first-person vantage.’ … seems to fly in the face of our everyday experience.” (28) This difference from a Third Person view seems to be an Absolute qualitative difference.


An outstanding example of the First Person Vantage is the following: “There is a notion of what it feels like to perceive something. The phenomenon of pain offers a great example. When we are in pain, it hurts, but when we observe someone else in pain, no matter how closely, it does not hurt (though the activity of mirror neurons may make us flinch a little). So clearly there is something different about the subjective experience of pain that is not observable as the physical experience of pain. These subjective experiences … are known as qualia.” (13)

The ‘other’:

“There are two senses of ‘intentionality'” … ” All of these focus on the relation between ourselves and the ‘other’.” (15) Which is an Absolute qualitative difference


“First, there is intensionality, which is the ‘aboutness’ of our thoughts.” (15). “the ‘aboutness‘ of something from the inner or mental state seems to require, or at the very least, presuppose, an outer or external state” (23) “All of these [senses of intentionality] focus on the relation between ourselves and the ‘other’“. (15)

Outside vs. Inside:

First person vantage and interactions with ‘The other’ have accustomed us to a seemingly absolute qualitative difference between Outside and Inside.

Objective pull:

“The supposition that mental states (or representations) are governed by the same principles as physical states is what Pylyshyn calls ‘the objective pull‘, ‘the tendency to view the cognitive process in terms of properties of the represented objects'” (17).
I think, a similar tendency or habituation may lead us to try and view our consciousness too much like an outside object, with our usual approach of distancing, isolating, fixing, aboutness and representation (which McGilchrist calls the ’emissary’) ?


“Second, there is intentionality, which is understood in the common sense of our ‘intending‘ to do something.” (23) “All of these [senses of intentionality] focus on the relation between ourselves and the ‘other’“. (15)

Distinctively human

Whatdistinguishes humans from rocks, plants and lizards” (19), and is it an Absolute qualitative difference ?

Free will:

“In philosophy, and in particular in the context of the problem of consciousness, it [intentionality] has to do with the idea of free will versus determinism.” (15) Free will also seems like distinctively human.


“Humans speak – and think – in language. This might be one of the more remarkable stages of evolution. It is certainly one that distinguishes humans from rocks, plants and lizards.” (21)


“‘For Dennett, language must have arisen out of social practices of communication, rooted in basic animal gestures and sounds in an initially accidental association with features of the environment. Only afterward could these elements have become words, spreading and combining and developing into complex structures of reference.'” (21, quoting Hart)


“[S]emantics has to do with what we call the ‘aboutness‘ of a word, sentence or sequence of sentences”. (23) Words may refer to the outside, physical world.

Physical vs. Non-physical:

References (words, thoughts) to the outside physical world let the Outside vs. Inside difference appear as a difference between a Physical and a Non-physical realm. Not everybody realizes that “there is not, in human nature, a separate mental realm that reasons abstractly about the physical realm.” (06)


Concepts are often viewed as a non-physical representation of something in the physical world. But: “Our thoughts about objects are not representations of the external world, they are not inferred from experience, they are sensations of the external world (which J.J. Gibson would call direct perception), and are experienced directly.” (03)


(Ideas expressed by words)


“There’s a large body of thought that views not just ideas but other content such as ‘concepts‘ and ‘information’ as irreducibly and necessarily non-physical.” (25) And a concept is viewed as a non-physical representation of something from the physical world. “In truth, there is nothing more mysterious about ideas, concepts and information than there is about categories (and, arguably, ideas, concepts and information are no more than the modern instantiation of categories).” (25)


“We [humans] didn’t suddenly come into being, consciousness didn’t suddenly come into being, and nor either does an idea in our head suddenly come into being.” (11) “The argument that there is some mystical non-natural aspect to languages is rapidly being proven false in the domain of natural language processing today.” (22) But the appearance of human competencies, language and ideas seems sudden and mystical. Like an “‘evolutionary saltation between pre-linguistic and linguistic abilities'” (21, quoting Hart) , like “evolutionary short cuts such as an innate capacity for language” (21) , like a “‘gap’ in evolutionary history” (11) , like “‘a discontinuity'” “‘between mere accidental associations and intentional signs'” (24, quoting Hart).

Recognition and Emergence:

“There are two ways of talking about ’emergent results’ … One way is to think of it as an outcome. … The other way of thinking of emergent is to see it as a pattern. Mess around with some ingredients and eventually they take the form of something you recognize as a chocolate cake. Or evolve from one form of biological life to another to another and eventually you end up with something you recognize as a rabbit. That’s what I think Dennett means. It’s important to understand this distinction, I think, because it helps us understand the ‘suddenness’ of the emergence of language (or consciousness, or any of the other phenomena we are discussing). When you are manipulating a pattern of entities, order may ‘suddenly’ appear out of chaos, but what changed suddenly was not the pattern of entities but rather our perception of them.” (12)

The numbers refer to the sections of the article:

01 Consciousness
11 Suddenness
15 Intentionality Again
17 Rationality
19 Absolute Qualitative Difference
21 Language
22 Grammatical Constraints and Powers
23 Semantics, Again
24 Conventions and Physicality
25 Memes
28 The First-Person Vantage

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Reflecting or objectives?

In the final week of the #OpenEdMOOC, I learned some connections that I had not been aware of: How openness is also related to learning analytics and algorithms. I had been familiar with the idea that algorithms must be transparent (mainly via K. Zweig and her and I participated in the ‘data donation’ that took place before our federal election in September and attempted to get this transparency. But I had not thought about how companies would be tempted to abuse student data when they are trying to sell their ‘secret sauce’ of learning — although I had been skeptical against such recipes before.

At least now, this MOOC paid off for me, and it was the first one after a long time that I did not drop out before the last week. So I want to share what I noticed about my own learning and motivation and reluctance.

There were elements that motivated me to reflect and engage, and there were elements that put me off. The latter ones often included a task, or an objective, or the big final project, and I was surprised about myself how often the edX platform with its rigid goal-directed framing, increased my reluctance to ‘obey’. For example, the ‘prompts’, the ‘due dates’, the ‘next’ button, the ‘activities’, and in particular the size of the ‘project’: a 1 hour lesson. (I did not mind writing the three little essays in CCK08 despite I was not a for-credit learner because this felt like just the right size for voluntary engagement.)

I don’t doubt that such tight pacing, or ‘lock-step’ walkthrough, across a wide field of content might be useful for some at-risk learners. But I think many adult learners do not like such a tight prescriptive style, and for workplace learning such formal structures are even more unpopular.

But even worse: I noticed that for me, such MOOC ‘objectives’ (“Detail how…”, “Describe how…”) actually inhibit reflections in the sense of: What struck me as susprising or salient or resonating?. Because, for the latter, a ‘broad vigilant attention’ is needed (sorry for borrowing once again from McGilchrist), while the guiding objectives switch off this kind of attention and turn over to a ‘narrow focus’ kind of attention, to follow the tip of the teacher’s pointer stick, so to speak. So, the well-meant suggestions for ‘activity’ may just put off from reflective activity — and maybe this is why reflecting is so unpopular among pressed students?

Image: adapted from Distant Shores Media/Sweet Publishing (under CC-BY-SA) and Rodin (Public Domain).

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