Study links student cheating to whether a course is popular or disliked

examWe already know that extrinsically motivated students (mainly those driven by grades and testing) are far more likely to cheat than those who are more intrinsically motivated. I bookmarked yet another example of this effect just the other day but there are hundreds if not thousands of research papers that confirm this in many different ways. And, as this article reaffirms, we already know that mastery learning approaches (that focus on supporting control, appropriate levels of challenge, and, ideally, social engagement) tend to make cheating far less likely, because they tend to better support intrinsic motivation. Hardly anyone cheats if they are doing stuff they love to do, unless some strong extrinsic force overrides it (like grades, rewards, punishments, hard-to-meet deadlines, etc). 

This research reveals another interesting facet of the problem that exactly accords with what self-determination theory would predict: that, whether or not the pedagogy is sensible (supportive of intrinsic motivation) or dumb (extrinsically driven), a student’s dislike of a course appears to predict an increased likelihood of cheating. This is pretty obvious when you think about it. If someone does not like a course then, by definition, they are not intrinsically motivated and, if they are still taking it despite that, the only motivation they can possibly have left is extrinsic.

The increased chances of cheating on disliked courses, whether or not mastery learning techniques are used, is completely unsurprising because it ain’t what you do, it’s the way that you do it. If mastery learning techniques are not working then it probably means that we are simply not using them very well. Most likely there is not enough support, or not enough learner control, or insufficient social engagement, or not enough/too much challenge, or there’s too much pressure, or something along those lines. It is actually much more difficult and usually far more time consuming to teach well using techniques that respect learner autonomy and individual needs than it is to follow the objectivist instructivist path, at least in an institutional environment that deeply embeds extrinsic motivation at its very core, so it is not surprising that it quite often fails.  It is also very possible that the problem is almost entirely due to the surrounding educational ecosystem. For instance if it is one that forces students down institutionally-determined paths whether or not they are ready, whether or not it matters to them, or if not enough time is allowed for it, or if the stakes for failure are high, then even well-designed courses with enthusiastic, supportive, skilled, well-informed, compassionate, unpressured teachers are not likely to help that much.

Some people will take a pragmatic lesson from this to look more carefully for cheating on courses that they know to be disliked. That’s not the solution. Others will look at those courses and try to find ways to make them more likeable. That’s much better. But really, once we have done that, we need to be wondering about why anyone would be taking a course that they dislike in the first place. And that points to a central problem with our educational systems and the tightly coupled teaching and accreditation that they embed deep in their bones. Given enough time, support, and skilled tuition, almost anyone can learn almost anything, and love doing so. We live in a time of plenty, where there are usually countless resources, people, and methods to learn almost anything, in almost any practical way, so it makes no sense that people should still be forced to learn in ways that they dislike, at inappropriate times, and at an inappropriate pace. If they do, it is because (one way or another) we make them do so, and that’s the root of the problem. We – the educators and, above all, the educational system – are the cause of cheating, as much as we are the victims of it. And we are the ones that should fix it.

The original paywalled paper can be found here.

Address of the bookmark:

Originally posted at:

This was actually accepted for an IEEE conference and then published

I invite you to draw your own conclusions about this paywalled paper and the amount of quality control and editorial input that goes into IEEE publications nowadays. Here’s the abstract, which is one of the more coherent passages in the paper:

Abstract—The momentum contemplate evaluates the relationship among online social recreations and the e-learning utilization by look at the impact of social, subjective and teaching nearness on e-learning use between female understudies by method for playing on the web social diversions. This study utilizes an exploratory research plan, comfort test procedure. The outcomes propose that all scales are basically related with E- learning use. It is found that E-learning uses is emphatically tremendous and has a direct related with social nearness. The relationship between E-learning use and psychological nearness has a decidedly strong enormous connection; in like manner, the relationship between E-learning use and teaching nearness has an emphatically strong colossal connection. The disclosures inferred that the characteristic of online social amusements; both intellectual and teaching nearness impact E-learning utilization.

There’s not enough research about female understudies. I’m glad that someone is filling that gap. It’s well worth what otherwise appear to be the subscription fees IEEE is charging (US$33 in case you were wondering) . 

Address of the bookmark:

Originally posted at:

The NGDLE: We Are the Architects | EDUCAUSE

A nice overview of where the NGDLE concept was earlier this year. We really need to be thinking about this at AU because the LMS alone will not take us where we need to be. One of the nice things about this article is that it talks quite clearly about the current and future roles of existing LMSs, placing them quite neatly within the general ecosystem implied by the NGDLE.

The article calls me out on my prediction that the acronym would not catch on though, in my defence, I think it would have been way more popular with a better acronym! The diagram is particularly useful as a means to understand the general concept at, if not a glance, then at least pretty quickly…

ngdle overview

Address of the bookmark:

Originally posted at:

The return of the weblog – Ethical Tech

Blogs have evolved a bit over the past 20 years or so, and diversified. The always terrific Ben Werdmuller here makes the distinction between thinkpieces (what I tend to think of as vaguely equivalent to keynote presentations at a conference, less than a journal article, but carefully composed and intended as a ‘publication’) and weblogging (kind of what I am doing here when I bookmark interesting things I have been reading, or simply a diary of thoughts and observations). Among the surprisingly large number of good points that he makes in such a short post is that a weblog is best seen as a single evolving entity, not as a bunch of individual posts:

Blogging is distinct from journalism or formal writing: you jot down your thoughts and hit “publish”. And then you move on. There isn’t an editorial process, and mistakes are an accepted part of the game. It’s raw.

A consequence of this frequent, short posting is that the product isn’t a single post: it’s the weblog itself. Your website becomes a single stream of consciousness, where one post can build on another. The body of knowledge that develops is a reflection of your identity; a database of thoughts that you’ve put out into the world.

This is in contrast to a series of thinkpieces, which are individual articles that live by themselves. With a thinkpiece, you’re writing an editorial; with a blog, you’re writing the book of you, and how you think.

This is a good distinction. I also think that, especially in the posts of popular bloggers like Ben, the blog is also comprised of the comments, trackbacks, and pings that develop around it, as well as tweets, pins, curations, and connections made in other social media. Ideas evolve in the web of commentary and become part of the thing itself. The post is a catalyst and attractor, but it is only part of the whole, at least when it is popular enough to attract commentary.

This distributed and cooperative literary style can also be seen in other forms of interactive publication and dialogue – a Slashdot or Reddit thread, for instance, can sometimes be an incredibly rich source of knowledge, as can dialogue around a thinkpiece, or (less commonly) the comments section of online newspaper articles. What makes the latter less commonly edifying is that their social form tends to be that of the untarnished set, perhaps with a little human editorial work to weed out the more evil or stupid comments: basically, what matters is the topic, not the person. Untarnished sets are a magnet for trolls, and their impersonal nature that obscures the individual can lead to flaming, stupidity, and extremes of ill-informed opinion that crowd out the good stuff. Sites like Slashdot, StackExchange, and Reddit are also mostly set-based, but they use the crowd and an algorithm (a collective) to modulate the results, usually far more effectively than human editors, as well as to provide shape and structure to dialogues, so that dialogues become useful and informative. At least, they do when they work: none are close to perfect (though Slashdot, when used well, is closer than the rest because its algorithms and processes are far more evolved and far more complex, and individuals have far more control over the modulation) but the results can often be amazingly rich.

Blogs, though, tend to develop the social form of a network, with the blogger(s) at the centre. It’s a more intimate dialogue, more personal, yet also more public as they are almost always out in the open web, demanding no rituals of joining in order to participate, no membership, no commitment other than to the person writing the blog. Unlike dedicated social networks there is no exclusion, no pressure to engage, no ulterior motives of platforms trying to drive engagement, less trite phatic dialogue, more purpose, far greater ownership and control. There are plenty of exceptions that prove the rule and plenty of ways this egalitarian structure can be subverted (I have to clean out a lot of spam from my own blogs, for instance) but, as a tendency, it makes blogs still very relevant and valuable, and may go some way to explaining why around a quarter of all websites now run on WordPress, the archetypal blogging platform.

Address of the bookmark:

Originally posted at:

Instagram uses 'I will rape you' post as Facebook ad in latest algorithm mishap

Another in a long line of algorithm fails from the Facebook stable, this time from Instagram…

"I will rape you" post from Instagram used for advertising the service

This is a postcard from our future when AI and robots rule the planet. Intelligence without wisdom is a very dangerous thing. See my recent post on Amazon’s unnerving bomb-construction recommendations for some thoughts on this kind of problem, and how it relates to attempts by some researchers and developers to use learning analytics beyond its proper boundaries.


Address of the bookmark:

Original page

Infants make more attempts to achieve a goal when they see adults persist

A straightforward and briefly reported study that supports the rather obvious hypothesis that quite young (15-month-old) children can and do learn from observing adults, at least in the short term. The twist here is that adults in the study were deliberately trying to model an attitude (grit) more than a distinct behaviour, in an attempt to teach the kids to do the same.

It is fair to say that the researchers demonstrated to the kids that persevering with problems after initially failure can lead to desirable results, and that the kids appeared to be more inclined to do the same after watching adults doing so: this accords well with the title of the paper. I’m not sure that the adults adequately demonstrated grit, though. I don’t know about you, but I actually enjoy solving problems and positively relish the failures that teach me how to succeed. In fact, in many situations (programming, for example) I deliberately make things fail in order to understand how they do so, and that’s part of the fun, even though (and partly because) I may curse and fume when the process fails to enlighten me. Same for many commercially available puzzles, from Rubik’s Cubes to letter-sliding games. Seems to me that grit involves more than doing something enjoyable on the way to achieving some anticipated goal that matters to us. It’s often about doing unenjoyable things, sometimes for goals we don’t even find particularly interesting or worthwhile, often over a prolonged period. That’s not what was happening here. This is interesting, though, if only to confirm that really quite young kids are able to see others as beings like themselves, and to transfer the lessons of stories that they construct about what they perceive others to be doing into actions they then take themselves.

The brief timeframe of the study means that it doesn’t show whether this is how grit is actually learned over time.  The extent to which lessons persist depends on a great many things, including prior experience, repetition, who is repeating it, success in the short term, effectiveness of the attitude in overcoming meaningful challenges in the long term, social value of the attitude, current context, and counter-examples over time. Outside an experimental context we pick up attitudes and sentiments from kids as much as they do from us, from one another, and from the world at large. There are usually very many others around us who are all engaged in a rich reciprocal dance with us through which we collectively construct our various intersecting cultures and subcultures, including our attitudes and values. Also, life is seldom so neatly structured and categorized that a lesson can be so directly transferred from one context to another. At least, such cases are not the interesting ones. Though the experimenters tried to make the tasks a bit different, the study was really set up to highlight the similarities, and to lead to results that would please the children.  In real life, we usually need to connect one situation with another that is quite different, separated by time, and to choose between competing strategies to deal with it, often with others around us that are adopting different approaches, all of which will influence us. Often, we are not even particularly interested in the outcomes. It’s much harder to do experiments that reflect that reality. In fact, it’s probably impossible, at least without adopting the ethical precepts of Josef Mengele. The researchers laudably note a range of other limitations, including cultural differences, beliefs of children about adults, task specific issues, and so on, and make no extravagant claims that it can be generalized further. Indeed it cannot.

That said, this is good evidence for something that I believe is not a bad idea: that teachers (formal or otherwise) should act as they hope their students will act. A very large part of the role of a teacher is to model how people in their field (or society at large, in the case of younger kids) think and behave, to enact and demonstrate their approaches and attitudes,  perhaps more than to pass on the facts, skills, and technologies of their discipline, or to provide support for gaining such knowledge.

Bearing that in mind, while there is value in ‘grit’ and I don’t want to knock it too much, I think there are other attitudes that might matter a whole lot more, especially those that enable us to not just stick with stuff we don’t enjoy but to find pleasure and meaning in it. Passion is way more useful than grit, in the long run. Caring, too. Teachers that light fires in students’ hearts achieve way more than those that simply show them how to stick at things they hate.


Persistence, above and beyond IQ, is associated with long-term academic outcomes. To look at the effect of adult models on infants’ persistence, we conducted an experiment in which 15-month-olds were assigned to one of three conditions: an Effort condition in which they saw an adult try repeatedly, using various methods, to achieve each of two different goals; a No Effort condition in which the adult achieved the goals effortlessly; or a Baseline condition. Infants were then given a difficult, novel task. Across an initial study and two preregistered experiments (N = 262), infants in the Effort condition made more attempts to achieve the goal than did infants in the other conditions. Pedagogical cues modulated the effect. The results suggest that adult models causally affect infants’ persistence and that infants can generalize the value of persistence to novel tasks.

Address of the bookmark:

Original page

No, you aren't a 'visual' learner

It’s a damning indictment of our collective resistance to truth that the point of this article still has to be restated, yet again. Amazingly, 93% of the general public and 76% of educators still erroneously believe that we should be taught in ways that match our learning styles. I assume this is so in the US – unless things have changed recently, the percentages, for teachers at least, are even worse in some other countries where the idea has been pushed harder from the top down, such as the UK and Netherlands. To be quite clear: this belief is not supported by any compelling evidence at all.

The fact that it is false (or, at best, no more provable than, and just as likely as, astrology) doesn’t mean that designing for learning styles necessarily a terrible idea, inasmuch as it can encourage reflective practice on the part of teachers and can even result in quite useful outcomes. As the article puts it:

“If you’re trying to vary what you do in the classroom to respect different styles, variation in instruction is probably a good thing, anyway,” he says. But rather than formatting lessons differently for auditory, kinetic or visual learners, he and Macdonald suggest that teachers tweak their instruction based on content.

“I think it really depends on your objectives for the lesson,” Macdonald says. “Some types of content really lend themselves to visual presentation … if you’re teaching maps, that’s got to be visual. If you’re teaching music, those are [the] types of things that need to be auditory.

“But if your goal is to get a multifaceted exposure to certain content, it can be helpful to weave in all different types of modalities.”

That thinking about learning styles can be a useful design tool is a fair point, and one that I have often made myself (including in quite some detail in my first book), though it’s a happy side effect of a mistake, rather than a consequence of a good theory. Using star signs would probably work just as well.  I am not convinced that content should always lead design either: objectives-driven teaching is not the only fruit and, for some expansive subject areas and pedagogies, it is positively (positivistly?) harmful. But, notwithstanding its constraints and limitations, at least it is not based on a fiction.

There are many risks to using a false world model, even if it has some practical value or plausible results (pre-Copernican geocentric astronomy was better than Copernicus’s own theory at predicting movements of planets), not least of which being that it blinds us to real possibilities and leads us in worthless, wasteful, or even harmful directions. Even when the consequences include better teaching, it’s a terrible lesson to teach someone that they are a visual (or sensing, or whatever nonsense the particular theory suggests) learner. No they are not. They might have some habits, reinforced patterns, or preferences, sure. But that just means they need to try a bit harder to extend themselves and to learn to use some alternative approaches because they are definitely going to have to use them at some point when there’s no teacher in control of things but themselves, and nothing to fit their preferred style available. My learning style is and should be whatever the hell I need.

I’ve mentioned before that I believe a better (if less attractive) term would be ‘being-taught habits’ because one of the least savoury aspects of the whole learning styles gestalt is that it actually has little to do with learning, and everything to do with achieving better indoctrination; of asserting the power of the teacher (at least, it would if it worked). For that kind of thing, we’d learn more from the sciences and arts of the advertising industry than from any snake oil learning style theory. We might equally learn from preachers and religions: they are mostly pretty good at making people think and behave the way they wish.

There are other ways to gain the useful side-effects of designing for learning styles that do not rely on falsehoods, or that make no claims that they match reality one way or the other – de Bono’s Thinking Hats, for instance, or design-based research. And it doesn’t take much to make learning style theories less dumb. I am personally quite fond of Gordon Pask’s serialist/holist model, despite coming perilously close to a learning styles theory at times, because it describes a continuum of learning strategies, without suggesting too much (OK, fair enough, Pask slipped here and there) that such strategies be fixed, habitual, or generally preferred by particular learners.  They are simply perspectives we can choose as and when it is helpful to do so. However, if possible, when designing learning activities, we should use approaches that are based as much as we are able on how the world is, not how we think it should be. From that perspective, learning styles are a potentially dangerous and time-consuming dead end.

Address of the bookmark:

Original page

Amazon helps and teaches bomb makers

Amazon’s recommender algorithm works pretty well: if people start to gather together ingredients needed for making a thermite bomb, Amazon helpfully suggests other items that may be needed to make it, including hardware like ball bearings, switches, and battery cables. What a great teacher!

It is disturbing that this seems to imply that there are enough people ordering such things for the algorithm to recognize a pattern. However, it would seem remarkably dumb for a determined terrorist to leave such a (figuratively and literally) blazing trail behind them, so it is just as likely to be the result of a very slightly milder form of idiot, perhaps a few Trump voters playing in their backyards. It’s a bit worrying, though, that the ‘wisdom’ of the crowd might suggest uses of and improvements to some stupid kids’ already dangerous backyard experiments that could make them way more risky, and potentially deadly.

Building intelligent systems is not too hard, as long as the activity demanding intelligence can be isolated and kept within a limited context or problem domain. Computers can beat any human at Go, Chess, or Checkers. They can drive cars more safely and more efficiently than people (as long as there are not too many surprises or ethical dilemmas to overcome, and as long as no one tries deliberately to fool them). In conversation, as long as the human conversant keeps within a pre-specified realm of expertise, they can pass the Turing Test. They are even remarkably much better than humans at identifying, from a picture, whether someone is gay or not. But it is really hard to make them wise. This latest fracas is essentially a species of the same problem as that reported last week of Facebook offering adverts targeted at haters of Jews. It’s crowd-based intelligence, without the wisdom to discern the meaning and value of what the crowd (along with the algorithm) chooses. Crowds (more accurately, collectives) are never wise: they can be smart, they can be intelligent, they can be ignorant, they can be foolish, they can even (with a really smart algorithm to assist) be (or at least do) good; but they cannot be wise. Nor can AIs that use them.

Human wisdom is a result of growing up as a human being, with human needs, desires, and interests, in a human society, with all the complexity, purpose, meaning, and value that it entails. An AI that can even come close to that is at best decades away, and may never be possible, at least not at scale, because computers are not people: they will always be treated differently, and have different needs (there’s an interesting question to explore as to whether they can evolve a different kind of machine-oriented wisdom, but let’s not go there – SkyNet beckons!). We do need to be working on artificial wisdom, to complement artificial intelligence, but we are not even close yet. Right now, we need to be involving people in such things to a much greater extent: we need to build systems that informate, that enhance our capabilities as human beings, rather than that automate and diminish them. It might not be a bad idea, for instance, for Amazon’s algorithms to learn to report things like this to real human beings (though there are big risks of error, reinforcement of bias, and some fuzzy boundaries of acceptability that it is way too easy to cross) but it would definitely be a terrible idea for Amazon to preemptively automate prevention of such recommendations.

There are lessons here for those working in the field of learning analytics, especially those that are trying to take the results in order to automate the learning process, like Knewton and its kin. Learning, and that subset of learning that is addressed in the field of education in particular, is about living in a human society, integrating complex ideas, skills, values, and practices in a world full of other people, all of them unique and important. It’s not about learning to do, it’s about learning to be. Some parts of teaching can be automated, for sure, just as shopping for bomb parts can be automated. But those are not the parts that do the most good, and they should be part of a rich, social education, not of a closed, value-free system.

Address of the bookmark:

Original page


Update: it turns out that the algorithm was basing its recommendations on things used by science teachers and people that like to make homemade fireworks, so this is nothing like as sinister as it at first seemed. Nonetheless, the point still stands. Collective stupidity is just as probable as collective intelligence, possibly more so, and wisdom can never be expected from an algorithm, no matter how sophisticated.

Analytic thinking undermines religious belief while intelligence undermines social conservatism, study suggests

‘Suggests’ is the operative word in the title here. The title is a sensationalist interpretation of an inconclusive and careful study, and I don’t think this is what the authors of the study mean to say at all. Indeed, they express caution in numerous ways, noting small effect sizes, lack of proof of causality, large overlaps between groups, and many other reasons for extremely critical interpretation of the evidence:

“We would like to warn readers to resist the temptation to draw conclusions that suit their ideological worldviews,” Saribay told PsyPost. “One must not think in terms of profiles or categories of people and also not draw simple causal conclusions as our data do not speak to causality. Instead, it’s better to focus on how certain ideological tendencies may serve psychological needs, such as the need to simplify the world and conserve cognitive energy.”

This is suitably cautious and very much at odds with the title of the PsyPost article.

The study itself finds some confirmatory evidence that, in the US (and only in the US):

  •     Religion may be embedded more in Type 1 intuitions relative to politics.
  •     Processing liberal political arguments may require cognitive ability.
  •     Religious belief should be predicted uniquely by analytic cognitive style.
  •     Conservatism should be uniquely predicted by cognitive ability.

It is important to note, however, that ‘prediction’ in this instance has a very precise meaning of implying slightly increased odds of correlation between these factors, not that there is a causal connection one way or the other. The study simply adds a little more evidence to an already fairly substantial body of proof that cognitively challenged people, especially those more inclined to intuition than to reason (the two are statistically correlated), are somewhat more likely to be drawn both to religion and to right wing politics. Much as I would like it to imply the inverse – that intelligence and rationality are a cure for religion and right wing beliefs – there is absolutely nothing in this research to suggest that.

Part of the motivation for the study is the researchers’ observation of the growing antagonism to intelligence, expertise, evidence, and truth that is revealed in Trump’s victory, Brexit, ISIL, man-made climate change denial, and so on. While such evils are no doubt fuelled and sustained by (not to put too fine a point on it) stupid people in search of simple solutions to complex problems, it would be foolish (stupid, even) and highly inaccurate to suggest that all (or even a majority) of those exhibiting such attitudes and beliefs are stupid, or driven by intuition rather than reason, or both. As the study’s authors rightly observe, the value of this study is its contribution to understanding some of the complexity of the problem and should not be used to extrapolate exactly the same kind of simplified caricatures that cause it in the first place:

“…a more balanced understanding can only be reached via continued empirical research. Human beings may sometimes benefit from cognitive simplification of a complex and at times scary world of constant change and uncertainty. It does seem that certain aspects of religion and conservative ideology serve to deal with this, in slightly different ways. This is the direction that evidence points to thus far. However, researchers of course must resist this very need to simplify the world beyond a certain level.”

The original study can be found at

Address of the bookmark:

Original page

Highly praised children are more inclined to cheat

The title of this Alphr article is a little misleading because the point the article rightly makes is that it all depends on the type of praise given. It reports on research from the University of Toronto that confirms (yet again) what should be obvious: praising learners for who they are (‘you’re so smart’) is a really bad idea, while praising what they do (‘you did that well’) is not normally a bad idea. The issue, though, is essentially one of intrinsic vs extrinsic motivation. By praising the person for being a particular way you are positioning that as the purpose, rather than a side-effect, of the activity, and positioning yourself as the arbiter, so disempowering the learner. By praising the behaviour, you are offering useful feedback on performance that empowers the recipient to choose whether and how to do such things again, as well as supporting needs for relatedness (it shows you care) and competence (it helps them improve). Both forms of praise contribute to feelings of self-esteem, but only one supports intrinsic motivation. 

The nice twist in these particular studies (here and here) is that the researchers were looking at effects on morality. They found that ability praise (teling them they are smart) is very strongly correlated with a propensity to cheat. Exactly as theory would predict, kids who have been told that they are smart are significantly more likely to respond to the extrinsic motivation (the need to live up to expectations when given ability praise) by cheating, when given the opportunity. Interestingly, praising the behaviour (performance praise) has little or no effect on likelihood of cheating when compared with those given no praise at all: it is only when an expectation is set that the children are perceived as smart that cheating behaviour increases. It is also interesting, if tangential, that boys appeared to be way more likely to cheat than girls under all the conditions though, once primed by ability praise, girls were more likely to cheat than boys that had received no praise or performance praise.

The lesson is nothing like as simple as remembering to just praise the action, not the person. Praising behaviours can, when used badly, be just as disempowering as praising the person. For instance, while in some senses it might be possible to view grades as a kind of abbreviated praise (or punishment, which amounts to much the same thing) for a behaviour, there’s a critical difference: the fact that it will be graded is known in advance by the learner. This is compounded by the fact that the grade matters to them, often more than the performance of the activity itself. Thus, achieving the grade becomes the goal, not the consequence of the behaviour, and it reinforces the power of the grader to determine the behaviour of the learner, with a consequent loss of learner autonomy. That shift from intrinsic to extrinsic motivation is the big issue here, not the praise itself. There are lots of ways to give both performance praise and ability praise that are not coercive. They are only harmful when used to manipulate behaviour.

Address of the bookmark:

Categories Learning Tagged in , , , , , , , Leave a comment