Know thy students [...]

The overarching goal of teaching is not to deliver information to faceless crowds, but instead to cause learning to occur among enrolled students.4 Courses and classroom activities should be developed on the basis of helping students discover and construct knowledge, not on the basis of what the instructor wants to talk about.5 And importantly, to develop successful learning activities, instructors must have some insight into their students' relevant knowledge base, and they must also be sensitive to their students' sociocultural approaches to education.6 Otherwise, instructors risk more than just appearing "out of touch" — they risk developing ineffective educational experiences. Course planning involves predicting the effects of learning activities on a group of students, and to make successful predictions, we must have relevant knowledge about those whose behaviors we are trying to predict.7

For these reasons, experienced teachers advocate for instructors (particularly new instructors) to collect information about their students at the beginning of the semester, either by administering a questionnaire or by giving a short ungraded test that directly measures background knowledge.8 These efforts could help inform instructors about their students' interests, abilities, demographics, and skill sets, and ideally, the remainder of the course would be tailored to the general characteristics measured in this initial survey. (Source)


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5 points for teaching anything in the digital age [...]

5 points

  1. Be assistive
  2. Be connective
  3. Be interactive
  4. Be constructive
  5. Be reflective

These statistics are evidence that people are by nature connected learners. We learn through a process of inquiry that takes shape through social communication. It’s safe to say that humanity itself is a learning community; full of great teachers and great learners. (Source)

Education has been inadequately slow to move from conceptual frameworks that recognize digital age deficiencies in creating deep learning opportunities

Additionally, it is a reason that prototyping is an essential component of product development. In education, the new digital tools that we have available require the same process of innovative inquiry


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Mindlessly eating better [...]

Plate shapes and package sizes, lighting and layout, color and convenience: these are a few of hidden persuaders that can contribute to how much food a person eats. This review first posits that these environmental factors influence eating because they increase consumption norms and decrease consumption monitoring. Second, it suggests that simply increasing awareness and offering nutrition education will be disappointingly ineffective in changing mindless eating. Third, promising pilot results from the National Mindless Eating Challenge provide insights into helping move from mindless eating to mindlessly eating better. (Source)

It is less clear that consumers need more nutrition information than it is that they need better heuristics to help them develop a bias toward eating less and eating healthier.


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Good Python modules [...]

Most interesting modules


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Recognising excellent teaching [...]

Pointing to practices to be adopted and also a potential role for learning analytics to identify world-best practice

As an alternative to questionable instruments like student evaluations as the key indicator of quality, other indicators can be more systematically employed. Teaching is a profession, a domain of expertise, and should instead be determined, as is the case in other professions, by what the evidence says about quality. Progress in the learning sciences, in educational research and through scholarly evaluations is consistently providing meaningful advances in this evidence base. Excellent teaching needs to be determined and evaluated through expert review and recognition of world-leading practices that demonstrably enhance student thinking and understanding. Student perceptions of these practices are grossly ineffective for this purpose (Source)


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SELT surveys as the best indicator of quality teaching [...]

The great debate about the use of student experience surveys in higher education has again reared its ugly head. Merlin Crossley from UNSW recently pointed out, in a News Corp editorial, that although flawed, student experience surveys still provide the best indicator of teaching quality in higher education. While there is undoubtedly value in surveying students to determine their level of satisfaction, this argument misses the point when it comes to quality teaching. (Source)


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Freedom, power, planning [...]

With respect to the central concepts of political philosophy, namely the conceptual pair of power and freedom, Foucault’s bet was that people are likely to win more for freedom by declining to define in advance all the forms that freedom could possibly take. That means too refusing to latch on to static definitions of power. Only in following power everywhere that it operates does freedom have a good chance of flourishing. Only by analysing power in its multiplicity, as Foucault did, do we have a chance to mount a multiplicity of freedoms that would counter all the different ways in which power comes to define the limits of who we can be. (Source)

The irony of a philosophy that would define power once and for all is that it would thereby delimit the essence of freedom. Such a philosophy would make freedom absolutely unfree. Those who fear freedom’s unpredictability find Foucault too risky. But those who are unwilling to decide today what might begin to count as freedom tomorrow find Foucault, at least with respect to our philosophical perspectives, freeing. Foucault’s approach to power and freedom therefore matters not only for philosophy, but also more importantly for what philosophy can contribute to the changing orders of things in which we find ourselves


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Discipline – Focault [...]

Discipline, according to Foucault’s historical and philosophical analyses, is a form of power that tells people how to act by coaxing them to adjust themselves to what is ‘normal’. It is power in the form of correct training (Source)

Foucault argued that if you look at the way in which prisons operate, that is, at their mechanics, it becomes evident that they are designed not so much to lock away criminals as to submit them to training rendering them docile. Prisons are first and foremost not houses of confinement but departments of correction. The crucial part of this institution is not the cage of the prison cell, but the routine of the timetables that govern the daily lives of prisoners. What disciplines prisoners is the supervised morning inspections, the monitored mealtimes, the work shifts, even the ‘free time’ overseen by a panoply of attendants including armed guards and clipboard-wielding psychologists.

And the potential link to analytics - for both student and teacher

The purpose of constant surveillance is not to scare prisoners who are thinking of escaping, but rather to compel them to regard themselves as subject to correction. From the moment of morning rise to night’s lights out, the prisoners are subject to ceaseless behavioural inspection.

The most chilling line in Discipline and Punish is the final sentence of the section entitled ‘Panopticism’, where Foucault wryly asks: ‘Is it surprising that prisons resemble factories, schools, barracks, hospitals, which all resemble prisons?’ If Foucault is right, we are subject to the power of correct training whenever we are tied to our school desks, our positions on the assembly line or, perhaps most of all in our time, our meticulously curated cubicles and open-plan offices so popular as working spaces today.


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Learning analytics should be human mediated? [...]

Argument outlining need for analytics to be human mediated - part of a longer blog post and also part of a debate.

The “system” should not just be replicating current bad practice. Data should provide us with new ways to encourage a richer dialogue about education and knowledge. Learning analytics can’t just be a way to develop alerting and intervention systems that provide an illusion of understanding, that acquiesce to not particularly well thought out government driven monitoring processes such as the TEF.

In these days of alternative facts, distrust of expert knowledge, human intervention is more crucial than ever. Human intervention is not just an ethical issue, it’s a moral imperative. We need to care, our students need to care, our society needs to care. I”ll end now with the words of the Cassandra of EdTech, Audrey Watters (Source)


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Overcoming algorithm aversion (by making it protean) [...]

In this PhD thesis the abstract reads

Research shows that evidence-based algorithms more accurately predict the future than do human forecasters. Yet when forecasters are deciding whether to use a human forecaster or a statistical algorithm, they often choose the human forecaster. This phenomenon, which we call algorithm aversion, is costly, and it is important to understand its causes. In Chapter 1, we show that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster. This is because people more quickly lose confidence in algorithmic than human forecasters after seeing them make the same mistake. In Chapter 2, we investigate how aversion to imperfect algorithms might be overcome. We find that people are considerably more likely to choose to use an imperfect algorithm, and thus perform better, when they can modify its forecasts. Importantly, this is true even when they are severely restricted in the modifications they can make. Moreover, we find that people’s decision to use a modifiable algorithm is relatively insensitive to the magnitude of the modifications they are able to make. Finally, we find that giving people the freedom to modify an imperfect algorithm makes them feel more satisfied with the forecasting process, more likely to believe that the algorithm is superior, and more likely to choose to use an algorithm to make subsequent forecasts

A slim link to the idea of protean digital technology.

Implications for learning analytics.


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