School Types in England and Wales – Statistical Overview…

As of 2017, there were over 250 000 children in ‘Converter Academies’, 86, 000 students in sponsored academies, and 170 000 students in LEA maintained schools. This that in 2017 there were twice as many students in converter and sponsored academies combined as there are in LEA funded mainstream schools….

Number Pupils Schools Academies

Free Schools, meanwhile, cater to only just over 3000 students, with studio schools the least popular type of school, with only 1200 students.

Click on the link above, for the (slightly lame) interactive version… NB this is me still trying to get my head around Tableau!

 

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The Delhi Smog – A Consequence of Neoliberal Development?

A test match between India and Sri Lanka had to be repeatedly halted on Sunday because of the smog enveloping Delhi.

India smog 2

The Sri-Lankan cricket team, taking a break from smog-induced vomit sessions 

The Sri-Lankan team took the field after the lunch break wearing face masks, and play was halted for consultation with doctors. It then resumed, but was stopped twice more when two Sri Lankan bowlers left the field with breathing difficult and nausea; one of them was said to have vomited in the changing room. (further details are in this article in the Hindustan Times)*

This little story got me to digging around for evidence of the extent of pollution in Delhi – and it seems that it’s pretty bad – according to this BBC News Article pollution levels in early November 2017 reached 30 times the World Health Organisation’s acceptable limits, and the Indian Medical Association declared a state of medical emergency…

Thick smog in new Delhi on Tuesday express Photo by Prem Nath Pandey 07 Nov 17

Smog in Delhi

To my mind this is a great example of the relationship between development and environmental damage, which can be especially bad when development happens rapidly (or should I say ‘development’?) and there is a lack of regulation. Possibly yet another problems with neoliberal strategies of development?

*NB – The India cricket boss, CK Khanna, accused to Sri Lankans of making a ‘big fuss’, I guess it all depends on what level of pollution you regard as ‘normal’! 

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Kahoot for teaching A-level sociology

Kahoot is an online quizzing platform which allows teachers to create multiple choice quizzes which can be played in-class by students, who access the quiz on a mobile device.

Students need to go to Kahoot.it and need a pin (unique to each quiz, and only available once the teacher makes the quiz live) to enter…

There are a few different ‘game’ options (there’s a matching/ ordering version) for example, but here I’m focusing just on the ‘classic’ Kahoot….

How Kahoot works…

NB – I recommend you go check it out for yourself, nothing like practice to get your head around it! (If, of course, you think it’s worth the time investment…)

Questions are projected up like this

Before the screen below just the question appears, for a set amount of time (I like to set this at 10 seconds) – this is thinking time!

And students see the coloured options on their phones like this..

They simply tap the option they think is correct.

Students get points for correct answers and for how quickly they answered, and their ranked at the end of each question in a leader board, and yes of course, there’s an overall winner after all the questions have been answered…

I like to set up a Kahoot with 15-20 questions, which is ENOUGH! Although I’ve seen some with dozens of questions.

You might also like to read the following two posts to see how Kahoot compares to…

What I like about Kahoot

  • Christmas in coming, and I don’t know about you, but if it’s a toss up between starting ‘experiments in research methods’ or playing Kahoot on that slack last day of term… well let’s just say Milgram can wait until January!
  • It’s possibly the most fun you’ll have in class in all year…
  • The background  ‘data entry’ side of Kahoot is very easy to use – it’s basically the same as for Quizlet, and, as with Quizlet, you can duplicate, modify and repurpose other people’s work.

What I don’t like about Kahoot…

  • Oh how the children lold all term, yet oh how they wailed when they came to their exams and realised they had no clue WTF analysis was.
  • Unlike Quizlet, you don’t end up with nice Flashcards which the students can use to review knowledge, and the quizzes aren’t available offline afterwards. IMO Quizlet is far better a time investment for A level sociology teachers.
  • It actually has quite a discouraging effect on those in the bottom half of the leader board!
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Trump’s Tweets…

Donald Trump’s recent retweets of inflammatory anti-Muslim videos posted by the far right group ‘Britain First’ sparked outrage last week, a row which intensified when Theresa May said it was wrong for him to do so, which in turn prompted a twitter rebuke from Donald Trump in which he said suggested she should be focusing on the destructive Radical Islam in the UK rather than criticizing him.

Trump Tweets

The videos purported to show Muslims pushing a boy off a roof, destroying a statue of the Virgin Mary, and beating a boy on crutches.

Trump’s tweets prompted The Guardian to suggest that his proposed state visit should be cancelled, because it would be inappropriate to extend such a formal welcome to such a racist bigot

However, the Daily Mail points out that state visits have been extended to all sorts of immoral characters in the past – such as Nicolae Ceausescu of Romania and Robert Mugabe of Zimbabwe.

NB IMO the above statement from the Daily Mail is a great example of something which isn’t (technically) an argument) – that we shouldn’t cancel a proposed state visit because we have a tradition of setting a low-ethical bar for people invited to past state visits isn’t a rational reason for not changing current policy – it’s an irrational appeal to tradition/ emotion, thus not logical, thus not an argument. 

According to Max Hastings in the Daily Mail, Trump’s tweets also reveal something about the ‘special relationship’ between Britain and the USA – namely that the UK likes to flatter itself that there is one, but the reality is that this special relationship never actually amounts to much in terms of the USA doing anything for the UK… This might be a warning about not relying on the USA as one of our post-Brexit saviors.

As to why Trump posted those tweets, besides being an impetuous Racist, there may have been a self-interested political motive – these tweets may have been aimed at his own far-right American audience…. and he needs their support for his ‘Mexican Wall’ project.

So, all in all, as shocking as Trump’s Tweets were in terms of their revealing his horrible racism, the deeper-reality behind the tweets is even worse…

 

 

 

 

 

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How will Big Data Change Social Research?

Big data will change the nature of social research –  more data will do away with the need for sampling (and eradicated the biases that emerge with sampling); big data analysis will be messier, but this will lead to more insights and allow for greater depth of analysis; and finally it will move us away from a limiting hypothesis-led search for causality, to non-causal analysis based on correlation.

At least according to Mayer-Schonberger and Cuker (2017) Big Data: The Essential Guide to Work, Life and Learning in the Age of Insight.

Big Data Research

A third of social science researchers are already working with Big Data

 

Below I outline their summary of how Cukier thinks big data will change social research:

You might like to read my summary of the introduction to ‘Big Data’ first

More Data

The ability to collect and analyse large amounts of data in real time has many advantages:

It does away with the need for sampling, and all the problems that can emerge with biased sampling.

More data enables us to make accurate predictions down to smaller levels – as with the case of Google’s flu predictions being able to predict the spread of flu on a city by city basis across the USA.

It enables us to use outliers to spot interesting trends – for example credit card companies can use it to detect fraud if too many transactions for a particular type of card originate in one particular area.

When we use all the data, we are more likely to find things which we never expected to find…

Cukier uses Steven Levitt’s analysis of all the data from 11 years worth of Sumo bouts as a good example of the interesting insights to be gained through big data analysis.

A suitable analogy for big data may be the Lytro camera, which captures not just a single plane of light, as with conventional cameras, but rays from the entire light field… the photographer decides later on which element of light to focus on in the digital file…. And he can reuse the same information in different ways.

One of the areas that is most dramatically being shaken up by big data is the social sciences, which have traditionally made use of sampling techniques. This monopoly is likely to be broken by big data firms and the old biases associated with sampling should disappear.

Albert-Laszlo Barabasi examined social  networks using logs of mobile phones from about one fifth of an unidentified European country’s population – which was the first analysis done on networks at the societal level using a dataset in the spirit of n = all. They found something unusual – if one removes people with lots of close links in the local area the societal network remains intact, but if one removes people with links outside their community, the social network degrades.

Messier

All other things being equal, big data is ‘messier’ than small data – because the more data you collect, the higher the chance that some of it will be inaccurate. However, the aggregate of all the data should provide more breadth and frequency of data than smaller data sets.

Cukier uses the analogy of measuring temperature in a vineyard to illustrate this – if we have just one temperature gauge, we have to make sure it is working perfectly, but it we have a thousand, we will have more errors, but a much wider breadth of data, and if we take measurements with greater frequency, we will have a more sensitive measurement of changes over time.

When using big data, analysts are generally happy sacrificing some accuracy for knowing the general trend – in the big data world, it is OK if 2+2 = 3.9.

More data is sometimes all we need for 100% accuracy, for example chess games with fewer than 6 pieces on the board have all been mapped out in their entirety, thus a human will never be able to beat a computer again once this point has been reached.

The fact that messiness doesn’t matter that much is evidenced in Google’s success with its translation software – Google employed a relatively simply algorithm but fed it trillions of words from across the internet – all of the messy data it could find – this proves that simple models and lot of data trump smart models and less data.

We see messiness in action all over the internet – it lies in ‘tagging’ and likes being rounded up – none of this is precise, but it works, it provides us with usable information.

Ultimately big data means we are going to have to become happier with uncertainty.

Correlation 

It might be hard to fathom today, but when Amazon started up it actually employed book critics and editors to write reviews of books and make recommendations to customers.

Then the CEO Jeff Bezos had the idea of making specific recommendations to customers based on their individual shopping preferences and employed someone called Greg Linden to develop a recommendation system – in 19898 he and his colleagues applied for a patent on ‘item to item’ collaborative filtering – which allowed Amazon to look for relationships between products.

As a result, Amazon’s sales shot up, they sacked the human advisors, and today about 1/3rd of all its sales are based on their recommendations systems. Amazon was an early adopter of big data analytics to drive up sales, and today many other companies such as Netflix also use it as one of the primary methods to keep profits rolling in.

These companies don’t need to know why consumers like the products that they do, knowing that there’s a relationship between the products people like is enough to drive up sales.

Predictions and Predilections

In the big data world, correlations really shine – we can use them to gain more insights extremely rapidly.

At its core, a correlation quantifies the statistical relationship between two data values. A strong correlation means that when one of the data values changes, the other is highly likely to change as well.

Correlations let us analyse a phenomenon not by shedding light on its inner workings, but by identifying a useful proxy for it.

In the small data age, researchers needed to use hypotheses to select one or a handful of proxies to analyse, and hence hard statistical evidence on the relationship between variables was collected quite slowly; with the increase in computational power we don’t need hypothesis-driven analysis, we can simply analyse billions of data points and ‘stumble upon’ correlations.

In the big-data age we can use a data-driven approach to collecting data, and our results should be less biased and more accurate, and we should also be able to get them faster.

One such example of where this data-driven approach has been applied and strong big data correlations was the case of Google’s flu predictions. We didn’t need to know what flu search terms were the best proxy for ‘people with flu symptoms’, in this case, the data simply showed us which search terms were the best proxies.

With correlations there is no certainty, only probability, but this can still provide us with actionable data, as with the case of Amazon above, and there are many other examples of where data driven big data analytics are changing our lives. (p56)

We can use correlations to predict the future – for example, Wal-Mart noticed a correlation between Hurricanes and Flash Light sales, but also pop tarts, so when a Hurricane is predicted, it moves the pop tarts to the front of store and further boosts its sales.

Probably the most notorious use of big data correlations to make predictions is the American discount retailer, Target, who use their data on the products women buy as a proxy for pregnancy – women tend to buy non scented body lotions around the third month of pregnancy and then various vitamin supplements around the 6 month mark – big data even allows predictions about the approximate birth date to be made!

Finding proxies in social contexts is only one way that big-data techniques are being employed – another use is through ‘predictive analytics’, which aims to forsee events before they happen.

One example of predictive analytics is the shipping company UPS using them to monitor its fleet of 10s of 1000s of vehicles – to replace parts just before they wear out, saving them millions of dollars.

Another use is in health care – one piece of research by Dr Carolyn McGregor, with IBM,, used 16 different data streams to track the stats of premature babies – and found that there was a correlation between certain stats and an infection occurring 24 hours later. Interestingly this research found that an infant’s stability was a predictor of a forthcoming infection, which flew in the face of convention – again we don’t know why this is, but the correlation was there.

Illusions and Illuminations

Big data also makes it easier to find more complex, non-linear relationships than when working within a hypothesis-limiting small data paradigm.

One example of a non-linear relationship uncovered by big data analysis is that of the relationship between income and happiness – that happiness increases with income (up until about $30K per year, but then it levels out – once we have ‘enough’ adding on more money doesn’t make us any happier…

Big data also opens up more possibilities for exploring networks – by analyzing how ideas spread through the nodes of networks such as Facebook, for example.

In network analysis, it is very difficult to attribute causality, because everything is connected to everything else, and big data analysis is typically non-causal, just looking for correlations not ‘causation’.

Does big data mean the end of theory?

In 2008 Wired magazine’s chief editor argued that in the ‘Petabyte age’ we would be able to do away with theory – that correlation would be enough for us to understand reality – citing as examples Google’s search engine and gene sequencing – where simply huge amounts of data and applied mathematics replace every other tool that might be brought to bear.

However, this view is problematic because big data is itself founded on theory – it employs mathematical and statistical theories for example, and humans still select data, or at least the tools which select data, which in turn are often driven by convenience and economic concerns.

Having said that, Big Data does potentially move us away from theory and closer to empiricism than in the small data age.

 

 

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Where’s Our Aid Money Gone?

UK Development aid intended to maintain stability in Northern Syria has apparently ended up in the hands I Jihadists who abuse human rights.

This is according to a recent BBC Panorama documentary, which aired this Monday.

The problem seemed to be down to one private UK company who DFID channelled the money through.

The programme uses document evidence and interviews with aid workers based in Turkey who talk about bags of UK tax payers aid money being handed over to Syrian peacekeeping forces – who were actually working with local Jihadists to ‘maintain a balance of power’ in the region

The document evidence seemed to prove that the company knew this was going on…

So how strong an argument does this evidence make against aid?

Not a very strong one outside of this specific case IMO.

Sources

https://www.google.co.uk/amp/s/amp.theguardian.com/commentisfree/2017/dec/04/panorama-syria-allegations-uk-aid-transparency-bbc

 

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What is an Indicator?

An indicator provides a measure of a concept, and is typically used in quantitative research.

It is useful to distinguish between an indicator and a measure:

Measures refer to things that can be relatively unambiguously counted, such as personal income, household income, age, number of children, or number of years spent at school. Measures, in other words, are quantities. If we are interested in some of the changes in personal income, the latter can be quantified in a reasonably direct way (assuming we have access to all the relevant data).

Sociologists use indicators to tap concepts that are less directly quantifiable, such as job satisfaction. If we are interested in the causes of variation of job satisfaction, we will need indicators that stand for the concept of ‘job satisfaction’. These indicators will allow the level of ‘job satisfaction’ to be measured, and we can treat the resulting quantitative information as if it were a measure.

An indicator, then, is something which is devised that is employed as though it were a measure of a concept.

Direct and Indirect indicators 

Direct indicators are ones which are closely related to the concept being measured. For example questions about how much a person earns each much are direct indicators of personal income; but the same question would only be an indirect measurement of the concept of social class background.

 

 

 

 

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Assess the view that western models of education are not appropriate to developing countries (20)

Overview plan

  1. What are Western Models of Education?
  2. What are the arguments and evidence for western models being appropriate to developing countries?
  3. What are the arguments and evidence against/ what other models might be appropriate?
  4. Conclusion – when might Western models be appropriate/ when not?

This is a possible 20 mark essay which might come up on the AQA’s A-level sociology (7192/2) topics in sociology paper. Below is my extend plan. You might like to read this post on education and international development first, most of the material below is based on this.

Extended plan

1. What are Western Models of Education?

  • Free state education for all, funded by tax payer
  • Functions – apply Functionalism – crucial link to work and economy
  • Expensive, requires tax base, trained professionals
  • Industrial model/ factory model
  • National curriculums, standardised testing (downsides)

2. What are the arguments and evidence for western models being appropriate to developing countries?

  • Mainly modernisation theory – link to breaking traditional values
  • There is a correlation between education and economic growth.
  • Would anyone disagree with the idea that teaching kids to read/ keeping them out of work is a good idea? Near universal agreement.
  • Western companies are involved in running education systems in developing countries (linked to neoliberalism)

3. What are the arguments and evidence against western education being appropriate/ what other models might more appropriate?

  • Dependency theory argues western education is simply part of the colonial project – a ‘reward’ for the natives who obey the colonisers.
  • Western education focuses too much on Western history, it’s ethnocentric, and erases diverse voices (Galeano)
  • Bare Foot Education (people centred development) might be more appropriate – local education systems run by local people to meet local needs (focussing on agricultural technology, women’s empowerment for example).
  • Most obvious reasons ‘Western education’ might not work are due to numerous barriers to education – e.g. poorer countries cannot afford the teachers, rural populations are too dispersed.
  • Building on point d above, two of the biggest barriers are groups such as Boko Haram who prevent girls from getting an education.
  • Neoliberals and others suggest we can educate effectively in poor countries without the need for massive state sectors like in the west (through online learning, e.g. the hole in the wall experiment).

4. Conclusion – when might Western models be appropriate/ when not?

  • In principle the western idea of funding education for children for 11 years is hard to argue against
  • However, there are problems with many aspects of the western education system – top-down national curriculums for example, and the focus on too much testing, and the sheer expense.
  • Also, there are massive barriers to rolling out western style education systems in developing countries which would make massive state education difficult to maintain.
  • So in conclusion I’d say the most effective way to implement and improve education in poorer countries is to adopt some but not all aspects of western models – maybe having the state and aid money guarantee teacher training and reading programmes, combined with a more ground-up people centred development approach to make sure local people are included in shaping specific aspects of education to meet their local needs.

 

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Will E-learning Platforms change Education?

Big data enthusiasts argue that the greater data collection and analysis potential provided by e-learning platforms such as Khan Academy and Udacity provide much more immediate feedback to students about how they learn, and they thus predict a future in which schools and private data companies will work together in a new educational ecosystem…

This is a continuation of my summary of  Meyer-Schonberger and Cukier’s in their (2017) ‘Big Data: The Essential Guide to Work, Life and Learning in the Age of Insight.

You might like to read this previous post first – How will Big Data Change Education? (according to the above authors).

The advantages of e-learning platforms over traditional education

Khan Academy is well-known for its online videos, but just as important to its success is the software which collects data about how students learn, as well as what they are learning.

To date, Khan Academy has data on over a billion completed exercises, which includes information on not only what videos students watch and what tests scores they achieve, but also on the length and number of times they engage with each aspect of the course, and the time of day they did their work. This enables data analysts to deduce (probabilistically) how students learn most effectively, and to provide feedback as to how they might improve their learning.

The Kahn Academy is just one online learning platform, along with a whole range of MOOCs offered through Udacity, Coursera and edX, as well as SPOOCs (small, private online courses) which are collecting huge volumes of data on student learning. The volume of data is unprecedented in human history, and Cukier suggests that this could change the whole ecosystem of learning, incorporating third parties who do the data analysis and with the role of instructors (‘teachers’) changing providing advice on which learning pathways students should adopt.

At least some of the Khan Academy Data on learning is available to third parties to analyse for free, and information personal to students is presented to them in the form a dashboard, which allows for real-time feedback to take place.

Cukier contrasts the above, emerging ecosystem of online learning, to the present ‘backward’ way in which data is collected and managed in the current education system as backward (he actually uses the term ‘agrarian’ to describe the process) – in which students are subjected to a few SATs tests at predetermined stages, and this score is ‘born by them’ until the next test, which makes labelling by teachers more likely.

In addition to this, the school day and year are run in a 19th century style, pigeon holed into year groups, pre-determined classes, students exposed to the same material, and with digital devices often banned from classes. All of this means data cannot be harnessed and analysed.

Where does this leave existing institutions of learning?

Schools and universities are well poised to harvest huge amounts of data on students, simply because they have 1000s, or 10s of 1000s of students enrolled.

To date, however, these traditional education institutions have shown a very limited ability to collect, let alone analyse and use big data to better inform how students learn.

The coming change will affect universities first – these have mature students, and this audience is more than capable of digesting insights about how to learn more effectively… the big universities where fees are expensive and students don’t get much back in return are poised for disruption by innovators…

Some of the very top universities seem to have got the importance of BIg Data – MIT identified EdX as a crucial part of its forward strategy in 2013 for example, but some of the universities lower down the pecking order may find it difficult to compete.

The response of some forward looking schools is to embrace elearning – recognising the importance of getting and utilising more data on how students learn – Khan Academy is partnered with a number of schools, for example Peninsula Bridge, a summer school for middle schoolers from poor communities in the Bay area. – Cukier cites an example of one girl who managed to improve her maths due to this (again, evidence cited is almost non existent here!)

The chapter concludes with imaging a future in which schools are just part of a broader ecosystem of learning – which includes a much more prominent role for private companies and where data plays a more central role in learning.

Comments

There are number of factors which may contribute to schools’ inability to harness big data:

  1. Time limitations – as Frank Furedi argues in ‘Wasted’, the function of schools have expanded so that they are now expected to do more than just educate kids – thus an ever larger proportion of schools’ budgets are taken up with other aspects of child development; combined with meddling by successive governments introducing new policies every few years, schools are caught in the trap of having to devote their resources to adapting to external stimuli rather than being able to innovate.
  2. Financial limitations/ equality issues – correct me if I’m wrong, but any online course tailored to GCSEs or A-levels is going to cost money, and this might be prohibitively expensive!
  3. The negative teacher experience of governance by ‘small data’ – there is a staggering amount of small data already collected and teachers are governed by this – it might actually be this experience of being governed by data that makes teachers reluctant to collect even more data – no one wants to be disempowered!
  4. Child privacy rights – there is the not insignificant issue of letting big ICT education companies have access to our children’s learning data!

 

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Socrative for Teaching and Learning A-Level Sociology

Socrative is a real-time feedback learning-tool which allows teachers to quickly produce multiple choice, true/ false or open ended questions in order to assess student understanding.

Personally I think Socrative is the most useful online learning tool available to teachers and students studying A-level subjects, much more useful than Quizlet, for example, although it still has its limitations.

How to use Socrative

NB – You might like to just go sign up and try it out, unless you’re a total luddite (in which case go sit down with your tech-bod at school) you’ll find Socrative so easy to use…..

Teachers sign up for a ‘teacher account’ and can creating quizzes in advance of the lesson, or use the quick quiz option to ask one question at a time in class. Teachers will also need to create an online ‘room’ where students can join to take part in the quiz – you’ll need to call the room something simple live ‘Dave’s Sociology Room’. (Actually ideally something shorter than that – Maybe DSOC1, for example).

Once the teacher has started a quiz, students can access the quiz room by any browser, via the Socrative homepage or by the Socrative app if installed on phones/ tablets, and by entering the teacher’s ‘Room Name’ (which will be up on the screen once the quiz is live).

The teacher has the option to make progression through questions either 1 then all pause, or self-paced, and you can put in right or wrong answers, and add in explanation for why a particular answer is correct.

I’m not sure what the upper limit of entrants is, but Socrative has handled more than 20 in my class easily. The beauty of Socrative is that once students have completed all the questions, you get an overview of what questions they got right or wrong – here’s an example from a recent ‘education policies‘ recap I did at the beginning of one lesson the week after we’d taught social policies (in fairness to my teaching, questions 4 and 8 were designed to be tough! Also note that for question 9 I hadn’t set a ‘correct answer’ so it hasn’t colour coded).

socrative.jpg

clearly questions 4 and 8 need reviewing

 

And you can dig deeper into responses for each question too, simply by clicking on the question links above…. please note that in order to get a correct answer, students had to identify all three of the polices, and only those three!

Socrative questions

Incidentally, another great use for Socrative in sociology is simply to type in the same questions used in ‘opinion surveys’ to get an immediate feel for how students’s values correspond to that of the nation… here’s a sample of today’s students showing that they’re anti-immigration, but probably not quite as intolerant as their grandparents….

immigration survey

In the background of Socrative

Once you’ve signed up as a teacher, you get presented with the options below.. I won’t explain how it’s done, it’s so easy to use!

socrative review

Uses of Socrative for teaching A level sociology:

  • As with Quizlet, it’s great for recapping basic knowledge… however, an advantage over quizlet is that it allows you to enter much more challenging multiple choice questions, with answers close together to make students think.
  • You can tap into analysis and evaluation skills, simply by alternating multi choice knowledge questions with open ended questions asking students to simply justify their answers.
  • You can use the open ended question function to get students to write Point Explain Elaborate Evaluate essays collaboratively, live online.
  • With the quick question function, you can get students to select the best answer!
  • You get immediate feedback about what students need to review.
  • Socrative stores the reports for you, even with the free version.
  • You can collect a lot of data about formative learning here, especially if you can figure out a way of combining it with previous attendance, effort etc…

The Limitations:

  • For the free version, it only works when it’s live, you have to actually run it! The quizzes aren’t there all the time for constant review as they are with Quizlet.
  • Whose got time to actually use the data collected?

P.S. If you want to use the above education policies quiz – here’s the code…

SOC-31071794

 

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