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Posts Tagged ‘data

Being “data-driven” seems to have garnered a bad name in some schooling and education circles.

This is probably because of its misuse by edtech vendors for so-called analytics and misinterpretations of what being data-driven means by policymakers. Each is bad enough on its own. Both are lethal in combination.

But here are two recent examples of how being reliant on data is a good thing.

In a recent contest in Singapore, teams of students relied on shared pools of data to create visualisations.


Video source

The video above used data to create awareness of the difficulties that face families who have children with special needs.
 

Video source

The next video presented data to question commonly held misconceptions about ex-convicts.

Providing concrete visualisations of abstract data is not the same as being data driven. The former is about seeing what is not immediately apparent. The latter can sometimes be about playing the numbers game above all else, and that often ignores or harms the people that make up those numbers.

When being data-driven loses its original intent to inform decisions to actually help people, perhaps data visualisations like the ones above are a timely reminder of what good data might do.

I had an uncomfortable gut feeling when I read this CNA article about biometric payments being available to schools here in 2018.

I had to dig deep for why I was uncomfortable. After all, I am all for technology making lives better. And therein lay the problem: In doing good, there was also the potential for harm.

The good is the sheer convenience of going cashless while being able to track spending. This might be the start of basic financial literacy.

According to the news article, the system has safety measures:

Fingerprint information will not be stored on the device. Instead, the prints will be encrypted and stored securely in a cloud database.

Anti-spoofing technology will also be put in place to ensure that the fingerprints are real and that the person making the payment is present.

This is the trifecta of data accuracy (reading), data security (keeping), and data integrity (reliably identifying). If just one to fails, the system’s users are harmed. Take the recent Instagram hack, for example.

For the sake of argument, let us assume that the three data concepts are sound in practice. What is the harm then?

To answer this question, we need to ask at least one other question: What else can vendors do with the data that is accurate, “stored securely”, and reliable?

The short answer is lots. One needs only look at what Facebook and Google did (and continue to do) with our data. They offer their services for “free” to us because our data serves up advertisements which make these companies money. Lots of it.

One needs only to casually search for data breaches and infringements involving these two companies. For example:

The last item was not so much about the privacy of data as about the use and manipulation of data. That is my point: Assuring stakeholders that data is accurate, authentic, and safe is not enough; it is the lack of transparency and foresight about what can be done with that data.

Students are particularly vulnerable because adults make decisions about their data and the kids have no say in the biometric scheme. By this I am referring to the scheme being employed as a Smart Nation initiative, not the choice of whether to join the scheme.

The issue is so serious that the Electronic Frontier Foundation (EFF) has tips for teachers about student privacy. These include:

  • Making digital literacy part of the curriculum
  • Advocating for better training for teachers
  • Getting parental consent
  • Selecting technology tools carefully
  • Building community of like-minded privacy advocates

A Smart Nation needs people to make smart choices. To do that, people need good information. Where is the information about how the data might be used both intentionally and peripherally? What promises and standards of practice can service vendors and providers be held to? Where is the public debate on the data privacy of the especially vulnerable?

The London Underground system will get 4G coverage by 2019. Yay?

The writer’s reaction summarised in the tweet above was one of dismay. Mine was simply welcome to 2012.

I visited the UK twice two years ago and can relate to the wireless-less experience. I discovered during my second visit that some stations deep underground had wifi so I enjoyed intermittent access.

The article’s writer seems to be predicting some sort of social pandemonium brought about by people yammering loudly and incessantly.

Will it happen? Yes, but not likely to the extent and frequency he projects. Our own train system gets a few loud mouths who have no volume control or social awareness. But really, how many people actually talk that often on their phones?

The writer might get actual anecdotes and data from other systems that have 4G access about loud mouth frequency. He might also find out how such access actually helps commuters.

Being able to communicate by voice, video, text, or emoji provides a crucial channel for alerts and in emergencies. 4G access also activates many eyes in a human monitoring system of nefarious activities.

Writers might like making predictions based solely on opinion and limited experience. They could do better with critical data and lived experiences.

Now if only more readers learnt to tell the difference between these writers…

When I conduct workshops or do talks, I often bring my own Internet connection with a mifi device. 

When I had the presence of mind, I took note of how data I consumed. 

I estimated the amount of data by comparing the before and after quota of my prepaid 4G SIM account from M1.

My talks are interactive and I rely on Google Slides. But these sessions rarely extend beyond an hour and do not require as much data. 

My workshops last about three hours and rely on more media-rich resources. But I save on data consumption by making local versions of online videos. 

I share this as a reminder to myself and as a tip for others roughly how much data to set aside when bringing your own connection while providing professional development with others.

When I first heard the news that Twitter made its analytics dashboard available to all, I jumped on it straightaway.

I was surprised to learn of my reach or what Twitter calls impressions. That said I have no doubt that others have a far wider reach.

But now I am wondering about the reliability of the analytics dashboard.

I discovered the analytics tools on 28 Aug. However, the date and time seem to be set for some other part of the globe. That said, my reach for 27 Aug as recorded on the morning of 28 Aug was 27,263 (see screencapture below).

tweet_activity_analytics_for_ashley_1

The analytics engine was already collecting data for 28 Aug as evident by the small bar to the right of the highlighted one.

On 29 Aug, I checked for activity on the 28th. I moused over the 27th accidentally and noticed that the count went up to 28,842 (see screencapture below).

tweet_activity_analytics_for_ashley_2

I am not sure why the numbers changed.

Perhaps the counts got adjusted for the time and date difference. Perhaps older tweets were getting views two or three days after being posted and their hit counts were not yet stable.

The numbers seem to settle about two days into collection. It might be best then to monitor on a weekly or monthly basis.

That was lesson number one.

What is worrying is the low engagement. I have read a few reviews by other individual tweeters [example from Gizmodo] and they say the same thing.

Each of my tweets gets between 4000 to 5000 views. But you can count on two hands (and occasionally include the feet) the number of reader interactions with the tweets. These include retweeting, favouriting, clicking on embedded resources, etc.

The tweets with higher interactions tend to be question-oriented. Ask a question and you are likely to get responses. The tweets with lower interactions are information-oriented. Provide something of value and the consumer consumes. Do not expect a thank you, feedback, or a pass-it-on.

This behaviour is not unique to Twitter. When I was privy to my former department’s Facebook reports, our engagement rate was equally low.

If I was a company I would be concerned that customers were not engaging with me. As an educator carefully curating and sharing, I might be a bit concerned about the viewing habits of my informal audience and learners.

I used to say today’s learner seems to move at twitch speed. This is not another way of saying they have short attention spans because they do not. Anyone who has observed someone else immersed in a game or in a state of flow will realize how much focus gamers have.

I mean to say that they move superficially from one resource to another due to the breadth of information presented to them. Their rallying cry seems to be tl;dr (too long, didn’t read).

Now I am tempted to say that my followers move at Twitter speed. That might sound like superficial consumption, but at least they read and read lots of seemingly disparate information. It is the brain foraging as this MindShift article points out.

So another lesson might be to leverage on Twitter as the learner expects. Not so much in a forced provide-feedback-in-a-classroom way, but in an informal, scattered goodies way or a curiosity-driven, #hashtag-focused chat.

Today I would like to share three lessons on change management that one might draw from a utility bill.

It may sound strange, but there is one monthly bill I almost look forward to receiving every month. This is my utility bill for electricity, water, and gas.

I do not actually look forward to paying money. I like seeing the comparison table that I get via an e-bill.

utility_bill

This is my August summary. I take some pride that despite having a large apartment, I use comparatively little by way of utilities. The asterisks refer to comparisons with other apartments in my building and the national average based on the size of my apartment.

My household keeps our electricity bill low by using LED bulbs, using energy efficient appliances, rarely using the air-conditioner, and having devices that switch standby devices totally off. I am also a tyrant about electricity discipline.

We keep water waste to a minimum by having low-flow taps and adjusting the WC flow to its most efficient. I am not sure what we do with gas except that it is sometimes more efficient to microwave small amounts of water than to heat it over a stove. It boils down to good personal habits.

I have invested the most time, money, and effort in saving electricity because that is what I have the greatest control over and there are a variety of devices and processes at home that use it.

I have not changed any major appliance since I bought them almost a decade ago, but I got the most energy efficient ones I could then. I put the computing devices on power schedules so they do not run when we are not using them.

 
I initially had CFL lights (which were energy savers) but changed my often used lights to LEDs (which use even less electricity) despite the high initial cost. I also invested in two devices that prevent standby devices from using electricity (IntelliPlug by OneClick, exact model here).

I found out as much as I could about these devices, tried a few, monitored the results, and bought more when they seemed to be working.

The savings paid off almost immediately. Each month, I get reminded that what I started keeps working. When there are utility hikes, I do not see appreciable jumps.

So what are the lessons that might be scaled up and applied to change management?

First, it is important to invest in the long term. The short term might involve cost (money, time, effort, manpower, etc.) with no clear results for months or even years. But if you have a well-researched and/or proven strategy, you can be confident that it will pay off in the longer term.

Second, you must monitor the effects of change implementation. You must have a constant source of data to let you know that what you are doing is working or not. Objectively collected and analyzed data that yields good results is a morale booster and motivates change agents to keep pushing forward. Data that consistently points the other way is a clear sign to try something else.

Third, keep at it even when things are going well. The worst thing that can happen is to get complacent. Every process can be more efficient or more effective or something can come along to threaten a time-tried technique. It is important to stick to your guns when things do not seem to be going well or know when to switch tactics even if they are.

If you are ahead of the curve, your biggest competitor is yourself. If you want to keep staying ahead, keep establishing new long term goals, monitor your progress, and embrace constant change.

Rising above my experiences on getting data SIMs in Sweden and Denmark, I had five overall thoughts.

20140611-202606-73566794.jpg

First, it helps to be organized. SIM cards are small, finicky things that are easy to lose. I carry SIMs, adapters, sticky tape, and the SIM tray pokey pin thing in an SD card case. I might consider bringing SIM cutters too.

Second, in circumstances like mine, having an unlocked, dual SIM phone like the Moto G was invaluable. This phone was a cheap spare that also served as my son’s gaming device. I used one SIM slot for Lebara SMS and calls, and the other slot for Oister data. If the Lebara SIM worked properly, the spare slot could hold any other SIM, e.g., Singapore telco SIM for updates. Having your home country’s SIM is useful for receiving updates from family, credit card use, and, ugh, work.

Third, do not assume that all telcos operate the same way. Soon after I bought the Oister starter pack, a Finn entered the store and asked for a prepaid data SIM. We started chatting and he remarked that even though it was 2014, the standards of practice of prepaid SIMs were frustratingly varied. I agreed with him. But a combination of online research and friendly chats with people can minimize the frustration.

Fourth, the easy thing to do is pay ridiculous amounts of money to your home telco for calls, SMS, and data roaming. You learn a lot more and save some money by picking up a local SIM. Having a local number is also helpful to friends or contacts you might have in the country you are visiting.

Fifth, never underestimate how much data you might use, especially if you back up or sync photos online like me. Not all telcos will help you monitor your data use (Lebara provided rough voice messages if you called and sent an SMS notification when you had 50MB left; Oister offered no notifications). So go for more data than you need to avoid complications or hassles, and use a data monitoring tool/app on your device.

Hmm, maybe I should write about getting SIMs in other places I have travelled like Malaysia, Indonesia, the Philippines, Australia, and New Zealand.


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