News › 2017

Anna-Marie Fergusson (The University of Auckland) presented a workshop and webinar on Statistical Reasoning with Data Cards.

“Using data cards in the teaching of statistics can be a powerful way to build students’ statistical reasoning. Important understandings related to working with multivariate data, posing statistical questions, recognizing sampling variation and thinking about models can be developed. The use of real-life data cards involves hands-on and visual-based activities.”

Anna’s work using physical data cards and digital technology supports pedagogy required to effectively teach statistical reasoning. This talk presented material from the Meeting Within a Meeting (MWM) Statistics Workshop for Mathematics and Science teachers held at JSM Chicago (2016) which can be used in classrooms to support teaching statistical thinking and reasoning, key teaching and learning ideas that underpin the activities were also discussed.

Download the webinar accompanying files

Please share this excellent resource widely with your teaching colleagues and post any feedback you have about the resources or webinar.

Thanks to Michelle Dalrymple of Cashmere High School for sharing these photos of her Year 9 class taking part in CensusAtSchool.

Our press release with insights into our students’ school lunches received a range of media coverage, including:

Press release: May 2, 2017

School tuck shops are losing ground to home-packed lunches, according to latest results from the long-running CensusatSchool TataurangaKiteKura. In the past 10 years, the percentage of students buying lunches from tuck shops has halved.

Overall, 86% of primary and secondary school students brought their lunch from home on the day they responded to the survey, with just 5% buying from the tuck shop. When the same question was asked a decade ago, 79% were bringing lunch from home and 10% buying at their school’s tuck shop.

CensusAtSchool TataurangaKiTeKura is a national, biennial project run by the University of Auckland’s Department of Statistics that shows children the relevance of statistics to everyday life. In class, Year 5 to Year 13 students (aged 9 to 18) use digital devices to answer 35 online questions in English or te reo Māori, providing a unique snapshot of Kiwi childhoods. So far, more than 10,000 students have taken part, and they have answered several questions on food.

The Census asked “Where did you get your lunch from today?” with the possible answers “home” (overall 86%; primary 93%; high school 78%); “a shop on the way to school” (overall 3%; primary 2%; high school 3%); “the school shop” (overall 5%; primary 3%; high school 7%); “a friend at school” (overall 0.5%; primary 0.2%; high school 1%); “provided by my school” (overall 2%; primary 1%; high school 4%); and “don’t have any” (overall 3.6%; primary 1%; high school 7%).

The backdrop is growing childhood obesity and much public debate over what kids should be eating at school. An Education Review Office report released just before Easter found that most schools were doing a good job equipping young people to make good food choices, but acknowledged that factors such as family finances and attitudes, student price sensitivity and takeaway shops near schools could prevent children bringing or choosing good-quality lunches. Many school-run tuck shops lost money, so schools often contracted out to providers who “were profit-driven, and tended to be most interested in stocking what would sell well; not usually the healthy options”.

CensusAtSchool co-director Rachel Cunliffe, who has two school-aged children, says that she wonders if public discussions have raised parents’ awareness of the importance of the school lunches they provide, and that this has led to more concerted efforts to provide packed lunches. Mrs Cunliffe makes her two primary school-aged children daily packed lunches, and once a term they are allowed to buy lunch at school: “Of course, they tell me that everyone else gets to buy their lunches all the time.”

The past few years has also brought publicity about some school children going without breakfast or lunch, and Mrs Cunliffe says she was “relieved” that the number of children reporting that they had no lunch was fewer than expected. “That said, you don’t want to think that any students are going hungry,” she says. “I am hoping that the 7% of high-school students not having any lunch is because they didn’t get their act together to prepare it. A packed lunch does take some forethought and preparation.”

The Census also asked children who brought packed lunches how many items grown at home were among the food provided that day. A quarter said they had at least one home-grown item in their lunchbox.

This year’s edition of CensusAtSchool TataurangaKiteKura started on February 7. Teachers can register their classes and take part at any time before it finishes on July 7. The Census is part of an international effort to boost statistical capability among young people, and is carried out in Australia, the United Kingdom, Canada, the United States, Japan and South Africa.

The countries share some questions so comparisons can be made. In New Zealand, the Census started 2003, and is run by the University of Auckland’s Department of Statistics with support from Statistics NZ and the Ministry of Education.

Dear Awesome Teacher of Statistics

Have you heard of the Teaching Statistics Through Data Investigation MOOC for Educators? We continue to serve teachers from across the globe and have over 400 participants in the current session (open until June 30, 2017). Need a refresher? join us–it is still free!

Yearning for more??? Well I’d like to share a few opportunities and resources.

1. We will launch a SECOND Teaching Statistics course Fall 2017!  This course is a follow-up to TSDI and specifically focuses on Teaching Statistics Through Inferential Reasoning.  See the course description and outline here. If you have a favorite task, or online app, or video or other resource that helps you teach students to reason about using data and statistical ideas to make generalizations (informally or formally) beyond the data, we would love to feature some of your ideas in the new course (credited to you of course!)!  Please complete this brief form and upload (or provide links to) your favorite resources.

2. Learn about our new initiative for being a Hub for Innovation and Research in Statistics Education [http://hirise.fi.ncsu.edu/] and join our Facebook community so we can stay connected. https://www.facebook.com/groups/hirise.fi/

3. If you have not seen the Stats4Stem website, check it out!  It is a fantastic website full of resources for statistics teachers and their students to assist with teaching, learning, and assessment in statistics. http://www.stats4stem.org/

4. Want a free online tool for exploratory data analysis! Check out the ever-improving CODAP tool at http://codap.concord.org/

5. If you are interested in pursuing a graduate degree in statistics or mathematics education at NC State, check out  our PhD and Masters degrees! Not able to move to Raleigh?? Then consider the 12 credit (4 classes) online graduate certificate in Statistics Education! I’d love to continue learning with you!

Thank you for your continued commitment to making the world a better place through statistics and data literacy. Together we make a difference.

Many Smiles,

Hollylynne Lee

Professor, Mathematics and Statistics Education
University Faculty Scholar
Department of Science, Technology, Engineering, and Mathematics Education
Faculty Fellow, Friday Institute for Educational Innovation
NC State University

Waitara Central School

 

Waitara Central School

Waitara Central School

Thanks to Oron Smith of Waitara Central School for sharing these photos of his class taking part in CensusAtSchool.

Thanks to Claire Cheeseman at Langholm School for sending through these lovely photos of her students taking part in CensusAtSchool:

CensusAtSchool CensusAtSchool CensusAtSchool

Our press release with insights into our students’ screen time received a range of media coverage, including:

Eight in 10 teens and six in 10 primary school children say there are no limits on their screen time out of school – whether that’s playing computer games, using their phones, or browsing the internet.

The insights have emerged from the second data release from CensusAtSchool TataurangaKiTeKura, a national, biennial project run by the University of Auckland’s Department of Statistics that shows children the relevance of statistics to everyday life. In class, Year 5 to Year 13 students (aged 9 to 18) use digital devices to answer 35 online questions in English or te reo Māori, providing a unique snapshot of Kiwi childhoods. So far, more than 5,700 students have taken part.

Students were asked if, on a school day, there was a limit on the amount of screen time they had at home. Just 16% of high-school students and 37% of primary school students reported a limit. For those with limits, primary schoolers were allowed a median of an hour (the median is the middle amount in the range reported) and secondary students two hours.

Students were asked how often their screen time was supervised – with supervised meaning a parent or caregiver was watching or was in the same room as the child. Four in 10 primary schoolers said “a little,” and two in 10 “usually.” More than half of high school students said they were never supervised, with a further three in 10 saying they were supervised “a little.”

CensusAtSchool co-director Rachel Cunliffe, a former statistics lecturer and mother of four children aged 2, 4, 6 and 8, says she is “really surprised” at the results. “I imagined that in this completely wired world, the majority of kids would have limits – parents often discuss ways to find a balance between screen time and outdoor play time.”

Rachel Cunliffe points to Ministry of Health advice that outside of school, 5 to 18-year-olds spend less than two hours a day in front of the television, computers, and game consoles. She and her husband tried setting limits, but with four kids, that was hard to police. “Now, in our house, we have a list of morning, afternoon and evening jobs to be done on school days before the kids are allowed screen time, “ she says.

“By the time they’ve done everything expected of them, and their out-of-school school activities like swimming and karate, there’s not often long periods of time left for gaming. My eight-year-old has been pretty motivated to get through his jobs, and can get in an hour on the Playstation or tablet sometimes.”

So how are other school children using their screen time? Seven in 10 students said they spent time on their phone. Of that group, the most avid users were high school girls with 89% on their phones once school was out, and for a median of three hours – though a quarter spent 5 hours 30 minutes or more.

Four in ten students said they spent time gaming after school, with the keenest gamers high school boys. They spent a median of two hours in front of their Playstation, Xbox, Nintendo and the like – but a quarter spent four hours or more gaming.

CensusAtSchool also asked students what they did most often with their cellphones. Primary school boys reported playing games (27%) and primary school girls sending texts or instant messages (32%). At high school, it was all about social media for both girls (49%) and boys (31%).

This year’s edition of CensusAtSchool started on February 7. Teachers can register their classes and take part at any time before it finishes on July 7. CensusAtSchool is part of an international effort to boost statistical capability among young people, and is carried out in Australia, the United Kingdom, Canada, the United States, Japan and South Africa.

The countries share some questions so comparisons can be made.
In New Zealand, CensusAtSchool started 2003, and is run by the University of Auckland’s Department of Statistics with support from Statistics NZ and the Ministry of Education.

Statistics in school and the future of work  

Education Committee of the NZ Statistical Association. March 2017.

Purpose of this paper: anticipating change

We have a school statistical education system in New Zealand that we can be proud of: well designed for the needs of today’s workplace, and evolving to meet those needs better. If we want it to meet the needs of tomorrow’s workplace as well, do we need to adjust this system? This paper raises some questions about how statistical educators can act to anticipate change, and guide the further evolution of school statistics.

Research on the future of work shows that the workforce in 10, 15, and 20 years’ time will have a very different range and quantity of jobs to aim for. Some of this workforce is sitting in our statistics classes now.  What statistical education will best meet their lifelong needs?

The Education Committee welcomes feedback on this paper, and discussion of the implications for statistical education in New Zealand. Please contact Mike Camden m.camden@clear.net.nz regarding feedback or issues regarding curriculum planning and change.

 

Changes to the distribution of work and to the availability of work

The workforce faces two major changes:

  • the job market has jobs that will stay, change, go, or be newly created
  • the job market may have substantially fewer jobs.

To anticipate the first change, we need to ask what jobs will and won’t be around in say 10 years. Then we can ask what statistical skills the people in the jobs will need. We also need to ask what statistical skills matter to people when they shift jobs and change careers.

Jobs that can be automated by computer-controlled machines are at risk. This is not just about manufacturing. For example, it may include most driving jobs. Also, jobs are at risk that involve information processing which can be automated by software. These may include some accounting, health, and legal work.

The second major change above implies another:

  • a decrease in the availability of paid work puts stress on society’s decision-making methods.

As the employment scene changes, the income distribution of the population may change, and the wealth distribution may change. This means that the distribution of political decision-making power may change. It puts new pressures on how society makes good decisions.

We’re educating for life as well as for work, and ‘life’ includes participating in political decision-making.

The citizens who are our students now will need:

  • strong statistical skills for assessing data and data-based policies
  • strong probability skills for managing risk.

The first two changes above imply another:

  • people in the job market will need to deal resiliently with change.

Resilience includes abilities to manage periods without paid employment, and periods of further learning and reskilling. Resilience is about managing through times of disruptive change, as individuals, households, communities, and states. It includes, among other things, abilities at using data to make sound decisions.

So when we ask what today’s students need to go away with, an obvious answer is a set of abilities about flexibility and resilience: flexibility in learning new concepts and software skills, flexibility in transferring learning from one situation to a new one, ability to keep learning, and ability to cope with decisions that have plenty of uncertainty and variability.

Flexibility and higher-level skills

What do flexibility skills consist of? In Chris Wild’s address to the Wellington Maths Association, the answer goes like this: there’s (only) short-term value in the ability to operate any particular procedure, but there’s long-term value in the ability to take a set of instructions and operate an unfamiliar procedure. In Radio New Zealand’s Insight programme, a view is that educational thinking needs to shift away from facts and highly specialised skills to higher level skills that can be applied to a range of circumstances.

In New Zealand school mathematics and statistics education, we are already moving down that track, but we can keep investigating how to progress and how to stay ahead of the game.

Software for statistics and data graphics offers an obvious example. Students need skills with a particular software system, but they can also develop skills that will allow them to get into new software systems with new features.

 

Turning STEM into STEMS

A current response to the changing nature of work is to grow the STEM subjects, where STEM = Science, Technology, Engineering, and Mathematics. This response is already in action, in New Zealand and elsewhere. You can guess what the second S in STEMS stands for!  We need to ask now how we make sure that STEM has a very sound second S added to it and that statistics is built into it throughout. This was the subject of the Statistical Society of Australia’s symposium in June 2016: STEMS 2016: Putting Statistics into STEM in the Age of Data.

If the future workforce spends much of its time not in paid employment, then they’ll need skills in the arts: literature, music, drama, dance… So STEMS becomes STEAMS. They’ll certainly need ‘soft’ skills in employment: communication, logic, problem-solving, abilities in working with others, etc.  They’ll need the social sciences to be part of the first S in STEMS. What might not be so obvious is that all of these will need sound statistics behind them.

 

Questions for statistical educators

Here are some questions that we can ask ourselves, so that we anticipate future needs, and take preemptive action.

  • What statistical content will best support the (other) STEM subjects?
  • Do the STEM subjects have the best statistical content within themselves now?
  • How do we translate STEM into STEMS?
  • What statistical skills do workers need, if they are working with automated systems for producing goods, providing services, or processing information?
  • How do we make statistical skills flexible and transferable from task to task, job to job, and career to career?
  • How do we make sure that learners learn flexibility in their use of statistical skills? They will need to deal with new data structures, new software, new analysis approaches, and new graphics.
  • How do we ensure that sound statistical skills are used by the makers and users of dynamic and interactive graphics?
  • How do we tailor the probability in the curriculum so that it enables people to manage uncertainty and variability in their careers, work, and lives?
  • What professional development and resources do teachers need, as they enable enhanced statistical learning?
  • What are the technological implications to all of this?
  • What is data science and how does it connect with statistics?

 

Further sources of information relating to statistical education and the future of work

We have a vast amount of thinking available to us on the future of work, and some of it deals with the needs of today’s learners. Some of it discusses what flexibility for learners’ means. Our challenge is to adapt this thinking to school statistical education, and to make sure that it meets emerging needs. The notes below link to some of this thinking.

The Committee for Economic Development of Australia (CEDA) released its major report Australia’s future workforce? in 2015. They have been releasing further statements since, such as the press release More than five million Aussie jobs gone in 10 to 15 years. Among other findings, they say that ‘almost 40% of Australian jobs that exist today have a moderate to high likelihood of disappearing in the next 10 to 15 years’.

The UK Commission for Employment and Skills released The future of work: jobs and skills in 2030 in 2014They are interested in the future labour market and the implications for jobs and skills. The New Zealand Labour Party’s Future of Work Commission released The Future of Work (2016). It has a chapter on education and training: ‘The most important single driver of inclusion, resilience and adaptability in the future of work is education and training. We need to give the highest priority to an education and training system that is resilient, adaptable and inclusive.’

Several books explore the economic and political effects of the likely changes to work. McChesney and Nichols conclude that ‘moments of great turbulence will demand more democracy, not less.’ Statistical skills for citizens become more important.

The Chartered Accountants Australia and New Zealand are concerned that the workforce has the right skills: ‘Skills, training and education are increasingly important but can lose relevance quickly’.

The World Economic Forum’s very thorough report aimed, among other things, to ‘improve the current stock of knowledge around anticipated skills needs, recruitment patterns and occupational requirements.’  A note of relevance to us is that: ‘by one popular estimate, 65% of children entering primary school today will ultimately end up working in completely new job types that don’t yet exist.’

The International Association for Statistical Education made the creation of statistically skilled citizens the theme of its 2016 Round Table in Berlin: Promoting Understanding of Statistics about Society. In the Preface to the Proceedings,  Engel, Gal, and Ridgway, state the aim: ‘Our declared ambition was to promote curriculum reform in statistics education that will broaden the skills that students acquire, in order to make them … also more empowered citizens who can take an active or more informed role in civic life.’

They describe some of the contents: ‘Besides addressing cognitive knowledge elements (mathematical and statistical skills, socio-historical awareness and knowledge) some papers focused on how introducing issues of statistics about society provides opportunities to engage students in evaluating what social justice means to them through the lens of quantitative analytics. Thus, some papers investigated issues beyond cognitive skills, and addressed topics of beliefs, attitudes and values inherently involved when investigating social data.’

They relate statistics to citizenship: ‘With the rise of a political culture in which public debate is framed by appeals to emotion disconnected from the details of policy – so called post-truth or post-factual politics – it is ever more important for citizens to be critical consumers of media reports, being aware of misuse of statistics and knowing effective ways to overcome them.’

The 27 papers in the Proceedings, and the workshops and posters, contain a wealth of current thinking that we can make use of.

ProCivicStats is an initiative by statistical educators in six universities, and is supported by the European Commission. Like the Round Table, which it supported, its motivation is not specifically the future of work, but citizen engagement: ‘Social phenomena are complex, and democracies need citizens who can explore, understand, and reason about information of a multivariate nature’. Its site already contains links to many appropriate resources.

 

What now: statistical thinking with attitude

The answers too many of the questions above is to do what we already do, and centre the skills on statistical thinking. We need to ensure that learners and teachers have a deep understanding of statistical thinking, and know that it involves a wide variety of thought processes and attitudes.

These processes and attitudes of statistical thinking were first detailed by Wild and Pfannkuch (1999), and they already underlie the statistics and probability in the New Zealand Curriculum (2007). The changes to the NCEA achievement standards through the realignment process were also designed to support statistical thinking as intended by the Curriculum.

We now need to work towards the next stage of curriculum development. We tap into the thinking already being done about the future of work and its effects on society, and translate this into plans for the next stage of statistical education.

 

Links and references

Chartered Accountants Australia and NZ. The future of work: how can we adapt to survive and thrive? February 2016. https://www.charteredaccountantsanz.com/news-and-analysis/insights/future-inc/the-future-of-work

 

Committee for Economic Development of Australia. Australia’s future workforce? 2015.

http://www.ceda.com.au/research-and-policy/policy-priorities/workforce

 

Committee for Economic Development of Australia. More than five million Aussie jobs gone in 10 to 15 years. 2016. http://www.ceda.com.au/2015/06/16/five-million-Aussie-jobs-gone-in-10-to-15-years

 

Engel J, Gal I, and Ridgway J.  Preface to the Proceedings, in Promoting Understanding of Statistics about Society; Conference Proceedings. IASE Roundtable Conference, Berlin, Germany, 2016. ISBN number: 9789073592377. http://iase-web.org/documents/papers/rt2016/Preface_Roundtable.pdf

 

Fisher N, Howley P ,Martin M, Ryan L. STEMS2016: Putting Statistics into STEM in the Age of Data. Statistical Society of Australia. 2016. https://stems2016.com/report/

 

Future of Work Commission. The Future of Work. New Zealand Labour Party. 2016.

https://d3n8a8pro7vhmx.cloudfront.net/nzlabour/pages/2371/attachments/original/1478147232/43229_LoO_Future_of_Work_Full_Document_FINAL_2_LR.pdf?1478147232

 

Joanna MacKenzie, Insight: Digital Disruption & the Fourth Industrial Revolution: is New Zealand Ready?Radio NZ. 5 June 2016.

http://www.radionz.co.nz/national/programmes/insight/audio/201803034/insight-the-future-of-

 

McChesney R, Nichols J. People get ready: the fight against a jobless economy and a citizenless democracy. 2016. Nation Books, NY.

 

Ministry of Education, The New Zealand Curriculum. 2007.  Ministry of Education, New Zealand. http://nzcurriculum.tki.org.nz/

 

ProCivicStat: Promoting civic engagement via explorations of evidence. Website under development in 2017:

http://community.dur.ac.uk/procivic.stat/

 

UK Commission for Employment and Skills. The future of work: jobs and skills in 2030. 2014. https://www.gov.uk/government/publications/jobs-and-skills-in-2030

 

Wild C, Pfannkuch M. (1999). Statistical thinking in empirical inquiry. International Statistical Review v67 n3 1999. http://iase-web.org/documents/intstatreview/99.Wild.Pfannkuch.pdf

 

Wild C. Gazing into the data future. Address to Wellington Mathematics Association / Victoria University of Wellington. December 2016. https://www.stat.auckland.ac.nz/~wild/talks/2016VicTeachersDay/

 

World Economic Forum. The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution. January 2016. WEF. http://www3.weforum.org/docs/WEF_Future_of_Jobs.pdf