Students can explore and ask investigative questions about stickland people.

The data cards are virtual within the stickland environment.聽 For a physical copy of the stickland data cards click here.

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Participants used familiar statistics tools and approaches, such as data cards, collaborative group tasks and sampling activities, and also try out some new computational tools for learning from data. Statistical concepts covered include features of data distributions and informal inference.聽聽

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Anna and Liza considered some guiding principles for creating data sets for different types of statistical investigations and explored methods for getting modern data, including working with APIs, querying databases, using geocoding, getting data from sensors and creating data sets from online information.

The links to Anna’s website with al the links are in the google doc:

https://docs.google.com/document/d/1bZXmxbenUSshlI81vZevtbag_q9eVyv1S8pD1K-xFM4/edit

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Anna demonstrated how to build models with images and explore them in more detail. She looked at ways you can
start incorporating data science (and digital technologies) within your teaching of the current statistics curriculum. How are photos of cats different from photos of dogs? Is Google to blame for student鈥檚 lack of care about squares? Anna guided teachers to find answers to these questions using modelling tasks she designed.

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“Using data cards in the teaching of statistics can be a powerful way to build students鈥� 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聽talk presented material from the聽聽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.

Here are the files that accompany Anna’s webinar: 聽webinar files statistical reasoning with data cards

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

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We have a clear learning progression for how 鈥渢o make a call鈥� when making comparisons, but how do we make a call about whether a probability distribution model is a good model? As we place a greater emphasis on the use of real data in our statistical investigations, we need to build on sampling variation ideas and use these within our teaching of probability in ways that allow for key concepts to be linked but not confused. This year Anna undertook research into teachers鈥� knowledge of probability distribution modelling. Anna shared what she learned from this research, and also shared a new free online tool and activities she developed that allows students to use informal inferential reasoning to assess the fit of probability distribution models.

This link聽has the resources from Anna’s workshops.聽鈥�

Note: The video of Anna’s workshop is in four parts.

Part one

Part two

Part three

Part four

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Scholarship Statistics programmes. Tony Stanton (Rutherford College) and Mark Hooper (Otago Boys聽High School) shared their ideas.

Facilitators: Anna Fergusson and Dr Marie Fitch, University of Auckland

Summary of discussion led by Tony Stanton

Tony has been at Rutherford for six years. Each year they have between 5 鈥� 10 students participating in the Scholarship Statistics programme. They don鈥檛 have a strict selection process 鈥� if students are interested they can come to the tutorials. They also look for and target students based on results from previous years and internals for the current year. Student perception can be that Scholarship Statistics is hard but this is not necessarily the case. Tony think there was better retention this year in the programme because students had to pay for entry. The tutorials were run after school starting at the end of term 1 鈥� each one around 1 to 1.5 hours.

Tony used Google classroom and Google docs to set assignments. The idea was that students would try out the questions in the assignments before coming to the session to discuss the answers. This changed over the year so that the sessions were used more for discussion and collaboration within the Scholarship group about the questions set in the assignment. One of the reasons for this was that student often didn鈥檛 know how to start solving the problem themselves. One of the advantages of using Google was direct feedback to students and also students could share their work. Sharing work had to be negotiated with students 鈥� Tony felt some were initially embarrassed about sharing their work. But after a few times of sharing work students gained confidence and could see the merits of this approach. The discussion with students was not always about how to do the question but also about how they were marked e.g. looking at exemplar scripts and looking for what was and what was not accepted by the marker.

Tony mostly used past exam questions, some from SINCOS (mixed quality) and thinks commercial papers like SINCOS could be getting better because there are more years of the re-aligned Scholarship papers available. Students sat a practice exam for Scholarship Statistics at the same time as the school exams, but outside of the timetabled exams as the school does not have a uniform policy for practice exams for Scholarship.

There was some discussion around how students cope with all the Scholarship tutorials. Tony said there was no school policy on timetabling Scholarship sessions and so Scholarship tutors had to negotiate with other subjects. It was also discussed need to take holistic approach with each student and discourage over entry into Scholarship subjects. Scholarship tutors need to avoid pressuring students to take your subject 鈥� think about the whole person and what is best for that student.

Tony would discuss with students how Scholarships are award (around 3% of the cohort of Level 3 statistics students e.g. 200 students roughly 6 students with Scholarship). Some students like to work independently but Tony would really encourage these students to collaborate with others. Food helps as well in terms of motivation to attend sessions.

Tony starts the programme with standards not covered in the Year 13 statistics course (e.g. AS91584 & AS91583 鈥� main ideas being re-randomisation, experimental design, margin of errors, sampling methods), and then includes the topics/standards in the tutorials as they have been covered in class. Tutors also need to remember to cover key ideas from level 2.

Summary of discussion facilitated by Marie Fitch

It can be hard to get students (particularly boys?) to write stuff down so you can mark it and give feedback to them. Suggestions were to look closely at literacy levels of students. Also, competition helps with boys, so if you put a number on what they do (e.g. marks) this can motive them to write. Other ideas were to get students writing on the computer rather than on paper, and use competition through something like Socrative to be the first to get an answer up on the screen for others to see. And idea passed through from Louise Addison鈥檚 workshop earlier in the day was to demand writing 鈥� stand and wait until the students write something and not move on until they do write something (see the resources for Louise鈥檚 workshop).

In terms of selecting students, not many schools participating in the discussion group had a selection process 鈥� mostly let students opt in if they wanted to. One school uses performance in Social Science as a way to pick good writers which seems to work for them Others have a partial selection process in that their accelerated pathway feeds their top students into the Scholarship programme. Some schools encourage their Year 12 students to be involved and see this as an effective way to keep students committed to the programme. There was a reminder to keep the student鈥檚 learning and achievement at the forefront. Their Level 3 achievement should come first.

Friday lunchtime sessions have not worked for some schools, but sessions at McDonalds (twice a year!) were a hit! Before school weekly tutorials are also effective and twice a term on Sunday with Pizza. Another approach was to make Scholarship part of what was taught during class time rather than running separate sessions. If you can, get your Scholarship tutorial timetabled during your non-contact that might work.

In terms of resources, people used things like the Nayland College website, SLC material, chapters from workbooks and the AME Scholarship Statistics workbook. It is important not just to focus on questions and to use the tutorial time to do interesting activities and to get them thinking. For example, using weird or controversial articles from the paper to stimulate discussion or activities 鈥� challenge students to go figure it out! The stats teachers nz facebook page is also a good source of articles or interesting data. The videos from Chris Wild鈥檚 91茄子 to Insight course are also on youtube . The 鈥淎gainst all odds鈥� videos are also quite good (these have been shortened and modernised and are available here . Different applications like whatsap and facebook groups can be used to get collaboration between students. For example, they can take a photo of question, share it with the group, and then contribute answers.

To find out more about how writing is marked, use the schedule but also the exemplars. Look for things that have been ticked and things that have been ignored e.g. students who wrote comments that were too generic. The markers are not looking for waffle but for specific comments with evidence (figures and context). Focus also on the time component with students to guide their writing. They should be hitting key points and the markers are not looking for quantity. Students will need to write more concisely than the internals.

At the moment, appears that probability and probability distributions is not more than one question out of five, and some questions have become more structured 鈥� but you never know what the next exam will look like. If you are going to do a practice exam for Scholarship Statistics in Term 3 you might need to chop down a Scholarship paper, or keep in the questions not yet covered so they can see what鈥檚 in-store. It might also be good practice for them to experience the three hour exam

Don鈥檛 forget you can get access to the copyrighted material used in any exam by logging in to the secure area of the NZQA website (see your SRM for NZQA for more information).

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For the data cards, rather than put/indicate gender on the card, a fictional name, taken from the names of children entered in the 2015 Auckland kids marathon was used.

The relevant questions from the 91茄子 2015 survey are:

Q1, Q2, Q17, Q27 cellphone, facebook, snapchat, Q31 TV, and Q32 reading (the questions can be聽found here).

The diagram below shows what each part of the data card represents:

Download the data cards

Students can explore聽 virtually and ask investigative questions about stickland people. Students choose stickland people for their sample, they can then sort virtually and if required download the sample data into iNZight, CODAP, csv.

For some great teaching notes and ideas for using data cards, check out

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