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Data Visualisation A learning activity for statistics and probability.

Data Visualisation A learning activity for statistics and probability. A presentation by: Wendy Lewis, Kristy Nardelli , Chanel Scheman , Benjamin Sua , Anna Verren & Jing Wang (Anna). Lesson activity overview. Students will need access to computers for this activity

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Data Visualisation A learning activity for statistics and probability.

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  1. Data VisualisationA learning activity for statistics and probability. A presentation by: Wendy Lewis, Kristy Nardelli, Chanel Scheman, Benjamin Sua, Anna Verren & Jing Wang (Anna)

  2. Lesson activity overview • Students will need access to computers for this activity • First lesson is about showing students YouTube clips outlining Data Visualisation, get students to register at ManyEyes and learning how to use the website • http://www-958.ibm.com/software/data/cognos/manyeyes/ • The Activity will be presented to students on a handout (see Appendix A) they can read through this then the students need to form small groups (3 – 5) • Students are to decide who will to what on the task

  3. Lesson activity overview (continued) • The activity is based on a factitious job of helping a TV channel change their programing. This activity consists of three task. • Task 1: Students are required to create and conduct a survey asking participants to rate 4 TV programs. This data is then used to create a data visualisation using the many eyes website • Task 2: Students use real world data from a table of Screen Australia to create a data visualisation which shows what age group watches the most TV

  4. Lesson activity overview (continued) • Task 3: students visit website with national TV ratings available and compare these ratings to their findings. • Task 4: Students write a report summarizing their findings and decisions from Task 1, 2 & 3. the Students are required to inclued several statistical descriptions of their data. • Task 5: Each student keeps a day to day journal about the participation in their group and how/ why certain decisions are made.

  5. Demonstrations Data Visualisation Using Many Eye http://www.youtube.com/watch?v=MNer7wAdjxU http://www.youtube.com/watch?v=xekEXM0Vonc

  6. Innovative Teaching and learning dimensions. • Collaboration • The students work in groups to create their surveys, data visualisations and then a group report on the decisions that they have made. • By keeping journals students must share responsibility of the work • Knowledge building • Groups will have to evaluate the information given and the data they collect to determine what information/ data they use and how they will use it. They will then need to analyse their data to make decisions.

  7. Innovative Teaching and learning dimensions. (continued) • Use of ICT for learning • By using data visualisation software students will be able to create displays which are accurate, clear, and well organised. They could do this by hand, but would likely face problems with the layout and consistence of size/ shape/ colour in their data visualisations. • These data visualisations will allow students to see what the data is representing, more clearly than tables alone. • Students use the internet to find information on TV ratings and viewing habits in Australia. ICT makes this a lot more practical

  8. Innovative Teaching and learning dimensions. (continued) • Self-regulation • The students will be given a time frame in which to complete this task (2 lessons), however students will be allowed to choose who in the groups does what task and what order they do them in. • Real-world problem solving and innovation. • This task requires students to collect and compare two sets of real data, one they collect and one taken from a website. Their findings are then shared with their school community.

  9. Timeframe • This activitycould be taught over four lessons. • These lessons don't have to be consecutive, lessons between activity lessons could be used to teach other content • The first lesson would include investigating and demonstrating data visualisations, constructing and conducting the survey. • The during the remaining three lessons students would have to manage their own time to complete all components of the activity

  10. Syllabusoutcomes and dot points Mathematics: Stage 4 Outcome: A student... • Communicatesand connects mathematical ideas using appropriate terminology, diagrams and symbols (MA4-1WM) • Recognisesand explains mathematical relationships using reasoning(MA4-3WM) • Collects, represents and interprets single sets of data, using appropriate statistical displays (MA4-19SP) (Mathematics K-10 Draft Syllabus Version 2)

  11. Syllabusoutcomes and dot points Mathematics: Stage 4 Students... • Investigate techniques for collecting data, including census, sampling and observation (ACMSP284) • Identify and investigate issues involving numerical data collected from primary and secondary sources (ACMSP169) (Mathematics K-10 Draft Syllabus Version 2)

  12. References • ITL research information retrieved from http://www.itlresearch.com/images/stories/reports/ITL%20LEAP21%20Learning%20Activity%20Rubrics%20-%202012.pdf • Syllabus information retrieved from http://boardofstudies.nsw.edu.au/syllabus-draft-k10/version-2.html

  13. Appendix A • Channel Seven Programing Project • https://docs.google.com/document/d/1yZZgnQxyx8u6RSi-e1FNYcp87ogxWddmz9w-Oj547bI/edit

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