Using and interpreting data in schools
ACER-accredited short courses
More dates coming soon.
ACER-accredited short courses
More dates coming soon.
Using and interpreting data in schools
ACER accredited online course
Description
This course is a foundation level professional learning program focused on developing teachers’ expertise in using and interpreting different types of data in a school context. It is designed for teachers and school leaders who wish to build solid shared understandings and shared language about the kinds of data used in schools, the different ways in which data can be represented, and what they can tell teachers about student learning.
For schools progressing through the Progressive Achievement Learning Series this course would be appropriate at Phases 1–4.
A fully facilitated course
ACER-accredited online courses provide a highly interactive experience supported by an experienced facilitator. The course design encourages interaction and collaboration in conjunction with appropriate and effective pedagogies. The online facilitator in your course will promote interaction and communication among participants through building and conveying knowledge and modelling relevant skills.
Recommended prior learning
This foundation course has no recommended prior learning.
Intended learning outcomes
Participants will be able to:
This course focuses on Professional Standard 5 at the Graduate, Proficient, Highly Accomplished and Lead levels.
This course focuses on Professional Standard 5: Assess, provide feedback and report on student learning, particularly Professional Standard 5.4. Interpret student data.
This course is targeted to the teaching levels indicated in the table below.
| Graduate appropriate for this level | Proficient appropriate for this level | Highly Accomplished appropriate for this level | Lead appropriate for this level |
|---|---|---|---|
|
Demonstrate understanding of assessment strategies, including informal and formal, diagnostic, formative and summative approaches to assessing student learning. |
Use student assessment data to analyse and evaluate student understanding of subject/content, identifying interventions and modifying teaching practice. |
Work with colleagues to use data from internal and external student assessments for evaluating learning and teaching, identifying interventions and modifying teaching practice. |
Coordinate student performance and program evaluation using internal and external student assessment data to improve teaching practice. |
Course in detail
The course is delivered online and consists of a number of modules and assessments. The modules are interactive and participants work through examples and activities to build skills and knowledge.
Module 1: Introduction to data
This is a gentle introductory module that defines key terms and concepts. Topics include, items and values, data collection, and a data collection scenario.
Module 2: Data in schools
This module gives examples of school data and how to record, organise, examine, make inferences and test hypotheses with data, and shows how you can focus on your purpose for using the data available to you.
Module 3: Assessment and measurement scales
This module introduces the four scales of measurement, how to summarise data with each scale of measurement, and includes case studies of school assessment data, and psychometric modelling.
Module 4: How can data be represented?
This module focuses on organising data to tell a story. There are two case studies, representing data in tables, and demographic variables. Topics covered include measures of central tendency, mean, median and mode, measure of spread, different shapes of normal distributions and using standard deviation to analyse distributions.
Module 5: Measure of central tendency
This module examines what the three measures of central tendency are and how they are determined. It looks at when it is useful to determine the mean, median and/or mode and what the respective advantages and disadvantages of bar graphs, line graphs, pie charts and scatter plots are.
Module 6: Measures of spread
This module examines what the 'range' of data is and how it can be determined, what quartiles and the IQR are and why are they are important. It looks at the various components of a box plot and what the advantages of using box plots are and the circumstances in which they should be used.
Module 7: Measures of spread: means, standard deviations and histograms
This module examines what normal distributions are and how can they be used. It looks at standard deviations, and how are they calculated, components of a histogram and the different shapes distribution of data can form.
Module 8: What data can tell us about…
This module investigates educational reports and focuses on the questions to consider when reading data. It includes how to find meaning from locally and externally generated reports. It looks at school and system level data, how to interpret ICSEA and national and international data.
Module 9: Comparing data
This module focuses on comparing data locally and globally, comparing data mathematically and visually, and comparing statistical samples. It introduces an independent research activity relevant to your work context.
Module 10: Data for research
In this module, participants learn how to build on the knowledge gained in this course to further data analysis expertise. It suggests pertinent questions to ask when researching, and the factors that influence learning outcomes.
Standard courses are 20 hours over 10 weeks. However, we will be happy to run tailored intensive courses to suit individual schools. Please contact us to discuss details.
Learning assurance tasks
A multiple-choice quiz, and a data manipulation task.
On successful completion of this course, participants will receive an ACER certificate of achievement.
Course mode: Online
Course duration: 20 hours over 10 weeks
Resources: All resources are included in the course
Cost: $660.00 (including GST)
For further information please contact the Student Administrator
ph: +61 3 9277 5202
e: courses@acer.org
courses@acer.org
03 9277 5202