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Hello!
Welcome to our Open Education Resource (OER) on the Quantified Self, a movement in which people use technology such as mobile devices to collect data about their own lives and use this information to improve their well-being (Lee, 2013; Lee et al., 2016; Pappas, 2023; Rust et al., 2016).
If you have ever tracked your steps taken, calories eaten, or sleep cycle, you have engaged in the quantified self movement.
While the quantified self is very established in the health and fitness world - to monitor health-related activities and data (Eynon, 2015), there is an opportunity in education to use data to improve learning behaviours (Pappas, 2023).
(Popov, 2018)
(New Scientist, 2015)
Watch this video for an introduction to the quantified self.
While it is presented in the context of health data and our well-being, it still provides a good introduction to the topic.
Engage with our Sildo and add the ways you may already 'quantify' yourself. This will give our class an idea of how much data and the types of data already being collected about our lives.
quantified self in education
quantified self in education
Eynon (2015) and Rivera-Pelayo et al. (2012) discuss how the quantified self is closely related to learning analytics, which refers to the measurement, collection, analysis and reporting of data for the purposes of understanding and optimising learning (Society for Learning Analytics Research, n.d.). The data that is collected through mobile and wearable technologies provides a rich source of data - data that has not been available before - that can provide information about learners (Pappas, 2023; Rivera-Pelayo et al., 2012).
There is opportunity for learners to gain actionable educational insights about themselves, and there is also opportunity for educators to use this data to better support learners.
Click through the following slides that illustrate the types of data currently collectible via mobile and wearables technologies and the types of educational insights that may derived from this data:
Reflection Question:
What educational insights would you be interested in learning about yourself? What data would be needed to derive these insights and is this data already available?
Share your response to this question on the ETEC 523 blog.
Using data in learning activities
Using data in learning activities
In addition to using data to gain actionable educational insights, Lee (2013) and Lee et al. (2016) discuss how quantified self data can also be used in learning activities. They discuss the need for students to develop more fluency with data and statistical reasoning and discuss activities that give students the opportunity to read, interpret, and engage in active sense-making using their own data.
The following are some examples of how quantified self data can be integrated into learning activities:
'Quantified Recess' where students use activity trackers to get numerical records of activity levels during recess. This can be turned into a class competition and can also be integrated into math and statistics lessons (Lee, 2013).
Collecting and summarizing the class' collective data to find patterns and regularities (Lee, 2013).
Creating visualizations from individual or group data and learning about the different ways data can be presented to convey information.
Reflection Question:
How could you integrate quantified self data into a learning activity? Do the data and tools already exist?
Share your response to this question on the ETEC 523 blog.
Continue to explore:
Continue to explore:
ABOUT THE CREATORS:
ABOUT THE CREATORS:
Shannon W.
Shannon is an educator based in Vancouver, B.C. She is a Chartered Professional Accountant (CPA), meaning that numbers have always been a part of her career. This may explain her interest and passion towards the quantified self.
Shannon strongly believes that everyone should have some degree of financial literacy and this extends to data literacy, to leverage data that is already being collected about us. If we can learn and gain insights to better ourselves, whether healthwise or educationally, we should take advantage of this.
Alan L.
Alan is an educator based in Shanghai, China. He has taught over 8 years and is currently the Science Curriculum Coordinator at the Shanghai United International School - Shangyin Campus.
With a passion for numbers, he has worked hard in leading his school through accreditation, with a focus on school policies and systems on effective assessments, that balances quantitative and qualitative data for the betterment of students.
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