Linzi's EDC blog

This video helps to illustrate the issues of hyperextension. While some young dancers and even uneducated teachers post videos and images online of unsafe practice, professionals such as Misty Copeland or physiotherapists specialising in dance can educate the dance population. Videos that demonstrate how to control physical defects, bad habits or how to execute technical exercises not only safely but well can allow progression without injury. There are many videos available but unless a young dancer is following the online activity of a physiotherapist (which is doubtful) algorithms will not influence the distribution. Inspirational performers that are advocates within the dance industry and profession can help distribute important safety guidelines by releasing short videos like the one above. We all love to have a youtube binge which involves watching countless videos of our favourite singer, dancer or speaker through TED talks. Algorithms can sometimes guide us in the right direction and if more videos like this are produced then hopefully we can educate young dancers and (teachers) of today.

 This video and information provided below is what I feel describes Williamson’s (2014 p.98) description of ‘smart’ pedagogic systems created from Learning Analytics(LA).  By using LA in this way we can create an academic and psychometric profile for each individual user which can be compared and matched with an entire population of user profiles.

References:

Williamson, B. (2014). Governing software: Networks, databases an algorithmic power in the digital governance of public education. Learning, Media an dTechnology, 40(1), 83-105. DOI: 10.1080/17439884.2014.924527

Description from YouTube:

Insight is the world’s first intelligent learning system that provides objective and detailed measurement and analysis of early vision and cognition behaviours using eye gaze technology.
Featuring engaging small step progressive teaching activities delivered at the right level and pace for each individual’s unique learning style.Core Skills Assessment

Insight uses Intelligent Analytics, based on real data, designed to meet the needs of students with complex physical, intellectual and sensory disabilities.

Progression Map

Insight has specially designed activities arranged in a Progressive Road Map of skills with small incremental steps to ensure success and motivation at each learning stage. Each activity has been mapped to well-respected special education assessment and teaching techniques plus the latest clinical theories.

Insight Analysis

Insight provides detailed eye gaze analysis and interpretation of students’ behaviours and offers an invaluable insight into students’ strengths and areas of difficulty to help inform all teaching practice. Insight is the first of it’s kind to offer unique calibration and device independent scores to include all learners.

Progress Tracking

Teachers can now track performance in all learning goals to give a snapshot of overall progress whilst evaluating performance over time. Insight will also compare an individual’s performance to that of similar peers across the globe – a world first!

Insight provides objective intelligent suggestions that guide activity choices based on scores, skill progression plus eye gaze data from peer groups. Activities are recommended across a range of learning goals to suit individualised learning styles.

I’m still catching up with last week after a full on work load but I am finding this youtube video useful to retain information related to big data and Learning Analytics. Videos are fortunately good as they can be reviewed over and paused when taking notes. It’s agreed by many scholars and the articles that I read that there is an insane amount of data available if not too much data – most in the  learning context goes unanalysed. Information overload present a challenge to researchers but in particular the teachers who are trying to develop the learning environment. Difficulties collecting data is caused by the bureaucracies in some schools. Privacy and ethics come in to play so study can only take place with data collected or the dat that already exists (Eynon, 2013).  Boyd and Crawford (2012)  ask the question regarding what is and is not quantifiable knowledge in the social domain?

References:

Boyd, Danah, & Crawford, K. (2012). CRITICAL QUESTIONS FOR THE BIG DATA. Information, Communication & society, 15(5), 662-679. DOI: 10.1080/1369118x.2012.678878

Eynon, R. (2013). The rise of big data: What does it mean for education, technology, and media research? Learning, Media and technology, 38(3), 237-240. DOI. 1080/17439884.2013.771783.

Liked on YouTube: Week 1: Introduction to Learning Analytics https://youtu.be/idHxNSTZhNM

References:

Beer, D. (2016). The social power of algorithms. Information, Communication & Society, 20(1), 1-13. DOI: 10.1080/1369118x.2016.1216147

Boyd, Danah, & Crawford, K. (2012). CRITICAL QUESTIONS FOR THE BIG DATA. Information, Communication & society, 15(5), 662-679. DOI: 10.1080/1369118x.2012.678878

Liked on YouTube: Experience the Shakespeare Shuffle in 360 https://youtu.be/GM8hscEqD3M

We were sent course details at the beginning of the course and given instructions to set up our personal blogs. This video was used as an example for the IFTTT feeds. I watched the video during the preparation week and it went  over my head as I couldn’t put it into context. It has since popped up in other blogs during the community cultures block and again through algorithms it has popped up in my YouTube video recommendations. This time the viewing was not only digestible but engaging, maybe I’m making progress after all!