Mentee Minute
March 3, 2014 - Volume 10 - Data Analysis
Data Analysis
Data Analysis presents a category in which online learning has a distinct advantage over face to face instruction. The amount of data and more importantly the quality of the data available is a useful tool for ensuring student success. Advanced data analysis by online instructors is still in the preliminary stages. The primary purpose of adding this element to the observation rubric is to begin the discussion and reflect on the possible best practices.
School-wide Goal #3:
100% of teachers show evidence of utilizing data analysis tools in order to improve student achievement.
Data Analysis Interview with Dr. Joe Cozart, Associate Director of Strategic Planning
1) Why should GaVS instructors use data analysis?
The wealth of data available in online classrooms gives it a distinct advantage over traditional classrooms so if instructors fail to use that data, then the class risks becoming basically the same as the old traditional classroom, just with a different delivery model. The data can inform instructors on how well students are learning, what gaps in knowledge exist, how to best group students, and what topics students need more help in just to name a few examples.
2) Which analytics report do you find most easy to use? Why?
The large gradebook heatmap is the easiest report to utilize. There is only one filter to set, with only one checkbox. So you just click to show students then click run report. The report then shows grade items sorted by worst performance overall to best. By viewing the lower assignments, teachers can quickly see if there is a type of assignment or overall unit where students disproportionately struggle. Also, the color ratings provide a quick visual on grade distributions. So, if there are lots of 100s and 0s, the grade is not discriminating well, it is just a participation grade and teachers might consider removing that assignment.
3) Which analysis report do you find most beneficial? Why?
The tool usage report is a great way to see how active each student is in the course from a single page. This can give great information to share with students and parents when calling or emailing. By understanding what tools students use, a teacher can provide training to the class on underutilized tools and give more attention to the tools students seem to find the most helpful.
4) Are there other resources you recommend for instructors who want to learn more about data analysis?
This is an increasingly popular area in online learning so there is a wealth of sites, articles, and videos in learning analytics. A few popular ones are below. Also, if you are really interested, keep an eye out for Massive Open Online Courses (MOOCs) in learning analytics.
JIT Data Analysis Resources
Where Can I Learn More?
Videos
For those of you who learn best from video, a body of lectures and interviews is starting to grow:
Learning Analytics. Strata 2012 Keynote, Steve Schoettler
Envisioning a System-wide Learning Analytics Platform. International Higher Education 2011 Keynote Address, George Siemens
Learning Analytics: Dream, Nightmare or Fairydust? Ascilite 2011 Keynote Address, Simon Buckingham Shum
Interviews with Learning Analytics researchers, Athabasca University MOOC
Learning Analytics Invited Lecture Series, Athabasca University MOOC
Video replays from International Conference on Learning Analytics & Knowledge
Introductory Articles
UNESCO Policy Brief: Learning Analytics (Simon Buckingham Shum, Nov. 2012)
Penetrating the Fog: Analytics in Learning and Education. Phil Long and George Siemens (2011), EDUCAUSE Review Online, 46, 5, pp.31-40
JISC CETIS Analytics Series of reports for educational institutions (2012)
Learning Analytics: Moving from Concept to Practice. Malcolm Brown (2012), EDUCAUSE Learning Initiative Briefing (and many other EDUCAUSE analytics reports)
Data and Reflection Examples: Kudos to our spotlight faculty
Smore Analytics
Quiz Statistics for Targeted Remediation
Quiz Statistics for Targeting Difficult Concepts
Words are equally valuable when using data.
Heat maps can be useful to see a wide variety of scores.
How to start a data analysis reflection.
HELP VIDEOS FOR DATA ANALYSIS
General Reminders
Requirements for EPortfolio for March:
- 1 artifact of professional development with reflection
- 1 data analysis on grades with reflection
- 1 best teaching practice
- 1 differentiation example
Be sure to send out TheSIS progress reports Tuesday March 4th in addition to your course updates and failure calls.
Spring break is April 7-11.
Cool Tool Feature - Kelly Gardner
MLA Example: http://blnds.co/19Pfyfa
Blendspace: https://www.blendspace.com/lessons
How to Read Your Evaluation
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Authors
Kelly Gardner ~ GaVS 2012/2013 & 2013/2014 Teacher of the Year Finalist; GaVS English Department Mentor; GaVS English Instructor since 2007