measuring digital professional development

Measuring Digital Professional Development

Analytics for the Use of Web and Social Media Materials

View the slides at facdev.niu.edu/slate14analytics

Presenters

Stephanie RichterAssistant Directorsrichter@niu.edu

Peter GowenOnline Analytics Coordinator

pgowen@niu.edu

The Need for Web and Social Media Analytics

Faculty Development and Instructional Design Center

Faculty Development and Instructional Design Center

niu.edu/facdev

Teaching with Blackboard

niu.edu/blackboard

Academic Integrity Tutorial

niu.edu/ai

Responsible Conduct of Research Tutorial

niu.edu/blackboard

Social Media

@facdev@NIUBlackboard@NIUTeachOnline

facdev facdev

Faculty Development and Instructional Design Center

Web Analytics

Why Web?

• Programs• Services• Resources

* No (or little) “cross-talk”

Analytics

The use of data, statistical analysis, and explanatory and predictive models to gain insights and act on complex issues

Bichsel, 2012, p. 6

On Data

• Data let you answer questions– Are our resources being used?– What is being used?– How are they being used?– Why?*

*May not be possible, or at least not easy

Why Google Analytics?

• Measure utilization easily• Measure behavior (with some work)

• Key terms– Traffic: Pageviews or Users, per given time span– Visits/Sessions: A (default) 30-minute sliding activity

window– Hits/Pageviews: A webpage request from a web

browser– Visitors/Users: A unique ID set by Google per browser

What can GA do?

Screenshot from Google Analytics

What can GA do?

Fall 2013 Spring 2014 Summer 2014

Pageviews 140,951 128,990 39,630Users 48,236 48,462 17,531

Traffic for Teaching w/ Bb,Aug. 16, ‘13 – Aug. 15, ‘14

What can GA do?

95.07% from the US

67.04% from Illinois

Geography of Sessions to Teaching w/ Bb,Aug. 16, ‘13 – Aug. 15, ‘14

~160 countries

What can GA do?

/index/students/safeassign/assess/safeassign/students/index/faq/qa/safeassign

135,20727,635

5,9944,4084105

Deeper analysis:• Traffic over time, per page• Categorizing pages

Top 5 Pages for Teaching w/ Bb

What can GA do?

Top 10 Browsers

Desktop v Mobile

What can GA do?

Top 10 visiting schools

Google Analytics Resources

• Get started with Analytics• How To Set Up Google Analytics Account Setu

p 2014 (YouTube tutorial)

• Setup Checklist (for all/advanced features)

Social Media Analytics

Key Terms

• Users– Follower: someone who sees Twitter posts in their

stream– Like: someone who (maybe) sees your posts on

Facebook in their News Feed– Subscriber: someone who received notifications

of new videos posted on YouTube

Key Terms

• Engagement– Retweet: someone shares your Twitter post with

their followers– Favorite: someone appreciates or approves of

your tweet– Like: someone appreciates or approves of your

Facebook post– Share: someone reposts your Facebook post to

their friends– View: someone begins watching a video on

YouTube

Social Media Presence

@facdev@NIUBlackboard@NIUTeachOnline

facdev facdev

Followers on Twitter

Aug '13 Sep '13 Oct '13 Nov '13 Dec '13 Jan '14 Feb '14 Mar '14 Apr '14 May '14 June '14 July '140

100

200

300

400

500

600

700

800

@facdev @niublackboard @niuteachonline

Twitter Analytics – Tweet activity

Twitter Analytics - Followers

8/13 9/13 10/13 11/13 12/13 1/14 2/14 3/14 4/14150

155

160

165

170

175

180

185

190

195

200

facdev

Likes on Facebook

Facebook Insights

Views on YouTube

8/13 9/13 10/13 11/13 12/13 1/14 2/14 3/14 4/140

200

400

600

800

1000

1200

1400

facdev

YouTube Analytics

Conclusions

What We Have Learned

• Online resources are heavily used, at NIU and around the world

• Top pages are a priority for updates• Popular topics may need additional workshops• Mobile users are a small but growing group• Significant site traffic comes from other

universities and colleges• Social media engagement is growing but

needs further analysis

Next Steps

• Look at traffic to segments of content instead of single pages

• Identify trends in topics over time • Compare trends to consultation trends and

workshop schedule• Investigate user behavior more deeply – page visits vs. searches – page visits vs. question submission– in-page behavior

Questions?

Stephanie Richtersrichter@niu.edu

Peter Gowenpgowen@niu.edu

View the slides at facdev.niu.edu/slate14analytics

References

• Bichsel, J., 2012. Analytics in higher education: Benefits, barriers, progress, and recommendations. Louisville, CO: EDUCAUSE Center for Applied Research. Available from: http://net.educause.edu/ir/library/pdf/ERS1207/ers1207.pdf [Accessed 21 February 2014].