The Absolute Beginner’s Guide to Google Analytics
Kristi Hines June 24th, 2015
- How many people visit my website?
- Where do my visitors live?
- Do I need a mobile-friendly website?
- What websites send traffic to my website?
- What marketing tactics drive the most traffic to my website?
- Which pages on my website are the most popular?
- How many visitors have I converted into leads or customers?
- Where did my converting visitors come from and go on my website?
- How can I improve my website’s speed?
- What blog content do my visitors like the most?
a Google Analytics account. If you have a primary Google account that you use for other services like Gmail, Google Drive, Google Calendar, Google+, or YouTube, then you should set up your Google Analytics using that Google account. Or you will need to create a new one.
Big tip: don’t let your anyone (your web designer, web developer, web host, SEO person, etc.) create your website’s Google Analytics account under their own Google account so they can “manage” it for you. If you and this person part ways, they will take your Google Analytics data with them, and you will have to start all over.
go to Google Analytics and click the Sign into Google Analytics button.
Google Analytics offers hierarchies to organize your account. You can have up to 100 Google Analytics accounts under one Google account. You can have up to 50 website properties under one Google Analytics account. You can have up to 25 views under one website property.
more on Google Analytics in this IMS blog
Data Analytics a Key Skill for Administrators in K–12
A recent report highlights how data can open the door for K-12 school administrators to maximize student outcomes.
Report authors also call on state policymakers to help lead the charge for more literate school administrators. School and district administrators need to model and support effective data use at every level, including as part of classroom instruction
more on data analytics in education in this IMS blog
Supporting Analytics through Data Integration and Governance
Support analytics initiatives with data integration and governance. The changing landscape of enterprise IT is characterized by an expanding set of services, systems, and sourcing strategies. Data governance, cross-enterprise partnerships, and data integration are key ingredients in supporting higher education’s growing need for reliable information.
Enterprise IT Case Studies
In this set of EDUCAUSE Review case studies, see how Drake University, the University of Tennessee, and the University of Montana improved their analytics initiatives through data integrations and governance.
more on analytics in this IMS blog
Free Webinar: Driving Decisions With Data
with Analytics On Demand, you can add value to your library’s existing data and unlock key insights about your community.
Monday, July 24, 2017 12 p.m. Central
Tune in to this free 60-minute webcast Joining us for this webinar are:
- Jason Kucsma, deputy director, Toledo Lucas County (Ohio) Public Library
- Liz Bondie, education sales consultant, Gale, a Cengage company
more on data analytics in this IMS blog
Call for Chapters: Responsible Analytics and Data Mining in Education
• Who collects and controls the data?
• Is it accessible to all stakeholders?
• How are the data being used, and is there a possibility for abuse?
• How do we assess data quality?
• Who determines which data to trust and use?
• What happens when the data analysis yields flawed results?
• How do we ensure due process when data-driven errors are uncovered?
• What policies are in place to address errors?
• Is there a plan for handling data breaches?
Call for Chapter Proposals page (https://big-data-in-education.blogspot.com)
more on data mining in this IMS blog
more on analytics in this IMS blog
Call For Chapters: Responsible Analytics and Data Mining in Education: Global Perspectives on Quality, Support, and Decision-Making
SUBMIT A 1-2 PAGE CHAPTER PROPOSAL
Deadline – June 1, 2017
Title: Responsible Analytics and Data Mining in Education: Global Perspectives on Quality, Support, and Decision-Making
Due to rapid advancements in our ability to collect, process, and analyze massive amounts of data, it is now possible for educators at all levels to gain new insights into how people learn. According to Bainbridge, et. al. (2015), using simple learning analytics models, educators now have the tools to identify, with up to 80% accuracy, which students are at the greatest risk of failure before classes even begin. As we consider the enormous potential of data analytics and data mining in education, we must also recognize a myriad of emerging issues and potential consequences—intentional and unintentional—to implement them responsibly. For example:
· Who collects and controls the data?
· Is it accessible to all stakeholders?
· How are the data being used, and is there a possibility for abuse?
· How do we assess data quality?
· Who determines which data to trust and use?
· What happens when the data analysis yields flawed results?
· How do we ensure due process when data-driven errors are uncovered?
· What policies are in place to address errors?
· Is there a plan for handling data breaches?
This book, published by Routledge Taylor & Francis Group, will provide insights and support for policy makers, administrators, faculty, and IT personnel on issues pertaining the responsible use data analytics and data mining in education.
· June 1, 2017 – Chapter proposal submission deadline
· July 15, 2017 – Proposal decision notification
· October 15, 2017 – Full chapter submission deadline
· December 1, 2017 – Full chapter decision notification
· January 15, 2018 – Full chapter revisions due
more on data mining in this IMS blog
more on analytics in this IMS blog
#1: Adjust Your Content Mix
On Facebook, go to Insights > Posts > Post Types to review the engagement by the type of content you posted (post, link, image, video). On Twitter, you can see a snapshot of each post you’ve made by going to Settings > Analytics > Tweets.
#2: Fine-tune Your Posting Schedule
On Facebook, go to Insights > Posts > When Your Fans Are Online. For Twitter, you can use a tool such a Tweriod to find out when the bulk of your followers are online.
#3: Inform Your Messaging
On Facebook, open the Ads Manager and go to Audience Insights. On Twitter, you can check your audience data by going to Settings > Twitter Ads > Analytics > Audience Insights.
#4: Boost Your Engagement
On Twitter, go to Settings > Analytics > Tweets and take a look at which post topics get the most engagement. On Facebook, go to Insights > Posts > Post Types and then switch the engagement metrics in Facebook to show reactions, comments, and shares for each post rather than post clicks or general engagement.
more on social media analytics in this blog
ACRL e-Learning webcast series: Learning Analytics – Strategies for Optimizing Student Data on Your Campus
This three-part webinar series, co-sponsored by the ACRL Value of Academic Libraries Committee, the Student Learning and Information Committee, and the ACRL Instruction Section, will explore the advantages and opportunities of learning analytics as a tool which uses student data to demonstrate library impact and to identify learning weaknesses. How can librarians initiate learning analytics initiatives on their campuses and contribute to existing collaborations? The first webinar will provide an introduction to learning analytics and an overview of important issues. The second will focus on privacy issues and other ethical considerations as well as responsible practice, and the third will include a panel of librarians who are successfully using learning analytics on their campuses.
Webcast One: Learning Analytics and the Academic Library: The State of the Art and the Art of Connecting the Library with Campus Initiatives
March 29, 2016
Learning analytics are used nationwide to augment student success initiatives as well as bolster other institutional priorities. As a key aspect of educational reform and institutional improvement, learning analytics are essential to defining the value of higher education, and academic librarians can be both of great service to and well served by institutional learning analytics teams. In addition, librarians who seek to demonstrate, articulate, and grow the value of academic libraries should become more aware of how they can dovetail their efforts with institutional learning analytics projects. However, all too often, academic librarians are not asked to be part of initial learning analytics teams on their campuses, despite the benefits of library inclusion in these efforts. Librarians can counteract this trend by being conversant in learning analytics goals, advantages/disadvantages, and challenges as well as aware of existing examples of library successes in learning analytics projects.
Learn about the state of the art in learning analytics in higher education with an emphasis on 1) current models, 2) best practices, 3) ethics, privacy, and other difficult issues. The webcast will also focus on current academic library projects and successes in gaining access to and inclusion in learning analytics initiatives on their campus. Benefit from the inclusion of a “short list” of must-read resources as well as a clearly defined list of ways in which librarians can leverage their skills to be both contributing members of learning analytics teams, suitable for use in advocating on their campuses.
open academic analytics initiative
where data comes from:
- students information systems (SIS)
- Video streaming and web conferencing
- Co-curricular and extra-curricular involvement
D2L degree compass
Predictive Analytics Reportitng PAR – was open, but just bought by Hobsons (https://www.hobsons.com/)
IMS Caliper Enabled Services. the way to connect the library in the campus analytics https://www.imsglobal.org/activity/caliperram
student’s opinion of this process
benefits: self-assessment, personal learning, empwerment
analytics and data privacy – students are OK with harvesting the data (only 6% not happy)
8 in 10 are interested in personal dashboard, which will help them perform
Big Mother vs Big Brother: creepy vs helpful. tracking classes, helpful, out of class (where on campus, social media etc) is creepy. 87% see that having access to their data is positive
recognize metrics, assessment, analytics, data. visualization, data literacy, data science, interpretation
INSTRUCTION DEPARTMENT – N.B.
determine who is the key leader: director of institutional research, president, CIO
who does analyics services: institutional research, information technology, dedicated center
analytic maturity: data drivin, decision making culture; senior leadership commitment,; policy supporting (data ollection, accsess, use): data efficacy; investment and resourcefs; staffing; technical infrastrcture; information technology interaction
student success maturity: senior leader commited; fudning of student success efforts; mechanism for making student success decisions; interdepart collaboration; undrestanding of students success goals; advising and student support ability; policies; information systems
developing learning analytics strategy
understand institutional challenges; identify stakeholders; identify inhibitors/challenges; consider tools; scan the environment and see what other done; develop a plan; communicate the plan to stakeholders; start small and build
ways librarians can help
idenfify institu partners; be the partners; hone relevant learning analytics; participate in institutional analytics; identify questions and problems; access and work to improve institu culture; volunteer to be early adopters;
questions to ask: environmental scanning
do we have a learning analytics system? does our culture support? leaders present? stakeholders need to know?
questions to ask: Data
questions to ask: Library role
learning analytics & the academic library: the state of the art of connecting the library with campus initiatives
causation versus correlation studies. speakers claims that it is difficult to establish causation argument. institutions try to predict as accurately as possible via correlation, versus “if you do that it will happen what.”
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