Searching for "analytics"

Twitter Social Media Analytics

#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.

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more on social media analytics in this blog

https://blog.stcloudstate.edu/ims?s=social+media+analytics

analytics in education

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.

my notes:

open academic analytics initiative
https://confluence.sakaiproject.org/pages/viewpage.action?pageId=75671025

where data comes from:

  • students information systems (SIS)
  • LMS
  • Publishers
  • Clickers
  • Video streaming and web conferencing
  • Surveys
  • Co-curricular and extra-curricular involvement

D2L degree compass
Predictive Analytics Reportitng PAR – was open, but just bought by Hobsons (https://www.hobsons.com/)

Learning Analytics

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

librarians:
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

questions:
pole analytics library

 

 

 

 

 

 

 

 

 

 

 

 

 

 

literature

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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More on analytics in this blog:

https://blog.stcloudstate.edu/ims/?s=analytics&submit=Search

data analytics education

Analytics for Achievement: White Paper

Around the world, in both developing and developed countries, too many primary and secondary students are falling below proficiency levels. Measuring and monitoring performance and understanding the factors at play in student achievement can help educators create the right conditions and design the most effective interventions for student success.

link to the article (PDF file) ; THE_IBM_data_Analytics_for_Achievement k12

learning analytics

ACRL e-Learning webcast series: Learning Analytics – Strategies for Optimizing Student Data on Your Campus

http://www.ala.org/acrl/learninganalytics

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

Webcast Two: Privacy and the Online Classroom: Learning Analytics, Ethical Considerations, and Responsible Practice
April 13, 2016

Webcast Three: Moving Beyond Counts and Check Marks: Bringing the Library into Campus-Wide Learning Analytics Programs
May 11, 2016

Predictive Analytics

Educational Intelligence and the Student Lifecycle – Leveraging Predictive Analytics for Profit in Higher Education

This presentation will begin on Wednesday, August 12, 2015 at 02:00 PM Eastern Daylight Time.

Wednesday, August 12, 2015 02:00 PM EDT

This webinar will provide an overview of the student lifecycle – from lead generation to job placement. You will learn what the components are and how student data can be leveraged for competitive gain through the use of predictive analytics tools. While these technologies have been in use by other industries for many years, especially in the area of assessing consumer demand, higher education is a relatively late adopter. As an example of benefit, colleges and universities can deploy them to determine which students are most at risk for attrition and – armed with deep, historical data – craft segment-specific retention strategies designed to compel them to persist toward degree completion. During this session, Eduventures analysts will provide concrete examples of how predictive analytics has been used within the student lifecycle at a variety of institutions, citing interviews with practitioners, that led to measurable performance improvements. To conclude, we will uncover the benefits of sharing data amongst key stakeholders to the ultimate gain of the institution and its constituents.

Speakers:

Jeff Alderson
Principal Analyst
Max Woolf
Senior Analyst

Audience members may arrive 15 minutes in advance of this time.

 

Twitter Analytics

How to Improve Your Tweets Using Twitter Analytics

http://www.socialmediaexaminer.com/improve-tweets-using-twitter-analytics/

Twitter ads and Twitonomy are helpful and cost-effective. Find time to go through these reports to see what works for you and your competition. The improvement in results from your Twitter marketing will be worth it.

Once you get comfortable with this kind of data review, check back every week, month or quarter to make sure that you are still hitting the optimal mark. The social media world moves fast, and analytics will help you keep pace with the changes.

mobile technology, badges, flipped classrooms, and learning analytics according to Bryan Alexander

Very short video of Bryan Alexander, senior fellow at the National Institute for Technology in Liberal Education, discussing the issues and opportunities facing mobile technology, badges, flipped classrooms, and learning analytics: 

http://online.qmags.com/CPT0113/default.aspx?sessionID=C711175DBEE9188D0D93C2F28&cid=2335187&eid=17730&pg=18&mode=2#pg18&mode1

personalized learning and achievement gap

https://www.edsurge.com/news/2022-03-28-can-personalized-learning-be-scaled-to-ease-teacher-burdens-and-close-achievement-gaps

McGraw Hill Plus, a new tool, Focusing first on math and then expanding to ELA and science, its objective is to make personalized learning scalable.

Smith: The modern classroom sits at the intersection of blended learning, competency-based learning and personalized learning.

reimagine instructional time and use technology to scale personalized learning.

First, pulling data into one place is the key fundamental driver that will change the teacher workflow. Second, we need to manipulate that data into some advanced data visualization tools, so it’s easy for teachers to understand and use. Third, we need to be able to visualize student performance and take action on it.
Using these data analytics, we can drive personalized learning based on student performance. And the last thing is the automation of teacher workflow.

eachers get data visualization from different sources, such as an adaptive software solution like our ALEKS program, our Redbird Mathematics, or our recently acquired Achieve3000 Literacy.

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