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 Reviewcase studies, see how Drake University, the University of Tennessee, and the University of Montana improved their analytics initiatives through data integrations and governance.
In an article entitled ‘Why Vine Died,’ Casey Newman reported the following, “Former executives say that a major competitive challenged emerged in the form of Instagram, which introduced 15-second video clips in June 2013.
Instagram remained stable with the introduction of new features like stories and video channels, resources of it’s parent company, Facebook, and the introduction of ads to the platform that look very similar to the posts in a user’s feed.
In addition to a total logo redesign, Instagram shifted its focus from just pictures, to longer video (from 15 sec. to one minute) and direct messaging features, such as group posts and disappearing video. Explore Channels in Discover let people discover new photo and video content based on interests. Instagram Stories added a new element to the Instagram experience showing highlights from friends, celebrities and businesses one follows without interfering with their feed. Instagram also caters to business needs through its Instagram for Business platform that allows for instant contact, detailed analytics and easy-to-follow linked content.
Most recently, Instagram released live video in their stories feature. Users can start a live stream in their Instagram story and view comments and feedback from their viewers in real time! This feature is similar to apps like musical.ly and live.ly which has over 80 million users and 62% of its users are under 21.
#StudentVoices #MillennialMondays #WhatToWatch
#MillennialMondays is a new series that aims to discuss relevant topics on careers and business from a millennial perspective.
In scholarly and scientific publishing, altmetrics are non-traditional metrics proposed as an alternative to more traditional citation impact metrics, such as impact factor and h-index. The term altmetrics was proposed in 2010, as a generalization of article level metrics, and has its roots in the #altmetrics hashtag. Although altmetrics are often thought of as metrics about articles, they can be applied to people, journals, books, data sets, presentations, videos, source code repositories, web pages, etc. They are related to Webometrics, which had similar goals but evolved before the social web. Altmetrics did not originally cover citation counts. It also covers other aspects of the impact of a work, such as how many data and knowledge bases refer to it, article views, downloads, or mentions in social media and news media.
more on analytics and metrics in education in this IMS blog
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.
As you may be aware that TERI is a global think-tank knowledge driven organisation working in the field of Energy, Environment and Sustainable Development. TERI is organising it’s one of the flagship event ICDL 2016 from
13 to 16 December, 2016 at India Habitat Center, Lodhi Road, New Delhi. The theme of the conference is “Smart Future: Knowledge Trends that will Change the World”. (URL: http://www.teriin.org/events/icdl/)
As we understand that in the current scenario all enterprises are heading towards Digital Transformation, which derives business value for an effective decision making process. To be a part of this transformation strategy, all stakeholders at various levels should be aware of certain pertinent components, which are mentioned below. This conference is a unique platform to brainstorm and network with leading speakers and digital luminaries. Some of the major thrust areas to be covered are:
Innovation and Knowledge Management
Big Data and Analytics
Social Media and Analytics
Internet of Things (IoT)
To get yourself and your team to engage in one of these issues, we would request you to kindly share your skills, expertise and experiences with audiences in this thought provoking and stimulating interactive platform of ICDL 2016.
The U.S. Bureau of Labor Statistics backs that up, predicting that employment of statisticians will grow 34 percent between 2014 and 2024. Not surprisingly, the bureau notes, that is “much faster than the average for all occupations.”
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.
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
7 Things You Should Know About First-Generation Learning Analytics. Published:
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.”