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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

influential tools for online learning

Online Learning’s ‘Greatest Hits’

Robert Ubell (Columnist)     Feb 20, 2019

https://www.edsurge.com/news/2019-02-20-online-learning-s-greatest-hits

dean of web-based distance learning

Learning Management Systems

Neck and neck for the top spot in the LMS academic vendor race are Blackboard—the early entry and once-dominant player—and coming-up quickly from behind, the relatively new contender, Canvas, each serving about 6.5 million students . The LMS market today is valued at $9.2 billion.

Digital Authoring Systems

Faced with increasingly complex communication technologies—voice, video, multimedia, animation—university faculty, expert in their own disciplines, find themselves technically perplexed, largely unprepared to build digital courses.

instructional designers, long employed by industry, joined online academic teams, working closely with faculty to upload and integrate interactive and engaging content.

nstructional designers, as part of their skillset, turned to digital authoring systems, software introduced to stimulate engagement, encouraging virtual students to interface actively with digital materials, often by tapping at a keyboard or touching the screen as in a video game. Most authoring software also integrates assessment tools, testing learning outcomes.

With authoring software, instructional designers can steer online students through a mixtape of digital content—videos, graphs, weblinks, PDFs, drag-and-drop activities, PowerPoint slides, quizzes, survey tools and so on. Some of the systems also offer video editing, recording and screen downloading options

Adaptive Learning

As with a pinwheel set in motion, insights from many disciplines—artificial intelligence, cognitive science, linguistics, educational psychology and data analytics—have come together to form a relatively new field known as learning science, propelling advances in a new personalized practice—adaptive learning.

MOOCs

Of the top providers, Coursera, the Wall Street-financed company that grew out of the Stanford breakthrough, is the champion with 37 million learners, followed by edX, an MIT-Harvard joint venture, with 18 million. Launched in 2013, XuetangX, the Chinese platform in third place, claims 18 million.

Former Yale President Rick Levin, who served as Coursera’s CEO for a few years, speaking by phone last week, was optimistic about the role MOOCs will play in the digital economy. “The biggest surprise,” Levin argued, “is how strongly MOOCs have been accepted in the corporate world to up-skill employees, especially as the workforce is being transformed by job displacement. It’s the right time for MOOCs to play a major role.”

In virtual education, pedagogy, not technology, drives the metamorphosis from absence to presence, illusion into reality. Skilled online instruction that introduces peer-to-peer learning, virtual teamwork and other pedagogical innovations stimulate active learning. Online learning is not just another edtech product, but an innovative teaching practice. It’s a mistake to think of digital education merely as a device you switch on and off like a garage door.

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more on online learning in this IMS blog
http://blog.stcloudstate.edu/ims?s=online+learning

learning experience design

Building a Learning Innovation Network

https://www.insidehighered.com/digital-learning/blogs/technology-and-learning/building-learning-innovation-network

new interdisciplinary field of learning innovation emerging.

Learning innovation, as conceptualized as an interdisciplinary field, attempts to claim a space at the intersection of design, technology, learning science and analytics — all in the unique context of higher education.

professional associations, such as POD, ELI, UPCEA, (https://upcea.edu/) OLC (https://onlinelearningconsortium.org/), ASU GSV (https://www.asugsvsummit.com/) and SXSW Edu (https://www.sxswedu.com/) — among many other conferences and events put on by professional associations.

A professional community of practice differs from that of an interdisciplinary academic network. Professional communities of practice are connected through shared professional goals. Where best practices and shared experiences form the basis of membership in professional associations, academic networks are situated within marketplaces for ideas. Academic networks run on the generation of new ideas and scholarly exchange. These two network models are different.

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https://elearningindustry.com/learning-experience-design-instructional-design-difference

“Learning Experience Design™ is a synthesis of Instructional Design, educational pedagogy, neuroscience, social sciences, design thinking, and User Experience Design.”

The Process: ADDIE Vs. Design Thinking

The Process: ADDIE Vs. Design Thinking

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more on LX design in this iMS blog
http://blog.stcloudstate.edu/ims?s=learning+design

ARLD 2019

ARLD 2019

Paul Goodman

Technology is a branch of moral philosophy, not of science

The process of making technology is design

Design is a branch of moral philosophy, not of a science

 

System design reflects the designer’s values and the cultural content

Andreas Orphanides

 

Fulbright BOYD

 

Byzantine history professor Bulgarian – all that is 200 years old is politics, not history

 

Access, privacy, equity, values for the prof organization ARLD.

 

Mike Monteiro

This is how bad design makes it out into the world, not due to mailcioius intent, but whith nbo intent at all

 

Cody Hanson

Our expertise, our service ethic, and our values remain our greatest strengths. But for us to have the impat we seek into the lives of our users, we must encode our services and our values in to the software

Ethical design.

Design interprets the world to crate useful objects. Ethical design closes the loop, imaging how those object will affect the world.

 

A good science fiction story should be able to predict not the automobile, ut the traffics jam. Frederic Pohl

Victor Papanek The designer’s social and moral judgement must be brought into play long before she begins to design.

 

We need to fear the consequences of our work more than we love the cleverness of our ideas Mike Monteiro

Analytics

Qual and quan data – lirarainas love data, usage, ILL, course reserves, data –  QQLM.

IDEO – the goal of design research isn’t to collect data, I tis to synthesize information and provide insight and guidance that leads to action.

Google Analytics: the trade off. besides privacy concners. sometimes data and analytics is the only thing we can see.

Frank CHimero – remove a person;s humanity and she is just a curiosity, a pinpoint on a map, a line in a list, an entry in a dbase. a person turns into a granular but of information.

Gale analytics on demand – similar the keynote speaker at Macalester LibTech 2019. https://www.facebook.com/InforMediaServices/posts/1995793570531130?comment_id=1995795043864316&comment_tracking=%7B%22tn%22%3A%22R%22%7D

personas

by designing for yourself or your team, you are potentially building discrimination right into your product Erica Hall.

Search algorithms.

what is relevance. the relevance of the ranking algorithm. for whom (what patron). crummy searches.

reckless associsations – made by humans or computers – can do very real harm especially when they appear in supposedly neutral environments.

Donna Lanclos and Andrew Asher Ethonography should be core to the business of the library.

technology as information ecology. co-evolve. prepare to start asking questions to see the effect of our design choices.

ethnography of library: touch point tours – a student to give a tour to the librarians or draw a map of the library , give a sense what spaces they use, what is important. ethnographish

Q from the audience: if instructors warn against Google and Wikipedia and steer students to library and dbases, how do you now warn about the perils of the dbases bias? A: put fires down, and systematically, try to build into existing initiatives: bi-annual magazine, as many places as can

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