Posts Tagged ‘Predictive Analytics’

Susan Grajek at Bryan Alexander on IT and education

Susan Grajek at Bryan Alexander on IT and education

Forum takes a deep dive into higher education and technology. On Thursday, March 23rd, from 2-3 pm EST we will be joined by Susan Grajek, the vice president for communities and research at EDUCAUSE

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Top 10 IT Issues, 2017: Foundations for Student Success

D2L Brightspace conference Normandale

Our discussion:

Faculty migration from text-based to media-rich content: crowdsourcing the meaningful application of LMS (D2L) quizzes from Plamen Miltenoff
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Main speaker: Ken Chapman

mapping what students are looking at the screen
intelligent agent: dancing hamster
immediate gratification – certification, this is practically badges
story builder – D2L tool
D2L dropbox – look previous assignments and submissions within dropbox
time savers: 1. miss an assignment deadline – use agent. My note: how does it roll over? how much time and effort to condition it after it is rolled over?
 text expanders: create codes in the browsers to evoke repetitions  (;runon)
“Daylight Experience” is the D2L new look and feel put on D2L. nice clean modern looking.
assignment grader for Android has Daylight Experience. https://youtu.be/9B2EgPW_J38
PIE (Product Ideas Exchange) – https://community.brightspace.com/sharedresources/glossary/library/product_ideas_exchange_pie 
score a rubric while assessing discussion posts
Mobile First, API Access, Assessments, Advanced CBE (competency-based education programs), Predictive Analytics (recommendation system to pick right course, red flags, Dashboards,
Content:
interactive publisher material. Dates and Feeds on Mobile, Curriculum Planning
Capture: my note – how does it fit with MediaSpace
ePortfolio my note – how does it fit TK-20
Repository – open content, publishers, how to bring easier into a course
Adaptive learning
D2L purchased a module. publisher packets, adaptive textbooks. D2L looks at it as an engine where faculty feeds the idea and the engine is making the links and structuring the ideas into content. It also the engine checks what learners already know and based on results finds knowledge gaps.
need well defined learning objective, good content and ways to assess the material.
Start with creating support course delivery, test preparation.

predictive analysis

Driving positive change in the student life cycle

https://www-01.ibm.com/marketing/iwm/dre/signup?source=ibm-analytics&S_PKG=ov18048&S_TACT=C3310AVW&dynform=4817

How to make better decisions faster

IBM Predictive Analytics Solutions for Education can help you improve outcomes

Your data is a record of what’s already happened. But did you know that the same data—combined with the right analytical tools—can give you a forward-looking view of your situation, along with recommendations for decision making?

Read this white paper to learn how predictive analytics can help your institution address a range of challenges, from increasing graduation rates student by student to optimizing recruitment, fundraising and the performance measures that matter most. 

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.