Data Analytics a Key Skill for Administrators in K–12
more on data analytics in education in this IMS blog
more on data analytics in education in this IMS blog
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
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.
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
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
counting how many times students use electronic library resources or visit in person, and comparing that to how well the students do in their classes and how likely they are to stay in school and earn a degree. And many library leaders are finding a strong correlation, meaning that students who consume more library materials tend to be more successful academically.
carefully tracking how library use compares to other metrics, and it has made changes as a result—like moving the tutoring center and the writing lab into the library. Those moves were designed not only to lure more people into the stacks, but to make seeking help more socially-acceptable for students who might have been hesitant.
a partnership between the library, which knows what electronic materials students use, and the technology office, which manages other campus data such as usage of the course-management system. The university is doing a study to see whether library usage there also equates to student success.
The issue of privacy also emerged during a session on libraries and data at the annual Educause conference earlier this month.
Part 1: March 13, 2019 | 1:00–2:30 p.m. ET
Part 2: March 20, 2019 | 1:00–2:30 p.m. ET
Part 3: March 27, 2019 | 1:00–2:30 p.m. ET
A picture is worth a thousand words, but developing a data picture worth a thousand words involves careful thought and planning. IT leaders are often in need of sharing their story and vision for the future with campus partners and campus leadership. Delivering this message in a compelling way takes a significant amount of thought and planning. This session will take participants through the process of constructing their story, how to (and how not to) incorporate data and anecdotes effectively, how to design clear data visualizations, and how to present their story with confidence.
During this course, participants will:
NOTE: Participants will be asked to complete assignments in between the course segments that support the learning objectives stated below and will receive feedback and constructive critique from course facilitators on how to improve and shape their work.
Leah Lang, Director of Analytics Services, EDUCAUSE
Leah Lang leads EDUCAUSE Analytics Services, a suite of data services, products, and tools that can be used to inform decision-making about IT in higher education. The foundational service in this suite is the EDUCAUSE Core Data Services (CDS), higher education’s comprehensive IT benchmarking data service.
more Educause webinars in this IMS blog
Tony Wan Feb 5, 2019
From launching new tablets to virtual-reality curriculum, Microsoft has added plenty to its educational offerings
DataSense, a data management platform developed by Brightbytes.
DataSense is a set of professional services that work with K-12 districts to collect data from different data systems, translate them into unified formats and aggregate that information into a unified dashboard for reporting purposes.
DataSense traces its origins to Authentica Solutions, an education data management company founded in 2013.
A month later, BrightBytes acquired Authentica. The deal was hailed as a “major milestone in the industry” and appeared to be a complement to BrightBytes’ flagship offering, Clarity, a suite of data analytics tools that help educators understand the impact of technology spending and usage on student outcomes.
Of the “Big Five” technology giants, Microsoft has become the most acqui-hungry as of late in the learning and training space. In recent years it purchased several consumer brand names whose services reach into education, including LinkedIn (which owns Lynda.com, now a part of the LinkedIn Learning suite), Minecraft (which has been adapted for use in the classroom) and Github (which released an education bundle).
Last year, Microsoft also acquired a couple of smaller education tools, including Flipgrid, a video-discussion platform popular among teachers, and Chalkup, whose services have been rolled into Microsoft Teams, its competitor to Slack.
Submit proposals at http://www.iolug.org
Submissions are invited for the IOLUG Spring 2019 Conference, to be held May 10th in Indianapolis, IN. Submissions are welcomed from all types of libraries and on topics related to the theme of data in libraries.
Libraries and librarians work with data every day, with a variety of applications – circulation, gate counts, reference questions, and so on. The mass collection of user data has made headlines many times in the past few years. Analytics and privacy have, understandably, become important issues both globally and locally. In addition to being aware of the data ecosystem in which we work, libraries can play a pivotal role in educating user communities about data and all of its implications, both favorable and unfavorable.
The Conference Planning Committee is seeking proposals on topics related to data in libraries, including but not limited to:
Mar 04 – Mar 31, 2019
Delivery Mode : Asynchronous Workshop
Levels : Beginner,Intermediate
Eligible for Online Teaching Certificate elective : No
Data visualization is about presenting data visually so we can explore and identify patterns in the data, analyze and make sense of those patterns, and communicate our findings. In this course, you will explore those key aspects of data visualization, and then focus on the theories, concepts, and skills related to communicating data in effective, engaging, and accessible ways.
This will be a hands-on, project-based course in which you will apply key data visualization strategies to various data sets to tell specific data stories using Microsoft Excel or Google Sheets. Practice data sets will be provided, or you can utilize your own data sets.
Week 1: Introduction and Tool Setup
Week 2: Cognitive Load and Pre-Attentive Attributes
Week 3: Selecting the Appropriate Visualization Type
Week 4: Data Stories and Context
Upon completion of this course, you will be able to create basic data visualizations that are effective, accessible, and engaging. In support of that primary objective, you will:
Basic knowledge of Microsoft Excel or Google Sheets is required to successfully complete this course. Resources will be included to help you with the basics should you need them, but time spent learning the tools is not included in the estimated time for completing this course.
What are the key takeaways from this course?
Who should take this course?
more on digital storytelling in this IMS blog
more on data visualization in this IMS blog
Kristi Hines June 24th, 2015
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
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