Aug
2018
K12 administrators and data analytics
Data Analytics a Key Skill for Administrators in K–12
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more on data analytics in education in this IMS blog
https://blog.stcloudstate.edu/ims?s=data+analytics
Digital Literacy for St. Cloud State University
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more on data analytics in education in this IMS blog
https://blog.stcloudstate.edu/ims?s=data+analytics
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.
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more on analytics in this IMS blog
https://blog.stcloudstate.edu/ims?s=analytics
https://www.linkedin.com/groups/934617/934617-6255144273688215555
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
Synopsis:
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.
Important Dates:
· 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
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more on data mining in this IMS blog
https://blog.stcloudstate.edu/ims?s=data+mining
more on analytics in this IMS blog
https://blog.stcloudstate.edu/ims?s=analytics
presented by Prof. Bart Rienties from the Open University, The United Kingdom.
To register, go to https://www.eventbrite.com.au/e/learning-analytics-adoption-in-higher-education-reviewing-six-years-of-experience-at-open-registration-105611406560
Time and date: Thursday, Jun 11, 2020, 5:00 PM – 6:00 PM Central European time
(11:00 AM–12:00 PM Eastern US time, 8:00 AM–9:00 AM Pacific US time, 4:00 PM–5:00 PM London, UK Time)
Location: Zoom (meeting URL provided in the registration email)
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more on learning analytics in this IMS blog
https://blog.stcloudstate.edu/ims?s=learning+analytics
Valuing data over design instinct puts metrics over users
Benek Lisefski August 13, 2019
https://modus.medium.com/data-driven-design-is-killing-our-instincts-d448d141653d
Overreliance on data to drive design decisions can be just as harmful as ignoring it. Data only tells one kind of story. But your project goals are often more complex than that. Goals can’t always be objectively measured.
Data-driven design is about using information gleaned from both quantitative and qualitative sources to inform how you make decisions for a set of users. Some common tools used to collect data include user surveys, A/B testing, site usage and analytics, consumer research, support logs, and discovery calls.
Designers justified their value through their innate talent for creative ideas and artistic execution. Those whose instincts reliably produced success became rock stars.
In today’s data-driven world, that instinct is less necessary and holds less power. But make no mistake, there’s still a place for it.
Data is good at measuring things that are easy to measure. Some goals are less tangible, but that doesn’t make them less important.
Data has become an authoritarian who has fired the other advisors who may have tempered his ill will. A designer’s instinct would ask, “Do people actually enjoy using this?” or “How do these tactics reflect on our reputation and brand?”
Digital interface design is going through a bland period of sameness.
Data is only as good as the questions you ask
When to use data vs. when to use instinct
Deciding between two or three options? This is where data shines. Nothing is more decisive than an A/B test to compare potential solutions and see which one actually performs better. Make sure you’re measuring long-term value metrics and not just views and clicks.
Sweating product quality and aesthetics? Turn to your instinct. The overall feeling of quality is a collection of hundreds of micro-decisions, maintained consistency, and execution with accuracy. Each one of those decisions isn’t worth validating on its own. Your users aren’t design experts, so their feedback will be too subjective and variable. Trust your design senses when finessing the details.
Unsure about user behavior? Use data rather than asking for opinions. When asked what they’ll do, customers will do what they think you want them to. Instead, trust what they actually do when they think nobody’s looking.
Building brand and reputation? Data can’t easily measure this. But we all know trustworthiness is as important as clicks (and sometimes they’re opposing goals). When building long-term reputation, trust your instinct to guide you to what’s appealing, even if it sometimes contradicts short-term data trends. You have to play the long game here.
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more on big data in this IMS blog
https://blog.stcloudstate.edu/ims?s=big+data
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.
https://events.educause.edu/courses/2019/a-thousand-words-and-a-picture-storytelling-with-data
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.
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more Educause webinars in this IMS blog
https://blog.stcloudstate.edu/ims?s=educause+webinar
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: