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An effective institutional analytics program has become essential to providing proactive student services and informing strategic actions. Leveraging 
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The 2022 EDUCAUSE Horizon Report profiles the trends and key technologies and practices shaping the future of data and analytics, and envisions a numb
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Campus leaders are beginning to explore leveraging analytics as a vehicle for supporting diversity, equity, and inclusion (DEI). Critical steps includ
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As institutions prepare for fall 2020 and beyond, they are exploring their needs for data and analytics. These efforts emphasize measuring and improvi
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Analytics have been an important part of measuring student engagement at UMBC, especially during the pandemic.
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Researchers are gaining a better understanding of how people learn—both what works and what doesn’t go so well—in the classroom. The next step is t
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At the 2019 Enterprise Summit, higher education IT, business and finance, and institutional research professionals gathered to explore the future and
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Progress on data and analytics has stalled. EDUCAUSE is working with NACUBO and AIR to produce an analytics statement advocating for these important e
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Today’s designers of data analytics systems are using thirty-year-old mental models around scarcity of compute and are thus crippling their designs, n
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Within higher education, there is near universal recognition that analytics have transformative potential. So why doesn’t every institution have a rob
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Universities have seized on big data to count every click their students make in learning management systems, but the focus needs to be on improving learning.
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With predictive analytics, colleges and universities are able to “nudge” individuals toward making better decisions and exercising rational behavior to enhance their probabilities of success.
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Even though the work required to yield significant results in institutional analytics is hard and the journey long, the cost of doing nothing is no longer an option for most higher education institutions.
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Analyzing data across the institution to build a true picture of student engagement and using targeted, scripted reporting for meaningful insights has
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Bentley students now tackle data analytics and work with large, real-world data sets early in their college careers, thanks to new and redesigned introductory courses.
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To deploy an analytics strategy effectively, institutions must avoid missteps at all phases of the project. We asked several IT leaders what stumbling
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![Creating a Culture of Analytics [video] | Learning Analytics, Educational Data Mining, Adaptive Learning | Scoop.it](https://img.scoop.it/m-z3gQO-HbSitcBr5FcQgDl72eJkfbmt4t8yenImKBVvK0kTmF0xjctABnaLJIm9)
An important tool to address how institutions are failing certain student populations is analytics. Colleen Carmean discusses how we can do the work o
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Colleges and universities must decide how to structure learning environments for the fall academic term and beyond to deliver quality instruction whil
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One of the keys to realizing student outcomes is using analytics to provide a best assessment on what will happen in the future.
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We asked several leaders in the EDUCAUSE community where they currently stand on the use of predictive analytics for student success.
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Implementing a learning analytics system across all higher education institutions in Wales provides a model for the opportunities for such services at
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Augmented analytics and “explainable AI” are just two changes to data and analytics technology that should have "significant disruptive potential" over operations in the next three to five years.
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Learning analytics is the use of data, analysis, and predictive modeling to improve teaching and learning.
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With access to predictive analytics and more data than ever before, how can universities avoid invading students’ privacy while promoting academic success?
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If I were into scrying (the art of predicting the future by gazing into a crystal ball), I would prophesy that EDUCAUSE Review readers will have two equal and opposite reactions on seeing an issue devoted to predictive analytics. The first reaction might be: "Are we still talking about how to use predictive analytics?" And the second reaction might be: "I wonder what predictive analytics we are using on our campus." We are all accustomed to tracking technologies that are emerging or that may seem to be more hype than substance, but what do we make of technologies like analytics? Here is a combination of tools and practices whose fundamental value is rarely questioned but that have not achieved the traction we might have expected by now. This issue of EDUCAUSE Review is a timely consideration of the state of predictive (and other) analytics across higher education: How are these tools and practices being used, how can they be better used, and how can institutions understand their own progress? How are the tools and practices of predictive analytics being used, how can they be better used, and how can institutions understand their own progress with analytics?
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