{"id":17301,"date":"2021-08-03T06:48:27","date_gmt":"2021-08-03T10:48:27","guid":{"rendered":"https:\/\/news.elearninginside.com\/?p=17301"},"modified":"2023-05-09T15:58:38","modified_gmt":"2023-05-09T19:58:38","slug":"a-peek-into-the-future-predictive-analytics-in-education","status":"publish","type":"post","link":"https:\/\/news.elearninginside.com\/a-peek-into-the-future-predictive-analytics-in-education\/","title":{"rendered":"A Peek into the Future: Predictive Analytics in Education"},"content":{"rendered":"<p>In 2015, the management of the Kennesaw State University in Georgia (KSU) decided to redesign its Foundations for Healthy Living course (WELL 1000). The aim was to address common pain points that haunt many educational institutions, such as unsatisfactory grades and the drop-out ratio, reflected in a high DFWI (D, fail, withdraw, incomplete) rate.<\/p>\n<p>Over just two years, the KSU managed to <a href=\"https:\/\/edscoop.com\/data-analytics-tool-sees-fail-rate-plummet-in-kennesaw-state-course\/\" target=\"_blank\" rel=\"noopener nofollow\">reduce this key metric<\/a> for the WELL 1000 course by 48%, from 25% to 13%. To this end, the university used various methods, including tailored curriculums, online learning platform integration, and providing an overall more interactive experience for students.<\/p>\n<p>All these solutions had one thing in common: they were suggested by predictive analytics. The success story of the KSU goes to show that the data-driven approach, adopted years ago by tech giants like <a href=\"https:\/\/news.elearninginside.com\/is-amazon-building-its-own-lms\/\" target=\"_blank\" rel=\"noopener\">Amazon<\/a> and <a href=\"https:\/\/news.elearninginside.com\/binge-learning-online-education-can-learn-netflix\/\" target=\"_blank\" rel=\"noopener\">Netflix<\/a>, has a place in education, too.<\/p>\n<p>In this article, we take a closer look at the current and potential applications of predictive analytics in learning. Read on to learn how you can harness data in your educational facility and discover best practices that will guarantee a smooth transition into the world of advanced analytics.<\/p>\n<h2>What Is Predictive Analytics?<\/h2>\n<p>Predictive analytics is a broad term that refers to <a href=\"https:\/\/news.elearninginside.com\/coursera-launches-new-msc-in-machine-learning\/\" target=\"_blank\" rel=\"noopener\">machine learning<\/a> algorithms that make informed conclusions based on high volumes of data. In other words, it\u2019s how we apply modern technology to take a look into the future and improve the way we work, live and learn.<\/p>\n<p>Predictive analytics is now more popular than ever, even though the concept has been around for quite some time. The main drivers for the adoption of predictive analytics software include more affordable computing, greater internet coverage, cloud computing expansion, and facilitated access to ever-growing amounts of data.<\/p>\n<h2>Powering Smart Decisions<\/h2>\n<p>Data-driven decisions have become part and parcel of modern organizations in all verticals, including education. In its essence, predictive analytics helps unearth business insights that nurture data-based decision-making. Here are some examples:<\/p>\n<ul>\n<li>In <strong>online<\/strong> <strong>retail<\/strong>, predictive analytics considers historical data to target priority customers and analyze their on-site behavior.<\/li>\n<li>When applied in <strong>healthcare<\/strong>, predictive analytics solutions facilitate risk assessment and make it easier to deliver treatment adjusted not to the average patient but to specific ones.<\/li>\n<li>The <strong>construction <\/strong>industry benefits from predictive analytics at every stage, from budgeting to managing construction teams.<\/li>\n<\/ul>\n<p>When it comes to the applicability of predictive analytics, education is no different from these sectors. So let\u2019s see how you can use it to analyze and avoid risks, predict student behavior, and ultimately, improve the quality of your education.<\/p>\n<h2>Identifying Trends<\/h2>\n<p>Just like healthcare and finances, education is driven by numerical data. The chances are that you already have generous volumes of records to feed into analytical tools. Think grades, attendance, graduation rates, course and program enrollment, or even library records.<\/p>\n<p><a href=\"https:\/\/news.elearninginside.com\/learning-analytics-and-its-potential-to-bridge-education-silos-an-interview-with-david-niemi\/\" target=\"_blank\" rel=\"noopener\">Finding patterns based on input data<\/a> is the essential use of predictive analytics. By analyzing data sets from the last few months or years, predictive software solutions help you better understand how students interact with your organization. Which teaching formats bring the best student outcomes? What factors affect an exam\u2019s passing rate? Applying modern predictive analytics methods will help you find answers to these and more fundamental questions.<\/p>\n<h2>Identifying Students at Risk<\/h2>\n<p>Student success can be attributed to a range of factors. For example, time and effort spent on studying, individual abilities, or resource availability. However, social considerations also impact students\u2019 grades \u2014 and, consequently, their outlooks for the future. Teachers alone cannot be expected to take note of all their students\u2019 issues, especially when dealing with large student groups.<\/p>\n<p>Predictive analytics can help determine what makes some students consistently score As and others perform poorly. For instance, suppose a clear pattern shows that those who study an hour daily for a particular course pass the exam effortlessly. This is a clear signal for teachers how to help underperforming students improve their final scores.<\/p>\n<h2>Minimizing Drop-Out Rates<\/h2>\n<p>It is possible to use predictive analytics to help students stay on track by identifying those who are most likely to drop out. <a href=\"https:\/\/www.softonlinetraining.com\/oracle-fusion-procurement-training\" target=\"_blank\" rel=\"noopener\">Oracle Fusion procurement training<\/a> can use this approach by identifying which areas students struggle in and tailoring their course content.<\/p>\n<p>Student retention is one of the main concerns of schools and universities \u2014 and for a good reason. One study <a href=\"https:\/\/educationdata.org\/college-dropout-rates\">reports<\/a> that 40% of undergraduates drop out of college, with 30% of first-year students not even making it to their sophomore year.<\/p>\n<p>Data \u2014 when properly interpreted \u2014 can set a student who is likely to drop out back on a course to graduation. Thus, predictive analytics indirectly improves student grades but also helps them make the right choices.<\/p>\n<p>If a student finds out that he or she is unlikely to qualify for the desired program based on historical data, a teacher can advise him or her on an alternative. With that knowledge, students who would otherwise drop out have better chances of graduating.<\/p>\n<h2>Personalizing the Curriculum<\/h2>\n<p>Knowing how metrics like attendance or student engagement pan out over time, you can adjust the curriculum to individual student preferences and levels. In addition, thanks to predictive analytics, you can identify unpopular courses and decide whether to modify or replace them.<\/p>\n<p>Making the educational content more relevant and suited to the needs of your students can make all the difference between graduating and dropping out. This is especially important for freshers, who are the most likely to abandon their studies. If you learn that new students consistently fall short of the first-year requirements, you can act in time to prevent it, e.g. by updating recruitment procedures or adapting the curriculum.<\/p>\n<h2>Things Worth Remembering<\/h2>\n<p>Here are a few tips that will help you make the best use of predictive analytics tools in your school or university:<\/p>\n<ul>\n<li><strong>Don\u2019t trust the algorithm blindly.<\/strong> Remember that in the end, you\u2019re in charge. So use your best judgment to decide if a data-based decision makes sense in a given scenario.<\/li>\n<li><strong>Ensure that data governance rules are in place.<\/strong> For example, not all faculty members need access to all student information. To remain compliant, restrict data availability so that individual workers can only get the information they need.<\/li>\n<li><strong>Keep students in control of their data.<\/strong> You\u2019ll need their consent to use personal information, so be transparent about it. Demonstrate how sharing that information with you is in the student\u2019s best interest.<\/li>\n<\/ul>\n<p><strong><img loading=\"lazy\" decoding=\"async\" class=\"size-thumbnail wp-image-17302 alignleft\" src=\"https:\/\/news.elearninginside.com\/wp-content\/uploads\/2021\/08\/Andrey-150x150.png\" alt=\"andrey kotopov\" width=\"150\" height=\"150\" srcset=\"https:\/\/news.elearninginside.com\/wp-content\/uploads\/2021\/08\/Andrey-150x150.png 150w, https:\/\/news.elearninginside.com\/wp-content\/uploads\/2021\/08\/Andrey-599x604.png 599w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/>Andrey Koptelov<\/strong> is an innovation analyst at <a href=\"https:\/\/www.itransition.com\/\" target=\"_blank\" rel=\"noopener nofollow\">Itransition<\/a>, a custom software development company headquartered in Denver. With a profound experience in IT, he writes about new disruptive technologies and innovations in artificial intelligence and machine learning.<\/p>\n<p><em>Featured Image: Max Hopman, Unsplash.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In 2015, the management of the Kennesaw State University in Georgia (KSU) decided to redesign its Foundations for Healthy Living course (WELL 1000). The aim was to address common pain points that haunt many educational institutions, such as unsatisfactory grades and the drop-out ratio, reflected in a high DFWI (D, fail, withdraw, incomplete) rate. Over [&hellip;]<\/p>\n","protected":false},"author":114,"featured_media":17303,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[5,27986],"tags":[],"class_list":["post-17301","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","category-education-technology"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>A Peek into the Future: Predictive Analytics in Education - eLearningInside News<\/title>\n<meta name=\"description\" content=\"The use of predictive analytics in education remains controversial. But its applications are starting to return positive results.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/news.elearninginside.com\/a-peek-into-the-future-predictive-analytics-in-education\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Peek into the Future: Predictive Analytics in Education - eLearningInside News\" \/>\n<meta property=\"og:description\" content=\"The use of predictive analytics in education remains controversial. 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