{"id":5424,"date":"2016-01-26T10:00:21","date_gmt":"2016-01-26T09:00:21","guid":{"rendered":"https:\/\/www.teachonmars.com\/blog\/2016\/01\/the-adventures-of-analytics-in-learning-land\/"},"modified":"2019-08-28T16:21:30","modified_gmt":"2019-08-28T14:21:30","slug":"the-adventures-of-analytics-in-learning-land","status":"publish","type":"post","link":"https:\/\/www.teachonmars.com\/en\/blog\/2016\/01\/the-adventures-of-analytics-in-learning-land\/","title":{"rendered":"The adventures of analytics in Learning Land"},"content":{"rendered":"

Web users surf, depending on to their wishes and needs. They click here and there, comment, buy, like \u2026 and learn! All their littlest traced movements produce a torrent of information. Welcome to the Big Data!<\/p>\n

Marketing professionals first captured the “Big Data” to appeal and promote customer shopping. Amazon, with its recommendations algorithms, is a renowned example.<\/p>\n

Nowadays, web data analysis is going far beyond marketing borders<\/span>. Learning data from LMS (Learning Management System) and especially mobile learning platforms can also generate valuable information.<\/p>\n

How? Which educational data should be measured? Which learner behavior may be profitably investigated? What resulting actions will be implemented?<\/p>\n

For most, \u201cLearning analytics<\/strong> is the measurement, collection, analysis and reporting of data about learners and their contexts<\/span>, for purposes of understanding and optimizing learning and the environments in which it occurs\u201d (Learning analytics definition<\/a>).\u00a0The time for \u201cBig Data in\u00a0Education\u201d is now!<\/p>\n

Digitization has brought a whole new dimension, allowing collecting and processing massive and systematic data related to the acquisition of knowledge (progression, scores…) and to users\u2019 behavior with the training system (assiduity, connexion duration…): what\u2019s their favorite pedagogic format? When and where do they ordinarily connect to train on their mobile device? Do learners move around while learning on their mobile? What are their preferred activities? What\u2019s their rhythm?\u2026<\/p>\n

Adaptive learning<\/strong>, i.e. individualized training, was born form the understanding of these parameters: suggest users upcoming activities based on their level of knowledge and learning habits<\/span>. And therefore increase their training efficiency.<\/p>\n

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Who benefits from learning analytics?<\/h4>\n

At the heart of the training, the learner and his progression!\u00a0A data-driven approach will provide learners<\/em><\/span> with trainings adapted to their real-time needs, as learning analytics will allow developing adaptive learning and large-scale customization.<\/p>\n

Moreover, studying learners’ behaviour allows\u00a0highlighting their inactivity phases and setting learners back in an appealing learning situation in such critical times. For example, let\u2019s suppose a learner never accesses his\u00a0(mobile) training\u00a0in the afternoon, you\u00a0might plan a daily notification around 3pm to change this habit\u2026<\/p>\n

Not only learners, but also trainers<\/em><\/span> will take advantage of proficient learning analytics. Connexion\/deployment rates, attendance reports, training activities progression rates, questionnaire scores are just a few of them. Their review will inform trainers on their training quality (example: a systematically skipped content), progression and completion (example: insufficient completion), learners\u2019 knowledge level and motivation\u2026 And will eventually help them take corrective actions or decide on new more effective pedagogic formats (compare completion rate on desktop vs on mobile device).<\/p>\n

More generally, compare individuals\u2019 training impact to their boosted performance will demonstrate the training value to the organization. Stakeholders<\/em><\/span>\u2019 ultimate objective is naturally to enhance the overall organization performance; therefore they need to accurately assess the value added by their training policies.<\/p>\n

<\/h4>\n

How to measure learning analytics and benefit from them?<\/h4>\n

Among the various learning analytics methods, let\u2019s dig inside some of them.<\/p>\n