Learning Analytics Market Research Report by Forecast to 2023Posted by Kiran on November 13th, 2019 Learning Analytics Market Scenario: Market Research Future (MRFR) postulates that the global learning analytics market is slated to register 26% CAGR during the forecast period (2017-2023). The proliferation of mobile devices is estimated to favor the market growth in the coming years. Such analytical tools enable the data to improve their learning and the environment in which the learning takes place. Learning analytics evolve from a branch of science like statistics, psychology, sociology, information science, machine learning, and data mining in order to interpret the gathered data during teaching, learning, education administration, and other services. Browse Full Report Details @https://www.marketresearchfuture.com/reports/learning-analytics-market-5634 Competitive Dashboard: The prominent players operating in the global learning analytics market are Cornerstone OnDemand (U.S.), Jenzabar (U.S.), IBM Corporation (U.S.), McGraw-Hill Education (U.S.), Blackboard Inc. (U.S.), SAP AG (Germany), Knewton (U.S.), Oracle Corporation (U.S.), Saba Software Inc. (U.S.), Microsoft (U.S.), D2L Corporation (Canada), Kronos (U.S.),and Pearson Inc. (U.K). Market Potential and Pitfalls: The market’s growth is chiefly directed by the augmenting need to evolve competitive strategies in order to sustain the market coupled with the increased focus on personalized learning. The accelerating increase in mobile devices like laptops, smartphones, and mobile tablets are some of the major factors likely to offer a better prospect to the market in the coming years. Several business organizations can determine the completion of training courses quantitatively, but on the other hand, find it very difficult to measure the qualitative aspects like social learning and informal experiences, and their results. Leaning analytics help to clarify the intangible learning experiences. Companies also require to retain a talented workforce in order to develop innovative products so that they can sustain in the market. Thus, business organizations across the globe lay stress on developing learning culture for their employees which helps to empower learning analytical tools in order to upsurge the innovation in the organization. Such factors are estimated to boost the learning analytics market throughout the globe. With the emergence of m-learning and e-learning, the market is likely to flourish. On the contrary, the dearth of technical expertise in order to implement learning analytics coupled with the lack of data storage infrastructure are some of the top barriers considered to vitiate the market growth throughout the estimated period. Moreover, issues related to data protection, monitoring, data possession, and data controlling are estimated to impede the market growth in the coming years. Learning Analytics Market Segmental Analysis: The global learning analytics market has been segmented on the basis of services, tools, application, deployment, and end-user.
Regional Insights: Geographically, the learning analytics market span across regions namely, Asia Pacific, North America, Europe, and the Rest-of-the-World (RoW). Considering the global scenario, North America is considered to exhibit a significant growth rate over the appraisal period. The U.S. and Canada are considered to lead the region in the coming years. The growth is credited to the increasing implementation of analytics tools like social network analysis and visual data analysis. The European region is predicted to register a substantial growth rate in learning analytics market owing to the presence of economies such as Germany, the U.K, and France as these countries are likely to implement analytics tools in the coming years. The Asia Pacific region, on the other hand, is anticipated to expand at the fastest growth rate. Countries like Japan, India, and China are likely to lead the market in this region due to gradual growth in the adoption of business enterprises to implement learning analytics tools like content analysis and predictive analysis techniques. Like it? Share it!More by this author |