The education sector tends to continuously evolve due to growing digitization in the industry and adoption of mobile devices among users. The volume, variety, and speed with which data is generated is rapidly increasing. This data can be easily harnessed and analyzed to provide powerful insights regarding user behavior, preferences, and future actions. Students using various education hubs such as digital platforms or university campuses for studying leave data footprints behind in the course of their study. Universities are using this data to understand how students learn and optimize their solutions in order to enhance student experience. Education and learning analytics are being used by education hubs for a better understanding of products and their customers.
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Analytic tools help the education sector increase efficiency, spot opportunities and trends, and be more innovative. The education sector is a data-rich sector as universities use as well as generate large volumes of data each day. Also, the data generated ranges from socio demographic data (gender, level of education, age, language, etc.) to statistics (frequency and time of utilization, number of clicks, response time), or from performance indicators (such as test results) to behavior (interactions with the machine or between individuals).
This data can be used to experiment with diverse types of trainings with students in order to evaluate their response time, personalize and strengthen their course, and provide them regular feedback. Thus, education and learning analytics can play an important role in the education sector as they help in providing better feedback to students, increasing retention, enhancing teaching and learning, and recording attendance data.
Major factors driving the education and learning analytics market include rise in the need for data-driven assessments in order to improve the quality of education and increase in the adoption of mobile-based learning. However, a lack of awareness about analytics solutions among end-users and demand for highly skilled professionals to manage and deploy analytics solutions are some of the major hindrances of the education and learning analytics market.
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The global education and learning analytics market can be segmented based on component, analytics, end-use industry, and region. In terms of component, the education and learning analytics market can be classified into software and services. The services segment can be further bifurcated into professional and managed services. Professional services include consulting, integration & implementation services, and training & support services.
Based on software, the global education and learning analytics market can be categorized into on premise, cloud-based, and hybrid solutions. In terms of analytics, the education and learning analytics market can be divided into predictive analytics, prescriptive analytics, descriptive analytics, and others. Based on end-use industry, the global education and learning analytics market can be segmented into K-12, higher education, enterprise, and more. The enterprise segment can further be classified into large enterprises and small and medium enterprises.