Blockchain-Enabled Automatic Learning Method for Digital Gaming Systems Based on Big Data

Overview Of Resource Automatic Learning Method

In today’s world, big data is being utilized in many industries. E-commerce has advanced and made people’s lives easier. Right words like personalization are getting a lot of attention nowadays. As a result, the education community has paid close attention (Baskar et al., 2020). Researchers in education are looking into how big data can be used in the field. The education technology researchers have a problem to solve: using big data to achieve personalized learning. Measures of blockchain-enabled performance are used to evaluate a company's ability to translate operating results into financial goals. This type of indicator includes comparable measures. Finally, making sound decisions about the process necessitates a thorough knowledge of both types of measurements and what they indicate for digital gaming. When it comes to comparing consumer and operational needs, metrics are essential (Amudha et al., 2018).

This generation of students has shifted from being information consumers to becoming content creators, and as technology has advanced and educational concepts have changed, so has the learning environment (Gheisari et al., 2021). Students monitor, record, and master the characteristics of various learners in an all-around manner using big data-driven online learning. They can construct learning models based on the characteristics of Students and generate personalities for different kinds of learners (Nguyen et al., 2020). As a result of personalized learning methods and technologies, the learning material of each student is no more the same. It is dynamically provided according to the learner’s learning trajectory, providing a tailored environment for learning for the student (Saravanan et al., 2020).

Big data has made waves in the technological world for some time now and is being implemented at different levels in different organizations to reveal the potential of data piles that they own internally and the data available to them from external sources. With big data analytics with cloud-based big data analytics, organizations and companies can make informed decisions using big data practically and cost-effectively (Manogaran et al., 2020). Institutions collect basic information, including demographics, socioeconomic position, educational credentials, and student performance during the period they have been a member of the institute regarding exams, scores, attendance, and placement status from both students and employees. Students' performance can be improved, blockchain-enabled AI can tailor their learning experience, and a positive learning environment can be created using cloud-based big data analytics for digital gaming in Indian schools (Zhang et al., 2021). The evaluation of the performance of human resources is the most important aspect of any practical company. Companies have the option of rewarding or punishing workers based on their performance evaluations. Because of the increased complexity of work and increased competition for jobs due to society’s improvements and improvement, it is increasingly difficult to solve difficulties completely using the inherent employees’ knowledge (Liu et al., 2020). As a result, assessing workers ongoing development has never been a part of the conventional performance evaluation system. There are many similarities between big data in companies and the educational system. Models and frameworks for business intelligence have long been developed and modified to fit into the educational framework (Revathi et al., 2015). In fact, for this reason, the name academia Intelligence is most appropriate for describing the methods utilized to acquire insights into the educational system as a whole, including reporting and analytic tools (Zheng et al., 2021). Academia Intelligence can use existing big data analytics concepts like recommender systems and social network analysis and Skill Assessment tools to develop a comprehensive system that uses available data to improve organizational decision-making and individual team productivity on an individual team basis (Ali et al., 2018). Using big data analysis, professors can identify areas where students are struggling or succeeding, understand the unique needs of students, and develop personalized learning strategies for blockchain-enabled AI. In addition, it gives students more freedom to determine the direction in which they want to take their education for digital gaming.