Abstract
Recent progress in technology has altered the learning behaviors of students; besides giving a new impulse which reshapes the education itself. It can easily be said that the improvements in technologies empower students to learn more efficiently, effectively and contentedly. Smart Learning (SL) despite not being a new concept describing learning methods in the digital age- has caught attention of researchers. Smart Learning Analytics (SLA) provides students of all ages with research-proven frameworks, helping students to benefit from all kinds of resources and intelligent tools. It aims to stimulate students to have a deep comprehension of the context and leads to higher levels of achievements. The transformation of education to smart learning will be realized by reengineering the fundamental structures and operations of conventional educational systems. Accordingly, students can learn the proper information yet to support to learn real-world context, more and more factors are needed to be taken into account. Learning has shifted from web-based dumb materials to context-aware smart ubiquitous learning. In the study, a SLA dataset was explored and advanced ensemble techniques were applied for the classification task. Bagging Tree and Stacking Classifiers have outperformed other classical techniques with an accuracy of 79% and 78% respectively.
Highlights
Learners are fostered with smart learning and intelligent design to impart education thanks to the progress in computer technologies
The goal of this study is to review broadly and systematically the trends of Smart Learning Analytics (SLA) from the perspectives of different types of analytics and the several decision-making support systemsin which learning analytics intervention is designed
While SLA holds the key for the future of education, there are some obstacles that researchers and practitioners have to overcome challenges such as technological or social
Summary
Learners are fostered with smart learning and intelligent design to impart education thanks to the progress in computer technologies. Smart learning environment delivers guidance, support, and suggestions to the learners at the right time, in the right place, and form This context-aware environment enables the system to adapt the subject contents and course contents. Zhu et al [6] summarized the smart learning environment as a personalized, learner-centric, adaptive, context-aware, and ubiquitous environment that supports high-end digital technology; a four-tier smart pedagogy framework to enrich learners with knowledge and skills was designed. This framework included class-based differentiated instruction, individual-based personalized learning, group-based collaborative learning, and mass-based generative learning. Pedagogical theory, educational ideology, teacher’s learning leadership, and educational structures are key challenges to mention in this domain [5]
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