Personalized learning caters to diverse learning styles and needs. Advancements in technology allow institutions to deliver individualized content based on student preferences such as time, location, and mode of delivery. Institutions are using adaptive courseware, personalized learning pathways, and digital tutoring solutions to provide students with immediate feedback. Adaptive learning technologies emulate and support educators by providing personalized interactions with individual students. This provides the best possible personalized learning experience for every student.
Using the latest AI trends, virtual teaching assistants help faculty personalize lessons by gathering data on a student's learning progress, identifying strengths and weaknesses, and suggesting where extra support is needed. These virtual assistants also predict a student's success or failure in a course based on their prior performance and the course's historical data. This allows faculty to intervene and offer remedial training when required.
Changes in pedagogy, such as flipped learning, are a trend in which direct instructions are transformed from group learning to individual learning. The resulting group space is transformed into a dynamic, interactive learning environment in which the educator guides students as they apply concepts and engage creatively with the subject matter.
Next-generation hyperlearning management, or course management, systems can facilitate flipped learning.
Institutions are also changing how they approach exams, assessments, and awarding degrees. For instance, project-based learning is a new approach that provides the building blocks for organizational skills, collaboration, and time management — tools that all students need. With project-based learning, students are assessed by analyzing their learning paths through practical and experiential learning or fieldwork. Then they are awarded with microcredentials.
Institutions are leveraging cloud-based software systems and software-as-a-service to create personalized learning experiences and to manage student data. Institutions are defining the data-capture process for learning situations and administrative processes; thus, over time, a body of data is built. Online and offline teaching platforms help students complete courses on time, with the assistance of AI systems that offer personalized guidance.
Other AI solutions include virtual personal assistants, early warning analysis, automatic attendance, grading automation, adaptive learning, and adaptive assessments.
Some of the other trending technologies used in student student learning management and success include:
A leading U.K. university and Infosys collaborated to create a flexible, innovative teaching and research approach that improves student experience in every interaction and increases student success rates. AI and machine learning were leveraged to develop cognitive models that take advantage of structured (assessments, student demography, classroom attendance) and unstructured (student interactions via voice, email, support tickets) student data. The systems identify disengaged students and trigger automated interventions to improve engagement. The student experience was further improved with a mobile app and virtual assistant.
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