How Universities Adopt AI/ML Technology : Real-life Use Cases of Today

1. How Universities Adopt AI/ML Technology: Real- life Use Cases of Today and A Peek into the Future October 28, 2021 Dash Technologies Inc Artificial Intelligence, Machine Learning AI data-driven tools help universities optimize enrollment and operations, but it is challenging to boost their use and training.

2. In recent years, the higher education world abuzz with the prospects of utilizing Artificial Intelligence, news of the success of data-fed virtual teaching assistants, and smart enrollment counselor chatbots. With the help of Artificial Intelligence (AI) and Machine Learning (ML), universities and colleges hope to offer time-consuming administrative and academic activities, make IT operations more efficient, enhance their enrolment in an atmosphere of decline and deliver a better learning experience students. The Education Advisory Boardsays, “MarketMachine Learning as a Service to strategic requirements instead of simply another flash technological gimmick.” Machine Learning- A Branch of AI: Machine learning includes speech recognition, natural language processing, neural networks, deep learning, pattern recognition, supervised learning, unsupervised learning, and reinforced learning. At Dash Technologies, we largely leverage AI or ML so that our technology can provide knowledge, cover a range of topics, and interact across many platforms to students whenever they need it. ML enables our technology to learn from big data to identify or categorize the requirements of students. AI/ML in Education Sector: Education industry leaders have been working for digitization for years. However, the COVID-19 pandemic drove companies to boost their digital efforts and use emerging technologies like AI & ML. The idea is to use AI/ML technologies to allow machines and systems to work efficiently and effectively. AI/ML has considerable significance in higher education since universities seek out affordable technologies that, under extraordinary financial constraints, can provide students with tailored assistance and service.

3. The Collaboration between AI/ML & Universities: The AI has been used largely for education in some applications that contribute to skills development and testing systems. The hope is that AI will help fill gaps in learning and teaching so that universities and teachers can do more than ever before because AI educational solutions will continue to grow. AI can promote efficiency, personalization and streamline administrative tasks so that teachers may offer time and flexibility to understand and adapt the unique talents of man where robots strive. The vision of AI in Education is where students work together to get the greatest result by harnessing the best qualities of machines and teachers. For the students of the Mandarin language, IBM Research and the Institute Rensselaer Polytechnic partnered on a new technique. AI assistant helps students feel like they were in a Chinese restaurant, park, or Tai Chi class, where they may use an AI chat agent to speak Mandarin. Real-life AI & ML Use Cases of Today: Let us look at various use cases worldwide that already make a difference for AI and ML.

4. •Virtual Assistants Chatbots can act as virtual assistants and resolve real-time inquiries by integrating AI and ML. It allows a teacher to spend more time on practical lesson planning, from administrative responsibilities. It offers solutions for queries regarding their future job, mistakes at the last quiz, faculty feedback, and more. •Digital Assessment or Exams The lockdown affected exams, and universities had to cancel or postpone examinations in most circumstances. Institutes eventually realized that the new normal would be online learning. Retinal scanning, environmental stimulus tracking, and IP tracking will soon gain ground to engage and evaluate online examination environments. The data produced by such digital exams combined with the strength and capacity of Machine Learning generate automatic assessment papers and help teachers focus on the facilitative part of the course for each student. •Education for Special Child (ASD) A wide study in learning theories always took place in the broad Autism scope disorder (ASD). In this case, artificial intelligence and machine learning can be quite helpful. AI offers highly personalized learning for exceptional children and teaches

5. and improves responses in some areas while considering the students’ speed and duration of learning. •Learning with Customized Solutions The new reality is tailor-made courses. AI and ML empower individual education. The programs can forecast the learner’s mood, progress, and learning to change modules and assignments. In recent years, many EdTech companies have emerged in this area. •Enrolment Process Imagine going to school and getting assistance on your course plans and student enrollment data to help you develop a personalized path! In addition to helping students pave their way, the machine learning model also suggests developing certain talents using artificial intelligence. Conclusion- The Promise of AI/ML for Higher Education: In higher education, artificial intelligence and machine learning have become more and more important. The AI-powered applications will not replace teachers, they will empower them, and universities worldwide will already use them. At the same time, the time needed for routine tasks, allowing the faculty to focus on teaching and research, will be reduced. It’s interesting to note how the rate of adaptation in the new normal is increasing. Would you want to explore our offering of AI Development Services? Contact us and explore how you can benefit from our services and solutions. Create the next chapter together in Artificial Intelligence with Dash!