The global NLP in education market is anticipated to grow at a CAGR of 22.8% during the forecast period (2023-2030). The market growth is attributed to the technological change happening in education sector. To remain up-to-date educational institutions are continuously updating and incorporating technology into their teaching approaches, practices, and curriculum. In addition, the pandemic has further accelerated the digital adoption, and the parent community has come to understand the value, necessity, potential, and strength of technology in providing a comprehensive education.
Browse the full report description of “Natural Language Processing (NLP) in Education Market Size, Share & Trends Analysis Report by Offering (Solution and Service), by Model Type (Rule-based NLP, Statistical NLP, and Hybrid NLP), by Application (Data Extraction, Risk & Threat Detection, Intelligent Tutoring & Language Learning, Corporate Training, and Others), and by End-User (Academic User, and EdTech Provider) Forecast Period (2023-2030)” at https://www.omrglobal.com/industry-reports/nlp-in-education-market
Pedagogy recognizes that the learning process is different for every student at any level, from early education to post-graduation. The pace of student learning is different for each student. Some have special needs that require different teaching methods. NLP and computational linguistics in education involve the understanding of speech and text through software and algorithms to improve, scale, and broaden the reach of education in society. Technologies like chatbots, voice assistants, translators, and many other tools provide support to student in their field of education. New invention in technology are even making learning more fun for students. The release of BERT by Google, marks the beginning of a new era in NLP. BERT is a model that broke several records for how well models can handle language-based tasks. BERT was originally implemented in the English language at two model sizes BERTBASE and BERTLARGE. BERT has already been pre-trained, which means that it has learned the representations of the words and sentences as well as the underlying semantic links that they are related with, in contrast to deep learning neural networks which need very huge quantities of data. BERT can be fine-tuned for certain tasks like sentiment classification on smaller datasets. Latest technological advancement will make learning more and accessible for students. For instance, in March 2023, Amazon and the IIT Bombay announced the creation of the Amazon IIT–Bombay AI-ML initiative. It is a multiyear collaboration that will fund research projects, PhD fellowships, and community events, such as research symposia. It will advance artificial intelligence (AI) and machine learning (ML) within the speech, language, and multimodal-AI domains.
Market Coverage
• The market number available for – 2022-2030
• Base year- 2022
• Forecast period- 2023-2030
• Segment Covered-
o By Offering
o By Model Type
o By Application
o By End-User
• Regions Covered-
o North America
o Europe
o Asia-Pacific
o Rest of the World
• Competitive Landscape- Includes IBM Corp., SAS Institute Inc. and Microsoft Corp., among others.
Key questions addressed by the report
• What is the market growth rate?
• Which segment and region dominate the market in the base year?
• Which segment and region will project the fastest growth in the market?
• Who is the leader in the market?
• How are players addressing challenges to sustain growth?
• Where is the investment opportunity?
Global NLP in Education Market Report Segment
By Offering
• Solution
• Services
By Model Type
By Application
By End-User
Global NLP in Education Market Report Segment by Region
North America
• United States
• Canada
Europe
• UK
• Germany
• Italy
• Spain
• France
• Rest of Europe
Asia-Pacific
• China
• India
• Japan
• South Korea
• Rest of Asia-Pacific
Rest of the World
• Latin America
• Middle East & Africa
To learn more about this report request a sample copy @ https://www.omrglobal.com/request-sample/nlp-in-education-market