Richmond, Dec. 19, 2023 (GLOBE NEWSWIRE) -- According to a research report "NLP in Education Market”, by Offering (Solution {Text-based NLP Solution [Language translation tools, Text-to-speech converters, Sentiment analysis tools and Plagiarism checkers], Video-based NLP Solution [Video captioning tools, Video transcription tools and Video summarization tools], Image-based NLP Solution [Optical character recognition (OCR) tools, Image captioning tools and Image recognition tools] and Audio-based NLP Solution [Speech recognition tools, Voice-to-text converters and Audio transcription tools} and Services {Professional Services [Consulting, Integration and Support and Maintenance] and Managed Services}), Model Type (Rule-based NLP, Statistical NLP and Hybrid NLP), Application (Sentiment Analysis & Data Extraction, Risk & Threat Detection, Content Management & Automatic Summarization, Intelligent Tutoring & Language Learning, Corporate Training and Others), End-user (Academic User and EdTech Provider), and Region - Global Forecast to 2030.
Global NLP in Education Market Report Scope:
| Report | Details |
| Market size value in 2023 | USD 102.0 Million |
| Market size value in 2030 | USD 249.8 Million |
| CAGR (2023-2030) | 13.7% |
| Forecast Period | 2023–2030 |
| Historic Data | 2019 |
| Forecast Units | Value (USD Million/USD Billion) |
| Segments Covered | Offering, Model Type, Application, End User and Region |
| Geographies Covered | North America, Europe, Asia Pacific, and RoW |
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| Sample of Companies Covered |
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TOC Covers in Depth & Breath on NLP in Education Market
170 - Market Data Tables
65 - List of Figures
225 – Pages
The report includes Vendor Assessment (Company Profiles, Market Positioning, Strategies, Recent Developments, Capabilities & Product Offerings / Mapping), Technology Assessment (Developments & Economic Impact), Partner & Customer Ecosystem (Product Services, Proposition & Key Features) Competitive Index & Regional FootPrint by MarketDigits.
Market Overview
Natural Language Processing (NLP) stands as a sub-field within Artificial Intelligence (AI) that empowers systems to comprehend text and spoken words in a manner akin to human understanding. The widespread utilization of AI solutions is becoming increasingly evident as the awareness of their benefits grows. NLP, a subset of AI, specializes in processing and mining unstructured data, encompassing text, video materials, voice, and sentences. In the Education Market, NLP plays a crucial role in swiftly identifying individuals facing challenges in reading comprehension and delivering automated, instantaneous feedback. The rising demand for personalized learning platforms is anticipated to propel the market forward in the coming years, driven by students seeking user-friendly methods to grasp academic concepts. As technology continues to advance, with AI taking center stage, NLP is poised to seize lucrative opportunities in the education sector. Machine learning technology, in particular, enables the analysis of classroom discourse to gauge individuals' sentiments on various topics during lessons or lectures. The growing enterprise adoption of cloud computing is expected to open vast opportunities for NLP in education, leveraging its capacity for in-depth analysis of unstructured data from diverse sources, including internet content and social media discussions. Additionally, global governmental initiatives promoting modern technology for improved academic understanding stand as a significant driving force for market growth.
Major Vendors in the Global NLP In Education Market:
- IBM
- ABBYY
- Attivio
- Automated Insights
- Avaamo
- AWS (Amazon Web Services)
- Baidu
- Carnegie Learning
- Chivox
- Cognii
- Gecko
- Haptik
- Microsoft
- NICE
- Primer.ai
- SAS Institute
- Sensforth.ai
- Width.ai
- Yellow.ai
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Advancements in NLP increase the demand
Natural Language Processing (NLP) has undergone significant advancements and has found widespread applications in the education sector, emerging as a valuable asset in this domain. The education sector is now witnessing the substantial impact of NLP, particularly in the analysis and comprehension of students' natural language interactions. NLP systems play a pivotal role in offering feedback, personalized recommendations, and learning materials tailored to individual needs, thereby aiding students in learning, practicing language skills, and monitoring their progress efficiently. These algorithms automate the evaluation process for specific types of essays and programming code, providing detailed feedback to enhance areas of weakness. Sentiment analysis, another facet of NLP, gauges student sentiments, emotions, and attitudes by analyzing spoken and written expressions. This capability enables NLP systems to identify signs of emotions, distress, engagement, and confusion, facilitating timely interventions, counseling, or additional support for students in need. The ongoing evolution of Deep Learning and AI further enhances the capabilities of NLP. As a result, the demand for NLP in the Education Market is experiencing rapid growth.
Market Dynamics
Drivers:
- Rising Demand for Efficient Language Learning
- Increasing Adoption of Predictive Analytics to Provide Targeted Support to Students at Risks
- Evolution of AI and Deep Learning
Opportunities:
- Growing Adoption of NLP to Assess Student Performance
- Soaring Demand for Personalized Learning
- Significant R&D Activities by Market Vendors
Increasing adoption of learning analytics
The NLP in Education Market is witnessing a notable surge in the adoption of learning analytics, reflecting a growing recognition of its transformative impact. Learning analytics, within the realm of NLP, involves the systematic analysis of educational data to gain insights into student learning behaviors, performance patterns, and engagement levels. Educational institutions are increasingly leveraging NLP-powered learning analytics to track and assess students' natural language interactions, enabling personalized feedback, tailored recommendations, and targeted learning materials. This data-driven approach not only enhances the learning experience for students but also empowers educators with valuable insights to refine teaching strategies and optimize educational outcomes. The increasing adoption of learning analytics within NLP in the Education Market underscores a strategic shift towards data-driven decision-making and personalized learning experiences in the realm of education.
The market for NLP in Education is led by North America.
In 2022, the NLP in Education Market in North America emerged as the dominant force, capturing a substantial market share. This region holds a significant position in natural language processing technology, as it is a prominent hub for AI and machine learning technologies. Moreover, the presence of key market players in the United States fosters innovation and contributes to the overall growth of the natural language processing market. Within the North American region, the U.S. specifically held the largest market share in the NLP in Education market, while the Canadian NLP in Education market exhibited the fastest growth.
Furthermore, the Asia Pacific NLP in Education market is poised for substantial growth. This upswing is attributed to the increasing smartphone usage, rapid technological advancements, the digitalization of economies, and proactive initiatives by regional governments. The Asia Pacific region boasts a robust IT infrastructure, coupled with extensive software and service offerings, and holds leadership positions in cutting-edge industries such as robotics, providing a fertile ground for profitable market expansion. Notably, China leads the NLP in Education market in terms of market share, while the Indian market exhibits the fastest growth within the Asia-Pacific region.
The Statistical NLP Segment is Anticipated to Hold the Largest Market Share During the Forecast Period
The market is segmented based on Model Type into Rule-based NLP, Statistical NLP, and Hybrid NLP. Statistical NLP emerges as a pivotal player in the field of NLP for educational purposes, demonstrating heightened accuracy in natural language tasks such as recommender systems, language translation, sentiment analysis, and named entity recognition. Leveraging the ability to learn from extensive data, statistical models exhibit superior generalization compared to rule-based systems. They efficiently scale with large volumes of text data, a task that proves challenging for rule-based systems as the number of rules increases. In contrast to rule-based systems, statistical NLP demonstrates greater adaptability to new domains and languages. Its effectiveness in handling complex data and training without manual updates has led to an increased demand for the Statistical model type in the NLP in Education Market.
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