NLP in Education Market

NLP in Education Market Size - Growth, Report & Analysis

The NLP in Education Market size accounted for $99 million in 2023. It is expected to grow at an effective CAGR of 18.1% from 2023 to 2028. The revenue forecast for 2028 is set for the valuation of $228 million. The base year for estimation is 2022 and the historical data available for the years from 2023 to 2028. 

The growing evolution of AI and deep learning, digital transformation, cloud-native, and conversational AI will drive the market.

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NLP in Education Market Growth Dynamics

Driver: Rising demand for efficient language learning

NLP is used in language learning applications to provide better pronunciation feedback, enhance the quality of translations, and create conversational bots that allow students to practice speaking with an AI-powered virtual tutor. It is used to analyze student data such as performance history, learning style, and preferences to create personalized learning experiences. By tailoring the learning experience to individual students, NLP can help improve engagement and retention. NLP systems can accommodate different learning styles by delivering content in multiple formats, such as visual, auditory, and kinaesthetic, providing flexible, student-centered teaching. NLP applications can also help educators gather data and insights that can be used to shape instruction and improve student learning outcomes.

Restraints: Limited data availability

The effectiveness of NLP technology relies on large amounts of data. However, data in the education industry can be limited due to privacy regulations and other concerns. The limited data can limit the accuracy and usefulness of NLP technology in the education market. NLP technology can be complex and difficult to use for individuals who are not familiar with the technology. This can limit its adoption and effectiveness in the education market. NLP technology is typically designed to work with one or a few languages, which can create a challenge for educators and students who speak other languages or dialects.

Opportunity: Increasing adoption of learning analytics

NLP can analyze data from student transcripts and other educational documents to provide insights into student performance and learning trends. NLP can help teachers identify areas where students struggle and adjust their teaching methods accordingly. NLP can be used to develop language learning tools that provide personalized learning experiences to students. By analyzing the student’s vocabulary, sentence structure, and pronunciation, NLP algorithms can offer tailored feedback and recommendations to help them improve. NLP can analyze student essays and other written assignments to provide automated grading.

Challenge: Increasing requirement for customization

The NLP in education market often requires customized NLP solutions that meet the specific requirements of teachers, students, and institutions. However, developing and deploying customized solutions can be challenging and time-consuming, especially for smaller organizations with limited resources. The NLP in education market requires NLP models that are accurate and easy for non-technical users, such as teachers and students. Balancing usability and accuracy can be challenging, as more complex models may be more accurate but less user-friendly, and vice versa. Language can vary significantly across different education settings, including schools, grade levels, and subject areas. This variation makes it difficult to develop NLP models that can accurately identify and extract information across different educational domains.

NLP in Education Market  Ecosystem

Based on end-user, academic segment to hold highest market share during  forecast period

NLP solutions help academic user to enhance the learning experience for students, improve the efficiency of teaching and administrative processes, and provide insights that can inform decision-making. NLP can be used to enhance language learning by analyzing speech patterns, identifying pronunciation errors, and providing feedback to students. NLP can be used to create intelligent content for educational purposes, such as textbooks and online courses. This can help in making the content more interactive, engaging, and relevant to the student’s needs.

Based on model type, statistical NLP model to hold highest market share during  forecast period

Statistical NLP can achieve higher accuracy in natural language tasks such as language translation, sentiment analysis, and named entity recognition. This is because statistical models can learn from a large amount of data and generalize better than rule-based systems. Statistical NLP can be easily scaled to handle large volumes of text data, whereas rule-based systems can become unwieldy as the number of rules increases. Statistical NLP can adapt to new domains and languages easily than rule-based systems. It can be trained on new data without requiring manual updates to rules, making it an effective approach for handling complex and dynamic language data.

Based on application, corporate training segment to have highest growth rate during  forecast period

NLP solutions help improve the effectiveness, efficiency, and scalability of corporate training programs while reducing costs and improving the learner’s experience. NLP solutions can help to personalize the training experience by analyzing the learner’s language, speech patterns, and behaviors. With this information, the training program can be tailored to meet the specific needs of each learner. NLP solutions can reduce the cost of training by automating repetitive tasks, such as grading and assessment, and by reducing the need for physical training materials and instructors.

North America to account for the highest market share during the forecast period.

Key players:

This research study outlines the market potential, dynamics, and major vendors operating in the NLP in education market. Key and innovative vendors in the NLP in education market include IBM (US), Microsoft (US), Google (US), AWS (US), SAS Institute (US), Inbenta (US), Baidu (China), Welocalize (US), Yellow.ai (US), NICE (US), ABBYY (US), Automated Insights (US), Width.ai (US), Revolve.ai (Islamabad), Primer.ai (US), Carnegie Learning (US), Gecko (US), Ivy.ai (US), Attivio (US), Conversica (US), Avaamo (US), Aylien (Ireland), Haptik (India), Gupshup (US), Sensforth.ai (US), Chivox (China), and Cognii (US). The study includes an in-depth competitive analysis of these key players in the NLP in Education market with their company profiles, recent developments, and key market strategies.

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Scope of the Report

NLP in Education Market Highlights

This research report categorizes the NLP in Education Market to forecast revenues and analyze trends in each of the following submarkets:

Recent Developments:

• In March 2023, Yellow.ai launched Salem, which is a new AI-powered customer service channel available on WhatsApp.
• In February 2023, Microsoft launched Automated ML supports NLP, which allows ML professionals and data scientists to bring text data and build custom models for tasks such as multi-class text classification, multi-label text classification, and named entity recognition (NER).
• In January 2023, IBM announced IBM Partner Plus. This new program reimagines how IBM engages with its business partners through unprecedented access to IBM resources, incentives, and tailored support to deepen its technical expertise and help speed time to market.
• In December 2022, NICE launched ElevateAI, a new AIaaS solution that brings the power of Enlighten AI, its purpose-built CX AI, to the developer community.
• In November 2022, Google announced an ambitious new project to develop a single AI language model that supports the world’s 1,000 most spoken languages.

Frequently Asked Questions (FAQ):

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