NLP-based personal learning assistant for school education

Mathew, Ann Neethu; Rohini, V; Paulose, Joy

doi:10.11591/ijece.v11i5.pp4522-4530

Cited by 22 publications

(12 citation statements)

References 24 publications

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“…We used the Facebook messenger platform because a large majority of Moroccan university students uses Facebook especially with this period of pandemic that the world is experiencing in the face of Covid-19.  Natural language processing: after the chatbot receives the user request, every received message is processed through NLP, [18], [22], [23], [45].  Bot logic: the bot logical flow of interactions  Machine learning: every time the bot receives a message, it can improve its answers.…”

Section: Research Methods 21 Chatbot Frameworkmentioning

confidence: 99%

Engaging students to fill surveys using chatbots: University case study

Belhaj

Hamdane

Chaoui

et al. 2021

IJEECS

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The use of chatbot or conversational agents is becoming common these days by the companies in many fields to make smart conversations with users. Backed by artificial intelligence and natural language processing they provide a strong platform to engage users. These positive aspects of chatbots can be beneficial in the educational sector, especially in conducting online survey. This study aims to explore the feasibility of a new chatbot approach survey as a new survey method in Moroccan university to overcome the web survey’s common response quality problems. Indeed, having student feedback before and after graduation is essential for university assessment. This new approach keeps students engaged, supportive, and even excited to offer feedback without getting bored and dropping the conversation, especially in Moroccan universities known by an overcrowding of students where it is difficult to get their feedback. This feedback feeds into our university' databases for further reporting and decision making to improve the quality of educational content and student-oriented services. Finally, we have shown the effectiveness of our approach by a comparative data study between the traditional online survey and the use of this chatbot.

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Section: Research Methods 21 Chatbot Frameworkmentioning

confidence: 99%

Engaging students to fill surveys using chatbots: University case study

Belhaj

Hamdane

Chaoui

et al. 2021

IJEECS

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show abstract

“…In 2020, Verma Shivang et al [21] mentioned about Jabberwacky's main goal that was to transition from a text-based system to a fully voice-driven system. Ann Neethu Mathew et al [22] have implemented an NLP-based personal learning assistant for school education. The chatbot proposed in this paper requires the potential to cover the whole subject's contents which can be achieved by enhancing the ontology and knowledge base.…”

Section: Literature Surveymentioning

confidence: 99%

Advanced NLP Models for Technical University Information Chatbots: Development and Comparative Analysis

Attigeri,

Agrawal,

Kolekar

2024

IEEE Access

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The process to obtain the information about university/institute is a critical stage in the academic journey of prospective students who are seeking information about the specific courses which makes that university/institute unique. This process begins with exploration to general information about universities through websites, rankings, and brochures from various sources. Most of the time, information available on different sources leads to discrepancies and influences student's decisions. By addressing inquiries promptly and providing valuable information, universities can guide individuals in making informed choices about their academic future. To address this, the chatbot application is the most effective tool to be implemented and make it functional on university's functional website. A chatbot is an artificially intelligent tool which can interact with humans and can mimic a conversation. This tool can be implemented using advanced Natural Language Processing (NLP) models to provide the pre-defined answers to the student's queries. Chat-bot is very helpful for query resolution during the counseling process of the institute as it will provide official/uniform information and can be accessed 24x7. Therefore, the aim of this research work was to implement a chat-bot using various NLP models and compare them to identify best one. In this work, five chat-bot models were implemented using neural networks, TF-IDF vectorization, sequential modeling and pattern matching. From the results, it was observed that neural network-related models had better accuracy than TF-IDF and pattern matching model, and sequential modeling is the most accurate model because it prevents over-fitting. Furthermore, a chat-bot having any kind of optimizer can improve the result and it is most important that pattern matching, and semantic analysis should be the parts of a chat-bot for real time scenarios.

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“…Through systematic review of the literature, it was found that chatbots that are built for student's assistance are rare and do not include many features. The most recent student's assistance chatbot found in literature was an intelligent tutoring system built using NLP ontology in 2021 to assist school students in their learning journey [1]. Due to the rareness of similar chatbots, we surveyed the literature to investigate the key approaches, methodologies, and applications that can be used to build the features or the main modules of our academic assistance chatbot.…”

Section: Literature Reviewmentioning

confidence: 99%

Academic assistance chatbot-a comprehensive NLP and deep learning-based approaches

K. Negied,

H. Anwar,

M. Abouaish

et al. 2024

IJEECS

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<span>The rapid growth of digital technologies and natural language processing (NLP) have revolutionized the field of education, creating new demand for automated academic assistance systems. In this paper, we present an NLP-based academic assistance chatbot designed to provide comprehensive support to students and researchers using deep learning techniques. <br /> The chatbot incorporates a range of intelligent features to assist with university recommendations, article writing, automatic question answering (QA), and job search. By leveraging sentiment analysis and sarcasm detection models. The proposed chatbot could offer accurate and insightful university recommendations. Additionally, the chatbot incorporates spell and grammar checking, summarization, paraphrasing, and topic modeling capabilities to aid users in enhancing their writing skills. The QA module enables users to obtain quick and precise answers to factoid-based questions. Moreover, the chatbot helps with internships and job search. According to literature, this work presents the first assistance chatbot that encapsulates all features that may be needed by a university student to facilitate and improve his/her learning process. The results demonstrated clearly in the body of the paper showed the success achieved by the academic assistant proposed and built in this work in all its features or modules to offer help to university students and graduates.</span>

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NLP-based personal learning assistant for school education

Cited by 22 publications

References 24 publications

Engaging students to fill surveys using chatbots: University case study

Engaging students to fill surveys using chatbots: University case study

Advanced NLP Models for Technical University Information Chatbots: Development and Comparative Analysis

Academic assistance chatbot-a comprehensive NLP and deep learning-based approaches

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