Digital Technologies in the Educational Process and the Effectiveness of Their Use

Mutovkina, Nataliya

doi:10.1007/978-3-031-24475-9_77

Cited by 1 publication

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Outcomes show that learning through the proposed AI chatbot has a positive impact on memory retention and learning outcomes compared to the www.ijacsa.thesai.org learning through Google search engine. Hence, a chatbot is considered an effective tool [10] to support learners and encourage them to freely ask their questions without being evaluated or misjudged.…”

Section: B Problem Statementmentioning

confidence: 99%

An Evolutive Knowledge Base for “AskBot” Toward Inclusive and Smart Learning-based NLP Techniques

Azhari,

Hilal,

Daoudi

et al. 2023

IJACSA

View full text Add to dashboard Cite

Intelligence chatbots have shown a growing interest in different domains including e-learning. They support learners by answering their repetitive and massive questions. In this paper, we develop a smart learning architecture for an inclusive chatbot handling both text and voice messages. Thus, disabled learners can easily use it. We automatically extract, preprocess, vectorize, and construct AskBot's Knowledge Base. The present work evaluates various vectorization techniques with similarity measures to answer learners' questions. The proposed architecture handles both Wh-Questions starting with Wh words and Non-Wh-Questions, beginning with unpredictable words. Regarding Wh-Questions, we develop a neural network model to classify intents. Our results show that the model's accuracy and the F1-Score are equal to 99,5%, and 97% respectively. With a similarity score of 0.6, our findings indicate that TF-IDF has performed well, correctly answering 90% of the tested Wh-Questions. Concerning No-Wh Questions, soft cosine measure, and fasttext successfully answered 72% of Non-Wh-Question.

show abstract

Section: B Problem Statementmentioning

confidence: 99%