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Paper ID:IJSREM64419

A Survey of Artificial Intelligence Tools for Learning, Scholarly Research, and Academic Writing

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64419

Volume:

10 |

5 |

May 2026

Pages:

1-3

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM64419

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Dr.K.Saraswathi

Dr.K.Saraswathi

Department of General Engineering

Annai Mathammal Sheela Engineering College

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M. Shanmugapriyan

M. Shanmugapriyan

Department of Computer Science

Nehru Memorial College

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Abstract

Artificial Intelligence (AI) has become an important component of modern education, research, and professional writing. This review presents a detailed discussion of AI-based tools that support machine learning development, scientific research, and academic content creation. Major machine learning frameworks such as Scikit-learn, TensorFlow, Theano, Keras, Caffe, MXNet, and Google ML Kit are examined for their capabilities in data analysis, neural network implementation, and model deployment. The paper also reviews AI-assisted research platforms including PDFgear, Consensus, Scite, Elicit, Semantic Scholar, SciSpace, OpenRead, ResearchRabbit, Humata AI, Perplexity AI, ChatDOC, and PDF.ai. These tools help researchers locate relevant literature, summarize complex documents, evaluate citations, and improve information retrieval. In addition, AI writing assistants such as Grammarly, QuillBot, Writesonic, ChatGPT, TextCortex, Zeno Assistant, and ZenoChat are discussed for their ability to enhance grammar, paraphrasing, summarization, and content generation. The review highlights the growing impact of AI technologies on academic productivity, knowledge acquisition, and research quality.

KEYWORDS

Artificial Intelligence Machine Learning Deep Learning Frameworks Research Assistance Academic Writing Natural Language Processing Literature Review Scholarly Communication Educational Technology

Cite This Article

Dr.K.Saraswathi, M. Shanmugapriyan, "A Survey of Artificial Intelligence Tools for Learning, Scholarly Research, and Academic Writing," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-3, May 2026. https://doi.org/10.55041/IJSREM64419

Full Article/Conclusion

Artificial intelligence tools have become indispensable resources for modern learners, educators, researchers, and writers. Machine learning frameworks simplify the development of intelligent systems, while research assistance platforms accelerate literature review and knowledge discovery. Writing assistants enhance the quality, clarity, and originality of academic documents. The continued advancement of AI technologies is expected to further improve productivity, accuracy, and accessibility across educational and research environments. Organizations and institutions that effectively integrate these tools can achieve greater efficiency and innovation in knowledge creation and dissemination.

References

[1]              Mulam, V. R. (2024). Machine Learning and AI Innovations      with Python: Trends and Future Directions. International Journal for Multidisciplinary Research (IJFMR), 6(3),            1–12. [2]             Medavarapu, S. S. (2024). Advancements in Deep Learning: A Review of Keras and TensorFlow Frameworks. Journal of Scientific and Engineering  Research, 11(5), 282–286. [3]             Rao, M. N. (2023). A Comparative Analysis of Deep Learning Frameworks and Libraries. International Journal of Intelligent Systems and Applications in Engineering, 11(2s). [4]             Pedregosa, F., et al. (2011). Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825–2830. [5]             Abadi, M., et al. (2016). TensorFlow: A System for Large-Scale Machine Learning. OSDI Conference Proceedings, 265–283. [6]             Al Rfou, R., et al. (2016). Theano: A Python Framework for Fast Computation of Mathematical Expressions. arXiv preprint arXiv: 1605.02688. [7]             Chollet, F. (2015). Keras: Deep Learning Library for Theano and TensorFlow. GitHub Repository. [8]             Jia, Y., et al. (2014). Caffe: Convolutional Architecture for Fast Feature Embedding. ACM Multimedia, 675–678. [9]             Chen, T., et al. (2015). MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems. arXiv preprint arXiv: 1512.01274.          [10] Scite Inc. (2023). Scite: Smart Citation Indexing Platform.

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Publication Date

6/1/2026

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Double-Blind Peer Review

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