applsci-logo

Journal Browser

Journal Browser

Applications of Artificial Intelligence in Innovative Education

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 June 2026 | Viewed by 712

Special Issue Editors


E-Mail Website
Guest Editor
Departamento de Automática, Ingeniería Eléctrica y Electrónica e Informática Industrial, Escuela Técnica Superior de Ingenieros Industriales, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
Interests: Internet of Things; artificial intelligence; sustainable development; innovative education

E-Mail Website
Guest Editor
UPM Laser Centre, Polytechnical University of Madrid, C/Alan Turing 1, 28031 Madrid, Spain
Interests: artificial intelligence; software engineering; interdisciplinary applications; information systems; innovative education

Special Issue Information

Dear Colleagues,

The integration of Artificial Intelligence (AI) in education is reshaping how we learn, teach, and assess. AI enables adaptive learning environments, personalized instruction, and intelligent, automated evaluation processes. Its ethical and responsible use is necessary to ensure inclusive and equitable education.

We are pleased to invite you to contribute to this Special Issue, ‘Applications of Artificial Intelligence in Innovative Education’, which will encourage the exchange of knowledge related to AI-based tools, models, and strategies that enhance teaching, learning, and automated assessment.

In this Special Issue, original research articles and reviews are welcome. Research areas may include, but are not limited to, the following:

  1. Innovative uses of AI by teachers and students.
  2. Empirical research involving students.
  3. Intelligent and automated educational assessment.
  4. Virtual tutors, chatbots, and intelligent learning assistants.
  5. Ethical, social, and pedagogical aspects of the use of AI in education.
  6. Emerging AI-based applications in innovative education.

We look forward to receiving your contributions.

Prof. Dr. Ascensión López-Vargas
Prof. Dr. Ángel García-Beltrán
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • innovative education
  • artificial intelligence
  • chatbots
  • automated assessment
  • emerging tools

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

22 pages, 1921 KB  
Article
Hybrid Semantic–Syntactic NLP Framework for Intelligent Grading of Short Answers and Cloze Questions
by Olaniyan Julius, Silas Formunyuy Verkijika and Ibidun C. Obagbuwa
Appl. Sci. 2026, 16(7), 3191; https://doi.org/10.3390/app16073191 - 26 Mar 2026
Viewed by 423
Abstract
The increasing demand for scalable and fair assessment of open-form responses in digital education shows the need for intelligent grading systems capable of balancing syntactic precision with semantic understanding. This study proposes a hybrid semantic–syntactic NLP framework for automated grading of short-answer and [...] Read more.
The increasing demand for scalable and fair assessment of open-form responses in digital education shows the need for intelligent grading systems capable of balancing syntactic precision with semantic understanding. This study proposes a hybrid semantic–syntactic NLP framework for automated grading of short-answer and cloze-type questions. The framework integrates a rule-based matcher for syntactic accuracy, MPNet (Masked and Permuted Pre-trained Network) embeddings for semantic similarity, and a fine-tuned DeBERTa (Decoding-enhanced Bidirectional Encoder Representations from Transformer with Disentangled Attention) regressor for continuous score prediction, while a T5-small model provides pedagogically aligned feedback generation. Evaluations were conducted using benchmark corpora, synthetic cloze datasets, and a domain-specific short-answer corpus. Results demonstrate that the hybrid system outperforms traditional baselines, achieving 91% accuracy, a 0.89 F1 score, a mean absolute error of 0.36, and strong inter-rater agreement (κ = 0.87), aligning closely with human graders. Qualitative analyses show that the framework successfully recognizes paraphrased responses, assigns partial credit, and generates meaningful feedback. Ablation studies further validate the necessity of each subsystem, with performance significantly declining when components were removed. The findings confirm that the proposed framework is both computationally robust and pedagogically valuable, establishing a foundation for scalable, interpretable, and fair automated grading in contemporary educational environments. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Innovative Education)
Show Figures

Graphical abstract

Back to TopTop