Educational Equity Gap and Artificial Intelligence in STEM Subjects

A special issue of Education Sciences (ISSN 2227-7102).

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 7213

Special Issue Editor


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Guest Editor
School of Computing and Engineering, University of West London, London W5 5RF, UK
Interests: STEM in education; equity gap; artificial intelligence in education; innovative teaching in mathematics

Special Issue Information

Dear Colleagues, 

This Special Issue of Educational Sciences welcomes submissions from contributors focused on the “Educational Equity Gap and Artificial Intelligence in STEM Subjects”.

This Special Issue focuses on the longstanding challenge faced by education scholars and practitioners of STEM in attempting to provide innovative teaching and learning approaches to narrow the equity gap of all students regardless of gender, ethnicity, or economic background. Artificial intelligence (AI) has the potential to address some of the principal challenges in education today and may accelerate progress in educational equity as well as quality for all students by modernizing teaching and learning practices, particularly regarding minority students.

All research methods will be considered, including quantitative, qualitative, and mixed-methods research, that explore issues relating to the equity gap in STEM education and the possible development of a more equitable society by considering artificial intelligence and emerging technologies. Machine learning and AI are fast-growing analytical procedures that are gaining eminence and can potentially transform the educational equity gap by changing learners’ experiences both within and beyond amphitheaters through innovative and improved learning processes as well as pedagogical strategies.

The topics of this Special Issue include, but are not limited to, the following:

  1. Educational equity gap in STEM education;
  2. Pedagogical models to address the attainment gap in STEM education;
  3. Design and development of effective uses of emerging technologies, including AI in STEM teaching and learning;
  4. Benefits and challenges relating to the application of AI in teaching or learning contexts in STEM subjects;
  5. Implementing AI in inclusive STEM education to tackle the equity gap.

I look forward to receiving your contributions.

Dr. Anastasia Sofroniou
Guest Editor

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Keywords

  • educational equity gap
  • attainment gap
  • innovative teaching and learning approaches in STEM
  • minoritized ethnic backgrounds
  • inclusive education
  • diversity
  • artificial intelligence
  • emerging technologies

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Published Papers (1 paper)

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Review

39 pages, 2654 KiB  
Review
Emotions Matter: A Systematic Review and Meta-Analysis of the Detection and Classification of Students’ Emotions in STEM during Online Learning
by Aamir Anwar, Ikram Ur Rehman, Moustafa M. Nasralla, Sohaib Bin Altaf Khattak and Nasrullah Khilji
Educ. Sci. 2023, 13(9), 914; https://doi.org/10.3390/educsci13090914 - 8 Sep 2023
Cited by 13 | Viewed by 6452
Abstract
In recent years, the rapid growth of online learning has highlighted the need for effective methods to monitor and improve student experiences. Emotions play a crucial role in shaping students’ engagement, motivation, and satisfaction in online learning environments, particularly in complex STEM subjects. [...] Read more.
In recent years, the rapid growth of online learning has highlighted the need for effective methods to monitor and improve student experiences. Emotions play a crucial role in shaping students’ engagement, motivation, and satisfaction in online learning environments, particularly in complex STEM subjects. In this context, sentiment analysis has emerged as a promising tool to detect and classify emotions expressed in textual and visual forms. This study offers an extensive literature review using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) technique on the role of sentiment analysis in student satisfaction and online learning in STEM subjects. The review analyses the applicability, challenges, and limitations of text- and facial-based sentiment analysis techniques in educational settings by reviewing 57 peer-reviewed research articles out of 236 articles, published between 2015 and 2023, initially identified through a comprehensive search strategy. Through an extensive search and scrutiny process, these articles were selected based on their relevance and contribution to the topic. The review’s findings indicate that sentiment analysis holds significant potential for improving student experiences, encouraging personalised learning, and promoting satisfaction in the online learning environment. Educators and administrators can gain valuable insights into students’ emotions and perceptions by employing computational techniques to analyse and interpret emotions expressed in text and facial expressions. However, the review also identifies several challenges and limitations associated with sentiment analysis in educational settings. These challenges include the need for accurate emotion detection and interpretation, addressing cultural and linguistic variations, ensuring data privacy and ethics, and a reliance on high-quality data sources. Despite these challenges, the review highlights the immense potential of sentiment analysis in transforming online learning experiences in STEM subjects and recommends further research and development in this area. Full article
(This article belongs to the Special Issue Educational Equity Gap and Artificial Intelligence in STEM Subjects)
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