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Artificial Intelligence-Powered Higher Education: A New Era of Learning, Rights...
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Artificial Intelligence-Powered Higher Education: A New Era of Learning, Rights Protection, and Human-Machine Synergy

A special issue of Trends in Higher Education (ISSN 2813-4346).

Deadline for manuscript submissions: closed (30 January 2026) | Viewed by 21601

Special Issue Editors

Prof. Dr. Carlos Hervás-Gómez

E-Mail Website
Guest Editor
Department of Teaching and Educational Organization, University of Sevilla, 41013 Sevilla, Spain
Interests: artificial intelligence; teacher training; ICT; education research; emerging educational technologies; computational thinking
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. María Dolores Díaz-Noguera

E-Mail Website
Guest Editor
Department of Teaching and Educational Organization, University of Sevilla, 41013 Sevilla, Spain
Interests: artificial intelligence; school organization; teacher training; education research; emerging educational technologies; computational thinking
Special Issues, Collections and Topics in MDPI journals
Dr. Liliana Mâță

E-Mail Website
Guest Editor
Teacher Training Department, Vasile Alecsandri University of Bacău, 600115 Bacau, Romania
Interests: adoption of AI in education; teacher training; ICT; emerging technologies in education; education research; personalised learning; technology-enabled learning; digital competences
Dr. Nadia Barkoczi

E-Mail Website
Guest Editor
Department of Teacher Training, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
Interests: adoption of AI in education; teacher training; ICT; emerging technologies in education; education research; personalised learning; technology-enabled learning; digital competences

Special Issue Information

Dear Colleagues,

Today, in the different activities we engage in throughout the day, from how we interact to how we learn, inform ourselves, or make decisions, everything revolves around artificial intelligence. It has become part of our daily lives. Artificial intelligence is one of the most impactful technologies globally; it has become ubiquitous in everyday life. A wide range of examples illustrate how AI has penetrated various aspects of human life, such as access to information via the internet, the consumption of news and entertainment, the identification of people using facial recognition surveillance systems, the functioning of financial markets, and the movements of drivers and pedestrians. As AI advances, possibilities that were once only speculative may soon become tangible.

Throughout history, technologies that use language have been major turning points. These include the invention of writing, which enabled the symbolic treatment of language; the printing press, which facilitated the wider and faster dissemination of knowledge; and the creation of computers capable of processing binary language. All these milestones led to the age of digital information and technology.

As we continue to use AI, it will be discovered that many problems, in terms of applying it to various processes, remain to be overcome. In this regard, the most critical questions that educational institutions must address are what to teach students in this technology-based society and how the many disruptive technologies will alter the way people work. Thus, students must understand that repetitive and routine jobs will eventually be mechanised and performed by robots, artificial intelligence, and automation. However, jobs will always require creativity, critical thinking, and emotional intelligence. At present, many institutions do not teach students the skills they need for their future careers.

This Special Issue aims to explore the impact of artificial intelligence on education: analysing how AI technologies are transforming teaching and learning methods; assessing the protection of rights in AI-driven education; fostering human–machine collaboration; promoting the development of 21st century skills; and analysing case studies and best practices.

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

  • Innovations in personalised learning;
  • Artificial intelligence and accessibility in education;
  • Ethics and privacy in education with artificial intelligence;
  • The development of digital competences;
  • Collaboration between teachers and artificial intelligence systems;
  • Automated assessment and feedback;
  • The impact of artificial intelligence on higher education;
  • Policies and regulations for education with artificial intelligence;
  • The future of artificial intelligence education;
  • Case studies and best practices.

We look forward to receiving your contributions.

Prof. Dr. Carlos Hervás-Gómez
Prof. Dr. María Dolores Díaz-Noguera
Dr. Liliana Mâță
Dr. Nadia Barkoczi
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 double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Trends in Higher Education is an international peer-reviewed open access quarterly 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 1200 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

  • artificial intelligence applied to education
  • personalised learning
  • accessibility ethics
  • privacy
  • digital competences
  • human–machine collaboration
  • automated assessment
  • digital transformation
  • educational innovation
  • emerging technologies
  • self-regulated learning

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

Published Papers (5 papers)

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36 pages, 506 KB  
Article
Artificial Intelligence in Statistics Education: Leveraging LLMs for Analysis and Learning
by Enrico di Bella and Sara Preti
Trends High. Educ. 2026, 5(2), 39; https://doi.org/10.3390/higheredu5020039 - 7 May 2026
Viewed by 283
Abstract
Large Language Models (LLMs), such as GPT (GPT-5.5) by OpenAI and Gemini (Gemini 3.2 Pro) by Google DeepMind, have shown impressive capabilities in text generation and code assistance. This study evaluates their performance in generating R code—that is, computer scripts written in the [...] Read more.
Large Language Models (LLMs), such as GPT (GPT-5.5) by OpenAI and Gemini (Gemini 3.2 Pro) by Google DeepMind, have shown impressive capabilities in text generation and code assistance. This study evaluates their performance in generating R code—that is, computer scripts written in the R programming language for statistical analysis—using both classic educational datasets, including “The Lady Tasting Tea”, “Titanic”, “Iris”, and more recent datasets likely not included in the models’ training data. We assess the accuracy, readability, and educational relevance of the generated code, providing both quantitative and qualitative evaluations that highlight strengths and limitations of LLMs. Our findings suggest that while LLMs generate correct and interpretable R code in many cases, critical human oversight remains essential when integrating AI into educational contexts to ensure rigor and avoid potential misuse. Full article
(This article belongs to the Special Issue Artificial Intelligence-Powered Higher Education: A New Era of Learning, Rights Protection, and Human-Machine Synergy)
14 pages, 245 KB  
Article
Exploring Strategies to Detect and Mitigate Bias in AI in Education: Students’ Perceptions and Didactic Approaches
by María Ribes-Lafoz, Borja Navarro-Colorado and José Rovira-Collado
Trends High. Educ. 2026, 5(2), 33; https://doi.org/10.3390/higheredu5020033 - 3 Apr 2026
Viewed by 1302
Abstract
The increasing integration of Generative AI (GenAI) into higher education, particularly in the domain of language teaching, presents both opportunities and challenges. While AI-powered tools such as ChatGPT-5 can support language learning by generating personalised content which enables real-time interaction and feedback, they [...] Read more.
The increasing integration of Generative AI (GenAI) into higher education, particularly in the domain of language teaching, presents both opportunities and challenges. While AI-powered tools such as ChatGPT-5 can support language learning by generating personalised content which enables real-time interaction and feedback, they also risk perpetuating biases embedded in training data. These biases can appear in linguistic, cultural or socio-political forms, reinforcing stereotypes and influencing language norms. Therefore, equipping students and educators with strategies to critically assess AI outputs is essential for ethical and responsible AI use in language education. While recent research highlights the risks of algorithmic bias, less attention has been given to the perceptions and attitudes of pre-service teachers, whose future practice will shape classroom uses of these technologies. This exploratory pilot study adopts a survey-based approach to examine pre-service teachers’ baseline awareness of bias in artificial intelligence, with particular attention to linguistic and cultural dimensions Data were collected through an online questionnaire administered to 65 undergraduate students enrolled in Primary Education degree programmes. The study documents baseline perceptions prior to any instructional intervention and provides preliminary empirical evidence to inform the future design of pedagogical strategies aimed at developing critical AI literacy in teacher education. Full article
(This article belongs to the Special Issue Artificial Intelligence-Powered Higher Education: A New Era of Learning, Rights Protection, and Human-Machine Synergy)
14 pages, 915 KB  
Article
Artificial Intelligence and Training in Values in Higher Education: An Inter-University Study Between Spain and Ireland
by José Antonio Ortí Martínez and Esther Puerto Martínez
Trends High. Educ. 2026, 5(1), 21; https://doi.org/10.3390/higheredu5010021 - 20 Feb 2026
Viewed by 743
Abstract
This study examines the role of artificial intelligence (AI) as a mediating tool in values training, based on university students’ reflections on their own values and those represented in literary characters. The research, developed at the Catholic University of Murcia (Spain) and University [...] Read more.
This study examines the role of artificial intelligence (AI) as a mediating tool in values training, based on university students’ reflections on their own values and those represented in literary characters. The research, developed at the Catholic University of Murcia (Spain) and University Collegue Cork (Ireland) integrated the humanistic approach of literature with the pedagogical potential of AI. An exploratory–descriptive mixed-methods design was applied with 126 students of Education and Philology. The instruments included the Hall–Tonna questionnaire, a 12-item Likert scale, and open-ended questions, analyzed using descriptive statistics, mean comparison, and thematic content analysis. The results reflect a preference for values such as justice, perseverance, and empathy, with cultural differences: in Spain, solidarity and community spirit stood out; and in Ireland, integrity and individual responsibility stood out. A total of 78% positively rated AI mediation for its capacity to stimulate critical reflection and ethical debate, although risks linked to technological dependence and cultural bias were noted. It is concluded that the synergy between literature and AI enhances ethical and civic education, provided it is implemented from an ethical and humanizing perspective. Full article
(This article belongs to the Special Issue Artificial Intelligence-Powered Higher Education: A New Era of Learning, Rights Protection, and Human-Machine Synergy)
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15 pages, 1056 KB  
Article
AI-Generated, Personality-Tailored Cases in Teacher Education: A Feasibility Study of Student Experiences
by Vidar Sandsaunet Ulset, Lars Harald Eide and Brage Kraft
Trends High. Educ. 2025, 4(4), 71; https://doi.org/10.3390/higheredu4040071 - 24 Nov 2025
Viewed by 1003
Abstract
Higher education faces increasing demands to address student diversity in engagement, learning preferences, and professional readiness. This study examined the feasibility of integrating personality-tailored case-based learning in teacher education. Building on the Big Five personality model and principles of differentiated, case-based pedagogy, we [...] Read more.
Higher education faces increasing demands to address student diversity in engagement, learning preferences, and professional readiness. This study examined the feasibility of integrating personality-tailored case-based learning in teacher education. Building on the Big Five personality model and principles of differentiated, case-based pedagogy, we developed a prototype that generated individualized case descriptions using a personality inventory and generative AI. The intervention was implemented in a teacher education course, with 37 students (≈79%) completing an anonymous evaluation survey. Quantitative measures included emotion-word selections and Likert-type ratings of case relevance and group discussions; qualitative data were collected through open-ended reflections. Findings indicated that students experienced the intervention as engaging, relevant, and appropriately challenging. Group discussions received the highest ratings, with students emphasizing the value of peer dialogue for gaining new perspectives and making sense of the cases. Qualitative themes highlighted the realism of personalized scenarios, opportunities for reflection, and the importance of scaffolding, while challenges included unclear instructions and limited diversity among cases. The study demonstrates the feasibility and perceived pedagogical value of personality-tailored cases as a scalable model of differentiation in higher education. Future research should adopt controlled designs to disentangle the effects of personality instruction, feedback, and personalization, and systematically evaluate the distinctiveness of generated cases. By integrating psychological self-insight with authentic practice scenarios, personality-informed case-based learning shows promise for enhancing student agency, reflective competence, and readiness for professional practice. Full article
(This article belongs to the Special Issue Artificial Intelligence-Powered Higher Education: A New Era of Learning, Rights Protection, and Human-Machine Synergy)
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17 pages, 402 KB  
Systematic Review
A Systematic Review of the Use of AI in EFL and EL Classrooms for Gifted Students
by Carmen García-López, María Tabuenca-Cuevas and Ignasi Navarro-Soria
Trends High. Educ. 2025, 4(3), 33; https://doi.org/10.3390/higheredu4030033 - 10 Jul 2025
Cited by 3 | Viewed by 7199
Abstract
There is a growing body of literature that focuses on the applicability of artificial intelligence (AI) in English as a Foreign Language (EFL) and English Language (EL) classrooms; however, educational application of AI in the EFL and EL classroom for gifted students presents [...] Read more.
There is a growing body of literature that focuses on the applicability of artificial intelligence (AI) in English as a Foreign Language (EFL) and English Language (EL) classrooms; however, educational application of AI in the EFL and EL classroom for gifted students presents a new paradigm. This paper explores the existing research to highlight current practices and future possibilities of AI for teaching EFL and EL to address gifted students’ special needs. In general, the uses of AI are being established for class instruction and intervention; nevertheless, there is still uncertainty about practitioner use of AI with gifted students in EFL and EL classrooms. This review identifies 42 examples of GenAI Models that can be used in gifted EFL and EL classrooms. In addition, the research conducted thus far has highlighted the positive contribution of the use of AI in EFL and EL environments, albeit some disadvantages and challenges have also been identified. The results also endorse the use of AI with gifted students as an asset and highlight the need for AI literacy for both teachers and gifted students in order to adapt to this new educational paradigm. In conclusion, more studies are needed, as many aspects regarding both teachers’ and gifted students’ use of AI remain to be elucidated to improve future applications of AI to teach EFL and EL to gifted students. Full article
(This article belongs to the Special Issue Artificial Intelligence-Powered Higher Education: A New Era of Learning, Rights Protection, and Human-Machine Synergy)
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