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How Artificial Intelligence Can Enhance Education: Current Practices and Challenges

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

Deadline for manuscript submissions: closed (15 January 2025) | Viewed by 38894

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Special Issue Editor

Prof. Dr. Julie Delello

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Guest Editor

School of Education, The University of Texas at Tyler, Tyler, TX 75799, USA
Interests: professional interests focus on academic innovations; artificial intelligence; emerging technologies; gerontechnology; esports; social media platforms for authentic learning

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) is transforming various aspects of education, from curriculum design to assessment and feedback. AI offers the potential to enhance the quality and effectiveness of teaching and learning by providing personalized and adaptive learning experiences, streamlining administrative tasks, and supporting early intervention and remediation. However, AI also poses significant challenges and risks, such as data privacy and security, algorithmic bias and fairness, and ethical and social implications. Striking a balance between harnessing the benefits of AI for enhanced education and addressing the associated risks is crucial in ensuring a responsible and equitable integration of these technologies (Delello et al., 2024).

The use of AI and its effects on teaching and learning have not been fully investigated. In fact, according to the 2023 Teaching and Learning Horizon Report, the absence of best practices on how to incorporate AI is an obstacle for its widespread use (Pelletier et al., 2023). Leveraging insights and approaches from diverse fields, this Special Issue aims to shed additional light on the utilization of AI to support learning and consider how educators can responsibly integrate such technologies.

Original research articles, case studies, and reviews are invited. The scope of the submission should focus on the use of artificial intelligence (AI) to support learning environments and may include (but is not limited to) items such as the following:

Conversational AI (chatbots, virtual agents, ChatGPT);
Intelligent tutoring and personalized learning;
Immersive learning environments (gaming, simulations);
The use of data analytics and AI for decision making;
Improved accessibility opportunities;
Equity, inclusion, and differentiation of learning;
Academic integrity (cheating, plagiarism, and policy development);
Ethics, data privacy, and the potential for bias;
Testing, grading, and assessment;
AI literacy, overreliance, and student motivation;
Preparing the future workforce.

We look forward to receiving your contributions.

References

Delello, J. A., Sung, W., & Mokhtari, K., & De Giuseppe, T. (2024, in press). Are K-16 educators prepared to address the educational and ethical ramifications of artificial intelligence software? Proceedings of the Future of Information and Communication Conference (FICC) 2024, Lecture Notes in Networks and Systems.

Pelletier, K., Robert, J., Muscanell, N., McCormack, M., Reeves, J., Arbino, N., & Grajek, S., Birdwell, T., Liu, D., Mandernach, J., Moore, A., Porcaro, A., Rutledge, R., & Zimmern, J. (2023). 2023 Educause Horizon Report, Teaching and Learning Edition, 5. 2023 EDUCAUSE Horizon Report | Teaching and Learning Edition | EDUCAUSE Library

Prof. Dr. Julie Delello
Guest Editor

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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Education Sciences is an international peer-reviewed open access monthly 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 1800 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

education
artificial intelligence
large language models
disruptive technologies
emerging technologies
teaching
learning

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Published Papers (10 papers)

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Research

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23 pages, 3191 KiB

Open AccessArticle

Technology and Emotions: AI-Driven Software Prototyping for the Analysis of Emotional States and Early Detection of Risky Behaviors in University Students

by Alba Catherine Alves-Noreña, María-José Rodríguez-Conde, Juan Pablo Hernández-Ramos and José William Castro-Salgado

Educ. Sci. 2025, 15(3), 350; https://doi.org/10.3390/educsci15030350 - 11 Mar 2025

Viewed by 484

Abstract

Technology-assisted emotion analysis opens new possibilities for the early identification of risk behaviors that may impact the well-being of university students, contributing to the creation of healthier, safer, and more proactive educational environments. This pilot study aimed to design and develop a technological prototype capable of analyzing students’ emotional states and anticipating potential risk situations. A mixed-methods approach was adopted, employing qualitative methods in the ideation, design, and prototyping phases and quantitative methods for laboratory validation to assess the system’s accuracy. Additionally, mapping and meta-analysis techniques were applied and integrated into the chatbot’s responses. As a result, an educational technological innovation was developed, featuring a chatbot structured with a rule-based dialogue tree, complemented by an ontology for knowledge organization and a pre-trained artificial intelligence (AI) model, enhancing the accuracy and contextualization of user interactions. This solution has the potential to benefit the educational community and is also relevant to legislative stakeholders interested in education and student well-being, institutional leaders, academic and well-being coordinators, school counselors, teachers, and students. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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27 pages, 668 KiB

Open AccessArticle

AI in the Classroom: Insights from Educators on Usage, Challenges, and Mental Health

by Julie A. Delello, Woonhee Sung, Kouider Mokhtari, Julie Hebert, Amy Bronson and Tonia De Giuseppe

Educ. Sci. 2025, 15(2), 113; https://doi.org/10.3390/educsci15020113 - 21 Jan 2025

Cited by 1 | Viewed by 6716

Abstract

This study examines educators’ perceptions of artificial intelligence (AI) in educational settings, focusing on their familiarity with AI tools, integration into teaching practices, professional development needs, the influence of institutional policies, and impacts on mental health. Survey responses from 353 educators across various levels and countries revealed that 92% of respondents are familiar with AI, utilizing it to enhance teaching efficiency and streamline administrative tasks. Notably, many educators reported students using AI tools like ChatGPT for assignments, prompting adaptations in teaching methods to promote critical thinking and reduce dependency. Some educators saw AI’s potential to reduce stress through automation but others raised concerns about increased anxiety and social isolation from reduced interpersonal interactions. This study highlights a gap in institutional AI policies, leading some educators to establish their own guidelines, particularly for matters such as data privacy and plagiarism. Furthermore, respondents identified a significant need for professional development focused on AI literacy and ethical considerations. This study’s findings suggest the necessity for longitudinal studies to explore the long-term effects of AI on educational outcomes and mental health and underscore the importance of incorporating student perspectives for a thorough understanding of AI’s role in education. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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13 pages, 617 KiB

Open AccessArticle

“We Should Not Be Like a Dinosaur”—Using AI Technologies to Provide Formative Feedback to Students

by Tony Burner, Yngve Lindvig and Jarl Inge Wærness

Educ. Sci. 2025, 15(1), 58; https://doi.org/10.3390/educsci15010058 - 9 Jan 2025

Cited by 1 | Viewed by 1893

Abstract

Artificial intelligence (AI) technologies have the potential to enhance learning, teaching, and assessment by providing AI-generated feedback to students. This study used five different AI plug-ins and four different knowledge bases for the optimization of feedback in classroom formative assessments. The sample consisted of 26 students and 13 teachers at five secondary schools in Norway. Interviews and unstructured observations were used to collect data. The findings indicate that AI-generated feedback is appreciated by both students and teachers. It provides immediate subject-specific, concrete, and relevant feedback. High-performing students were motivated to further improve their writing. However, some students found the feedback to be too general or complicated, and the teachers who had not conducted whole-term periodic planning struggled with using AI for formative assessment purposes. Finally, both students and teachers contend that the teacher needs to have the last word when AI takes over formative feedback procedures. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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25 pages, 1331 KiB

Open AccessArticle

An Experiment of AI-Based Assessment: Perspectives of Learning Preferences, Benefits, Intention, Technology Affinity, and Trust

by Ari Alamäki, Umair Ali Khan, Janne Kauttonen and Stephan Schlögl

Educ. Sci. 2024, 14(12), 1386; https://doi.org/10.3390/educsci14121386 - 17 Dec 2024

Viewed by 2779

Abstract

The rising integration of AI-driven assessment in education holds promise, yet it is crucial to evaluate the correlation between trust in general AI tools, AI-based scoring systems, and future behavioral intention toward using these technologies. This study explores students’ perspectives on AI-assisted assessment in higher education. We constructed a comprehensive questionnaire supported by relevant studies. Several hypotheses grounded in the literature review were formulated. In an experimental setup, the students were tasked to read a designated chapter of a paper, answer an essay question about this chapter, and then have their answers evaluated by an AI-based essay grading tool. A comprehensive data analysis using Bayesian regression was carried out to test several hypotheses. The study finds that remote learners are more inclined to use AI-based educational tools. The students who believe that AI-based essay grading is less effective than teacher feedback have less trust in AI-based essay grading, whereas those who find it more effective perceive more benefit from it. In addition, students’ affinity for technology does not significantly impact trust or perceived benefits in AI-based essay grading. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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10 pages, 460 KiB

Open AccessArticle

Artificial Intelligence-Assisted Music Education: A Critical Synthesis of Challenges and Opportunities

by Javier Félix Merchán Sánchez-Jara, Sara González Gutiérrez, Javier Cruz Rodríguez and Bohdan Syroyid Syroyid

Educ. Sci. 2024, 14(11), 1171; https://doi.org/10.3390/educsci14111171 - 28 Oct 2024

Viewed by 6155

Abstract

Artificial intelligence (AI) is a hot topic that presents new challenges and opportunities for the improvement of educational processes. The disruptive and transformative force of this new technological development implies the adaptation of educational ecosystems for its use and integration as a didactic and pedagogical resource. From this perspective, a systematic literature review has been conducted to analyze the didactic potential of generative AI tools in the field of promoting artistic creativity in music education. The research results confirm that the incorporation of AI in music education is paving the way for a more personalized, interactive and efficient learning experience. In addition, the analysis suggests nine fundamental fields of IA implementation in music education: virtual and augmented reality (VR; VA); learning personalization, intelligent tutoring systems; composition assistants; improved historical and contextual learning; assessment systems; interactive ear training and music theory systems; tools for music collaboration and performance; and assistive technologies. Furthermore, the challenges presented by the intersection of AI and digital didactics in the field of music education are discussed. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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17 pages, 541 KiB

Open AccessArticle

The Good and Bad of AI Tools in Novice Programming Education

by Rina Zviel-Girshin

Educ. Sci. 2024, 14(10), 1089; https://doi.org/10.3390/educsci14101089 - 6 Oct 2024

Viewed by 5591

Abstract

As AI coding tools become more prevalent in programming, it is essential to understand how they influence programming education. This study, conducted in a first-semester Introduction to Programming course, aimed to determine the positive and negative effects of these tools on students’ learning experiences and their ability to develop essential programming skills. Using a mixed-methods approach, we collected data from 73 teams of engineering students over a 12-week period. Students completed surveys and reported on their AI tool usage. We analyzed this data quantitatively to identify trends in tool familiarity, usage, and student satisfaction. Additionally, qualitative analysis of student reports provided insights into the specific ways AI tools were used and their perceived benefits and drawbacks. The findings revealed a significant increase in AI tool familiarity (from 28% to 100%) and usage among students. Students’ satisfaction with AI tools improved over time. The most prevalent tasks for which novice programmers used AI tools included creating comments (91.7%), identifying and correcting bugs (80.2%), and seeking information (68.5%), while other tasks were less common. While these tools offered benefits like assisting in learning and enhancing real-world relevance, they also raised concerns about cheating, over-reliance on AI tools, and a limited understanding of core programming concepts. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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17 pages, 836 KiB

Open AccessArticle

Improving Teaching and Learning in Higher Education through Machine Learning: Proof of Concept’ of AI’s Ability to Assess the Use of Key Microskills

by Christopher Dann, Shirley O’Neill, Seyum Getenet, Subrata Chakraborty, Khaled Saleh and Kun Yu

Educ. Sci. 2024, 14(8), 886; https://doi.org/10.3390/educsci14080886 - 14 Aug 2024

Cited by 1 | Viewed by 1658

Abstract

Advances in artificial intelligence (AI), including intelligent machines, are opening new possibilities to support teaching and learning in higher education. This research has found a ‘proof of concept’ in the application of machine learning in the assessment of educators’ use of four key microskills, drawn from an internationally established framework. The analysis of teaching videos where these microskills were demonstrated multiple times in front of a green screen or in a space formed the data set. Multiple videos of this nature were recorded to allow for increased analysis and deconstruction of the video components to enable the application of machine learning. The results showed how AI can be used to support the collaborative and reflective practice of educators in a time when online teaching has become the norm. Having achieved a ‘proof of concept’, this research has laid the groundwork to allow for the whole framework of ten microskills to be applied in this way thus adding a new dimension to its use. Providing such critical information that is not currently available in such a systematic and personalised way to educators in the higher education sector can also support the validity of formative assessment practices. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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21 pages, 2779 KiB

Open AccessArticle

Effectiveness of Using ChatGPT as a Tool to Strengthen Benefits of the Flipped Learning Strategy

by Gilberto Huesca, Yolanda Martínez-Treviño, José Martín Molina-Espinosa, Ana Raquel Sanromán-Calleros, Roberto Martínez-Román, Eduardo Antonio Cendejas-Castro and Raime Bustos

Educ. Sci. 2024, 14(6), 660; https://doi.org/10.3390/educsci14060660 - 18 Jun 2024

Cited by 10 | Viewed by 5551

Abstract

In this study, we evaluate how ChatGPT complements and enriches the traditional flipped learning strategy in higher education, particularly in engineering courses. Using an experimental design involving 356 students from basic programming courses in undergraduate engineering programs, we compared the normalized learning gain between groups that used the ChatGPT-assisted flipped learning strategy (focus groups) and those that followed a traditional video-based flipped learning methodology (control groups). The intervention lasted ten weeks, with two sessions of two hours each week. A pre-test–post-test analysis revealed that the focus groups showed significant improvement in normalized learning gain values compared to the control groups. These results confirm that incorporating ChatGPT into the flipped learning strategy can significantly enhance student performance by providing a more active, interactive, and personalized approach during the teaching–learning process. We conclude that the flipped learning strategy, upgraded with the assistance of ChatGPT, provides an effective means to improve understanding and application of complex concepts in programming courses, with potential to be extended to other areas of study in higher education. This study opens routes for future research on the integration of artificial intelligence into innovative pedagogical strategies with the goal of scaffolding the learning experience and improving educational outcomes. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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Review

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12 pages, 244 KiB

Open AccessReview

Navigating AI Integration in Career and Technical Education: Diffusion Challenges, Opportunities, and Decisions

by Jeffrey C. Sun and Taylor L. Pratt

Educ. Sci. 2024, 14(12), 1285; https://doi.org/10.3390/educsci14121285 - 25 Nov 2024

Cited by 1 | Viewed by 2479

Abstract

This review paper explores the integration of artificial intelligence (AI) in career and technical education (CTE). CTE is an educational domain often overlooked in discussions about teaching and learning and notably omitted in the extant literature about AI’s application in educational settings. Although much of the existing literature focuses on AI in K-12 and higher education, CTE faces distinct challenges and opportunities in both education and the application of AI because CTE programming is more hands-on and industry-connected. This paper, grounded in Diffusion of Innovations theory, examines AI tool adoption processes among CTE educators by analyzing both barriers and opportunities. Key findings suggest that while AI offers significant benefits, its adoption is hindered by systemic factors. This paper contributes to the literature by highlighting the importance of contextualizing AI adoption within the distinct pedagogical practices and industry partnerships of CTE. It emphasizes the need for targeted strategies that address CTE-specific challenges, including robust infrastructure, equitable resource distribution, and fostering a culture of innovation among educators. The implications of this work underscore AI’s potential to bridge the gap between education and workforce demands, positioning CTE programs as critical sites for preparing students for the next phase of workforce under Industry 5.0. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

Other

Jump to: Research, Review

14 pages, 236 KiB

Open AccessEditor’s ChoiceOpinion

A Cross-Era Discourse on ChatGPT’s Influence in Higher Education through the Lens of John Dewey and Benjamin Bloom

by Koki Mandai, Mark Jun Hao Tan, Suman Padhi and Kuin Tian Pang

Educ. Sci. 2024, 14(6), 614; https://doi.org/10.3390/educsci14060614 - 6 Jun 2024

Cited by 3 | Viewed by 2338

Abstract

Since its release in November 2022, ChatGPT and the related AI technology have disrupted multiple fields of society where people anticipate its pathways with a mixture of hope and fear. Among the affected fields, education, in particular, may incur one of the largest impacts in the future partly due to its nature of learning and teaching knowledge, an element that is more or less questioned by the rise of these technologies. As education can be seen as a component that determines the future of every other field of society, tools such as ChatGPT must be optimally regulated to enhance its gain or mitigate its loss. To contribute to this goal, this paper approaches the state of ChatGPT and its expected impacts on higher education through the lens of two major educational theories—John Dewey’s Reflective-Thought-and-Action model and revised Bloom’s taxonomy—aiming to propose possible evaluative criteria for the optimal usage of ChatGPT in academia. As ChatGPT is a relatively new topic of research yet a topic that requires an immediate focus due to its capabilities, this paper also aims to provide these criteria as one of the concrete starting points of future research in this field. Full article

(This article belongs to the Special Issue How Artificial Intelligence Can Enhance Education: Current Practices and Challenges)

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