Jul 2026· IC-ITECHS· Vol 6, pp. 139-148· 0 citations
TL;DR
The conclusion of this study affirms that the adaptation of the PBL model in the GenAI era requires the redesign of problem scenarios, the development of critical AI literacy, the formulation of ethical guidelines, and faculty training to utilize AI responsibly.
Abstract
This study aims to explore and synthesize the literature on the adaptation of the Problem-Based Learning (PBL) model in the era of Generative Artificial Intelligence (GenAI) in higher education. The background of this research is the rapid development of GenAI, such as ChatGPT, which has transformed the educational landscape; however, a knowledge gap remains regarding how the PBL model fundamentally adapts. This study employs a systematic literature review method with a scoping review approach following the PRISMA guidelines. The literature search was conducted across four major databases (Scopus, Web of Science, ERIC, and ScienceDirect) with publication limits from 2021 to 2026. The findings identified five main themes: Forms of GenAI integration in PBL; shifting roles of educators and students; challenges and ethical considerations; opportunities and benefits; and pedagogical strategies for effective implementation. The findings indicate that GenAI not only functions as an assistive tool but also transforms the essence of the PBL process through personalized learning, real-time feedback, and the redefinition of educator roles from knowledge providers to facilitators and learning designers. The conclusion of this study affirms that the adaptation of the PBL model in the GenAI era requires the redesign of problem scenarios, the development of critical AI literacy, the formulation of ethical guidelines, and faculty training to utilize AI responsibly.
ChatGPT has rapidly gained popularity among educators and learners, demonstrating its potential to facilitate interactive learning, personalized assistance, and academic support, and the need for guidelines, digital literacy, and ethical frameworks to ensure productive and balanced use of AI in education.
Anuradha Dwivedi, Pragati Pandey, Naveen Mni· International journal of com...· 0 citations
Artificial Intelligence (AI) has brought about significant changes in the educational landscape, driven primarily by the advancement of generative models and the increasing availability of tools capable of supporting teaching and learning processes. This study aimed to analyze the main possibilities and challenges associated with AI in pedagogical practice through a structured narrative literature review. Searches were conducted in the Web of Science Core Collection, Scopus, ERIC, SciELO, and Google Scholar, prioritizing publications from 2019 to 2026, while earlier foundational sources were retained when methodologically or conceptually relevant. The final interpretive corpus comprised 31 core sources, including peer-reviewed empirical studies, systematic and scoping reviews, meta-analyses, and institutional guidance. Evidence was synthesized into four themes: evolution and educational applications of AI, pedagogical potential, ethical and institutional challenges, and the changing role of teachers. The literature identifies opportunities for personalized learning, pedagogical planning, accessibility, formative assessment, and teaching-material development, but also recurring concerns involving information reliability, academic integrity, privacy, algorithmic bias, digital inequality, and teacher preparedness. Recent evidence indicates that positive outcomes are heterogeneous and depend on pedagogical scaffolding, human verification, institutional governance, and AI literacy. AI should therefore be understood as a supportive educational technology rather than a substitute for teacher mediation. Its integration requires critical, ethical, and pedagogically grounded use that preserves student autonomy, assessment validity, and educational equity.
A. F. da Silva, Rosimeire Rozendo, Cristiane Aparecida Simão Silverio· Brazilian Journal of Science· 0 citations
Aim/Purpose: This study examines how generative artificial intelligence (GenAI) and web-based augmented reality (WebAR) can be integrated into a project-based introductory environmental design course and how students perceive the usefulness, feasibility, and demands of the resulting workflow.
Background: GenAI and AR are increasingly used in design education, but they are often taught as separate tools. A practical account is needed of how a broad AI-AR research agenda can be translated into bounded, novice-appropriate learning tasks.
Methodology: A descriptive classroom case study was conducted in one first-year course with 38 students working in 11 groups. The implementation comprised eight four-period stages, including a fieldwork stage conducted during the public holiday period. Evidence included teaching records, site-investigation reports, archived project outputs, course assessment records, and 36 responses to a non-login post-course questionnaire that collected no direct identifiers. Questionnaire responses were analyzed descriptively at the item level, and short open-ended responses were used to contextualize the findings.
Contribution: This study documents a course-specific procedure, described here as research-to-teaching task translation, through which a broad GenAI-WebAR research agenda was narrowed into bounded and assessable undergraduate tasks. The term is used as a descriptive label for the procedure implemented in this course rather than as a new theoretical framework. The study also presents a project-based workflow connecting site observation, problem framing, ComfyUI-supported visual generation, iterative judgment, and Kivicube-based WebAR presentation.
Findings: All 11 groups submitted the required types of project output during the course. During subsequent verification, complete archived deliverable sets could be opened and inspected for 10 groups. Component-level fulfillment varied across site-report completeness, correspondence with the original redesign, map or site positioning, and technical execution. Students generally perceived the workflow positively, particularly the continuing need for human design judgment, the connection between software learning and real design problems, and the contextual communication value of WebAR. However, perceived support from ComfyUI for rapid initial ideation was comparatively lower, while technical complexity and time pressure remained practical concerns.
Recommendations for Practitioners: Instructors should sequence site observation before AI generation, constrain task scope for novice learners, teach criteria for contextual fit and design responsibility, and provide workflow templates and staged feedback. WebAR can be used to reconnect generated representations with location and audience.
Recommendation for Researchers: Future studies should use comparison groups, independent performance-based assessments, pre- and post-course measures, and larger or multi-course samples to examine learning outcomes beyond student perceptions and group project completion.
Impact on Society: Cloud-based GenAI and browser-based AR may reduce hardware and installation barriers for introductory design activities in institutions with comparable access to platforms, internet connectivity, and instructional support.
Future Research: Future work should test the workflow across design disciplines, student populations, course durations, institutional settings, and levels of technical support.
Yang Liang, Ke-Xin Hao, Si-Rui He et al.· Journal of Information Techn...· 0 citations
This proposed research work will be evaluated using real-time data collected from various university students via a research study to provide insight into how GAI has impacted the creative quotient of students who prefer to utilize modern tools over the traditional teaching-learning methodology.
Renuka Devi D, Midhun Chakkaravarthy· International Journal of Ele...· 0 citations
Critical thinking is an essential competency for addressing the challenges of contemporary education. The objective of this systematic review was to analyze the teaching strategies with the strongest scientific support for its development across different educational contexts. The study was conducted according to the PRISMA 2020 guidelines through the review of twenty studies published between 2022 and 2026, selected from specialized databases according to quality and relevance criteria. The results show that problem-based learning, project-based learning, metacognition, and active methodologies are the most effective strategies for strengthening analysis, argumentation, problem-solving, and self-regulation skills. Likewise, generative artificial intelligence emerges as a complementary resource whose impact depends on appropriate pedagogical mediation. It is concluded that the development of critical thinking requires a comprehensive educational approach that articulates didactic innovation, teacher training, and emerging technologies.
Violeta Chamaya Becerra, Juan Pedro Soplapuco Montalvo· Minerva· 0 citations
Generation Alpha consists of children born from 2010 until 2025. It is the first generation of students to grow up completely in an era described by ubiquitous digital technology, artificial intelligence, high-speed internet, smart devices, and hyper-connected settings. In this regard, the present paper examines new pedagogical perspectives for Generation Alpha, which are based on the unique features of their cognitive, social, and epistemological abilities. The research, which involves a systematic review of current literature on the subject, identifies the most important theoretical models of education, including constructivism, connectivism, and digital native learning model. They underpin modern educational methods, such as gamification, adaptive personalized learning, collaborative projects and immersion in AR/VR environments. The study points out the need to transition from the traditional approach of content delivery to a student-centered, skills-based one.
Unknown authors· EPRA International Journal o...· 0 citations
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