Search Results (42)

The rapid advancement of Artificial Intelligence (AI) technologies has significantly transformed teaching, learning, and research practices within higher education institutions (HEIs). Although a growing body of literature has examined the application of AI in higher education, existing studies remain fragmented, often focusing on isolated tools or outcomes, with limited synthesis of best practices, core functionalities, and implementation challenges across diverse contexts. To address this gap, this systematic review aims to comprehensively examine the best practices, functionalities, and challenges associated with the integration of AI in HEIs. A comprehensive literature search was conducted across major academic databases, including Google Scholar, Scopus, Taylor & Francis, and Web of Science, resulting in the inclusion of 35 peer-reviewed studies published between 2014 and 2024. The findings suggest that effective AI integration is supported by best practices, including promoting student engagement and interaction, providing language support, facilitating collaborative projects, and fostering creativity and idea generation. Key AI functionalities identified include adaptive learning systems that personalize educational experiences, predictive analytics for identifying at-risk students, and automated grading tools that improve assessment efficiency and accuracy. Despite these benefits, significant challenges persist, including limited knowledge and skills, ethical concerns, inadequate infrastructure, insufficient institutional and management support, data privacy risks, inequitable access to technology, and the absence of standardized evaluation metrics. This review provides evidence-based insights to inform educators, institutional leaders, and policymakers on strategies for leveraging AI to enhance teaching, learning, and research in higher education. Full article

This article introduces a framework for scientific and professional language training tailored for STEM (Science, Technology, Engineering and Mathematics) specialists, emphasising the integration of digital technologies and artificial intelligence (AI) in language education. The framework aims to develop students’ research communication skills and digital competencies, which are essential for effective participation in both national and international scientific discourse. The article discusses contemporary trends in STEM education, emphasising the importance of interdisciplinary approaches, project-based learning, and the utilisation of digital tools to boost language skills and scientific literacy. The article outlines the development and deployment of a digital platform aimed at supporting personalised and adaptive learning experiences, integrating various educational technologies and approaches. Empirical research conducted through a pedagogical experiment demonstrates the effectiveness of the framework, showing significant improvements in students’ academic and linguistic competencies across multiple modules. The findings highlight the importance of combining language training with STEM education to equip future engineers for the challenges of a globalised and digitalised professional world. This work reports on the “Enhancing Scientific and Professional Language Learning for Engineering Students in Kazakhstan through Digital Technologies” project conducted at Saginov Technical University (STU) in Kazakhstan and funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19678460). The research contributes to the ongoing discussion on improving language teaching in STEM fields, offering a framework that aligns with current educational demands and technological progress. Full article

This study investigates the utilisation of AI tools, including Grammarly Free, QuillBot Free, Canva Free Individual, and others, to enhance learning outcomes for 180 s-year telecommunications engineering students at Universidad Politécnica de Madrid. This research incorporates teaching methods like problem-based learning, experiential learning, task-based learning, and content–language integrated learning, with English as the medium of instruction. These tools were strategically used to enhance language skills, foster computational thinking, and promote critical problem-solving. A control group comprising 120 students who did not receive AI support was included in the study for comparative analysis. The control group’s role was essential in evaluating the impact of AI tools on learning outcomes by providing a baseline for comparison. The results indicated that the pilot group, utilising AI tools, demonstrated superior performance compared to the control group in listening comprehension (98.79% vs. 90.22%) and conceptual understanding (95.82% vs. 84.23%). These findings underscore the significance of these skills in enhancing communication and problem-solving abilities within the field of engineering. The assessment of the pilot course’s forum revealed a progression from initially error-prone and brief responses to refined, evidence-based reflections in participants. This evolution in responses significantly contributed to the high success rate of 87% in conducting complex contextual analyses by pilot course participants. Subsequent to these results, a project for educational innovation aims to implement the AI-PBL-CLIL model at Universidad Politécnica de Madrid from 2025 to 2026. Future research should look into adaptive AI systems for personalised learning and study the long-term effects of AI integration in higher education. Furthermore, collaborating with industry partners can significantly enhance the practical application of AI-based methods in engineering education. These strategies facilitate benchmarking against international standards, provide structured support for skill development, and ensure the sustained retention of professional competencies, ultimately elevating the international recognition of Spain’s engineering education. Full article

With the increasing deployment of large language models (LLMs) in diverse applications, security vulnerability attacks pose significant risks, such as prompt injection. Despite growing awareness, structured, hands-on educational platforms for systematically studying these threats are lacking. In this study, we present an interactive training framework designed to teach, assess, and mitigate prompt injection attacks through a structured, challenge-based approach. The platform provides progressively complex scenarios that allow users to exploit and analyze LLM vulnerabilities using both rule-based adversarial testing and Open Worldwide Application Security Project-inspired methodologies, specifically focusing on the LLM01:2025 prompt injection risk. By integrating attack simulations and guided defensive mechanisms, this platform equips security professionals, artificial intelligence researchers, and educators to understand, detect, and prevent adversarial prompt manipulations. The platform highlights the effectiveness of experiential learning in AI security, emphasizing the need for robust defenses against evolving LLM threats. Full article

Active learning strategies and methodologies place the students at the core of the learning process. The objective is to engage students in their own learning through significant activities that involve active participation. These activities are designed to promote collaboration, reflection, and practical application of the knowledge acquired to develop cognitive, social, and emotional competences. These methodologies are of particular interest in STEM disciplines and vocational education, where practice is a key element in the assimilation of theoretical concepts. In this line, a case study is presented where active methodologies have been applied to two groups of Vocational Education and Training in the area of Computer Science to improve interest and commitment. The present study focuses on two groups of first-year students enrolled in the Web Application Design course, one in the Programming subject and the other in the Markup Language subject. Both groups are heterogeneous, composed of young adults with significantly different backgrounds, skills, and motivation. The teaching–learning process is based on active methodologies, such as Project-Based Learning, Design Thinking, Flipped Classroom, or gamification, which are adapted for different subjects in the field of Computer Science. These methodologies facilitate the experimental design and testing of diverse solutions for programming problems, thereby enhancing students’ motivation and interest, while promoting creativity and reflection. The results show an improvement in the interest and commitment of the students in both groups. Despite the fact that less than 50% of students successfully passed in the initial examination, more than 75% students passed after the second-chance examination. The findings have consistently suggested that the implementation of active methodologies leads to significant enhancements in the proficiency, development, motivation, and self-learning capabilities of students, and that these methodologies make students more aware of their learning process. Full article

The Critical Pedagogies Research Team (PEDACRI-ULL) participates in the Program for the Inclusion of Migrants at Risk of Social Exclusion (PIPE) 2023-1-ES01-KA220-ADU-000160578, funded by the European Union. This project aims to design, implement and promote a transnational cooperation network to enhance the skills and competencies of migrants. Its purpose is to provide an educational response aligned with the European Commission’s Pact on Migration and Asylum.. Among its objectives, the program develops tools for professionals and institutions working with migrants, fostering collaborative learning to envision a culture of peace. In this essay, we explore the Pedagogy of Hospitality through critical pedagogies and the dialogue of knowledge. We propose a model of migrant citizenship based on an interlinguistic didactic relationship that promotes intercultural coexistence, grounded in an ethic of miscegenation. Furthermore, we advocate language teaching as a universal right and argue that hospitality should not be seen as an act of generosity but as a moral duty. This perspective supports an inclusive and just education, where language serves as a bridge for integration and mutual recognition. Full article

The application of Artificial Intelligence (AI) to teacher training is a rather recent phenomenon and there is a need for more research on its use in teacher education. This paper examines the use and interpretation of AI by student language teachers during a 10-week telecollaborative course between students from two universities, one in the USA and the other in Spain (n = 46). The course focused on Technology-Enhanced Project-Based Language Learning (TePBLL) and was divided into different ‘technological blocks’. This article is centered around the AI technology block. The analysis is based on three exit tickets (reflection prompts) that demonstrate participants’ thoughts and changing perspectives towards AI. Through thematic analysis of the open-ended responses, this study shows that participants initially appeared skeptical before moving to tentative optimism after first studying theory and examples of the application of AI, followed by the creation of AI-based lessons and activities. The student teachers identify AI as a means to personalize and make language learning more efficient while expressing concerns related to its overuse, ethical issues and potential for undermining critical thinking and creativity. This small study looks at the evolution of the student teachers’ concepts about and perspectives towards AI-enhanced language teaching and learning before, during and after they engage in the technology block. The findings suggest that hands-on training that includes lesson design helps student teachers view AI as a complementary tool for many aspects of their teaching, although this can only be achieved through an adequate pedagogical application. Full article

Recent research underscores the significance of data-led and collaborative reflection in enhancing teaching practices and professional development of teachers. While video-based reflections have been extensively studied, the potential of corpus-based methods remains underexplored. We address this gap in two ways. Firstly, we describe a research and development project in which we employed a corpus linguistic tool to analyse and reflect on our own lectures, with the ulterior aim of promoting a corpus-based reflective practice (CBRP) model that would help other teachers do the same. Secondly, we introduce collaborative micro auto-ethnography (CMAE) to illustrate how our model can facilitate the noticing of different aspects of teacher talk and lead to, what we call, snowball reflections (i.e., a sequence of reflective talk that extends a topic and spreads from one participant to the next). Our approach shows that corpus analysis, coupled with collaborative reflections, has the potential to not only enhance language use but also stimulate broader and deeper pedagogical discussions on and insights into teaching styles and student engagement, going beyond analyses of single words and lexico-grammatical patterns in teacher talk. We argue that there should be institutional support for developing new corpus-based professional development initiatives and that researchers can benefit from using ethnographic data together with detailed analyses of interactions. Full article

This study proposes incorporating generative artificial intelligence large language models (LLMs) into the Master of Science (M.Sc.) curriculum on digitization in construction. The aim was to help students generate computer code to solve, automate, and streamline practical challenges in advanced construction engineering and management (CEM). To this end, a host of problem-based learning (PBL) individual assignments and collaborative team projects were developed, alongside a combination of flipped classroom models and blended learning lessons, in order to teach effective interactions with LLMs and mitigate concerns, such as bias and hallucination. The effective interaction with LLMs not only facilitated code generation, which would otherwise be complex without additional formal training, but also provided a platform for strengthening basic project management skills, such as departmentalization, work breakdown structuring, modularization, activity delegation, and defining key performance indicators. The effectiveness of this approach was quantitatively and qualitatively evaluated within two new modules, Digital Engineering and Construction and Digital Technologies in Field Information Modeling. These modules were offered over three semesters each as part of a new M.Sc. program in Technology and Management in Construction at the Karlsruhe Institute of Technology. It was observed that 86.4% of students fully completed the PBL projects, while the remaining 13.6% achieved over 50% completion across all six semesters. Furthermore, anonymous student surveys indicated a teaching quality index of 100% in five semesters and 96.4% in one semester. These preliminary results suggest that the proposed strategy can be used to effectively integrate LLMs to support students in code generation for open-ended projects in CEM. Further research was, however, found to be necessary to ensure the sustainable revision and redesign of the problems as LLM capabilities evolve. Full article

Curiosity and question-asking are at the heart of science and engineering education. However, question-asking can be difficult for students due to several factors, including fear, language barriers, and cultural norms. This is especially true among Chinese students, who represent a growing number of upcoming engineers. To address this, in this case study from a university teaching reform project, we investigate the perceptions of curiosity and question-asking among Chinese science, technology, engineering, and mathematics (STEM) undergraduate students following a newly developed semester-long project in a second-year communications course at a recently established Sino-foreign engineering school in China. In this period, students engaged in project-based learning centered around Nobel Prize-winning research, allowing them to explore the driving questions behind groundbreaking discoveries. Through a combination of qualitative analyses from students’ personal reflections as well as from a post-survey, the study examines students’ perceptions of curiosity and question-asking, the influence of gender on these skills, and the role of failure and perseverance in scientific inquiry. Findings indicate that the project increased students’ curiosity and improved their confidence in asking questions while providing insights into gender differences. Moreover, students were inspired by the curiosity of the Nobel Laureates, by the “simplicity” of the questions asked, and by the great importance of tenacity, passion, and learning from mistakes. Full article

As artificial intelligence (AI) becomes increasingly prevalent, it has become a topic of interest in education. The use of AI in education poses complex issues, not only in terms of its impact on teaching and learning outcomes but also in terms of the ethical considerations regarding personal data and the individual needs of each student. Our study systematically analyzed empirical research on the use of AI in primary education, specifically for children aged 4–12 years old. We reviewed 35 articles indexed in SCOPUS, filtered them according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzed them, and categorized the findings. The research focused on the studies’ objectives, learning content, learning outcomes, learning activities, and the pedagogy of activities or the AI tools. Our categorization resulted in three main categories of research objectives regarding the creation, implementation, and evaluation of AI tools and five categories for learning content: AI and ML (machine learning) concepts in STEM and STEAM, language learning, mathematics, arts, and various other subjects. The learning activities were split into four categories: apply, engage, interact, use; project-based learning with multiple activities; experience and practice; and students as tutors. The learning outcomes were split into three levels: cognitive, affective, and psychomotor. The pedagogy of AI tools falls into four categories: constructivism, experiential learning, AI-assisted learning, and project-based learning. The implications for teacher professional development are discussed. Full article

This paper describes a project to build linguistic awareness among science educators at multiple levels: pre-service K–12 teachers, in-service K–12 teachers, and university faculty in both education and STEM fields. Educational linguists from a language-focused non-profit research organization created modules on teaching culturally and linguistically diverse students for a Master of Arts in Teaching (MAT) program for middle school science educators at a large urban U.S. university. The module content, which was integrated into three science education methods courses, was designed around three key principles: linguistic understanding, critical language awareness, and pedagogical modeling. A critical component to the project’s success was fostering “buy-in” from the various groups of educators through multiple means, including piloting materials with in-service science teachers, training university faculty on the language and literacy materials, and revising content based on feedback from the MAT program faculty and students. The findings demonstrate that over time, the educators re-examined their roles as teachers of language and literacy and reassessed their thinking related to science instruction, highlighting the efficacy of incorporating language development content into training and professional development for STEM educators at multiple levels. Full article

This study is part of a project on initial assessment of first language (L1) literacy in adult newcomers prior to the commencement of L2 studies in Swedish. Here, we explore the assessment summaries of newcomers’ L1 literacy, performed by L2-teachers, with assistance from an interpreter. According to the syllabus, instruction in Swedish for Immigrants (SFI) should be adapted to the individual´s needs and goals; however, SFI often fails to do so. L1 literacy—i.e., using texts in different domains (school, work, society, and everyday life)—serves as a foundation for L2 learning and teachers’ access to and utilization of students L1 literacy can significantly enhance instruction. From a sociocultural approach to literacy and based on Luke and Freebody’s ‘Four Resource Model’, a qualitative document analyses of L1 literacy assessment summaries (N = 50) demonstrated literacy practices form different domains of student life, beyond school literacy. Literacy practices from all four learner roles, i.e., Code-Breaker, Text Participant, Text User and Text Analyst were identified in the assessments to various degrees dependent on the students’ background, which is illustrated by a close analysis of 5 summaries. This information is both important for teachers’ planning of second language teaching and in the long term for the development of second language teacher education. Full article

This research aims to promote diversity and inclusion among higher education students by examining the integration of technology into project-based learning (PBL) for English as a foreign language (EFL) teacher candidates. Based on a mixed-methods approach and convenience sampling (n = 84 participants), this study involved pre-service teachers who collaboratively employed several authoring tools to create 16 digital comic strips for teaching English. The focus of the project was on inclusivity, cultural diversity, and affective education. This study consisted of five stages corresponding to different critical thinking skills: comprehension, negotiation, creation, presentation, and evaluation. The instruments used for quantitative data included a pre/post-survey based on two validated scales. Qualitative data were gathered through class discussions and semi-structured interviews. The results, analyzed through SPSS and QDA Miner Lite, revealed that teacher candidates lacked prior experience using digital tools to create EFL-inclusive materials. However, the study also highlighted increased awareness of inclusive education and strong advocacy for the integration of transformative technology in teacher training programs. Full article

One important internal factor influencing reading comprehension is a child’s executive functioning. The primary objective of this paper is to evaluate the effectiveness of a cognitive stimulation program, ExeFun-READ (a program focusing on executive functioning stimulation via the L1 (Slovak language) curriculum with a specific focus on enhancing reading comprehension). The program is explicitly based on the assumed bi-directional relationship between executive functioning and language abilities related to reading comprehension. The program is domain-specific; the curriculum of L1 (Slovak) is a curricular area in which cognitive mediation occurs. The study will investigate whether the domain-specific ExeFun-READ intervention had a positive effect on children’s executive functioning and language subcomponents of reading comprehension. Keeping in mind ecological validity, ExeFun-READ was designed primarily for educational purposes, specifically professional tutoring for low-performing students. The intervention consists of 30 units; each unit lasts for 45–60 min. A stimulation unit approximates a teaching unit rather than a clinical experimental intervention. In total, 151 low-performing students attending grade four from seven elementary schools took part in the project. The study employs a pre-test–training–post-test design with three conditions: experimental, active control, and passive control. In the current study, the intervention led to improved language abilities related to reading comprehension. Significant improvements were found in vocabulary (semantic knowledge), completion of sentences (syntactic knowledge), and classification of terms (verbal fluency and inferencing) in the group of children that received the ExeFun-READ intervention. In terms of executive functioning, the improvement only extended to switching fluency. Full article