International Journal of Technology Enhanced Learning (24 papers in press)

Regular Issues

• Effective online learning and training in higher education  
  by Monica Chaudhary, Udit Chawla 
  Abstract: The COVID-19 pandemic has created significant challenges for the global education community. The effectiveness of online learning has been questioned number of times in the past where student motivation becomes the single most important factor. This study aims at analysing student’s satisfaction while learning online and whether formal training to study online made any significant impact on student satisfaction. Data collection was done through a structured questionnaire across India. Three important facts identified for student satisfaction are Student’s awareness & knowledge of online learning, Teacher’s awareness & knowledge to teach online and Blended Learning Approach where students want to study online but along with traditional face to face teaching. Educational institutes and policy makers may take advantage by making appropriate policy in terms of training requirements. The study would also be beneficial for Edu Tech companies to brainstorm and make platforms that caters to student demand and flexibility.
  Keywords: COVID-19; online studying; student; satisfaction; learning system; technology.
  DOI: 10.1504/IJTEL.2024.10065659
   
  
• Analysing user needs for digital learning platform in cultural heritage: a case study on Jin Dynasty costumes  
  by Oulu Yue, Atithep Chaetnalao 
  Abstract: This study provides an in-depth analysis of user needs for a digital learning platform for cultural heritage, focusing on Jin Dynasty costumes. The study used a mixed-methods approach, combining qualitative expert interviews and extensive fieldwork with the analysis of 440 quantitative public surveys. The findings show a strong demand for interactive and immersive digital experiences that enhance understanding and engagement with cultural heritage. This study aims to develop a user-centred conceptual model that effectively combines traditional cultural knowledge with modern educational technology, emphasising users’ multi-dimensional and more profound experiences when participating in traditional cultural experiences, thereby enhancing users’ cultural learning experiences and interests. The model can effectively bridge the gap between traditional cultural knowledge and modern educational technology, and this approach deepens people’s comprehension and recognition of cultural heritage and enhances the educational effect of the digital platform.
  Keywords: digital learning platform; cultural heritage education; user-centred design; Jin Dynasty costumes; interactive learning.
  DOI: 10.1504/IJTEL.2024.10066054
   
  
• Design and development of a tangible machine learning-based object recognition and learning system for Indian kids suffering from Visual Agnosia  
  by Priyam A. Parikh, Heet Shah, Pinal Vaghela, Smruti Kankrecha 
  Abstract: Children with Visual Agnosia have problems recognising and remembering basic objects. Although they are not visually impaired, they may be disregarded in educational environments. They suffer from the issue of limited identification capacity and are unable to retain what they have seen. A physical device using machine learning has been developed to assist individuals with difficulties in recalling and recognising basic objects like fruits and vegetables. The gadget can recognise objects and provide detailed descriptions within a 100-word limit. The designed equipment aids children in retaining knowledge of several fundamental items and enhances their inquisitiveness towards them. Consequently, they are able to gradually develop their cognitive abilities, including sensorimotor and object permanence capabilities. The object detection is performed via the convolutional neural network (CNN) method implemented in TensorFlow. The equipment effectively conducted tests on more than 20 children, examining a minimum of 30 distinct items.
  Keywords: Visual Agnosia; TensorFlow; object detection; machine learning; convolutional neural network; CNN.
  DOI: 10.1504/IJTEL.2024.10066126
   
  
• Empowering students with modern pedagogical approaches: a case study on the fourth industrial revolution in the wake of coronavirus disease 2019  
  by Marcos Komodromos, Andreas Masouras, Tatiana Harkiolakis, Marios Vassiliou, Mekerdich Mike Costanian 
  Abstract: The fourth industrial revolution (4IR) has brought significant changes to the labour market, introducing new job roles and increasing the demand for soft skills. The rapidly evolving technological landscape demands effective communication, emotional intelligence, and problem-solving skills. This case study sought to understand the creative teaching methods that universities should adopt to prepare students for the future workforce and bridge the skills gap. The study utilised the human capital theory framework to examine the relationship between education and skills. To investigate this correlation, a qualitative case study was conducted, involving interviews with education experts using a semi-structured interview guide consisting of eight items. Upon analysing the data, it was discovered that universities could employ various pedagogical approaches such as formative analytics, experiential learning, and blended learning to prepare students with the skills needed for the future job market.
  Keywords: fourth industrial revolution; 4IR; pedagogical approaches; student empowerment; skills gap; talent mismatch; future of work; graduate empowerment; reskilling; and universities.
  DOI: 10.1504/IJTEL.2024.10066292
   
  
• E-learning system and its outcomes: the role of self-efficacy in the IS success model  
  by Mohammed Ali, Fawad Ahmed 
  Abstract: This research paper investigates the pivotal role of self-efficacy in predicting outcomes within the context of e-learning. Drawing upon the DeLone and McLean (DL&ML) information system success model and extending it to encompass the influence of self-efficacy, this study addresses a notable gap in the literature regarding the specificities of e-learning in Sudan a nation facing significant educational challenges, including conflicts. The data obtained from 157 students engaged with an e-learning system at one of Sudans universities. The results reveal that service quality and self-efficacy have a positive effect on user satisfaction and system use. The outcomes, as explained by system use and user satisfaction, aid in the improvement of e-learning strategies and provide insight into e-learning outcomes. This research seeks to extend the DL&ML model to incorporate self-efficacy as a determinant of e-learning success, thereby offering valuable insights for enhancing the efficacy of virtual education initiatives in developing country.
  Keywords: e-learning system; self-efficacy; information system; DL& ML IS success model; Sudan.
  DOI: 10.1504/IJTEL.2024.10066622
   
  
• Empowering young learners: m-learning application with adaptive learning and CCI standards  
  by S. Divyasri, M. Mohana, T.T. Dhivyaprabha, P. Subashini 
  Abstract: Mobile learning (m-learning) has become an essential component of education, particularly in the post-pandemic era. Many educational applications are available online, focusing on subjects like language, mathematics, and science. However, these apps often lack adaptive learning mechanisms and effective user design. This study aims to address these gaps by developing an m-learning application that adapts content dynamically based on students’ prior knowledge. Using child-computer interaction (CCI) standards, the application ensures usability by focusing on effectiveness, efficiency, and ease of learning. The study involved 65 students aged 8 to 10, and the app’s design was validated by five educational technology experts. Results showed that students found the app enjoyable and helpful for learning, particularly in their mother tongue. The adaptive and child-centric design significantly increased students’ engagement and self-learning abilities, providing instruction in bilingual languages while customising the learning experience through adaptive approaches.
  Keywords: adaptive learning; child-computer interaction; CCI; child-centric; learning style; mobile learning; young learners.
  DOI: 10.1504/IJTEL.2024.10067098
   
  
• Improving student learning and socialisation via technology-enhanced collaboration  
  by Steve Geinitz 
  Abstract: This study explores a new approach to collaborative learning using technology-enhanced assessments and a systematic pairing process in university-level computer science courses. Students first complete an individual quiz, then collaborate on a second quiz with a partner selected based on complementary performance. This method aims to enhance academic outcomes and socialisation by encouraging diverse interactions. Statistical analyses show that first- and second-year students perform better with varied knowledge levels in partners and prefer assigned partners over self-selection. The findings highlight the benefits of technology-enhanced collaborative learning in improving communication, teamwork, and socialisation skills, ultimately fostering a more connected and harmonious educational experience.
  Keywords: collaborative learning; continuous assessment; student socialisation.
  DOI: 10.1504/IJTEL.2024.10067535
   
  
• Task oriented mind games impact on the cool executive function domain and social skills of children with low functioning autism spectrum disorder  
  by Kanwaljit Kaur, Sesadeba Pany 
  Abstract: Limited research exists on children with low-functioning autism spectrum disorder (ASD), particularly in India. To date, no interventions targeting cool executive functions have been investigated for this group in the Indian context. This study aimed to evaluate the effectiveness of task-oriented mind games in enhancing cool executive functions and social skills in two children with low-functioning ASD case A (low-functioning ASD) and case B (low-functioning ASD with comorbid anxiety). A time-interrupted series design was employed for both cases. Key findings revealed significant improvements in cool executive functions (working memory, inhibition, cognitive flexibility, planning, and organisation) from pre-test to post-test, sustained through follow-up assessments. Case A showed a more pronounced reduction in the number of trials required for task completion compared to case B. Additionally, task-oriented mind games had lasting positive effects on both cool executive functions and social skills, while reducing anxiety-related behaviours in children with ASD.
  Keywords: anxiety; cool executive function; low functioning autism spectrum disorder; ASD; social skills.
  DOI: 10.1504/IJTEL.2024.10067689
   
  
• Generative AI in mathematics education: analysing student performance and perceptions over three academic years  
  by Blaženka Divjak, Barbi Svetec, Damir Horvat 
  Abstract: This study presents an approach in which generative AI (GenAI) chatbots are used to assist students in a problem-solving task resulting in a mathematical essay, introduced in the academic year 2022/2023 in a higher education mathematics course, and continued with in 2023/2024. We compared students’ results from these two years with the results from 2021/2022, when GenAI was not part of the task, using Kruskal-Wallis and Dunn tests. The total sample included 966 students. The 2022/2023 results (GenAI introduced) differed significantly from the other two years, with students being less successful. Conversely, 2023/2024 (GenAI standard) showed the best student results and no significant difference from 2021/2022 (no GenAI). In all the three years, results in the problem-solving essay correlated with success in previous formative and summative assessments. Student feedback highlighted advantages and disadvantages of interactions with GenAI, revealing a tendency to utilise GenAI more for theoretical than practical tasks.
  Keywords: artificial intelligence; generative artificial intelligence; chatbot; ChatGPT; problem-solving; assessment; mathematics.
  
  
• Efficacy of e-content designing and development training programme on digital competence of prospective teacher educators  
  by Seema Rani Thappa, Deep Shikha, J.N. Baliya, Sourabh Sharma, Neha Mehra 
  Abstract: The majority of researchers recommended that teachers to possess the necessary skills to integrate digital technology in the classroom, but there have not been much effort put forward to provide a training component for teachers to acquire these skills. The researchers did the experimental work by providing intervention based on technological pedagogical and content knowledge framework by adopting quasi-experimental design to investigate the efficacy of e-content designing and development training programme on the digital competence of prospective teacher educators. For this, 30 MEd and BEd students as a sample in an experimental group through purposive sampling technique. Two-week intervention has been provided and collected data has been analysed by using t-test on three aspects of digital competence. The research findings revealed that considerable difference in before and after scores in digital competence among pre service teachers and educators along with three dimensions that is technological competence, professional competence and pedagogical competence.
  Keywords: e-content; design and development; technology; pedagogy; digital competence; technology knowledge; pedagogical knowledge; professional knowledge.
  
  
• The impact of generative artificial intelligence on education: a comprehensive analysis of ChatGPTs influence on current research trends  
  by Gustavo Gutierrez Carreon 
  Abstract: This study presents a bibliometric analysis of 1,483 Scopus-indexed publications, focusing on the role of generative AI, particularly ChatGPT, in education. The findings highlight a significant increase in research activity from 2023, reflecting growing academic interest in AI integration. Leading contributors include the USA, Australia, China, and the UK. The study analyses the top 10 most-cited articles, addressing the opportunities and challenges AI poses, such as ethical concerns, pedagogical implications, and interdisciplinary applications. This research contributes to Information Technology Education by mapping AI adoption across disciplines, identifying critical gaps, and emphasising the need for targeted strategies. It underscores the importance of developing ethical frameworks to address issues like academic integrity and data privacy. These insights are valuable for educators, researchers, and policymakers aiming to leverage AI’s potential while ensuring its responsible use in education.
  Keywords: generative AI; ChatGPT; educational technology; information technology; AI in education.
  
  
• Architecture and prototype of a lightweight AI-powered personal learning assistant using open source small language model and multi-modal retrieval augmented generation  
  by Shilpi Taneja, Siddhartha Sankar Biswas, Bhavya Alankar, Harleen Kaur 
  Abstract: In a rapidly changing world where AI is now taking a centre stage in how we interact with various systems, we propose an AI-powered personal learning assistant to help learner gain better understanding of the open educational resources (OER). This assistant transforms the way learners engage with OERs that may contain images, video lectures, text based documents, etc., by interacting with them in natural language on their own local machines without any additional subscription costs. The assistant has multimodal capabilities and uses techniques like multimodal retrieval augmented generation (RAG) and open source small language and multimodal models. Detailed architecture and technology stack for implementation is presented in the paper. A prototype of the proposed assistant is developed and optimised by evaluating different models and adjusting the retrieval chunk-sizes. The assistant is hosted on local machine using open source tool, which makes this architecture cost-effective, light weight and ensures privacy.
  Keywords: multimodal large language model; MM-LLM; retrieval augmented generation; RAG; LlamaIndex; open education resources; personalised learning; learning assistant; open source language models; large language models; LLMs; small language models; SLMs; AI in education.
  DOI: 10.1504/IJTEL.2025.10069095
   
  
• Enhancing curriculum benchmarking by leveraging NLP: a case study of higher education in Tanzania  
  by Elia Ahidi Elisante Lukwaro, Rogers Bhalalusesa, Khamisi Kalegele, Devotha G. Nyambo 
  Abstract: The fast expansion of higher education institutions and the discrepancy between skill sets and labour market demands have heightened stakeholders concerns regarding the quality of education. Syllabi are the focal points of this study, as they act as the bridge between education and the skills or competencies required to demonstrate the relationship between the acquired education and the required market competencies. Benchmarking, which has its roots in business, is now widely used in education as a mechanism for evaluating educational metrics and practices and comparing them among institutions or with those of competitors with the aim of improving performance. This paper benchmarks the quality of syllabi using an NLP-based model, namely the sentence bidirectional encoder representations from transformers (SBERT). By utilising the course book to refine the SBERT model, which is a variation of all-MiniLM-L6-v2, an experiment is carried out to investigate the most effective parameter metric for model training. With an accuracy score of 92.64%, the model performance score demonstrates a high level of ability to discern conceptual and semantic relationships between sentences, leading to successful syllabi benchmarking outcomes. This work offers a perceptive mechanism to address the mismatch between educationally acquired skills and industry demands.
  Keywords: higher education; natural language processing; NLP; benchmarking; SBERT; performance; hyperparameter optimisation; Tanzania.
  DOI: 10.1504/IJTEL.2025.10069358
   
  
• Exploring the impact of explicit learning goals as a digital boundary object intervention in higher education  
  by Angela Fessl, Katharina Maitz, Sebastian Maximilian Dennerlein, Viktoria Pammer-Schindler 
  Abstract: Communicating clear learning goals are good practice in formal education. However, instructors often formulate vague and inconsistent goals, making it difficult for university students to use them as guidance for a lecture. This paper presents a method for systematically developing learning goals and a small web-app that displays these goals in a learning management system. We conceptualise the method, the learning goals, and the app as one connected digital boundary object. We evaluate this approach in four bachelor lectures at a technical university, each involving 150 to 500 students. Lecturers found the method easy to use and helpful for structuring content, while students appreciated the clear overview of the course content and the exam requirements. This study demonstrates how best practices based on theory can be implemented in digital learning environments. The digital boundary object can contribute to establishing a shared understanding across two social worlds, and to make knowledge boundaries permeable.
  Keywords: learning goals; learning goal method; self-regulated learning; learning goal app; boundary objects.
  
  
• Design of a learning progress visualisation tool and its impact on students’ motivation and results: a case study  
  by Cristina Alonso-Fernandez, José L. Jorro-Aragoneses, Carlos M. Alaíz 
  Abstract: Self-awareness of learning progress is crucial for students to identify strengths and areas needing improvement, and to boost their motivation. Learning analytics provide such information about learning progress. In this paper, we describe the design of a visualisation tool to track student progress in the topics covered throughout a university course. We also investigate its impact on students results and motivation to participate in optional learning activities. To evaluate the impact of the tool, we compared two groups of approximately 20 students during the whole semester. Our findings indicate that when they had access to the progress visualisation, students completed more review activities in course topics and were more consistent in their review activities throughout the course, while those in the control group engaged with these activities primarily near course deadlines. The methodology employed in this study could be adapted to other courses to further generalise our results.
  Keywords: visualisation tool; learning progress; student motivation; student results; learning analytics; case study; progress visualisation; Moodle.
  DOI: 10.1504/IJTEL.2025.10069106
   
  
• An investigation of the emergency remote teaching experience of Kyrgyz educators  
  by Rita Ismailova, Jamila Smanalieva, Elira Turdubaeva 
  Abstract: The lockdown caused by COVID-19 affected all aspects of life including education, which was transitioned to an online format. However, during this process, along with infrastructure difficulties, some countries faced stakeholder acceptance issues. In this study, the intention to use online teaching among educators of all levels in Kyrgyzstan was examined using the unified theory of acceptance and use of technology (UTAUT) model. According to results, performance expectancy and facilitating conditions of online teaching technologies had a positive effect on teachers acceptance of online teaching. However, factors such as effort expectancy, social influence, and homogenous motivation, as well as risk perception and trust had no impact on behavioural intention to use online teaching. That is, the intention to use online teaching among educators in the country was mostly defined by its usefulness. In addition, age and gender did not affect teachers acceptance of online teaching, while their education sector, the availability of personal computers, and computer literacy level had an impact on educators intention to teach online.
  Keywords: COVID-19; emergency remote teaching; ERT; unified theory of acceptance and use of technology; UTAUT model; technology use; online learning.
  
  
• Beyond traditional education: can public-private partnership-based recognition of prior learning transform education in developing countries?  
  by Roshan Lal Tamrakar, Suraj Kumar Mukti, Vimal Kumar Deshmukh 
  Abstract: The low uptake of skill development programs hinders achieving the UNs SDG 4 goals. Meanwhile, governments worldwide are promoting public-private partnership-based recognition of prior learning (PPP RPL) models. Despite significant efforts, engaging the public remains challenging. This study explores barriers affecting individuals behaviours and intentions toward adopting PPP RPL in developing countries. Using confirmatory factor analysis, it validates key constructs like performance expectancy (PFE), social influence (SCI), and technological anxiety and resistance (TAR). A UTAUT model for PPP RPL was developed, highlighting cognitive and affective trust (CAT) as crucial for actual adoption. Findings reveal that PFE and SCI significantly boost the intention to adopt PPP RPL, while trust critically impacts actual adoption. Interestingly, TAR, once considered influential, now has little effect due to improved internet access and familiarity with mobile technology. Performance-oriented, cost-effective skill programs that offer higher wages and social recognition are key motivators for adopting PPP RPL.
  Keywords: public private partnership; PPP; recognition of prior learning; RPL; skill development; UTAUT; Sustainable Development Goal 4; SDG 4; skill education.
  
  
• Effect of artificial intelligence-supported web technologies on the creative and reflective thinking skills of preservice teachers  
  by Cengiz Gündüzalp 
  Abstract: The study aimed to reveal the effectiveness of using artificial intelligence-supported web technology in lessons on preservice teachers creative and reflective thinking skills. The study used a convergent parallel design, one of the mixed-method techniques. The study employed an independent sample t-test and repeated measures ANOVA test while analysing the collected quantitative data; however, it used the content analysis method for the qualitative data analysis. Accordingly, the study findings revealed that the artificial intelligence-supported web technologies used in lessons resulted in no significant difference between students in-group and intergroup scores regarding their creative and reflective thinking skills. Considering their opinions, many of the students expressed that artificial intelligence technologies were ineffective in developing their creative and reflective thinking skills. In conclusion, the study findings indicated that using artificial intelligence-supported web technologies in lessons did not significantly affect students creative and reflective thinking skills.
  Keywords: artificial intelligence; creative thinking; reflective thinking; web technologies.
  
  
• Investigating the potentials of educational robotics and agile learning through scrum methodology in K-12 education: a systematic review  
  by Evangelia Anastasaki, Kostas Vassilakis, Edward Duca, Emmanuel Maravelakis, Antonios Konstantaras 
  Abstract: This paper reviews the current research literature on the potential of Educational Robotics (ER), the effects of Agile Scrum in educational settings, and the results of combining both in K-12 education. After systematically searching online literature databases, 127 relevant articles were located and included in the study. For each article, we analyse the purpose of the research and the results observed. The reviewed articles suggest that ER and the Scrum framework are powerful for developing students’ technical skills, agile mindsets, and collaboration skills. However, the fundamental limitations include the need for extensive teacher training, time-management processes, and high resource demands, making scalability difficult in underfunded or large-classroom settings. The systematic review outcomes are discussed in terms of their implications for future research, and they can provide helpful guidance for educators, practitioners, and researchers in the area.
  Keywords: agile learning; Scrum; educational robotics; K-12 programming; scratch; Python.
  DOI: 10.1504/IJTEL.2025.10070805
   
  
• Exploring avatar designs effect on student engagement in metaverse educational interactions  
  by Hasan Tinmaz, Preet Kawal Singh Dhillon 
  Abstract: Within educational contexts, the integration of metaverse presents unique opportunities for enhancing student engagement, with avatar design emerging as a pivotal factor in shaping the learning experience. This article concentrates on the outcomes of students avatar design regarding their virtual interactions. Through Likert-scale surveys and factor analysis (n = 424), the research identifies significant trends and dimensions such as gender and emotions and metaverse learning benefits, highlighting the importance of tailored educational strategies and gender-sensitive approaches. The findings emphasise the necessity of familiarity with immersive technologies and advocate for user-centric design principles in avatar creation for educational settings. The study offers valuable insights for practitioners involved in metaverse education and avatar design. This research provides a foundation for further exploration and innovation in metaverse education and avatar design, with future research directions including deeper investigations into avatar design dynamics, cross-cultural studies, and ethical considerations associated with virtual learning environments.
  Keywords: metaverse; digital persona; avatar; avatar customisation; user experience design; virtual education.
  DOI: 10.1504/IJTEL.2025.10071255
   
  
• The impact of 4C skills and technology use on senior high school students' achievement: a PLS-SEM approach  
  by Muhammad Aizri Fadillah, Sahyar, Yul Ifda Tanjung, Usmeldi, Muhammad Fazlan Akbar 
  Abstract: The present study aims to elucidate the factors contributing to student achievement in senior high schools in North Sumatra Province, Indonesia. The research method entailed collecting data by distributing an online questionnaire to two regional schools. The sample was selected using convenience sampling, and 179 valid responses were subjected to analysis. The relationship between critical, creative, collaborative, and communicative thinking (4C) skills and the mediating role of technology in learning on student achievement was analyzed using PLS-SEM. The results demonstrate that critical thinking and communication skills positively correlate with student achievement; however, not all 4C factors correlate directly. Technology in learning is an essential mediator in the relationship between communication and student achievement. This research provides insight into the importance of developing more effective learning strategies, particularly at the senior high school level, by considering the role of the 4C skills and technology integration in learning.
  Keywords: 4C skills; technology; learning; senior high school; PLS-SEM.
  DOI: 10.1504/IJTEL.2025.10071349
   
  
• Higher education during a global crisis: experiences migrating to a virtual learning environment in response to COVID-19  
  by Mahmoud T. Khasawneh, Jared R. Dmello, John C. Kilburn, Alicia Segovia, Daphne Sanchez 
  Abstract: In Spring 2020, academic institutions worldwide took measures to comply with the recommendations provided by health authorities to mitigate the spread of COVID-19. Institutions across the US transitioned to virtual learning environments as an emergency response. This study analyses the impact of an emergency transition to a virtual environment on learning experiences for both faculty and students at a mid-sized institution of higher learning. Although the emergency transition faced by institutions around the world has been criticised in the public domain as a mechanism of survival rather than teaching, the self-determination and motivation frameworks do provide the opportunity for high-quality learning within the education space. Thus, although not ideal, the emergency transition to a virtual learning environment in the Spring 2020 semester provided opportunities for institutions to innovate their course delivery mechanisms while still working to serve their campus communities.
  Keywords: higher education; COVID-19 emergency; virtual transition; pandemic learning; self-determination; motivation.
  DOI: 10.1504/IJTEL.2025.10071880
   
  
• Cultural intelligence in technology-enhanced language learning: nurturing cross-cultural competence in the digital age  
  by Esaya Britto Raphael 
  Abstract: This study explores the link between cultural intelligence (CI) and language proficiency in technology-enhanced language learning (TELL). Utilising a mixed-methods approach, the research combines quantitative surveys, including the cultural intelligence scale (CIS) and standardised language proficiency tests (TOEFL/IELTS), with qualitative interviews and focus groups involving 150 adult learners engaged in TELL programs. Additionally, usage data from TELL platforms were analysed to assess engagement patterns. Findings indicate a strong positive correlation (r = 0.45, p < 0.01) between CI and language proficiency, with motivational and metacognitive CI being key indicators of success. Additionally, frequent TELL platform users demonstrated higher CI scores than occasional users (F(1,148) = 9). The study highlights the role of TELL tools in fostering cross-cultural competence, emphasising their effectiveness in language acquisition.
  Keywords: cultural intelligence; CI; technology-enhanced language learning; TELL; cross-cultural competence; language proficiency.
  DOI: 10.1504/IJTEL.2025.10072480
   
  
• Latent profiles of computational thinking in first-year university students in Peru  
  by Edgar Marin-Ballon, Freddy Begazo-Zegarra, Fiorella Romero-Gomez 
  Abstract: This study aims to classify computational thinking (CT) among first-year Peruvian university students. A sample of 730 students was analysed, focusing on five key dimensions abstraction, decomposition, algorithmic thinking, evaluation, and generalisation using a validated CT evaluation tool and the mclust package in R. Four distinct CT profiles were identified, each highlighting unique strengths and weaknesses: Profile 1 exhibited high levels of CT skills, especially in evaluation and algorithmic thinking; Profile 2 showed moderate levels with a balanced distribution across dimensions; Profile 3 indicated significant weaknesses, particularly in decomposition; and Profile 4 had the lowest overall CT skills. Demographic variations explored through SPSS version 27 revealed significant differences in CT profiles based on the type of secondary school attended, with public school students excelling in abstraction. These findings contribute to the discourse on CT, offering practical guidance for educators to tailor interventions and enhance CT skills among university entrants.
  Keywords: computational thinking; CT; latent profile analysis; LPA; higher education; abstraction.