A summary of the third workshop on theory-informed user modeling for tailoring and personalizing interfaces

The third workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE) 1 took place in conjunction with the 24th annual meeting of the intelligent user interfaces (IUI) 2 community in Los Angeles, CA, USA on March 20, 2019. The goal of the workshop was to attract researchers from different fields by accepting contributions on the intersection of practical data mining methods and theoretical knowledge for personalization. A total of six papers were accepted for this edition of the workshop.

THE USE OF AI IN LANGUAGE LEARNING: WHAT YOU NEED TO KNOW

Kecerdasan Buatan adalah kekuatan transformasional dalam pendidikan, terutama dalam pembelajaran bahasa. Studi ini membahas berbagai alat AI yang digunakan untuk pembelajaran bahasa, seperti terjemahan mesin, teknologi ucapan, chatbot, dan konten yang dihasilkan oleh kecerdasan buatan. Studi ini secara komprehensif menjelajahi potensi dan tantangan yang terkait dengan peran kecerdasan buatan dalam pendidikan bahasa. Di satu sisi, kecerdasan buatan menawarkan manfaat seperti panduan personal, keterlibatan interaktif, dan pelacakan kemajuan. Namun, juga menimbulkan kekhawatiran tentang interaksi manusia yang berkurang, dampak potensial pada otonomi pembelajar, dan peran yang berkembang dari guru bahasa. Oleh karena itu, studi ini menekankan pentingnya menggabungkan prinsip-prinsip etika, transparansi, dan inklusivitas untuk memandu integrasi kecerdasan buatan dalam pendidikan secara bertanggung jawab. Penelitian ini menggunakan metodologi penelitian perpustakaan untuk membangun landasan teoritis yang kuat, menekankan peran penting integrasi kecerdasan buatan yang bertanggung jawab dalam meningkatkan pendidikan bahasa sambil menjaga standar etika yang tinggi

Innovating Language Education: An NMC Horizon Project Strategic Brief

The NMC is a leading educational technology organization. A main outcome of the collaboration between the Language Flagship Technology Innovation Center and the NMC was this publication, which highlights recommendations that emerged from discussions of major trends, challenges, and technology developments by experts and practitioners in language technologies in higher education. Innovating Language Education identifies main trends and areas of interest and constitutes a rich resource that includes key definitions and proofs of concept

The Role Of Gamification In English Language Teaching: A Literature Review

This literature review examines the impact of gamification in English language teaching (ELT) on motivation, engagement, and learning outcomes. Gamification, the integration of game elements into education, has gained attention as a promising approach to enhance language learning. The findings reveal that gamification positively influences student motivation in ELT. Elements like points, leaderboards, and rewards create a sense of achievement and intrinsic motivation. Engaged students are more likely to persist and participate actively in language learning. Gamification promotes active learning and engagement, with interactive activities involving vocabulary acquisition, grammar practice, and language production. It provides a safe space for students to experiment, apply knowledge, and develop linguistic skills. Collaboration and social interaction are fostered through gamification, encouraging teamwork and peer feedback. This enhances language and interpersonal skills. Immediate feedback and progress tracking in gamification offer valuable learning opportunities. Students receive real-time feedback and monitor their progress, enabling adjustments in learning strategies. However, implementing gamification in ELT faces challenges such as technology constraints and pedagogical considerations. Striking a balance between engagement and curriculum objectives is crucial. Teacher training and professional development are necessary. In conclusion, gamification plays a significant role in ELT by enhancing motivation, engagement, collaboration, and active learning. Despite challenges, embracing gamification and its best practice

A Systemic Review (2014–2023) on the Mobile-Assisted Blended Learning for English as a Foreign Language Education with a Focus on Empirical Studies

Over the past two decades, due to the rapid development of information and communication technologies (ICT), mobile learning (M-learning) and blended learning (BL) have emerged as new trends in sustaining English as a foreign language (EFL) education. The tumultuous COVID-19 pandemic has disrupted traditional teaching and learning, but it has also accelerated the integration of technology in EFL education. Mobile-assisted blended learning (MABL) combines mobile-assisted language learning (MALL) and BL into a single framework that effectively addresses their individual limitations when used in isolation. However, reviews of MABL, particularly in the context of EFL education, are scarce. Sourced from two major databases, namely Web of Science and Scopus, and two supplementary databases (Education Resources Information Center and Mendeley), 25 studies were extracted out of 205 in the latest decade, using specific exclusion and inclusion criteria. This review aims to shed light on the trend of utilizing advanced and effective pedagogy and teaching tools to benefit stakeholders in the sustainable development of English as a foreign language

Enforcing Customization in e-Learning Systems: an ontology and product line-based approach

In the era of e-Learning, educational materials are considered a crucial point for all the stakeholders. On the one hand, instructors aim at creating learning materials that meet the needs and expectations of learners easily and effec-tively; On the other hand, learners want to acquire knowledge in a way that suits their characteristics and preferences. Consequently, the provision and customization of educational materials to meet the needs of learners is a constant challenge and is currently synonymous with technological devel-opment. Promoting the personalization of learning materials, especially dur-ing their development, will help to produce customized learning materials for specific learners' needs. The main objective of this thesis is to reinforce and strengthen Reuse, Cus-tomization and Ease of Production issues in e-Learning materials during the development process. The thesis deals with the design of a framework based on ontologies and product lines to develop customized Learning Objects (LOs). With this framework, the development of learning materials has the following advantages: (i) large-scale production, (ii) faster development time, (iii) greater (re) use of resources. The proposed framework is the main contribution of this thesis, and is char-acterized by the combination of three models: the Content Model, which addresses important points related to the structure of learning materials, their granularity and levels of aggregation; the Customization Model, which con-siders specific learner characteristics and preferences to customize the learn-ing materials; and the LO Product Line (LOPL) model, which handles the subject of variability and creates matter-them in an easy and flexible way. With these models, instructors can not only develop learning materials, but also reuse and customize them during development. An additional contribution is the Customization Model, which is based on the Learning Style Model (LSM) concept. Based on the study of seven of them, a Global Learning Style Model Ontology (GLSMO) has been con-structed to help instructors with information on the apprentice's characteris-tics and to recommend appropriate LOs for customization. The results of our work have been reflected in the design of an authoring tool for learning materials called LOAT. They have described their require-ments, the elements of their architecture, and some details of their user inter-face. As an example of its use, it includes a case study that shows how its use in the development of some learning components.En la era del e¿Learning, los materiales educativos se consideran un punto crucial para todos los participantes. Por un lado, los instructores tienen como objetivo crear materiales de aprendizaje que satisfagan las necesidades y ex-pectativas de los alumnos de manera fácil y efectiva; por otro lado, los alumnos quieren adquirir conocimientos de una manera que se adapte a sus características y preferencias. En consecuencia, la provisión y personaliza-ción de materiales educativos para satisfacer las necesidades de los estudian-tes es un desafío constante y es actualmente sinónimo de desarrollo tecnoló-gico. El fomento de la personalización de los materiales de aprendizaje, es-pecialmente durante su desarrollo, ayudará a producir materiales de aprendi-zaje específicos para las necesidades específicas de los alumnos. El objetivo fundamental de esta tesis es reforzar y fortalecer los temas de Reutilización, Personalización y Facilidad de Producción en materiales de e-Learning durante el proceso de desarrollo. La tesis se ocupa del diseño de un marco basado en ontologías y líneas de productos para desarrollar objetos de aprendizaje personalizados. Con este marco, el desarrollo de materiales de aprendizaje tiene las siguientes ventajas: (i) producción a gran escala, (ii) tiempo de desarrollo más rápido, (iii) mayor (re)uso de recursos. El marco propuesto es la principal aportación de esta tesis, y se caracteriza por la combinación de tres modelos: el Modelo de Contenido, que aborda puntos importantes relacionados con la estructura de los materiales de aprendizaje, su granularidad y niveles de agregación, el Modelo de Persona-lización, que considera las características y preferencias específicas del alumno para personalizar los materiales de aprendizaje, y el modelo de Línea de productos LO (LOPL), que maneja el tema de la variabilidad y crea ma-teriales de manera fácil y flexible. Con estos modelos, los instructores no sólo pueden desarrollar materiales de aprendizaje, sino también reutilizarlos y personalizarlos durante el desarrollo. Una contribución adicional es el modelo de personalización, que se basa en el concepto de modelo de estilo de aprendizaje. A partir del estudio de siete de ellos, se ha construido una Ontología de Modelo de Estilo de Aprendiza-je Global para ayudar a los instructores con información sobre las caracterís-ticas del aprendiz y recomendarlos apropiados para personalización. Los resultados de nuestro trabajo se han plasmado en el diseño de una he-rramienta de autor de materiales de aprendizaje llamada LOAT. Se han des-crito sus requisitos, los elementos de su arquitectura, y algunos detalles de su interfaz de usuario. Como ejemplo de su uso, se incluye un caso de estudio que muestra cómo su empleo en el desarrollo de algunos componentes de aprendizaje.En l'era de l'e¿Learning, els materials educatius es consideren un punt crucial per a tots els participants. D'una banda, els instructors tenen com a objectiu crear materials d'aprenentatge que satisfacen les necessitats i expectatives dels alumnes de manera fàcil i efectiva; d'altra banda, els alumnes volen ad-quirir coneixements d'una manera que s'adapte a les seues característiques i preferències. En conseqüència, la provisio' i personalitzacio' de materials edu-catius per a satisfer les necessitats dels estudiants és un desafiament constant i és actualment sinònim de desenvolupament tecnològic. El foment de la personalitzacio' dels materials d'aprenentatge, especialment durant el seu desenvolupament, ajudarà a produir materials d'aprenentatge específics per a les necessitats concretes dels alumnes. L'objectiu fonamental d'aquesta tesi és reforçar i enfortir els temes de Reutilització, Personalització i Facilitat de Producció en materials d'e-Learning durant el procés de desenvolupament. La tesi s'ocupa del disseny d'un marc basat en ontologies i línia de productes per a desenvolupar objec-tes d'aprenentatge personalitzats. Amb aquest marc, el desenvolupament de materials d'aprenentatge té els següents avantatges: (i) produccio' a gran esca-la, (ii) temps de desenvolupament mes ràpid, (iii) major (re)ús de recursos. El marc proposat és la principal aportacio' d'aquesta tesi, i es caracteritza per la combinacio' de tres models: el Model de Contingut, que aborda punts im-portants relacionats amb l'estructura dels materials d'aprenentatge, la se-ua granularitat i nivells d'agregació, el Model de Línia de Producte, que ges-tiona el tema de la variabilitat i crea materials d'aprenentatge de manera fàcil i flexible. Amb aquests models, els instructors no solament poden desenvolu-par materials d'aprenentatge, sinó que també poden reutilitzar-los i personalit-zar-los durant el desenvolupament. Una contribucio' addicional és el Model de Personalitzacio', que es basa en el concepte de model d'estil d'aprenentatge. A partir de l'estudi de set d'ells, s'ha construït una Ontologia de Model d'Estil d'Aprenentatge Global per a ajudar als instructors amb informacio' sobre les característiques de l'aprenent i recomanar els apropiats per a personalitzacio'. Els resultats del nostre treball s'han plasmat en el disseny d'una eina d'autor de materials d'aprenentatge anomenada LOAT. S'han descrit els seus requi-sits, els elements de la seua arquitectura, i alguns detalls de la seua interfície d'usuari. Com a exemple del seu ús, s'inclou un cas d'estudi que mostra com és el desenvolupament d'alguns components d'aprenentatge.Ezzat Labib Awad, A. (2017). Enforcing Customization in e-Learning Systems: an ontology and product line-based approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90515TESI

Artificial intelligent based teaching and learning approaches: A comprehensive review

The goal of this study is to investigate the potential effects that Artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study’s emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates

A New Era of Artificial Intelligence in Education: A Multifaceted Revolution

The recent high performance of ChatGPT on several standardized academic test has thrust the topic of artificial intelligence (AI) into the mainstream conversation about the future of education. The objective of the present study is to investigate the effect of AI on education by examining its applications, advantages, and challenges. Our report focuses on the use of artificial intelligence in collaborative teacher-student learning, intelligent tutoring systems, automated assessment, and personalized learning. We also look into potential negative aspects, ethical issues, and possible future routes for AI implementation in education. Ultimately, we find that the only way forward is to accept and embrace the new technology, while implementing guardrails to prevent its abuse

Education in the age of Generative AI: Context and Recent Developments

With the emergence of generative artificial intelligence, an increasing number of individuals and organizations have begun exploring its potential to enhance productivity and improve product quality across various sectors. The field of education is no exception. However, it is vital to notice that artificial intelligence adoption in education dates back to the 1960s. In light of this historical context, this white paper serves as the inaugural piece in a four-part series that elucidates the role of AI in education. The series delves into topics such as its potential, successful applications, limitations, ethical considerations, and future trends. This initial article provides a comprehensive overview of the field, highlighting the recent developments within the generative artificial intelligence sphere