Increasingly, among international organizations concerned with unemployment rates and industry demands, there is an emphasis on the need to improve graduates’ employability skills and the transparency of mechanisms for their recognition. This research presents the Employability Skills Micro-credentialing (ESMC) methodology, designed under the EPICA Horizon 2020 (H2020) project and tested at three East African universities, and shows how it fosters pedagogical innovation and promotes employability skills integration and visibility. The methodology, supported by a competency-based ePortfolio and a digital micro-credentialing system, was evaluated using a mixed-method design, combining descriptive statistics and qualitative content analysis to capture complementary stakeholder perspectives. The study involved the participation of 13 lecturers, 169 students, and 24 employers. The results indicate that the ESMC methodology is a promising approach for supporting students in their transition from academia to the workplace. The implementation of the methodology and the involvement of employers entails rethinking educational practices and academic curricula to embed employability skills. It enables all actors to broaden their understanding of the relationship between higher education and the business sector and to sustain visibility, transparency, and reliability of the recognition process. These findings indicate that there are favourable conditions in the region for the adoption of the approach, which is a meaningful solution for the stakeholder community to address the skills gap.

The recent unexpected impact of the global pandemic on higher education has caused universities, governments, students, and teachers to reexamine all components of existing systems, including how to become more effective and efficient in using technologies for education. We have seen that moving classes online—either blended or fully online—can be done rapidly, but early reports show huge variations in quality, acceptance, completion, and learning. Thus, it is important to examine the existing research literature on pedagogical innovations and practices that use technologies. To understand this complex situation, the present study examines the current technological, organisational, and pedagogical trends and challenges using an exploratory design carried out in three stages. In stage one, a literature review of the academic and grey literature was conducted, identifying 14 trends of interest. These trends were used in a workshop and interview discussion between leading experts in the higher education field. Stage two focused on identifying 108 initiatives that represent these trends. Finally, 30 of these were selected as cases for further exploration in stage three. Using thematic analysis, the 30 cases were condensed into 12 main themes that represent the innovative practices that led to development of the IDEAS framework as a signpost on the roadmap of next-generation pedagogy for transforming higher education. IDEAS is presented in the discussion alongside examples and ways to apply it in higher education contexts.

Este artículo presenta el proyecto desarrollado durante el año 2011 por las unidades y centros de formación de las universidades públicas catalanas. El proyecto se orienta a la mejora de la calidad del sistema de educación superior y de la actividad del profesorado universitario mediante planes de formación específicamente diseñados con esta finalidad, centrándose primeramente en la identificación de competencias docentes definidas por la comunidad académica. Partiendo del contexto de implementación del Espacio Europeo de Educación Superior se identifican aquellas competencias propias de la función docente, para que posteriormente puedan ser adquiridas, desarrolladas y evaluadas mediante la formación, identificando modelos, estrategias, instrumentos y recursos que lo permitan. El proceso de identificación de las competencias docentes del profesorado universitario se ha desarrollado partiendo de una revisión bibliográfica del estado del arte, para posteriormente ser modificada y validada por grupos de discusión conformados por expertos en competencias y formación docente. Los resultados de identificación de dichas competencias han sido finalmente refrendados mediante una encuesta respondida por una muestra representativa de la comunidad académica de las ocho universidades públicas catalanas. El objetivo fundamental del proyecto que aquí presentamos no es otro que el de contribuir a una formación de calidad del profesorado universitario, que permita la adquisición, desarrollo y evaluación de las competencias que, como docente, gran parte de la comunidad académica considera que debe poseer para el ejercicio de su labor profesional, definidas como: interpersonal, metodológica, comunicativa, de planificación y gestión de la docencia, de trabajo en equipo y de innovación.

In July 2023, given the rise of LLMs (Large Langauge Models), RED convened this special issue on Generative AI and Education, where special attention was paid to its consequences for intelligent learning and educational evaluation. We wanted to give space to contributions that included research related to these topics. Also to experiences about intelligent learning and formative evaluation in ChatGPT contexts. The call was with these general questions Does AI have the potential to revolutionize existing teaching methods, assessment and student support? Creative thinking and problem solving are essential in modern and very complex environments. Could this AI help students deal with these problems? We also had doubts about its benefits. They could be summarized in this question: Generative AI will begin to serve as an active partner in social, creative and intellectual actions continuously over time, and not only as an answer to isolated questions: What are the impacts that will occur? Now those impacts are unknown in the practices that may exist. Another intention was: A theoretical framework is needed to address these questions and in general for an effective deployment of AI systems in education. It is necessary to do so beyond the results provided by empirical research. And that it does not guide and direct at new crossroads, both in research and practice. In the conclusions we see to what extent these expectations have been met. As a consequence, we deduce that the critical importance of theory in the design, development and deployment of AI in education is necessary now more than ever. But we are equally underserved. In this perspective, we continue to critically consider the relevance and continuity of existing learning theories when AI becomes a reality in classrooms. As that result is not met, we also reiterate the call to consider new frameworks, models and ways of thinking. We are referring to those that include the presence of non-human agents, which we hesitate to call a new technology, because it is more like an active partner than a simple technology, as has happened until now. This approach is precisely what makes us insist on a series of important questions for the future, precisely about the review of learning theories based on existing configurations. And to investigate what their alternatives would be in this case. We have done after extensive and exhaustive dissemination in your call. But, despite this and beyond these general conclusions that we have made, the special issue offers us evidence of a scarce empirical investigation of practical cases in the application of generative AI in education. However, of the hundred or so contributions received, seven have been selected in the previous editorial review. The rest have been discarded because they do not conform to the standards or are not the type of contributions requested (the literature reviews per se and the self-report studies stand out among them, due to their high number). Of those seven, six have passed editorial review. They are described at the end. The main contributions of this small number of contributions have been the confirmation of a low level of research and practice. Also, some very interesting contributions from the articles and essays by the invited authors. We draw your attention to these articles and the clear results and evidence obtained on the concrete use of generative AI in specific environments. Results of inevitable use by schools, universities and teachers in these environments or in others to which they can be transferred. En julio de 2023, ante el auge de los LLM (Large Langauge Models), RED convocó este número especial sobre IA generativa y Educación, donde se prestase especial atención a sus consecuencias para el aprendizaje inteligente y la evaluación educativa. Se quería dar espacio a contribuciones que incluyesen investigación relacionada con estos temas. Y también a experiencias sobre el aprendizaje inteligente y evaluación formativa en contextos ChatGPT. Hoy, un año después, publicamos este número, con estas preguntas de carácter general ¿la IA tiene el potencial de revolucionar los métodos de enseñanza, la evaluación y la ayuda al alumno, existentes? el pensamiento creativo y la resolución de problemas son fundamentales en entornos modernos y muy complejos ¿Esta IA podría ayudar a los alumnos a enfrentarse a esos problemas? También había otras cuestiones que podían ser planteadas como dudas de sus beneficios que se podrían resumir en ¿Cuáles son los impactos que se producirán cuando la IA generativa comience a servir como un socio activo en acciones sociales, creativas e intelectuales sostenidas, no sólo puntuales o como repuesta a preguntas aisladas? Ahora esos impactos en las prácticas que puedan existir son desconocidos. La otra intención era que, para abordar estas preguntas y en general la necesidad de un despliegue efectivo de los sistemas de IA en la educación, es preciso hacerlo desde un punto de vista teórico, más allá de los resultados que, sobre las interrogantes señaladas, nos proporcione la investigación empírica. Y que no guíe y dirija en nuevas encrucijadas, tanto en la investigación como la práctica. Ese marco teórico, suponíamos entonces, nos proporcionará los asideros y las andaderas para garantizar que los principios, los valores y las construcciones confiables configuren el uso de la IA en la educación. En las conclusiones vemos en qué escasa medida estas expectativas se han cumplido. Como consecuencia, lo que veíamos como una necesidad en esta convocatoria: la importancia crítica de la teoría en el diseño, desarrollo y despliegue de la IA en la educación se ve necesaria ahora más que nunca, pero...

The progressive shift from a transmissive to a competence-based approach emphasises the need to design new models and tools for competence assessment. In order to address this need, this study, firstly, introduces the assessment model for digital competence in primary and secondary schools developed within the H2020 CRISS project. The Competence Assessment Model (CAM) (1) embraces the integration pedagogy approach in which competences are embedded within the curriculum and (2) provides competence assessment scenarios (CAS). Secondly, the study presents the results of the evaluation of its quality from the teachers’ perspective through an instrument designed on the basis of nine competence assessment quality criteria. The CAM was tested in a large-scale pilot study conducted in 535 primary and secondary schools across Europe. The outcomes show that the CAM mainly fulfills two out of the nine quality criteria: meaningfulness and authenticity. However, the exploratory factor analysis also reveals that all these quality criteria can be summarized into four key quality factors that more accurately describe how CAM is experienced in school teaching. Out of these, the most relevant is the (1) efficiency over time, student monitoring, support and evaluation. The three secondary factors identified are (2) fairness and cognitive complexity, (3) meaningfulness and authenticity and (4) reproducibility and transparency. The study provides a conceptual and methodological approach for the evaluation of Digital Competence in the school context. Most of all, it helps highlight four factors that, according to teaching staff, describe the quality of the proposed model when applied to daily teaching practices.

This article presents the implementation of an assessment model for generic competences in K-12 enabled by open educational practices. It showcases a digital competence assessment model that outlines the design of competence assessment scenarios constructed by means of a collaborative process involving teachers from six European countries, learning designers, and researchers. Our study draws attention to the concept of open educational practices as a broad descriptor of four areas of teacher practice regarding design, content, teaching, and assessment. The process unfolds through three phases, where teachers’ engagement with collaborative processes and network-based tools facilitate the construction of active shared learning. It analyzes the joint creation of open practices, and the production of open educational resources. The scalability, flexibility, and adaptability of competence assessment scenarios underline their transferability to similar contexts. The experience may benefit educational institutions and communities of teachers interested in innovating and opening up education.