Gamification is an active methodology of great value that, in a quality educational environment, provides students with the necessary motivation to participate in their teaching-learning process. An emerging active methodology, which is based on the use of information and communication technologies (ICT) and requires an educational space that guarantees greater flexibility in the pedagogical dynamics in favor of academic achievement. This increase in interest in active methodologies, and specifically in gamification, has raised doubts about whether current educational spaces are prepared to host a renewal in methodology or if, on the contrary, they could undermine the attitude of change. For this reason, this research seeks to analyze whether current educational spaces are facilitating elements for the incorporation of gamification in the classroom. The methodological cut of the research is quantitative, specifically in two phases. On the one hand, a descriptive analysis of the results is carried out, obtaining information on the trend of each item. On the other hand, an inferential analysis is carried out around different variables to verify their possible influence on the evaluations of the participants. The results obtained, in the sample made up of 210 teachers distributed in the different centers and who carry out their educational activity from 3rd to 6th grade of primary school, indicate that teachers believe it is relevant to take into account the educational space when incorporating active methodologies in class.

How are telecommunications infrastructure, institutions and poverty related in a war-torn economy such as Afghanistan? Afghanistan has been plagued by poor governance, low usage of telecommunications, and extreme poverty levels which can be termed triple-challenges. High levels of political instability affected telecommunications investment and adversely affected the adoption and diffusion of modern technology. This study examines the asymmetric effect of telecommunications and governance (institutions) on poverty reduction over the period 1989–2019 using a nonlinear autoregressive distributed lag (NARDL) model. In the short run, we establish that information and communication technology, private domestic credit, governance, and educational access for males and females are essential tools that can be used for poverty reduction. In the long run, we also establish that Afghanistan can reduce poverty levels through the use of information and communication technology, governance, and educational access for both males and females. The following policy recommendations were suggested: research and development, robust policy formulation on governance and ICT, development of the ICT sector, and improved governance. These are critical in reducing the high poverty levels as well as solving the institutional challenges faced by Afghanistan.

In Costa Rica, there is no explicit recommendation from the competent authorities for the use of a specific phantom, so experts must explore what suppliers offer, among which the Normi Mam Digital phantom from PTW stands out. This article presents the results of the dosimetry and image quality control applied to the Normi Mam Digital phantom to validate it as equipment that complies with the recommendations of the Human Health Series No. 17. The results obtained were satisfactory, proving that the equipment complies with the tolerances recommended by international health bodies.

The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.

The rapid advancement of financial technology (Fintech) has revolutionized the way financial transactions are conducted, with E-payment services becoming increasingly integral to daily commerce. This paper examines consumer perceptions and attitudes towards E-payment services offered by Fintech companies, identifying key factors that influence their acceptance and usage. Employing a quantitative approach, the research integrates quantitative data from surveys and applied SEM (Structural Equation Modelling) through AMOS. Out of 450, 420 respondents have given their views on perceptual preferences and attitudes with the help of SPSS. KMO and Bartlett’s Test are executed to understand and to check the factors for implementing factor analysis further through extractions. Anticipated findings are expected to reveal a spectrum of consumer attitudes shaped by factors such as trust, security, convenience, and technological familiarity. It contributes to the existing literature by providing updated insights into consumer behaviour in the Fintech sector and suggesting actionable strategies for service providers to enhance user engagement and satisfaction. It holds the potential to inform both theoretical frameworks in technology acceptance and practical marketing strategies for Fintech companies aiming to optimize E-payment services for diverse consumer bases.