## 1 Introduction  
Augmented reality (AR) has shown great potential for learning by combining virtual objects with the real environment [1]. AR is an innovative tool that fosters creativity [2], facilitates the development of key digital skills [3], and increases student motivation and engagement by allowing them to explore educational content interactively, maintaining their long-term interest [2]. This impact is visible at all educational levels [4]: from early childhood education, where concepts are often introduced playfully, to higher education, where it provides practical experiences in different disciplines [5].  
Likewise, emotions play an important role in students' academic performance, as educational experiences are deeply tied to students' emotional states. In addition to improving the understanding of abstract concepts, AR can influence students' emotional states during the learning process. Evaluating this impact is key to optimizing the educational experience [6] and thus contributing to a more appropriate learning experience design.  
AR has been less widely used in virtual disciplines such as programming or algorithms than in other disciplines, such as history or engineering. However, AR also has educational potential for these fields. Thus, it can facilitate the understanding of algorithms by allowing the visualization of data structures and computational processes. Experiments with university students have shown that AR-based learning systems make it possible to reduce the cognitive load and improve the efficiency of algorithm learning, allowing for better visualization and understanding of structures such as trees, graphs, and optimization strategies [2]. However, challenges have been identified in the accessibility of the technology, the availability of suitable devices, and the need for teacher training for its effective implementation. As AR continues to evolve, it is crucial to further investigate its impact at different educational levels and to design pedagogical strategies that maximize its benefits in teaching algorithms [2]. Although AR has proven useful in teaching abstract virtual concepts, its impact on students has been insufficiently explored. This article presents a study of students' emotions while using the AR tool DARA, aimed at learning [PERSON]'s algorithm.  
This study addresses two main objectives. The first is to analyze the impact of using an augmented-reality-based tool (DARA) on students' emotional responses during the learning of [PERSON]'s algorithm. The second objective is to compare the effectiveness of two emotional assessment techniques--facial recognition based on artificial intelligence and the AEQ (achievement emotions questionnaire) psychometric questionnaire--for measuring students' emotions before, during, and after the learning experience.  
Based on these objectives, the following are the main contributions of this study. Firstly, the positive impact of an AR app on students' emotions in algorithm education was replicated. The replication of results is relevant, as a different measurement instrument was used. Secondly, the degree of increase or decrease in emotions was statistically different between the two instruments. This divergence was not expected and can be relevant for researchers focusing on the emotional impact of technology in education; thus, it deserves further research.  
This article is structured as follows: Section 2 presents related work, Sections 3 and 4 describe the technological resources and the methodology used, respectively, Section 5 analyzes the results obtained, Section 6 presents the discussion, and, finally, Section 7 reports the conclusions and future lines of research.