Agile software development has become a prevalent approach for capstone projects, particularly through the utilization of the Scrum framework. According to this framework, Sprint Retrospectives are imperative for teams to regularly reflect on and enhance their development process. However, empirical analysis of their content has received scant research attention.In this study, the Sprint Retrospective summaries produced during a final-year software capstone project were subjected to qualitative coding by two independent experts. The objective of this study was to ascertain which Agile practices were documented as having been adopted and to determine the variability in their adoption over time.The findings of the present study indicate that student teams predominantly reported adopting communication practices, followed by practices related to software versioning and integration, team proactivity, and acquiring technical knowledge. A thorough examination of the evolution of these practices reveals a discernible pattern. Initially, emphasis is placed on effective communication, while the final Sprint is characterized by a focus on technical mastery.

Student engagement is a persistent challenge in online engineering education. This study investigates the impact of microlearning delivered through an educational chatbot on motivation and academic performance in advanced Computer Engineering Course. A quasi-experimental design was employed with two parallel groups (n=74): the experimental group received ten focused microlearning capsules via chatbot, while the control group accessed equivalent content through standard video lectures. Motivation was measured using the Situational Motivation Scale (SIMS), and knowledge acquisition was assessed through a ten-item test. Results from independent simples t-tests showed significantly higher intrinsic motivation and self-determination index (SDI) scores in the chatbot group, along with superior test performance. These findings suggest that microlearning can effectively improve academic outcomes and Foster sustained Student engagement. The proposed approach offers a scalable and cost-efficient strategy for online and hybrid engineering education.

This paper presents an ingestion procedure into an interoperable repository called ALPACS (Access to Local Picture Archiving and Communication Systems). ALPACS serves clinical and hospital users who can access the repository data through an Artificial Intelligence (AI) application called PROXIMITY 1.0. This paper shows the automated procedure for data ingestion from the medical imaging provider into the ALPACS repository. The data ingestion procedure was successfully applied from the data provider (Hospital Clínico de la Universidad de Chile, HCUCH) by applying a pseudo-anonymization algorithm at the source and respecting the privacy of sensitive patient data. The transfer is done using international communication standards for health systems, allowing the replication of the procedure for other medical imaging provider institutions.

This paper describes a neural network based inference system developed as part of a bioinformatic application in order to help implement a systematic search scheme for the identification of genes which encode enzymes of metabolic pathways. The inference system uses BLAST sequence alignment values as inputs and generates a classification of the best candidates for inclusion in a metabolic pathway map. The system considers a workflow that allows the user to provide feedback with their final classification decisions. These are stored in conjunction with analyzed sequences for re-training and constant inference system improvement.