Towards a new proposal to evaluate the learning objects quality in learning strategies for education (QEES)

In Computer Science world several proposals have been developed for the assessment of the quality of the digital objects, based on the capabilities and facilities offered by current technologies and the available resources. Years ago researchers and specialists from both educational and technological areas have been committed to the development of strategies that improve the quality of education. At present, in the field of teaching-learning, another important aspect is the need to improve the manner of gaining knowledge and learning in education, which the use of learning strategies is a major advance in the teaching-learning process in institutions of higher education. This paper presents QEES, a proposal for evaluating the quality of the learning objects employed on learning strategies to support students during their education processes by using information extraction techniques and ontologies.

Developing a programme theory to explain how primary health care teams learn to respond to intimate partner violence: a realist case-study

Background: Despite the progress made on policies and programmes to strengthen primary health care teams’ response to Intimate Partner Violence, the literature shows that encounters between women exposed to IPV and health-care providers are not always satisfactory, and a number of barriers that prevent individual health-care providers from responding to IPV have been identified. We carried out a realist case study, for which we developed and tested a programme theory that seeks to explain how, why and under which circumstances a primary health care team in Spain learned to respond to IPV. Methods: A realist case study design was chosen to allow for an in-depth exploration of the linkages between context, intervention, mechanisms and outcomes as they happen in their natural setting. The first author collected data at the primary health care center La Virgen (pseudonym) through the review of documents, observation and interviews with health systems’ managers, team members, women patients, and members of external services. The quality of the IPV case management was assessed with the PREMIS tool. Results: This study found that the health care team at La Virgen has managed 1) to engage a number of staff members in actively responding to IPV, 2) to establish good coordination, mutual support and continuous learning processes related to IPV, 3) to establish adequate internal referrals within La Virgen, and 4) to establish good coordination and referral systems with other services. Team and individual level factors have triggered the capacity and interest in creating spaces for team leaning, team work and therapeutic responses to IPV in La Virgen, although individual motivation strongly affected this mechanism. Regional interventions did not trigger individual and/ or team responses but legitimated the workings of motivated professionals. Conclusions: The primary health care team of La Virgen is involved in a continuous learning process, even as participation in the process varies between professionals. This process has been supported, but not caused, by a favourable policy for integration of a health care response to IPV. Specific contextual factors of La Virgen facilitated the uptake of the policy. To some extent, the performance of La Virgen has the potential to shape the IPV learning processes of other primary health care teams in Murcia.

Aid decision algorithms to estimate the risk in congenital heart surgery

Background and objective: In this paper, we have tested the suitability of using different artificial intelligence-based algorithms for decision support when classifying the risk of congenital heart surgery. In this sense, classification of those surgical risks provides enormous benefits as the a priori estimation of surgical outcomes depending on either the type of disease or the type of repair, and other elements that influence the final result. This preventive estimation may help to avoid future complications, or even death. Methods: We have evaluated four machine learning algorithms to achieve our objective: multilayer perceptron, self-organizing map, radial basis function networks and decision trees. The architectures implemented have the aim of classifying among three types of surgical risk: low complexity, medium complexity and high complexity. Results: Accuracy outcomes achieved range between 80% and 99%, being the multilayer perceptron method the one that offered a higher hit ratio. Conclusions: According to the results, it is feasible to develop a clinical decision support system using the evaluated algorithms. Such system would help cardiology specialists, paediatricians and surgeons to forecast the level of risk related to a congenital heart disease surgery.

How to measure healthiness in buildings: Experiences in teaching with BIM tools

Introducing teaching about healthy solutions in buildings and BIM has been a challenge for the University of Alicante. Teaching attached to very tighten study plans conditioned the types of methods that could be used in the past. The worldwide situation of crisis that especially reached Spain and the bursting of the housing bubble generated a lack of employment that reached universities where careers related to construction, Architecture and Architectural Technologist, suffered a huge reduction in the number of students enrolled. In the case of the University of Alicante, students’ enrolment for Architectural Technology reached an 80% reduction. The necessity of a reaction against this situation made the teachers be innovative and use the new Bologna adapted study plans to develop new teaching experiences introducing new concepts: people wellbeing in buildings and BIM. Working with healthy solutions in buildings provided new approaches for building design and construction as an alternative to sustainability. For many years sustainability was the concept that applied to housing gave buildings an added value and the possibility of having viability in a very complex scenario. But after lots of experiences, the approved methodologies for obtaining sustainable housing were ambiguous and at the end, investors, designers, constructors and purchasers cannot find real and validated criteria for obtaining an effective sustainable house. It was the moment to work with new ideas and concepts and start facing buildings from the users’ point of view. At the same time the development of new tools, BIM, has opened a wide range of opportunities, innovative and suggestive, that allows simulation and evaluation of many building factors. This paper describes the research in teaching developed by the University of Alicante to adapt the current study plans, introducing work with healthy solutions in buildings and the use of BIM, with the aim of attracting students by improving their future employability. Pilot experiences have been carried out in different subjects based on the work with projects and case studies under an international frame with the cooperation of different European partner universities. The use of BIM tools, introduced in 2014, solved the problems that appeared in some subjects, mainly building construction, and helped with the evaluation of some healthy concepts that presented difficulties until this moment as knowledge acquired by the students was hard to be evaluated. The introduction of BIM tools: Vasari, FormIt, Revit and Light Control among others, allowed the study of precise healthy concepts and provided the students a real understand of how these different parameters can condition a healthy architectural space. The analysis of the results showed a clear acceptance by the students and gave teachers the possibility of opening new research lines. At the same time, working with BIM tools to obtain healthy solutions in building has been a good option to improve students’ employability as building market in Spain is increasing the number of specialists in BIM with a wider knowledge.