Modern handheld devices and wireless communications foster new kinds of communication and interaction that can define new approaches to teaching and learning. Mobile learning (m-learning) seeks to use them extensively, exactly in the same way in which e-learning uses personal computers and wired communication technologies. In this new mobile environment, new applications and educational models need to be created and tested to confirm (or reject) their validity and usefulness. In this article, we present a mobile tool aimed at self-assessment, which allows students to test their knowledge at any place and at any time. The degree to which the students' achievement improved is also evaluated, and a survey on the students' opinion of the new tool was also conducted. An experimental group of 20- to 21-year-old nursing students was chosen to test the tool. Results show that this kind of tool improves students' achievement and does not make necessary to introduce substantial changes in current teaching activities and methodology.

Clinical Decision Support Systems have the potential to reduce lack of communication and errors in diagnostic steps in primary health care. Literature reports have showed great advances in clinical decision support systems in the recent years, which have proven its usefulness in improving the quality of care. However, most of these systems are focused on specific areas of diseases. In this way, we propose a rule-based expert system, which supports clinicians in primary health care, providing a list of possible diseases regarding patient's laboratory tests results in order to assist previous diagnosis. Our system also allows storing and retrieving patient's data and the history of patient's analyses, establishing a basis for coordination between the various health care levels. A validation step and speed performance tests were made to check the quality of the system. We conclude that our system could improve clinician accuracy and speed, resulting in more efficiency and better quality of service. Finally, we propose some recommendations for further research.

Modern handheld devices and wireless communications foster new kinds of communication and interaction that can define new approaches to teaching and learning. Mobile learning (m-learning) seeks to use them extensively, exactly in the same way in which e-learning uses personal computers and wired communication technologies. In this new mobile environment, new applications and educational models need to be created and tested to confirm (or reject) their validity and usefulness. In this article, we present a mobile tool aimed at self-assessment, which allows students to test their knowledge at any place and at any time. The degree to which the students' achievement improved is also evaluated, and a survey on the students' opinion of the new tool was also conducted. An experimental group of 20- to 21-year-old nursing students was chosen to test the tool. Results show that this kind of tool improves students' achievement and does not make necessary to introduce substantial changes in current teaching activities and methodology.

In recent years, cloud computing has motivated new learning tools based on the cloud to collaborate and share content with a large number of students. Thus, the main objective of this paper is to propose structural equation modeling explaining the educational usage of cloud-based tools (CBTs) in terms of their adoption and application in learning activities within a virtual course. The data analysis used a representative sample from Galileo University, Guatemala. The results of the study revealed that usefulness is one of the main reasons for the rapid adoption of CBTs. The study also showed that in terms of educational usage, there is a greater correlation with lower order thinking skills than that with higher order thinking skills of Bloom's taxonomy. Finally, the evidence from this study suggests that from a student perception, peer-to-peer communication and collaboration can be a strong motivation to use CBTs on learning activities. INDEX TERMS Educational technology, structural equation model, virtual learning environment, e-learning technologies.