Salesian Journal on Information Systems

2-9

Authors: ALVES, M. A., SOUZA, L. T. F.

Smartphone users' satisfaction is related to several factors of interaction that represent criteria evaluated in the choice of the operating system. This paper investigates the usage satisfaction of Android, iOS and Windows Phone mobile operating systems users' and deals with multicriteria decision making. A survey was applied and 314 answers were obtained. The evaluated criteria and the scores obtained through the survey were the initial parameters for the multicriteria decision-making method TOPSIS. The method classified the three alternatives based on preferences over screen, terminology, learning and system capabilities. The iOS was the best classied in the proposed evaluations. Android got the second place in the Screen factors. In the others, Windows Phone was second and Android was third. A small variation in the weights did not change the order of classification found. Although ranking should reflect the decision makers preference, further investigations can be carried out using the TOPSIS method and its relationship to mobile devices interface.

20-37

Authors: LINDO, O. D.

A method for estimating the intangible value (INTVAL) impact of Information and Communication Technologies (ICTs) investments in organizations is presented. The method proposes conducting a comparative analysis of the impact projected by decision makers (DMs) with that perceived by user beneficiaries of the level of contribution of such technologies to the value-generating activities of their business unit. This will allow decision makers to determine: a) how an ICT investment is expected to impact their business unit’s value chain, b) how an ICT investment actually impacted their business unit’s value chain, and c) whether the INTVAL impact obtained with an ICT investment is aligned with the business’ strategic goals in terms of how many value-generating activities intended to be impacted were actually impacted at the predicted extent. A hypothetical example case is presented to illustrate the implementation of the method proposed.

46-74

Authors: ALOISE, A.F., FERREIRA, J.L.C., BARBOSA, J.L.V.

This paper proposes an educational recommendation system model based on prediction of students flunking in e-learning courses. RECD is proposed, a model of Educational Recommendation Systems which receives from some prediction system, among them MD-PREAD, statistical data on the possibility of learners' failure in a discipline and, based on these data, recommends to the target audience to reduce the number of apprentices who can fail. Techniques such as classification of user profiles, context awareness and Custom-er Relationship Manager were used to provide learners an opportunity not to fail in a discipline, or to improve the coeffi-cient of performance, to reduce the time enrolled in the course and to accelerate the certification Through pedagogical inter-ventions A prototype was designed to be experimented at the Federal Institute of Education, Science and Technology of Amazonas, in the program Open University of Brazil, in the Philosophy of Education course, in discipline of Brazilian Sign Language, in the second semester of 2015. We collected 30 teachers profiles, allowing the classification of the teacher profile using decision tree with RapidMiner. The prototype was also presented to 12 teachers so that they could make an evaluation of perceived ease of use and utility perception through the Technology Acceptance Model. It was concluded that RECD is a computational tool that can help teachers and course coordinators to rescue apprentices before the failure to culminate, in the discipline in progress.