期刊名称:Anais dos Workshops do Congresso Brasileiro de Informática na Educação
印刷版ISSN:2316-8889
出版年度:2018
卷号:7
期号:1
页码:64
DOI:10.5753/cbie.wcbie.2018.64
语种:Portuguese
出版社:Anais dos Workshops do Congresso Brasileiro de Informática na Educação
摘要:The development and use of computational applications to support teaching and learning, together with the evolution of mobile computing, have contributed significantly to the establishment of a new learning modality known as mobile learning. Despite the benefits and facilities offered by educational applications, some problems and issues they present must be addressed. Challenges associated with mobile learning are not limited to developmental aspects or technologies. We should also consider the pedagogical aspects of this kind of application. When dealing with domain-specific software, we must be concerned about domain requirements. Therefore, it is important to have expert knowledge in the requirements engineering team and, in the case of mobile learning applications projects, such knowledge come from educators, teachers and tutors. However, capturing and transferring tacit knowledge are not trivial tasks and a supporting mechanism that guides the requirements elicitation phase in mobile learning applications projects would be of major importance. Pattern languages as a method to describe tacit knowledge is acknowledged and could be used as a supporting mechanism. Patterns constitute a mechanism for capturing domain experience and knowledge to allow such experience and knowledge to be reapplied when a new problem is encountered. Similarly, pedagogical patterns try to capture expert knowledge of the practice of teaching and learning. Aiming to solve, or at least diminish, the problems associated with mobile learning and due the lack of pedagogical patterns for this purpose, this work aims to create a pedagogical pattern language to assist the requirements elicitation phase of mobile learning applications projects. In this context, a pedagogical pattern language, named MLearning-PL, was created. It is composed of 14 patterns and focuses on assisting in the definition of mobile applications in order to keep learners motivated and committed to using such applications, considering their different learning styles and an effective knowledge acquisition. Experimental studies comparing MLearning-PL to an ad hoc approach in a pedagogical problem resolution scenario were conducted. The results obtained provided preliminary evidences of the applicability, effectiveness and efficiency of MLearning-PL.