Premium
The effectiveness of a meaningful learning‐based evaluation model for context‐aware mobile learning
Author(s) -
Huang YuehMin,
Chiu PoSheng
Publication year - 2015
Publication title -
british journal of educational technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.79
H-Index - 95
eISSN - 1467-8535
pISSN - 0007-1013
DOI - 10.1111/bjet.12147
Subject(s) - computer science , strengths and weaknesses , context (archaeology) , analytic hierarchy process , field (mathematics) , process (computing) , artificial intelligence , knowledge management , management science , psychology , operations research , social psychology , paleontology , mathematics , pure mathematics , engineering , economics , biology , operating system
In recent years, context‐aware mobile learning ( CAML ) has been widely applied to various fields and has become a popular issue in educational research. Despite the tremendous potential of CAML and its growing significance, continued evaluations and refinements under the advice of field experts and instructors are crucial to ensure its validity, value and sustainability. In this paper, an evaluation model for CAML is developed based on meaningful learning theory using the analytic hierarchy process ( AHP ). To verify the effectiveness of the model, three different CAML learning activities are tested, and some experts are invited to evaluate and compare them. As a result, the strengths and weaknesses of each learning activity are obtained. With the aid of the evaluation model proposed in this work, CAML developers can progressively enhance the value of learning activities, thus improving this new approach to learning.