Sustainable Development Goals
Abstract/Objectives
In recent years, mobile computing devices have become considerable tools for teaching and learning in school (Grant, 2019). Due to their easy usage and accessibility, mobile learning become significant (Göksu & Atici, 2013). Mobile learning offers greater flexibility than traditional textbooks, having more without the limits of time and space. In addition, mobile learning also has more visual ways to help people learn than traditional ones. Location-based mobile learning, a sub-class of mobile learning, accounts for the learners’ location, allowing them to interact with the environment in the process of learning.
However, during location-based mobile learning, learners tend to become too focused on the learning targets, resulting in a lack of opportunities for interaction with the environment. Therefore, we aim to enhance interaction with the environment in location-based mobile learning by invoking incidental learning. Simultaneously, we seek to identify effective methods of invocation. This study developed a Mobile Learning App that allows participants to visit main learning targets and incidental learning targets. To use sound as the invocation mechanism, we also set up incidental learning targets with reminder sounds to compare to main learning targets regarding learning effectiveness.
Results/Contributions
The results indicated no significant difference in learning effectiveness between main learning and incidental learning. However, incidental learning with reminder sounds showed noticeably poorer performance compared to main learning.
If we could expand the functionalities of the mobile learning App, such as adding dynamic databases and backend systems, it would provide educators with greater flexibility, making it a valuable tool in instructional settings. This type of app-based learning approach could also enhance students' environmental knowledge and attitudes, contributing to the goal of sustainable development education.
Keywords
Location-based Mobile LearningMobile LearningIncidental Learning