| dc.description.abstract | Most studies in English as a foreign language (EFL) mentioned that teachers supported by harnessing artificial intelligence (AI) to generate learning feedback could enhance EFL learners’ learning achievement and motivation. However, the educational learning process of these interactions only educates and enhance human intelligence and knowledge. Furthermore, with the rapid development of technologies, there is a high potential to extend education to not only for human beings but also to all things, including digital or physical objects. Therefore, in this study, the combination of AI, Internet of Things (IoT), and mobile computing (formed as edge computing) will be utilized not only to educate human beings but also to all things. Hence, the XoT (Xducation of Things) framework was proposed to educate humans, AI, physical objects, and digital objects.
In this study, we proposed the XoT framework as a new education perspective, incorporating question and answering (Q&A) interactions to facilitate mutual learning among all things. To be more specific, the XoT framework was proposed to educate human beings and all things, including AI, physical objects, and digital objects. Furthermore, our edge computing approach empowers physical objects and digital objects with the ability to understand the human language, which is referred to as smartthings. Hence, besides all things including smartthings can be taught and learned from each other in the XoT environment, EFL learners as human beings also benefit from the Q&A interactions. Therefore, we conducted two empirical studies, including the development of XoT environments and quasi-experiments based on our proposed XoT framework for EFL learning.
In the first study, we designed and implemented an XoT environment specifically for EFL learning. Our investigation focused on examining how all things can effectively construct and build their knowledge through Q&A interactions. In addition, we developed a question forwarding mechanism (QFM) to help all things building their knowledge base rapidly. A quasi experiment was conducted with a total of 22 EFL learners that divided randomly into two groups, the experimental group (EG) consist of 11 EFL learners and the control groups (CG) consists of 11 EFL learners learn in the XoT environment with/without the QFM, respectively. A mix-method analysis was employed to investigate the results deeply. The results revealed that the EG, which utilized smartthings with the QFM were three times richer in the knowledge bases compared to CG. Hence, EFL learners in EG received better quality of Q&A interactions. Furthermore, the interactions between EFL learners and all things in the XoT environment not only contributed to increase the knowledge bases of smartthings but also help EFL learners enhance EFL writing in both groups. In addition, EG learners perceived that the XoT environment had potential to enhance their EFL writing skills after having the Q&A interactions with smartthing.
The results revealed that EG utilizing smartthings with the Smart QFM had achieved four times increase the specific knowledge bases for smart Q&A interactions compared to CG. In detail, EG learners received better quality of smart Q&A interactions with smartthings along with better answers compared to CG learners during in the first phase of smart Q&A interactions. In addition, the EG learners also received better quality questions during the second phase of Q&A interactions. Furthermore, the interaction between EFL learners and all things in the smart XoT environment not only increased the specific knowledge bases of smartthings but also helped EFL learners enhance their EFL writing in authentic contexts with meaningful content from contextual information. | en_US |