Cognitive Diffusion Model: Facilitating EFL Learning in an Authentic Environment Rustam Shadiev, Wu-Yuin Hwang, Yueh-Min Huang, and Tzu-Yu Liu Abstract—For this study, we designed learning activities in which students applied newly acquired knowledge to solve meaningful daily life problems in their local community – a real, familiar, and relevant environment for students. For example, students learned about signs and rules in class and then applied this new knowledge to create their own rules for a location in their community (e.g., playground rules that tell visitors what is or is not allowed to do in a local playground) to make it more environmentally friendly. To facilitate this, we developed a mobile learning system equipped with a dictionary as well as textual annotation, recording, and sharing functions. This mobile learning system enables students to take pictures of objects, describe them verbally or in writing, and share their work with peers. Our goal was to study the effectiveness of learning activities supported by a mobile learning system on the cognitive learning process by examining the changes in students’ cognitive processes and the distribution of students who reach a certain level of cognition before and after learning. Fifty-seven junior high school students participated in the research, and their views of the mobile learning system and interest in continuing use were also explored. Students were divided into one control ðn ¼ 26Þ group and one experimental ðn ¼ 31Þ group. The control group completed learning activities using a traditional approach while the experimental group used a learning system installed in tablet PCs. The effectiveness of the mobile PC system on students’ cognitive processes was tested by comparing the control and experimental groups’ pre-test and post-test outcomes. Changes in students’ cognitive processes were measured by calculating the differences in student scores among three tasks. The distribution of students who reached a certain level of cognition was derived based on their learning performance. Students’ perceptions were evaluated using a questionnaire survey. The mobile learning system kept records of how students used it. Our results show that the experimental students significantly outperformed the control students on test items related to high cognitive levels. Students made clear cognitive progress from the second topic to the third one. Most students rated the learning system highly and want to use it in the future. Finally, the results show that creating text annotations is the best indicator of learning. Based on these results, we recommend applying appropriate learning activities supported by a mobile learning system to facilitate students’ cognitive processes when they are studying English as a foreign language in an authentic environment. Index Terms— Learning technologies, learning environments, tablet PCs, devices for learning Ç 1 INTRODUCTION A COGNITIVE process is defined as a mental process by which knowledge is acquired and understood through thinking, experience, and the senses. Anderson and Krathwohl [1] argued that a cognitive process is different in terms of its complexity, and, thus, can be categorized from simple to more sophisticated. For example, when learning, some of us only obtain, store, and memorize knowledge while others transform and use it outside of its original con- text [45]. Therefore, one important issue the research and teaching community should consider is how to ensure that students engage in more complex cognitive processes. According to [21], cognitive processes can be promoted from simple to complex if students learn and apply new knowledge in a familiar authentic environment because that is where the knowledge will be used later in real life. Authenticity emphasizes meaningful learning in contexts that involve real-world problems [4]. A familiar environ- ment involves relevant and predictable situations from students’ background as well as previous experiences [41]. A familiar authentic environment creates advantages related to comprehension and application of new knowledge. For example, existing background knowledge of a familiar authentic environment is activated when learning takes place; thus the information-processing load related to con- textual knowledge is reduced. Related literature suggests that students can be situated in an authentic environment and learn using mobile tech- nology [18], [36], [40], [44]. For example, mobile multimedia tools (e.g., cameras, text editors, voice recorders, etc.) enable students to observe and capture real objects for learning from daily-life situations. Several recent studies have looked at facilitating learning by using such approaches [8], [11], [15], [17], [30]. However, our literature review reveals two failings in the previous research on this topic. First, studies of mobile-assisted learning have not paid much attention to cognitive processes. Particularly, little is known about how to cross the gap between simple and complex cognitive levels in a mobile-assisted learning environment. Although  R. Shadiev is with the School of Education Science, Nanjing Normal Uni- versity, No. 122, Ninghai Road, Nanjing 210097, Jiangsu Province, China. E-mail: rustamsh@gmail.com.  Y.M. Huang is with the Department of Engineering Science, National Cheng Kung University, No. 1, University Road, Tainan 70101, Taiwan. E-mail: huang@mail.ncku.edu.tw.  W.Y. Hwang is with the Graduate Institute of Network Learning Technol- ogy, National Central University, No. 300, Jhongda Rd., Jhongli 32001, Taiwan. E-mail: wyhwang@cc.ncu.edu.tw.  T.Y. Liu is with Bei-Zheng Junior High School, No. 14, Ln. 2, Sec. 3, ZhiNan Rd., Taipei 11605, Taiwan. E-mail: sixfish1018@googlemail.com. Manuscript received 7 Dec. 2015; revised 19 May 2016; accepted 22 May 2016. Date of publication 22 June 2016; date of current version 16 June 2017. For information on obtaining reprints of this article, please send e-mail to: reprints@ieee.org, and reference the Digital Object Identifier below. Digital Object Identifier no. 10.1109/TLT.2016.2574356 168 IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, VOL. 10, NO. 2, APRIL-JUNE 2017 1939-1382 ß 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.