Learning performance and cognitive load in mobile learning: Impact of interaction complexity

Abstract

In the increasing pervasiveness of today's digital society, mobile devices are changing the face of education. Students can interact with mobile devices in context-aware environment. This paper presents a mobile application based on expert system (Plant-E) for students to acquire knowledge about plant classification by answering decision-making questions. In order to study effectiveness of Plant-E and cognitive load of students who experience different kinds of interaction in learning process, another mobile application (Plant-G) only providing information pages of plants was developed. A quasi-experiment was conducted with three classes of 137 seventh graders. The three classes, Class A with 46 students using Plant-E in campus, Class B with 44 students using Plant-G in campus, and Class C with 47 students using Plant-G in a traditional classroom, constitute three groups with different interaction complexity. The research conducted pretest, posttest, and delayed test to evaluate learning performance of students in three classes and used a questionnaire to investigate their perceptions and attitudes towards proposed system. Results show that interaction complexity has an impact on students' learning performance and mental effort in mobile learning; the higher the interaction complexity is, the higher mental effort and the better learning performance in mobile learning will be.

AR Learning Environment Integrated with EIA Inquiry Model: Enhancing Scientific Literacy and Reducing Cognitive Load of Students

“…In this study, students obtained better learning achievement and higher cognitive load when they learned based on AR environments and traditional instructional model. Wang, et al [41] stated that the higher the interaction complexity is, the higher the mental effort and the better the learning performance in mobile learning will be. Since AR environments combine objects in real world and virtual world, students have more opportunities to interact with more factors during learning activity.…”

How Does Prior Knowledge Influence Learning Engagement? The Mediating Roles of Cognitive Load and Help-Seeking

“…The Cognitive Load Questionnaire was developed by Hwang et al (2013) based on the measures proposed by Paas et al (1994) and Sweller et al (1998). A Chinese version of the Cognitive Load Questionnaire been used in Chinese middle school classrooms (Wang et al, 2018). The Cognitive Load Questionnaire consists of five items for mental load and three items for mental effort.…”

Inquiry‐based mobile learning in secondary school science education: A systematic review

“…This explanation of cognitive load best fits the definition of the micro level (Vavoula et al, 2009). In a mobile context, users may be required to perform additional tasks (e.g., walking), and this could have an impact on the completion of the primary task (Harrison et al, 2013; Wang, Fang, & Miao, 2018). In this review, only one study [S25] paid attention to this evaluation aspect and indicated that using mobile technology while addressing an inquiry problem in an outdoor environment was challenging for secondary school students due to cognitive overload.…”