DESIGNING FOR THE SUBCONSCIOUS: A NEUROIS STUDY OF PRIMING AND IDEA GENERATION IN ELECTRONIC BRAINSTORMING

Thesis (Ph.D.) - Indiana University, Business, 2014There has been extensive research on electronic brainstorming (EBS) over the past two decades, yet little is known about how best to design technology to enhance overall team performance. This dissertation seeks to open a new door in EBS design: designing a system for the individual's subconscious. Before effective design interventions can be developed, the cognitive underpinnings of individual-level EBS interactions must be elucidated. These studies provide insight into the core of this issue by examining the neurophysiological correlates of the ideation process, specifically using electroencephalography (EEG), electromyography (EMG), and skin conductance to examine priming-induced changes in cognition and emotion during an EBS session. Furthermore, it extends prior research on the use of priming to enhance EBS performance, creating new design guidelines for EBS systems that are designed for the user's subconscious. The findings show that achievement priming changes cognition in areas of the brain related to creativity which correspond with increases in idea fluency and creativity. While the implications of this study will be directly applicable to design of EBS technology, future studies can examine the use of priming in other collaboration tools. There may also be implications for the design of other forms of technology. The use of NeuroIS to more fully understand information processing in teams can also enhance the collaboration literature, in that it can illuminate individual cognition limitations in team interactions and enhance our understanding of which aspects of team interactions have the biggest "bang for their buck" from a cognitive standpoint. These findings provide several avenues for future research

The effects of peer instruction through social learning environment towards students’ cognitive load and learning performance

The use of social media like Facebook as an educational tool has been reported to be able to promote learning and serve as a learning platform. However, Facebook also contributes to promote increased mental demand or Cognitive Load (CL). It is a challenge to learning due to the limitation of the working memory for information processing can have effects on learning performance. This situation has not been well emphasized by most instructors. Studies reported that Peer Instruction (PI) learning strategy has the potential to reduce CL while also improving learning performance but implementation of PI in social media is rather new. Thus, this study focuses on the development of a framework for best practices on the use of social media for education through enhancing learning performance and reducing CL using PI. A two-phase study was implemented for this purpose where Phase 1 involved a survey to 226 students at a Malaysian public university to identify students’ experience of CL during learning on social media. Findings confirm that students experience distractions during learning on Facebook with third party activities identified as the most distracting. Phase 2 was a mixed method study design involving a purposeful sample of 12 postgraduate students who underwent learning with Facebook. This study investigates the effect of PI for enhancing learning performance and reducing CL. Wilcoxon signed-rank test showed a significant reduction in students CL (p < 0.05) with a corresponding significant improvement in learning performance (p < 0.05) when PI was employed as an instructional strategy. A qualitative study involved collection of student reflections, participation data in whole class discussions and data from a focus group session were analysed using NVivo 10 CAQDAS software to aid the coding process. Findings showed CL sources on learning with social media include mental, time and affective demands. PI was found to bring about the reduction of CL through the following elements; ConcepTests, voting, peer discussion and mediated pre-class reading. A modified framework of PI implementation was developed that incorporates online mode, whole-class peer discussions in pre-class and post-class settings, pre-class ConcepTests, voting and mediated pre-class reading as means to reduce cognitive load. It highlights how the advantages of social media can be optimized. Findings from the study have implications for curriculum and instructional design and how it can support learning by reducing CL through PI

An ambient agent model for reading companion robot

Reading is essentially a problem-solving task. Based on what is read, like problem solving, it requires effort, planning, self-monitoring, strategy selection, and reflection. Also, as readers are trying to solve difficult problems, reading materials become more complex, thus demands more effort and challenges cognition. To address this issue, companion robots can be deployed to assist readers in solving difficult reading tasks by making reading process more enjoyable and meaningful. These robots require an ambient agent model, monitoring of a reader’s cognitive demand as it could consist of more complex tasks and dynamic interactions between human and environment. Current cognitive load models are not developed in a form to have reasoning qualities and not integrated into companion robots. Thus, this study has been conducted to develop an ambient agent model of cognitive load and reading performance to be integrated into a reading companion robot. The research activities were based on Design Science Research Process, Agent-Based Modelling, and Ambient Agent Framework. The proposed model was evaluated through a series of verification and validation approaches. The verification process includes equilibria evaluation and automated trace analysis approaches to ensure the model exhibits realistic behaviours and in accordance to related empirical data and literature. On the other hand, validation process that involved human experiment proved that a reading companion robot was able to reduce cognitive load during demanding reading tasks. Moreover, experiments results indicated that the integration of an ambient agent model into a reading companion robot enabled the robot to be perceived as a social, intelligent, useful, and motivational digital side-kick. The study contribution makes it feasible for new endeavours that aim at designing ambient applications based on human’s physical and cognitive process as an ambient agent model of cognitive load and reading performance was developed. Furthermore, it also helps in designing more realistic reading companion robots in the future