Mapping Learning and Game Mechanics for Serious Games Analysis in Engineering Education

In a world where students are increasing digitally tethered to powerful, ‘always on’ mobile devices, new models of engagement and approaches to teaching and learning are required from educators. Serious Games (SG) have proved to have instructional potential but there is still a lack of methodologies and tools not only for their design but also to support game analysis and assessment. This paper explores the use of SG to increase student engagement and retention. The development phase of the Circuit Warz game is presented to demonstrate how electronic engineering education can be radically reimagined to create immersive, highly engaging learning experiences that are problem-centered and pedagogically sound. The Learning Mechanics–Game Mechanics (LM-GM) framework for SG game analysis is introduced and its practical use in an educational game design scenario is shown as a case study.

Affect-Based Effects of Simulation Games on Learning

Empirical evidence has demonstrated the benefits of using simulation games in enhancing learning especially in terms of cognitive gains. This is to be expected as the dynamism and non-linearity of simulation games are more cognitively demanding. However, the other effects of simulation games, specifically in terms of learners’ emotions, have not been given much attention and are under-investigated. This study aims to demonstrate that simulation games stimulate positive emotions from learners that help to enhance learning. The study finds that the affect-based constructs of interest, engagement and appreciation are positively correlated to learning. A stepwise multiple regression analysis shows that a model involving interest and engagement are significantly associated with learning. The emotions of learners should be considered in the development of curriculum, and the delivery of learning and teaching as positive emotions enhances learning.

Job-demand for Learning, Job-related Learning and Need for Achievement

Individual learning is important, as it is both a precursor and an outcome of learning in organisations. Job-related learning is driven by external factors (e.g., the demands of the job) and internal factors (i.e., the personality of the individual). The study examined whether need for achievement moderates the relationship between job-demand for learning and job-related learning. Data were obtained from 153 full-time, white-collar employees from a range of industries. Hierarchical regression analysis using the product term revealed that need for achievement moderates the relationship between job-demand for learning and job-related learning. Specifically, although job-demand for learning is correlated positively to job-related learning for both the high and the low need for achievement groups, this correlation is stronger amongst the high group. The findings are discussed in terms of their implications for future research and practice.

Job-demand for Learning and Job-related Learning: the Mediating Effect of Job Performance Improvement Initiatives

This study examined whether job-performance-improvementinitiatives mediate the relationship between individuals’ job-demand for learning and job-related learning. Data were obtained from 115 full-time employees in a diverse range of occupations. A partial least squares analysis revealed that job-performance-improvement-initiatives mediate partially the effects of job-demand for learning on job-related learning. Several implications for future research and policy are drawn from the findings.