Practicing engineers are hired, retained, and rewarded for solving problems, so engineering students should learn how to solve workplace problems. Workplace engineering problems are substantively different from the kinds of problems that engineering students most often solve in the classroom; therefore, learning to solve classroom problems does not necessarily prepare engineering students to solve workplace problems. These qualitative studies of workplace engineering problems identify the attributes of workplace problems. Workplace problems are ill-structured and complex because they possess conflicting goals, multiple solution methods, non-engineering success standards, non-engineering constraints, unanticipated problems, distributed knowledge, collaborative activity systems, the importance of experience, and multiple forms of problem representation. Some implications for designing engineering curricula and experiences that better prepare students for solving workplace problems are considered.

Computers are increasingly widespread, influencing many aspects of our social and work lives, As we move into a technology-based society, it is important that classroom experiences with computers are made available for all students. The purpose of this study is to examine preservice teachers' attitudes towards computers. This study extends the technology acceptance model (TAM) framework, with subjective norm and facilitating conditions acting as external variables. Results shows that perceived usefulness, perceived ease of use and subjective norm were significant determinants of pre-service computer attitudes. Facilitating conditions did not influence computer attitude directly but through perceived ease of use. These findings demonstrate that social norm and facilitating conditions are potential variables that may be used to extend the TAM for research on computer attitudes.

This study assesses the pre-service teachers' self-reported future intentions to use technology in Singapore and Malaysia. A survey was employed to validate items from past research. Using the Technology Acceptance Model (TAM) as a research framework, 495 pre-service teachers from Singapore and Malaysia responded to an 11-item questionnaires containing four constructs: intention to use (ITU), attitude towards computer use (ATCU), perceived usefulness (PU), and perceived ease of use (PEU). Structural equation modelling (SEM) was employed as the main method of analysis in this study. A multi-group analysis of invariance was performed on the two samples. The results show that configural and metric invariance were fully supported while scalar and factor variance invariance were partially supported, suggesting that the 11-item measure of the TAM may be robust across cultures and that the factor loading pattern and factor loadings appeared to be equivalent across the cultures examined. While all the paths in the structural model were significant, the variance accounted for in the dependent variable (ITU) was much larger in the Malaysian sample relative to the Singaporean sample.

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Purpose -This paper aims to examine pre-service teachers' self-reported intention to use technology by employing the Theory of Planned Behavior (TPB) as the research framework. Design/methodology/approach -In total, 157 student teachers completed a survey questionnaire measuring their responses to four constructs in the TPB. These were administered at the beginning of the course in which technology was taught and used. Structural equation modeling (SEM) was used as the technique for data analysis. Findings -The results of this study showed that attitude toward usage and subjective norms were significant predictors of behavioral intention to use technology while perceived behavioral control was not. Overall, this study found that the three explanatory variables in the TPB explained about 40 percent of the variance in behavioral intention to use technology. Originality/value -This study contributes to the growing interests among researchers in using models to explain users' intention to use technology. While prior research have use the theory of planned in explaining variables of interest in psychology, this study attempts to test the explanatory ability of the TPB on the intention to use technology in an educational setting. By doing so, the paper hopes to obtain greater insights into the applicability of TPB to explain issues of educational interests.

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The aim of this study is to understand the relationship between metacognition and students' everyday problem solving. Specifically, we were interested to find out whether regulation of cognition and knowledge of cognition are related to everyday problem solving and whether students who perform better in the decision-making problem will better differentiate the various components of metacognition. Two hundred and fiftyfour fifth grade students completed a survey. We found evidence to suggest the existence of two major components of metacognition. Our results also suggest that at a higher level of decision-making, knowledge of cognition and regulation of cognition were differentiated in their use by participants.

Mobile learning technologies are spreading rapidly in educational institutions throughout the world. Although research findings concerning the efficacy of mobile technologies for improving student outcomes are generally promising, there are still significant gaps in the research literature, particularly data from direct observational studies. This empirical investigation focused on how students made use of tablet devices and digital pens for learning Chemistry in an undergraduate university course. Observational data in the form of videos and static images, as well as, interview responses, were the main sources of data collected for the study. Activity theory was employed as the guiding theoretical framework to analyse and interpret the data. Several themes emerged from the data analyses, including the affordances of digital pen technology for facilitating reflective thinking, flexibility, peer collaboration, emerging learning and focused learning. It was also found that the use of these mobile technologies was contextualized, dependent on individual differences, and had challenges, for example, there was limited synchronicity between the operational design of the mobile devices and natural human movement. One of the main implications of the research is that when higher education institutions consider the potential benefits and challenges associated with mobile technologies they should take account of the interactions that occur between components within a system including, students, technological devices, and emerging learning processes.