An application of the theory of reasoned action: Assessing success factors of engineering students

© 2016 TEMPUS Publications. Student attrition in engineering is of concern. This study investigated motivational factors necessary to succeed in engineering. The Theory of Reasoned Action (TRA) model was used to guide the suggested paths from learning strategy, interest, and intention to academic performance. Participants were 135 Malaysian and 132 Australian engineering undergraduates who had completed the Study Process Questionnaire (R-SPQ-2F) scale and the Learner Autonomy Profile (LAP-SF) scale. The correlation coefficient analysis showed strong interrelationships between learning strategy, interest and intention. The findings of the structural equation modelling (SEM) revealed unexpected but interesting findings between the two countries. Two different pathways were established for the Malaysian and Australian data suggesting that the TRA model is best suited to the Australian learning context. The findings of this study could help identify a suitable model for explaining success factors in engineering

Learning strategies as an enabler of study success

© 2017 Universiti Putra Malaysia Press. Engineering students enrol in engineering without a clear understanding of how they can achieve success in the field. The current study explores study strategies of engineering undergraduates across two geographical locations, Malaysia and Australia. Qualitative data were collected using semi-structured interviews, in which 16 final-year engineering undergraduates volunteered to participate. Data were analysed using a thematic coding approach and the NVivo software was used to assist with the coding process. The results suggested that engineering students at universities in both locations used very similar learning strategies to achieve different success outcomes such as to fulfil assessment criteria, to achieve a personal goal or success, to endure with challenges, to overcome challenges, to survive after failure and to keep persisting in the programme. Integrating knowledge, visualising engineering applications, optimising the use of learning materials and mastering engineering skills are examples of strategies that were frequently used by the students. The level of importance of each strategy is context dependent

Developing an instrument to measure the cognitive-affective-conative profile of engineering students

© 2017 IEEE. Learning strategies (cognition), emotion (affection) and conation are suggested as important elements of success for engineering students. Identifying student learning profile may help improve successful rate in engineering program. An instrument that can be used for reliably assessing the cognitive- affective-conative profile of students is needed. This paper report the development and initial testing of the questionnaire (CACQ). Quantitative procedures were used. The set of questionnaire was distributed to 207 final year engineering students after being reviewed by four experts. Each of the constructs reached a good reliability value. Strong and positive correlations were established between learning strategy, emotion, conation and achievement motivation measures. The strength of correlations between the constructs also provides an indicator to the unidimensionality of the constructs. This new questionnaire is a promising measure for assessing the cognitive, affective and conative profile of engineering students