The Impact of Work-Integrated Learning and Learning Strategies on Engineering Students’ Learning Outcomes in Thailand: A Multiple Mediation Model of Learning Experiences and Psychological Factors

Abstract

Learning outcomes (LOs) provide an essential foundation for evaluating the effectiveness of higher education institutions (HEIs). LOs have been accepted as criteria for accrediting academic programs; however, little is known about why students vary in their desired outcomes and how experiences in the workplace and learning strategies have different impacts on LOs. Based on social cognitive career theory (SCCT), this study investigated the relationships among work-integrated learning (WIL), learning strategies, institutional and goal commitments, engineering skill self-efficacy, engineering career outcome expectations, lifelong learning skills (LLLs), achievement goal orientation, and LOs. The participant pool consisted of 1,316 undergraduate engineering students from 11 HEIs in Thailand. Hypotheses regarding the causal relationships, including the direct and indirect effects, were examined by using structural equation modeling (SEM). Both the measurement and structural equation models showed a good fit to the data. The results of the SEM indicated that achievement goal orientation, LLLs, and engineering skill selfefficacy had significant positive direct effects on LOs. Learning strategies had a strong direct effect on LLLs and institutional and goal commitments. The practice of WIL in the workplace was an important factor in building engineering skill self-efficacy and LLLs. The mediation analysis indicated that learning experience (i.e., institutional and goal commitments) and psychological factors played important roles in the relationship between learning strategies and LOs. This study confirmed and expanded the SCCT research. Finally, theoretical and practical implications for LO development were identified based on the results.INDEX TERMS Work integrated learning, learning outcomes, learning strategies, career outcome expectations, lifelong learning skills, engineering skill self-efficacy.

Relationships between ICT competencies related to work, self-esteem, and self-regulated learning with engineering competencies

“…The average variance extracted (AVE) was between 0.18 and 0.38, which was lower than the standard 0.5 recommended by Hair, Black, Babin and Anderson [ 104 ] (see Table 3 ). However, when AVE is less than 0.5 but CR is greater than 0.6, the construct’s convergent validity is still sufficient, according to Fornell and Larcker [ 118 ] and Khampirat [ 119 ]. We should accept the AVE of these constructs because the CR exceeded the recommended standard.…”

Psychometric Properties and a Multiple Indicators Multiple Cause Model of the Career Aspiration Scale with College Students of Rural Thailand

“…In this respect, the use of the CAS-R can help measure motivations and ambitions at different stages of student life. Third, in the current context, in which COVID-19 affects student career development anxiety [89], self-training to have work-ready expertise and skills is essential [7,89,90], and the CAS-R can be a valuable option to assess one's aspirations. Students could obtain information to monitor their expectations, increase career aspirations, and improve essential competencies for their future jobs.…”

The Impact of Achievement Goal Orientation, Learning Strategies, and Digital Skill on Engineering Skill Self-Efficacy in Thailand

“…Achievement goal orientation also encourages individuals to specify criteria for working behavior and put in the effort to perform better to achieve performance goals. Those who have achievement goal orientation will be more successful in work than others who do not [26]. The concept of achievement goal orientation also divides the characteristics of goal orientation into various kinds.…”

“…The results provide better understanding of the importance of structural factors such as achievement goal orientation, learning strategies, and digital skills to explain the ENSE of students at higher education levels. The obtained information can benefit educational institutions, students, policy makers, and employers in designing learning activities, which helps support the ENSE of students, increase opportunities for employment, and promote career prosperity [26].…”