Abstract:

Based on a combination of motivations and personal representations, expectations influence engagement and performance in learning and achievement contexts. Research in this field shows the relevance of students’ academic expectations for their adjustment and success in higher education. In most cases, students show positive, and frequently very high expectations when they enter university. Higher levels of academic adaptation take place when these positive expectations are successfully balanced with the demands and challenges of the new academic context, contributing for students’ retention and academic success. In this paper we describe the expectations of first-year engineering students. Participants included 378 students (88,9% men; Mage=21,7 years; SD=6,78) of various engineering programs at a Portuguese Northern Polytechnic University Institute. Academic expectations for higher education were assessed with the Academic Perceptions Questionnaire (Expectations version; Almeida et al., 2012), which includes five dimensions of expectations: Training for employment/ career development, Quality of learning, Social pressure, Political involvement and citizenship, and Social interaction. In order to identify profiles of students, we conducted a k-means cluster analysis, specifying a solution of four clusters. The first cluster classifies students which present low expectations for political involvement and citizenship. The second cluster comprises students who report the highest levels of academic expectations in all the assessed dimensions. Students in the third cluster present low expectations for social interaction and social pressure. Finally, the fourth cluster comprises students with high expectations for the quality of learning and training for employment/ career development, and low expectations for social interaction. Differences were found between clusters, based on students’ ages (younger students vs. older, non-traditional students).

Keywords:

Students’ academic expectations, academic success, Students' adaptation, cluster analysis.