Ellián Tuero

Predicting approach to homework in primary school students

BACKGROUND The goal of this research was to study the weight of student variables related to homework (intrinsic homework motivation, perceived homework instrumentality, homework attitude, time spent on homework, and homework time management) and context (teacher feedback on homework and parental homework support) in the prediction of approaches to homework. METHOD 535 students of the last three courses of primary education participated in the study. Data were analyzed with hierarchical regression models and path analysis. RESULTS The results obtained suggest that students’ homework engagement (high or low) is related to students´ level of intrinsic motivation and positive attitude towards homework. Furthermore, it was also observed that students who manage their homework time well (and not necessarily those who spend more time) are more likely to show the deepest approach to homework. CONCLUSIONS Parental support and teacher feedback on homework affect student homework engagement through their effect on the levels of intrinsic homework motivation (directly), and on homework attitude, homework time management, and perceived homework instrumentality (indirectly). Data also indicated a strong and significant relationship between parental and teacher involvement.

Comparison of Personal, Social and Academic Variables Related to University Drop-out and Persistence

Dropping out of university has serious consequences not only for the student who drops out but also for the institution and society as a whole. Although this phenomenon has been widely studied, there is a need for broader knowledge of the context in which it occurs. Yet research on the subject often focuses on variables that, although they affect drop-out rates, lie beyond a university’s control. This makes it hard to come up with effective preventive measures. That is why a northern Spanish university has undertaken a ex post facto holistic research study on 1,311 freshmen (2008/9, 2009/10, and 2010/11 cohorts). The study falls within the framework of the ALFA-GUIA European Project and focuses on those drop-out factors where there is scope for taking remedial measures. This research explored the possible relationship of degree drop-out and different categories of variables: variables related to the educational stage prior to university entry (path to entry university and main reason for degree choice), variables related to integration and coexistence at university (social integration, academic integration, relationships with teachers/peers and value of the living environment) financial status and performance during university studies (in terms of compliance with the program, time devoted to study, use of study techniques and class attendance). Descriptive, correlational and variance analyses were conducted to discover which of these variables really distinguish those students who drop-out from their peers who complete their studies. Results highlight the influence of vocation as main reason for degree choice, path to university entry, financial independency, social and academic adaptation, time devoted to study, use of study techniques and program compliance in the studied phenomenon.

Corrigendum: Comparison of Personal, Social and Academic Variables Related to University Drop-out and Persistence

[This corrects the article on p. 1610 in vol. 7, PMID: 27803684.].

Freshmen Program Withdrawal: Types and Recommendations

University program dropout is a problem that has important consequences not only for the student that leaves but also for the institution in which the withdrawal occurs. Therefore, higher education institutions must study the problem in greater depth to establish appropriate prevention measures in the future. However, most research papers currently focus primarily on the characteristics of students who leave university, rather than on those who choose to pursue alternative courses of study and therefore fail to take into account the different kinds of abandonment. The aim of this paper is to identify the different types of dropout to define their characteristics and propose some recommendations. Thus, an ex post facto study was carried out on a sample of 1,311 freshmen from a university in the north of Spain using data gathered using an ad-hoc designed questionnaire, applied by telephone or an online survey, and completed with data available in the university data warehouse. A descriptive analysis was performed to characterize the sample and identify five different groups, including 1. Students persisting in their initiated degree 2. Students who change of program (within the same university) 3. Students transferring to a different university 4. Students enrolling in non-higher-education studies 5. Students that quit studying. Also, data mining techniques (decision trees) were applied to classify the cases and generate predictive models to aid in the design of differentiated intervention strategies for each of the corresponding groups.