22 SES 08 C, Doctoral Students and their Education
Doctoral studies can be seen as being at the pinnacle of education, gathering high achievers who have gone through an important selection process to reach it. However, despite former bright educational pathways, a large number of doctoral students will not complete their degree (Jairam & Kahl, 2012). The high attrition rate (30 to 50%) of doctoral students has been largely depicted as a worldwide major educational concern (Mason, 2012; Peltonen, Vekkaila, Rautio, Haverinen & Pyhältö, 2017).
A potential explanation of attrition among Phd students could lie in the motivational layer of doctoral experience. As it was largely demonstrated with high school students (Hayenga & Corpus, 2010) and college students (Allen, Robbins, Casillas & Oh, 2008), motivation is crucial to maintain a high level of tasks engagement and persistence. Without appropriate motivation, even the brightest students can feel compelled to give up. Existing research substains this assumption and highlighted that motivation is a critical component of doctoral completion (Lovitts, 2008; Mason, 2012). However, in depth investigations of the impact of motivation on doctoral completion is still lacking: (1) studies addressing the effect of motivation on doctoral completion are still scarce and mainly qualitative (London et al., 2014), (2) self-determination has barely been considered (Mason, 2012) and (3) motivational profiles have been largely neglected (Hayenga & Corpus, 2010). Further analysis of the actual effect of motivational variables on the doctoral experience is therefore needed (Mason, 2012) and will be endorsed by this study.
Motivation can be defined as “the inner energy sources that pushes people toward desirable outcomes” (Boekaerts, Van Nuland & Martens, 2010; p. 535). Self-determination Theory (Deci & Ryan, 2000) stands out as one of the major framework for understanding motivational process in educational context. This theory distinguished three fundamental psychological needs that will entail human behaviours, goals, and well-being: competence, autonomy, and relatedness. The main premise of this theory is that experiences of competence, autonomy and relatedness are paramount for academic engagement, perseverance and achievement.
The need for competence taps the importance of experiencing oneself as efficient within the academic context. The need for autonomy refers to the students’ need for self-determined behavior initiated according to personal desires rather than being controlled by others. The need for relatedness encompasses the perception of being connected, accepted, and valued by the others. Several studies emphasized the importance of the fulfillment of these needs, highlighting links with engagement, intention to persist, performance and actual retention in higher education (Hayenga & Corpus, 2010; Wright, Jenkins-Guarnieri & Murdock, 2012). Yet, despite the importance of each specific need, some authors argued that all three needs must be met together to effectively produce positive outcomes (Hayenga & Corpus, 2010; Mason, 2012).
To overcome the current lack of investigation of motivational processes among doctoral students, the purpose of this study is twofold. First, it aims at identifying and assessing the naturally occurring combinations of the satisfaction of the three fundamental needs of competence, autonomy, and relatedness among doctoral students. Such analysis will allow for a clearer depiction of the different motivational profiles among doctoral students. Second, the emerging combinations of needs were related to several important factors of the doctoral experience exerted from the literature, e.g., intention to persist, appropriation of the doctoral project, perceived progress and completion (Devos et al., 2017; Peltonen et al., 2017).
Based on a longitudinal sample of 945 doctoral students from two universities, cluster analyses were performed. Following the case made by several authors (Phinney et al., 2005), k-means cluster analyses were run with regard to the three fundamental needs in order to identify groups of students most highly similar within groups and most highly dissimilar between groups. To ensure our selection, we assessed the distribution of students in each cluster and the adjustment of the final cluster solution to the needs variability using MANOVA. Furthermore, a cross-validation procedure was set up that assess the replication of the cluster solution. Once the final cluster solution was set up, analyses of variance (ANOVA) were performed to identify the significant differences across the profiles on the doctoral outcomes. Finally, multi-group structural equation modeling was performed in order to analyze student’s variation on the outcomes variables according to their cluster. The data were gathered through four waves of self-reported questionnaire ranging over a period of one year and a half. At Time 1 (December), we measured the socio-demographic variables. At Time 2 (June, 6 months after T1), we measured the three fundamental needs (i.e. support from supervisor, doctoral peers and relatives).. At Time 3 (December, 1 year after T1), we measured students’ perceived progress, appropriation of the doctoral project, and intention to persist. At time 4 (June, 1 year and a half after time 1) doctoral completion was retrieved from administrative records.
Regarding cluster analysis, we could hypothesize that several complex profiles would emerge. According to the high connection between the needs (Mason, 2012), we could postulate that these variables would evolve together (cumulative hypothesis) and expected profiles respectively characterized by low, average and high scores on the three needs. Yet, according to the different sources of the needs (Appleton, Christenson & Furlong, 2008), we could also expect subgroups of students respectively characterised by a specific weakness on one needs (idiosyncratic hypothesis). The results partially confirmed these two assumptions. Statistical and theoretical criteria led to retain the five cluster solution which revealed meaningful profiles highlighting specific patterns of factors. In accordance with the cumulative hypothesis two patterns emerged with respectively low scores and high scores on the three needs. These patterns were respectively labeled Need-deprived profile and self-determined profile. As expected by the idiosyncratic hypothesis, three profiles were characterized by specific weaknesses on one of the three needs. These profiles were respectively labeled: self-doubting profile (low competence), controlled profile (Low autonomy) and isolated profile (Low relatedness). Preliminary Anovas provided meaningful results. As expected from previous studies (Hayenga & Corpus, 2010; Mason, 2012), the self-determined profile (whom all three needs are fulfilled) demonstrated the highest level on the different outcomes. Conversely, the deprived profile was the lowest. Moreover, differences among profiles characterized by specific weaknesses were found. Self-doubting profile demonstrated the lowest levels of doctoral perceived progress out of the three specific profiles. Moreover, controlled profile showed particularly low levels on intention to persist and appropriation of the project. Further analyses (performed in the next two months) will specify and qualify these first results. These results will be discussed during the paper presentation.
•Allen, J., Robbins, S., Casillas, A., & Oh, I.-S. (2008). Third-year College Retention and Transfer: Effects of Academic Performance, Motivation, and Social Connectedness. Research in Higher Education, 49(7), 647-664. doi:10.1007/s11162-008-9098-3 •Appleton, J. J., Christenson, S. L., & Furlong, M. J. (2008). Student engagement with school: Critical conceptual and methodological issues of the construct Psychology in the Schools (Vol. 45, pp. 369-386): John Wiley & Sons, Inc. •Boekaerts, M., Van Nuland, H. J. C., & Martens, R. L. (2010). Perspectives on motivation: What mechanisms energise students’ behaviour in the classroom. Handbook of educational psychology, 535-569. •Deci, E.-L., & Ryan, R.-M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268. •Devos, C., et al. (2017). Doctoral students’ experiences leading to completion or attrition: a matter of sense, progress and distress. European journal of psychology of education, 32(1), 61-77. •Hayenga, A. O., & Corpus, J. H. (2010). Profiles of intrinsic and extrinsic motivations: A person-centered approach to motivation and achievement in middle school. Motivation and Emotion, 34(4), 371-383. doi:10.1007/s11031-010-9181-x •Jairam, D., & Kahl Jr, D. H. (2012). Navigating the doctoral experience: The role of social support in successful degree completion. International Journal of Doctoral Studies, 7, 311-329. •London, J., Cox, M. F., Ahn, B., Branch, S., Zephirin, T., Torres-Ayala, A., & Zhu, J. (2014). Motivations for pursuing an engineering PhD and perceptions of its added value: A US-based study. International Journal of Doctoral Studies, 9, 205-227. •Lovitts, B. E. (2008). The transition to independent research: Who makes it, who doesn't, and why. The Journal of Higher Education, 79(3), 296-325. •Mason, M. M. (2012). Motivation, satisfaction, and innate psychological needs. International Journal of Doctoral Studies, 7(1), 259-277. •Peltonen, J. A., Vekkaila, J., Rautio, P., Haverinen, K., & Pyhältö, K. (2017). Doctoral Students’ Social Support Profiles and Their Relationship to Burnout, Drop-Out Intentions, and Time to Candidacy. International Journal of Doctoral Studies, 12, 157-173. •Phinney, J. S., Dennis, J. M., & Gutierrez, D. M. (2005). College Orientation Profiles of Latino Students From Low Socioeconomic Backgrounds: A Cluster Analytic Approach. Hispanic Journal of Behavioral Sciences, 27(4), 387-408. doi:10.1177/0739986305280692 •Wright, S. L., Jenkins-Guarnieri, M. A., & Murdock, J. L. (2012). Career Development Among First-Year College Students: College Self-Efficacy, Student Persistence, and Academic Success Journal of Career Development, 0(0), 1-19.
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