Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 10th May 2025, 12:20:07 EEST

 
 
Session Overview
Session
22 SES 07 B: Students Well Being and Retention
Time:
Wednesday, 28/Aug/2024:
15:45 - 17:15

Session Chair: Chris Kubiak
Location: Room 202 in ΘΕE 01 (Faculty of Pure & Applied Sciences [FST01]) [Floor 2]

Cap: 40

Paper Session

Show help for 'Increase or decrease the abstract text size'
Presentations
22. Research in Higher Education
Paper

Students Engagement in High School: a way to improve well-being

Maria Edite De Oliveira, Carolina Carvalho

Universidade de Lisboa, Portugal

Presenting Author: De Oliveira, Maria Edite; Carvalho, Carolina

Research on school engagement has a long tradition in understanding students' feelings of connection with their academic surroundings, values surrounding educational goals (Orthner, Jones-Sanpei, Akos & Rose, 2013), and participation in academic success (Orthner et al., 2013). High engagement with school can be linked to students' overall success and is of fundamental importance for understanding positive youth development (Li & Lerner, 2011). Engagement with school is characterized by several components, including students' sense of belonging, identification with school, and a sense of relatedness, whereas academic engagement refers to time on task, earned credits, and homework completion (Salmela-Aro & Upadyaya, 2013). The affective or emotional component refers to students' enjoyment and interest in school-related challenges, positive and negative reactions to teachers and classmates, and willingness to do one's schoolwork. The cognitive component, in turn, refers to students’ investment in schoolwork, as well as their thoughtfulness and willingness to learn and exert the necessary effort while studying. Finally, the behavioral component is described in terms of involvement, being present at school, and complying with school discipline rules (Salmela-Aro & Upadyaya, 2013). The concepts of three school engagement dimensions also describe students’ participation, commitment, positive and negative emotions, investment, and willingness to exert effort in one’s schoolwork, all of which refer to patterns rather than causes behind one’s actions. Thus, school engagement can be described as a multidimensional, developing, and malleable construct, including students’ (Carter, Reschly, Lovelace, Appleton & Thompson, 2012).

Normally, girls often exhibit higher levels of behavioral, emotional, and overall school engagement than boys (Li, Lynch, Kalvin, Lin & Lerner, 2011; Salmela-Aro & Upadyaya, 2012; Wang & Eccles, 2012), which may be related to girls’ tendency to perform better at school. Students from lower-income families are more likely than girls and higher socioeconomic status students to experience rapid decreases and follow unstable school engagement trajectories, often leading to school dropouts (Li & Lerner, 2011).

Experiences of belonging, positive relationships, autonomy, and competence are essential to psychological well-being; they provide the psychological “nutriments” or “resources” that sustain and enhance autonomous motivation and the engagement, persistence, and effort that flow from it. Moreover, if one or more of these nutriments is thwarted or denied, we quickly experience negative impacts on well-being, performance, and motivation (Dotterer & Lowe, 2012). Student mental well-being will be supported when teaching and learning practices actively engage students' intrinsic interests and communicate the importance and value of the knowledge and skills being developed. In this sense, students that are engaged in their classes and their universities express more good feelings, good relationships, and accomplishment, and these elements are essential for improving well-being.

In this study, we sought to explore the relationship between the involvement of 1st-year students in the university according to age and gender. Since we have students attending both day and night classes, we decided to establish age categories between 19-23 and more than 23. The research hypotheses to be evaluated are the following: Q1: students’ school engagement in the 1st year varies according to age. Q2: students’ school engagement in the 1st year varies according to gender (male/female). One hundred university students attending the 1st year participated in this study. Participants have a mean age between 19 and 57 years old and a mean of 23.9 (SD: 6.6).


Methodology, Methods, Research Instruments or Sources Used
In the present study, participants are students in the 1st cycle of undergraduate studies in the area of social sciences at a university in Lisbon, who gave their informed consent to participate in the study. One hundred surveys were answered, of which 70 were female and 30 were male, with the students' ages varying between 19 and 57 years old. In the present study, the Student Involvement Scale at the University was used: A QuadriDimensional Scale (EAE-E4D) constructed by Veiga (2013) and validated in a sample with 685 students from the 6th, 7th, 9th, and 10th years of schooling from various regions of Portugal. This scale contains 20 items with a Likert-type response, ranging from 1 (total disagreement) to 6 (total agreement). Each of the dimensions of involvement is assessed using a set of five items. For example, some items stand out in each of the four dimensions: cognitive (e.g., "When I am Reading, I try to understand the meaning of what the author wants to convey"); affectively (e.g., “My school is a place where I make friends easily”); behavioral (e.g., “I'm distracted in class”) and agentive (e.g., “During classes, I intervene to express my opinions”). For the different dimensions, the scale's internal consistency values (Cronbach's Alpha) varied between the maximum value of .87 for the agentive dimension and the minimum value of .69 for the behavioral dimension (Veiga, 2013). In the present study, the Covas scale (2017) was selected, as this scale encompasses four dimensions of involvement and is revised by the author for higher education, whereas the Veiga scale (2013) was validated for compulsory education. The research respected fundamental ethical principles with the protection of participants, their informed consent, confidentiality, privacy, and protection of data collection. Thus, participants were informed by researchers who explained the objectives of the investigation, the voluntary nature of participation, ensuring confidentiality, privacy, and anonymity of responses. The instrument was administered in the classroom and subject to the same conditions for two 1st-year classes of social and human sciences at a University of Lisbon. The collected data were directly exported to SPSS statistical analysis software database, version 23. In terms of statistical procedures used, descriptive statistical analysis was carried out for the general characterization of the sample; an inferential analysis was carried out to understand the homogeneity of the variables, and then a correlational analysis was carried out between variables and by dimension.
Conclusions, Expected Outcomes or Findings
Firstly, the results on the characterization of students' school involvement in the study with a minimum age of 19 and a maximum of 57; the average age was 23.9 years (SD: 6.6). Regarding the four dimensions of the scale, we found that the behavioral scale had the best average, 24.7, and the agentive scale had the worst average, 13.1 (SD: 3-8 and 5.8, respectively). In the first group (19-22 years old), there were very similar averages on the cognitive and affective scales (19.3 and 19.8), and on the behavioral scale, we obtained a higher average than the previous two (24.0) with the scale agency (12.0). We can conclude that in this age group, there are very adjusted behaviors towards study involvement, with cognitive and affective involvement having lower values. In terms of agentive involvement, this presents a very low value, indicating that there is no proactivity in the appropriation and integration of learning. In the second group (23-57 years old), the average on the four scales is slightly higher than the previous group, however, with the same pattern, the behavioral scale presenting the highest average value (25.6) and the average values of the cognition and affective scales with very similar values (20 and 20.6), respectively. Regarding sex, we found that in the group under 23 years old, 52 girls and 9 boys participated. It can be seen that the behavioral scale continues to have higher averages than other scales. In the group over 23 years old, the behavioral scale and the agency scale stand out with lower values compared to others.


References
Carter, C. P., Reschly, A. L., Lovelace, M. D., Appleton, J. J., & Thompson, D. (2012). Measuring student engagement among elementary students: Pilot of the student engagement instrument: Elementary version. School Psychology Quarterly, 27, 61–73. doi: 10.1037/a0029229
Dotterer, A. M., & Lowe, K. (2012). Classroom context, school engagement, and academic achievement in early adolescence. Journal of Youth and Adolescence, 40, 1649–1660. doi: 10.1007/s10964-011-9647-5
Lewis, A. D., Huebner, E. S., Malone, P. S., & Valois, R. F. (2011). Life satisfaction and student engagement in adolescents. Journal of Youth and Adolescence, 40, 249–262. doi: 10.1007/s10964-010-9517-6
Li, Y., & Lerner, R. M. (2011). Trajectories of school engagement during adolescence: Implications for grades, depression, delinquency, and substance use. Developmental Psychology, 47, 233–247. doi: 10.1037/a0021307
Li, Y., & Lerner, R. M. (2011). Trajectories of school engagement during adolescence: Implications for grades, depression, delinquency, and substance use. Developmental Psychology, 47, 233–247. doi: 10.1037/a0021307
Li, Y., Lerner, J. V., & Lerner, R. M. (2010). Personal and ecological assests and academic competence in early adolescence: The mediating role of school engagement. Journal of Youth and Adolescence, 39, 801–815. doi: 10.1007/s10964-010-9535-4
Orthner, D. K., Jones-Sanpei, H., Akos, P., & Rose, R. A. (2013). Improving middle school student engagement through career-relevant instruction in the core curriculum. The Journal of Educational Research, 106, 27–38. doi: 10.1080/00220671.2012.658454
Park, S., Holloway, S. D., Arendtsz, A., Bempechat, J., & Li, J. (2012). What makes students engaged in learning? A timeuse study of within- and between-individual predictors of emotional engagement in low-performing high schools. Journal of Youth and Adolescence, 41, 390–401. doi: 10.1007/s10964-011-9738-3
Salmela-Aro, K., & Upadyaya, K. (2013). Demands-resources model of engagement, burn out, and later adaptation in the school context Manuscript submitted for publication
Wang, M.-T., & Eccles, J. S. (2012). Social support matters: Longitudinal effects of social support on three dimensions of school engagement from middle to high school. Child Development, 83, 877–895. doi: 10.1111/j.1467-8624. 2012.01745.x


22. Research in Higher Education
Paper

Calling it Quits: a Longitudinal Study of Factors Associated with Dropout among Doctoral Students.

Anaïs Glorieux, Bram Spruyt, Joeri Minnen, Theun Pieter van Tienoven

Vrije Universiteit Brussel, Belgium

Presenting Author: Glorieux, Anaïs

It is in universities’ interest to have high numbers of thriving and successful PhD candidates. PhD students are an essential part of the research system, as Larivière (2012) showed that one-third of the research output at universities was produced by PhD students. Moreover, the unsuccessful completion of a PhD trajectory goes hand in hand with major financial, societal and psychological costs (Allan and Dory 2001; Golde 2005).

Aggregated across Europe, about 34% of all PhD students do not obtain their PhD degree within six years (Hasgall, Saenen, and Borrell-Damian 2019). In Australian, British, Canadian, and American universities, average dropout rates range between 30% and 50%, depending on the discipline (Bowen and Rudenstine 2014; Lovitts 2002; Golde 2005; Council of Graduate Schools 2008).

the PhD track is very different from other phases of education and brings along its specific challenges. A substantial group of PhD students works alone on their project under the supervision of one or more supervisors. Working collaboratively with peers is not always part of the PhD trajectory, which can sometimes make it a lonely process and renders the role of the supervisor all the more important (Cantor 2020). Additionally, the academic environment in which PhD students work is characterized by ever-increasing job demands and competition, due to among other things a growing number of undergraduate students who increasingly fall under the responsibility of PhD students, an increasing pressure to get research funding and publish, and a growing demand to be involved in other activities next to research (Gill 2014). Both the high dependency on the supervisor and the demanding academic environment might incentivise PhD students to quit.

Indeed, research found that factors related to supervision, the project itself and psychosocial factors are associated with the intention to quit the PhD (van Rooij, Fokkens-Bruinsma, and Jansen 2021). However, turnover intention does not always reliably predict actual turnover, nor are the variables explaining turnover intention necessarily the same as those explaining actual turnover (Cohen, Blake, and Goodman 2016). Therefore, we add to this line of work by studying how the received support of the supervisor, the experienced time pressure during the project, and the amount of passion one has for research can predict actual dropout. Contrary to previous studies – that tend to focus solely on administrative data or survey data – we combine administrative data on actual dropout with survey data on the experiences of the doctoral trajectory (n=589).

In this study, special attention is paid to the heterogeneity within the group of PhD students. Previous research does suggest that dropout rates between disciplines differ (Golde 1994; Wright and Cochrane 2000), yet deeper knowledge on the mechanisms behind this is lacking. The aim of this study, then, is to investigate whether certain characteristics of PhD students and certain experiences of the PhD trajectory are associated with dropout, and how the importance of these variables varies between scientific disciplines. These insights will enable university policymakers to develop targeted measures to reduce dropout. Specifically, the two research questions for this article are: “to what extent do support, time pressure and passion for research predict dropout?” and “does their potential predictive power vary across scientific disciplines?”.


Methodology, Methods, Research Instruments or Sources Used
To answer our research questions, we rely on longitudinal data from the VUB PhD Survey as well as administrative data of PhD students of the Vrije Universiteit Brussel (VUB). The VUB PhD Survey is organized on an annual basis and contains information on the subjective experiences of PhD students. The response rates for the waves vary between 42% and 49%.
The data of the VUB PhD survey were matched with administrative information on the current administrative enrolment status of PhD students: (1) successfully completed the PhD programme, (2) still active in the programme, or (3) dropped out of the programme.
For this paper, the used data was limited to the VUB PhD Survey waves from 2018 to 2021 and restrict the sample to PhD students who were in their first year of enrolment when completing the survey (n=589).
The combination of administrative data on the enrolment status with survey data on the subjective experiences of PhD students during their first year of enrolment enable us to investigate the effects of subjective indicators at moment t on moment t+1, and see whether they can predict dropout. Moreover, the university-wide data enable us to study differences within the heterogenous group of PhD students, by focusing on a group of PhD students (1) from various disciplines who (2) work under different contracts.
The dependent variable is a dummy-coded variable that indicates whether a PhD student dropped out. The independent variables are “experienced time pressure”, “satisfaction with supervisor support”, “passion for research”. Control variables were gender, nationality (Belgian or foreign), doctoral school (as a proxy for discipline) and the type of contract (teaching assistant, project funding, personal mandate, self-financed or other).
We used a two-step analysis to answer our research questions. Firstly, we performed a logistic regression analysis predicting dropout. Model 1 included background characteristics only (gender, nationality, doctoral school, and type of contract). In separate models, we successively combined the background characteristics with the following predictor variables:  the experienced support of the supervisor during the first year (model 2), the experienced time pressure during the first year (model 3), and passion of PhD students for their research in the first year (model 4). The fifth and final model included all variables.
Secondly, we stratified the final model by doctoral schools. We tested whether the effect parameters varied significantly between disciplines using calculations suggested by Paternoster and colleagues (1998).

Conclusions, Expected Outcomes or Findings
Results show that supervisor support is negatively related to dropout, and that this is especially important for PhD students in the human sciences. Time pressure is positively related to dropout. When stratified by scientific discipline, this effect was only significant for PhD students in human sciences and in the life sciences and medicine. Passion for research showed a negative association with dropout. Stratification by discipline showed that this effect was only found among PhD students in natural sciences and engineering. Furthermore, teaching assistants showed higher dropout rates, and female PhD students in human sciences and life sciences and medicine were less likely to drop out.
The findings highlight the need for universities to be aware of the diversity of PhD students when formulating support policies for PhD students. These policies could include facilitating supervisors to support academic integration of first-year PhD students and create better job resources; monitoring the implementation of research plans and the balance between research and teaching or clinical tasks to reduce experience time pressure; or facilitating state-of-the art research infrastructure to keep PhD students passionate about their research. Finally, special attention should be paid to the needs of teaching assistants, specifically to those in the human sciences, because even after taking supervisor support, time pressure and passion for research into account, they are still more likely to drop out.

References
Allan, Peter, and John Dory. 2001. “Understanding doctoral program attrition: An empirical study.” Faculty working papers, 17.
Bowen, William G., and Neil L. Rudenstine. 2014. In pursuit of the PhD. Princeton, NJ: Princeton University Press.
Cantor, Geoffrey. 2020. “The loneliness of the long-distance (PhD) researcher.” Psychodynamic Practice, 26(1): 56-67.
Cohen, Galia, Robert S. Blake, and Dough Goodman, D. 2016. “Does turnover intention matter? Evaluating the usefulness of turnover intention rate as a predictor of actual turnover rate.” Review of Public Personnel Administration, 36(3): 240-263.
Council of Graduate Schools. 2008. Ph.D. completion and attrition: analysis of baseline demographic data from the Ph.D. Completion Project. Washington D.C.: Council of Graduate Schools.
Gill, Rosalind. 2014. “Academics, Cultural Workers and Critical Labour Studies.” Journal of Cultural Economy, 7(1): 12–30.
Golde, Chris M. 1994. “Student descriptions of the doctoral student attrition process.” Paper presented at the Annual Meeting of the Association for the Study of Higher Education, Tucson, AZ.
Golde, Chris M. 2005. “The role of the department and discipline in doctoral student attrition: Lessons from four departments.” The Journal of Higher Education, 76(6): 669-700.
Hasgall, Alexander, Bregt Saenen, and Lidia Borrell-Damian. 2019. Doctoral Education in Europe Today: Approaches and Institutional Structures.  European University Association.
Larivière, Vincent. 2012. “On the shoulders of students? The contribution of PhD students to the advancement of knowledge.” Scientometrics, 90(2): 463-481.
Lovitts, Barbara E. 2002. Leaving the ivory tower: The causes and consequences of departure from doctoral study. Lanham, MD: Rowman & Littlefield Publishers.
Paternoster, Raymond, Robert Brame, Paul Mazerolle, and Alex Piquero. 1998. “Using the correct statistical test for the equality of regression coefficients.” Criminology, 36(4): 859-66.
van Rooij, Els, Marjon Fokkens-Bruinsma, and E. Jansen. 2021. “Factors that influence PhD candidates’ success: the importance of PhD project characteristics.” Studies in Continuing Education, 43(1): 48-67.
Wright, Toni, and Ray Cochrane. 2000. “Factors influencing successful submission of Ph.D. theses.” Studies in Higher Education, 25(2): 181–95.


22. Research in Higher Education
Paper

Climbing the Ivory Tower: Agency, Reflexivity and the Career Pathways of Care-experienced Academics in Higher Education

Neil Harrison, Simon Benham-Clarke

University of Exeter, United Kingdom

Presenting Author: Harrison, Neil

There has been increasing interest in understanding the higher education experiences of students who spent time ‘in care’ (e.g. with foster carers) as children, usually due to maltreatment or neglect within the birth family. Members of this group tend to have to overcome strong barriers to educational success, including social disruption, trauma, societal stigma and low expectations from professionals (Stein, 2012). Individuals who spent time in care are often referred to as ‘care-experienced’ and it is increasingly understood that their average educational outcomes are significantly lower than the general population (Berridge et al., 2020; Sebba et al., 2015).

Nevertheless, many care-experienced people thrive within the education system and achieve highly. Official figures for England (Department for Education, 2022) show that 13% of those in care at 16 enter higher education by 19; numbers appear to be growing, while care-experienced people often choose to study later (Harrison, 2020). Furthermore, Harrison et al. (2022) have estimated that around one-quarter of care-experienced graduates progress immediately into postgraduate study. However, almost nothing is currently known about those approaching the top of the academic ladder (Baker, 2022).

This paper therefore explores the experiences of care-experienced people who are now pursuing an academic career (i.e. as professors, lecturers, research fellows and similar), addressing the following research questions:

  • RQ1: What insights do the lived lives of the participants offer into successful pathways into and through higher education for people with experience of children’s social care?
  • RQ2: Why did the participants choose a career in academia, what challenges have they had to address to establish their careers and how have they overcome these?
  • RQ3: What mechanisms, if any, exist within universities to support the professional development of care-experienced academics (e.g. mentoring or funding streams)?
  • RQ4: How have the participants navigated issues of identity formation/renegotiation and communities of practice in academia?

We use Archer’s concept of reflexivity (2007, 2012) to explore the balance between individual agency and societal structures, with a focus on the ‘internal conversations’ that we have with ourselves. These help to guide our decisions and actions in relation to the enablements and constraints posed by the prevailing social structures. We also draw on the concept of ‘identity work’ (Brown, 2015) to explore the decisions that academics make about their professional lives. This is predicated on the idea that we can concurrently hold and project multiple identities that can be complementary, overlapping or even contradictory. Identity work captures the mental, emotional, social and physical labour that is invested in creating, maintaining and reconciling the identities that we deploy in professional settings.

While our study is focused exclusively on the United Kingdom, it has a wider relevance across European settings. There has been an increasing focus on care-experienced students in higher education, for example, in Ireland (e.g. Brady et al., 2019) and other European nations (e.g. Jackson and Cameron, 2014). We believe, however, that this is the first study to specifically address the lives of care-experienced academics.


Methodology, Methods, Research Instruments or Sources Used
Our study is situated in the critical realist tradition which combines realist ontology with interpretivist epistemology (e.g. Sayer, 2000).  This is powerful when seeking to understand the lives of individuals who encounter rigid societal structures, such as the care and education systems (Pawson, 2013).  Critical realist enquiry particularly seeks to shed light on how those systems can be adapted to challenge deep-rooted inequalities and support marginalised groups.  

We believe this is the first study anywhere in the world to engage with care-experienced academics as a group of interest.  Our first aim was therefore to learn more about the group’s size and composition, based on an assumption that the numbers are very small.  To this end, we devised a short online questionnaire and publicised an anonymous weblink that was distributed extensively through relevant organisations, online forums and key individuals, aiming to reach as many care-experienced academics as possible.

After four months, we received 31 valid responses.  The questionnaire’s second purpose was to collect contact details for those interested in being interviewed.  Twenty-five were invited, of whom 21 agreed.  Semi-structured interviews lasting 45-70 minutes were undertaken using Microsoft Teams, professionally transcribed and carefully anonymised, before being uploaded into Nvivo for analysis.  A brief interim report was then circulated to the interviewees by e-mail as a form of member checking and to invite any further thoughts.  The British Educational Research Association’s 2018 guidelines for ethical research practice informed the study, which was developed in conjunction with care-experienced people at all points.

To analyse the data, we used thematic analysis based on Braun and Clarke (2021).  This involved a close reading of the transcripts, a phase of open coding of relevant sections and then cycles of discussion to ensure shared understandings and to combine similar codes.  We then assembled the codes into overarching themes, again taking a dialogic approach to resolve any differences in interpretation.  We eventually agreed on eight themes to adequately describe the content of the interviews.

Conclusions, Expected Outcomes or Findings
The eight themes that we constructed from the interview data were: (1) Contrasting experiences of school, (2) Academic pathways and plans, (3) Precarities and safety nets, (4) Identity, academia and feelings of success, (5) Professional relationships and belonging, (6) Enablers for career progression, (7) Discourses of luck, and (8) Removing constraints and forging enablements.

This paper will focus primarily on three findings from the study.  Firstly, that the precarity increasingly associated with higher education careers (e.g. Leathwood and Read, 2022) is particularly profound for care-experienced academics who generally lack the familial ‘safety nets’ that most early career academics enjoy.  This is particularly marked in relation to an ongoing quest for stability that has its origins in the educational and social disruption that they underwent in childhood.

Secondly, there was a tension between narratives of self-reliance and help-seeking which was playing out through our participants’ academic careers.  Many discussed how they had become accustomed to relying on their own resources during childhood and early adulthood due to limited support or advice from family and professionals.  Others felt that their success was partly attributable to their willingness to ask for support from knowledgeable others who were able to provide practical help with career development.  

Thirdly, a significant question for many participants was whether or not to reveal their care-experienced status to colleagues or students, and, if so, the limits to the information shared.  This was contextualised around fears about stigma, microaggressions or other negative reactions, although some of our participants were purposively open as part of a wider role in advocating around care or to act as a role model for students.  Being a care-experienced academic thus required substantial identity work that was not required of their peers.

References
Archer, M. (2007) Making our way through the world: human reflexivity and social mobility. Cambridge: Cambridge University Press.
Archer, M. (2012) The reflexive imperative in late modernity. Cambridge: Cambridge University Press.
Baker, Z. (2022) How does a background of care affect graduate transitions? A literature review. York: University of York.
Berridge, D., Luke, N., Sebba, J., Strand, S., Cartwright, M., Staples, E., Mc Grath-Lone. L., Ward, J. and O’Higgins, A. (2020) Children in need and children in care: educational attainment and progress. Bristol/Oxford: University of Bristol and Rees Centre.
Brady, E., R. Gilligan and S. NicFhlannchadha (2019) Care-experienced young people accessing higher education in Ireland, Irish Journal of Applied Social Studies [online], 19, 1.
Braun, V. and V. Clarke (2021) Thematic analysis: a practical guide. London: Sage.
Brown, A. (2015) Identities and identity work in organizations. International Journal of Management Reviews 17(1): 20-40.
Department for Education (2022) Widening participation in higher education, https://explore-education-statistics.service.gov.uk/find-statistics/widening-participation-in-higher-education/2020-21.
Harrison, N. (2020) Patterns of participation in higher education for care-experienced students in England: why has there not been more progress? Studies in Higher Education 45(9): 1986-2000.
Harrison, N., Z. Baker and J. Stevenson (2022) Employment and further study outcomes for care-experienced graduates in the UK. Higher Education 83: 357-378.
Jackson, S. and C. Cameron (2014) Improving access to further and higher education for young people in public care: European policy and practice. London: Jessica Kingsley.
Leathwood, C., and B. Read (2022) Short-term, short-changed? A temporal perspective on the implications of academic casualisation for teaching in higher education. Teaching in Higher Education, 27(6), 756-771.
Pawson, R. (2013) The science of evaluation: a realist manifesto. London: Sage.
Sayer, A. (2000) Realism and social science. London: Sage.
Sebba, J., D. Berridge, N. Luke, J. Fletcher, K. Bell, S. Strand, S. Thomas, I. Sinclair and A. O’Higgins (2015) The educational progress of looked after children in England: linking care and educational data. Oxford/Bristol: Rees Centre and University of Bristol.
Stein, M. (2012) Young people leaving care: Supporting pathways to adulthood. London: Jessica Kingsley.


 
Contact and Legal Notice · Contact Address:
Privacy Statement · Conference: ECER 2024
Conference Software: ConfTool Pro 2.6.153+TC
© 2001–2025 by Dr. H. Weinreich, Hamburg, Germany