A data driven approach to student retention: the impact on leadership behaviour
| dc.check.embargoformat | Embargo not applicable (If you have not submitted an e-thesis or do not want to request an embargo) | en |
| dc.check.info | Not applicable | en |
| dc.check.opt-out | Not applicable | en |
| dc.check.reason | Not applicable | en |
| dc.check.type | No Embargo Required | |
| dc.contributor.advisor | Sammon, David | en |
| dc.contributor.advisor | Murphy, Ciaran | en |
| dc.contributor.author | McCarthy, Jonathan | |
| dc.date.accessioned | 2019-11-12T10:19:11Z | |
| dc.date.available | 2019-11-12T10:19:11Z | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019 | |
| dc.description.abstract | Student retention is important to all Higher Education Institutions (HEI’s). The typical focus has seen institutions identifying ‘at risk’ students by monitoring a set of factors such as student attendance, engagement, performance, socio-economic background, etc. Institutions want to identify ‘at risk’ students and intervene before the ‘at risk’ student becomes a retention statistic. Once the factors are identified, this typical model often provides data to decision makers (leaders and/or senior managers) to assist with the identification of ‘at risk’ students in each leader’s department. However, some HEI’s have also historically relied on more tacit knowledge (opinions, anecdotes and biases) rather than actual data. In a data driven culture, leaders make decisions based on data and information rather than intuition and bias. HEI’s typically provide relevant data to leaders creating an opportunity to craft an intervention to change student behaviour. Interestingly, whether HEI’s are using data or tacit knowledge, all typically employ the same next steps once an ‘at risk’ student is identified: intervene to try and change the ‘at risk’ student’s behaviour. These interventions are quite consistent across HEI’s and can include supports such as interaction with faculty, mentoring, career guidance, counselling, orientation programmes or even access to technology. These interventions, or supports, can be grouped into three categories: Academic, Environmental and Institutional. What is also interesting however, is that there are a number of methodological and theoretical gaps in the area of student retention research. The vast majority of the research has used positivist approaches to collect and analyse data and focused, understandably, on the perspective of the student. Exploiting these gaps, this exploratory study is building theory by analyzing data gathered through interviews, surveys and participant observation in a HEI. A single case study design is chosen with an Irish HEI as the case. Another crucial difference is that this research focuses on the perspective of the leader rather than the student. After moving towards a data driven culture, the paper will ask a number of key questions: 1. What characterises leadership behaviour in a typical* student retention model? 2. What is the impact of a data-driven approach on leadership behaviour in a student retention model? *A typical student retention model is one which may rely heavily on opinions, biases and anecdotes i.e. (non data-driven). It also focuses on 1st year full time students, which is also the primary focus of this research. | en |
| dc.description.status | Not peer reviewed | en |
| dc.description.version | Accepted Version | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | McCarthy, J. 2019. A data driven approach to student retention: the impact on leadership behaviour. PhD Thesis, University College Cork. | en |
| dc.identifier.endpage | 248 | en |
| dc.identifier.uri | https://hdl.handle.net/10468/8988 | |
| dc.language.iso | en | en |
| dc.publisher | University College Cork | en |
| dc.rights | © 2019, Jonathan McCarthy. | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ | en |
| dc.subject | Student retention | en |
| dc.subject | Leadership behaviour | en |
| dc.subject | Leadership behavior | en |
| dc.subject | Data analytics | en |
| dc.subject | Change management in public sector | en |
| dc.subject | Decision making | en |
| dc.thesis.opt-out | false | |
| dc.title | A data driven approach to student retention: the impact on leadership behaviour | en |
| dc.type | Doctoral thesis | en |
| dc.type.qualificationlevel | Doctoral | en |
| dc.type.qualificationname | PhD | en |
| ucc.workflow.supervisor | dsammon@ucc.ie |
