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Student Perspectives on Integration in Part-Time, Flexible Higher Education in Ireland; 'We Don't Socialise Here'
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Hunt, Nuala; Loxley, Andrew – Journal of Further and Higher Education, 2021
Despite efforts in Ireland to increase the number of part-time students in Higher Education, there was limited growth over twenty years 1997-2017. Part-time featured in widening participation strategies; however, this mode of learning has orientated towards employability. Retention of part-time students remains a problem for Higher Education. This…
Descriptors: Student Attitudes, Part Time Students, Academic Persistence, School Holding Power
Supervising the Professional Doctoral Student: Less Process and Progress, More Peripheral Participation and Personal Identity
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Mawson, Kate; Abbott, Ian – Management in Education, 2017
This article presents a discussion around issues of identity for part-time professional doctoral students. The current supervision arrangements of a professional doctoral programme were considered, using an exploratory study, to explore the idea that supervision for competent confident professionals should, in the early stages, focus on identity…
Descriptors: Graduate Students, Doctoral Programs, Self Concept, Part Time Students
Scaling Student Success with Predictive Analytics: Reflections after Four Years in the Data Trenches
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Wagner, Ellen; Longanecker, David – Change: The Magazine of Higher Learning, 2016
The metrics used in the US to track students do not include adults and part-time students. This has led to the development of a massive data initiative--the Predictive Analytics Reporting (PAR) framework--that uses predictive analytics to trace the progress of all types of students in the system. This development has allowed actionable,…
Descriptors: Predictor Variables, Reflection, Academic Achievement, Models
Identification of Early Predictors of Adult Learners' Academic Performance in Higher Education
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Yin, Sylvia Chong Nguik – IAFOR Journal of Education, 2016
Universities are inundated with detailed applicant and enrolment data from a variety of sources. However, for these data to be useful there is a need to convert them into strategic knowledge and information for decision-making processes. This study uses predictive modelling to identify at-risk adult learners in their first semester at SIM…
Descriptors: Foreign Countries, Predictor Variables, Models, College Freshmen