22 SES 08 C, Academic Work and Professional Development
Parallel Paper Session
The centrality of research within the role of academics working in the higher education sector is without question. Since the 1980s here has been increasing interest in the research productivity of academics. Indicators of research productivity, such as publication rates, are a determining factor in decisions related to promotion, tenure and the granting of research funding (Ramsden 1994). Research outputs also impact on the reputation of universities and other institutes of higher education as well as affecting the career trajectories of academics. The impact of research at a reputational level is evident in the impetus from management in universities to increase the global standing of their institutions through research outputs and the acquisition of research funding. Furthermore the investment in research has been aligned to the economic goals of countries and is explicitly stated in policy documents at European Union (EU) level. There is worldwide evidence that faculty research productivity is a central component in a number of areas of ascertaining the quality of higher education institutions (Teodorescu 2000).
A predictive model was developed to identify factors associated with research productivity amongst academics working full-time in the university sector in Ireland. Research productivity has been defined as: ‘the totality of research performed by academics in universities and related contexts within a given time period’ (Print & Hattie 1997: 454). A number of models of determinants of publications have been previously developed. Essentially they measure a comparable number of variables that are grouped under three headings: demographic predictors, academic predictors and institutional predictors (Shin and Cummings 2010). For example Shin and Cummings (2010), in their predictive model of research productivity, theorised that research outputs were related to the extent to which academics preferred research over teaching, time spent on research and teaching, research collaboration, research training, rank, time since completion of PhD, gender, number of children and discipline. Similarly, Porter and Umbach (2001: 181) developed an explanatory model of research productivity that consisted of five variable groupings. They hypothesised that research outputs were a ‘function of human capital, personal tastes, career status, teaching workload, demographics and academic discipline’. Human capital referred to the ability of the academic to do research; personal taste referred to attitudes towards research (emphasis toward teaching or emphasis toward research); career status measured faculty rank and years in post, and workload was identified through number of undergraduate and graduate courses taught during a semester. Demographic variables included gender, age, number of children and marital status. To date there has been no measure of the predictors of research productivity amongst academics working in the Irish higher education sector. Therefore based on previous research a regression model was developed to predict the factors associated with research productivity amongst academics in Ireland. This model consisted of three blocks of variables: demographic variables, individual academic variables, and institutional variables.
Abramo G., D’Angelo C., Di Costa F. (2009) Research collaboration and productivity: is there correlation? Higher Education, 57: 155-171. Fox, M.F. (1983) Publication productivity among scientists: a critical review, Social Studies of Science, 13: 285-305. Kaya, N, & Weber M. (2003) Faculty research productivity: gender and discipline differences. Journal of Family and Consumer Sciences, 95: 46. Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social Studies of Science, 35: 673–702. Marsh, H. W., & Hattie, J. (2002). The relation between research productivity and teaching effectiveness: Complementary, antagonistic, or independent constructs? Journal of Higher Education, 73: 603–641. Porter, S. R., & Umbach, P. D. (2001). Analyzing faculty workload data using multilevel modeling. Research in Higher Education, 42(2): 171–196. Print, M. & Hattie J. (1997) Measuring quality in universities: An approach to weighting research productivity. Higher Education, 33: 453-469. Ramsden P. (1994) Describing and explaining research productivity. Higher Education, 28: 207 – 226. Shin, J. & Cummings W. (2010) Multilevel analysis of academic publishing across disciplines: research preference, collaboration and time on research. Scientometrics, 85: 581-594. Smeby, J., & Try, S. (2005). Departmental contexts and faculty research activity in Norway. Research in Higher Education, 46: 593–619. Teodorescu, D. (2000) Correlates of faculty publication productivity: a cross-national analysis. Higher Education, 39: 201–22.
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