The Potential Effects of Wider Access to Higher Education on Degree Quality

Johnes, Jill

doi:10.1111/j.1468-2273.1992.tb01586.x

Cited by 10 publications

(10 citation statements)

References 15 publications

(21 reference statements)

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“…Thus, the OLS residual (u i ) provides a measure of each HEI's performance. This approach has been applied using output measures such as graduates' degree results, undergraduate non-completion rates, graduates' first destinations and research output (Johnes and Taylor, 1987, 1989a, b, 1990, 1992Johnes, 1996).…”

Section: Approaches To Efficiency Measurementmentioning

confidence: 99%

“…There are numerous possible inputs which could affect the quality and quantity of undergraduate teaching output. The most obvious is the quality of the student on arrival at university, and there is strong evidence of a positive relationship between previous academic achievement and degree results (Freeman, 1970;Johnes, 1992;Chapman, 1994;Rodgers and Ghosh, 2001;Smith and Naylor, 2001a;Bratti, 2002). The effect of entry qualification on degree achievement also appears to vary by subject of degree (Entwistle and Wilson, 1977;Sear, 1983).…”

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confidence: 99%

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Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education

Johnes

2006

Bulletin of Econ Res

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Data envelopment analysis (DEA) and multilevel modelling (MLM) are applied to a data set of 54,564 graduates from UK universities in 1993 to assess whether the choice of technique affects the measurement of universities' performance. A methodology developed by Thanassoulis and Portela (2002; Education Economics, 10(2), pp. 183-207) allows each individual's DEA efficiency score to be decomposed into two components: one attributable to the university at which the student studied and the other attributable to the individual student. From the former component, a measure of each institution's teaching efficiency is derived and compared to the university effects from various multilevel models. The comparisons are made within four broad subjects: pure science, applied science, social science and arts. The results show that the rankings of universities derived from the DEA efficiencies which measure the universities' own performance (i.e., having excluded the efforts of the individuals) are not strongly correlated with the university rankings derived from the university effects of the multilevel models. The data were also used to perform a university-level DEA. The university efficiency scores derived from these DEAs are largely unrelated to the scores 75 from the individual-level DEAs, confirming a result from a smaller data set (Johnes, 2006a; European Journal of Operational Research, forthcoming). However, the university-level DEAs provide efficiency scores which are generally strongly related to the university effects of the multilevel models.

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Section: Approaches To Efficiency Measurementmentioning

confidence: 99%

mentioning

confidence: 99%

Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education

Johnes

2006

Bulletin of Econ Res

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“…Although more moderate results were found by Richardson (1995) and Trueman and Hartley (1996), mature students outperformed their younger peers in vocational subjects and languages (Johnes, 1992) and in arts and social science subjects (Walker, 1975). There are also gender differences, with female students outperforming male students (Woodley, 1984;Hoskins et al, 1997); both single and married mothers in higher education performed better academically than other students, including mature students in general (Burns et al, 1993).…”

Section: Introduction and Literature Reviewmentioning

confidence: 67%

Being that bit older: mature students' experience of university and healthcare education

Shanahan

2000

Occupation Therapy Intl

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“…In support of this, researchers such as Johnes (1992) and Richardson (1994) have contended that younger students tend to outperform older students in mathematics and in the sciences.…”

Section: Resultsmentioning

confidence: 89%

The use of quantitative and qualitative methods in the analysis of academic achievement among undergraduates in Jamaica

McLaren

2012

International Journal of Research & Method in Education

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This paper describes a study which uses quantitative and qualitative methods in determining the relationship between academic, institutional and psychological variables and degree performance for a sample of Jamaican undergraduate students. Quantitative methods, traditionally associated with the positivist paradigm, and involving the counting and measurement of events and statistical analysis of a body of numerical data, constitute the primary research approach to this investigation. At the same time, qualitative methods are also employed to enhance the contextual meaning and to provide insight into the quantitativebased findings. Full account is taken of concerns relating to paradigmatic violations -that of the positivist and interpretivist in particular -and relevant literature is used to carve a clearer path towards an understanding and reconciliation of combining quantitative and qualitative methods. Further, implications for the findings as they relate to mixed-method design and institutional direction are discussed. Background Contesting methodologiesFor over three decades several debates or 'wars' (Gage 1989;Guba and Lincoln 1994;Rossi 1994) have raged in the social and behavioural sciences as to the superiority of one or the other of the two major social sciences research paradigms or models. These two models are known alternately as positivist (empirical-analytic, objectivist, functionalist) and interpretive (subjectivist, constructivist). Quantitative research methods have been traditionally associated with the positivist paradigm and qualitative research with the interpretive.A distinguishing characteristic of the quantitative method is the collection of numerical data (Jack and Clarke 1998) that, in turn, can be subjected to statistical procedures (Carter 2000a). Parahoo (1997) has identified three levels of quantitative research: descriptive, correlational, and causal, with causal referring to experiment as a research design.In descriptive research the overall aim is to 'discover new meaning, describe what exists, determine the frequency with which something occurs and categorize

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The Potential Effects of Wider Access to Higher Education on Degree Quality

Abstract: Against a background of rapidly increasing enrolment, both actual and planned, and the improbability of increasing resources, this paper explores the relationship between degree results and entry qualifications amongst students in all sectors of higher education.

Cited by 10 publications

References 15 publications

Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education

Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education

Being that bit older: mature students' experience of university and healthcare education

The use of quantitative and qualitative methods in the analysis of academic achievement among undergraduates in Jamaica

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