Distance learning and the empowerment of students: applied statistical analysis for students of the Built Environment.

2.50
Hdl Handle:
http://hdl.handle.net/2436/3979
Title:
Distance learning and the empowerment of students: applied statistical analysis for students of the Built Environment.
Authors:
Nicholas, John; Edwards, David
Abstract:
Built Environment students (including construction management, quantity surveying and so forth) generally exhibit limited understanding of mathematics and statistics, both from a theoretical and practical perspective (cf. Johnson, 1998; Llewellyn, 1999; Mtenga and Spainhour, 2000). This statement is supported by the fact that over half of the first year students (2001/2 intake) who completed an Individual Learner Profile (ILP) admitted to exhibiting poor mathematical skill. In addition, fewer than one in forty students have gained a mathematical qualification higher than a GCSE. Hence, undergraduate students are faced with a huge task when initially conceptualising the analytical component of a dissertation. Consequently, students elect to avoid robust and rigorous analysis in preference for elementary and somewhat naïve statistical methods to interpret any gathered data. This problem is further exacerbated by the reference to many ‘introductory’ statistical texts that are written for persons who have an ‘above average’ mathematical knowledge. Due to their background, Built Environment students struggle in transferring their data into a format that can be analysed and interpreted by statistical software. To do so requires time and commitment of staff combined with student initiative and drive. The problem here is that over 50% of students in the School of Engineering and the Built Environment (SEBE) attend University on a part time basis. Hence, physical restrictions limit these students’ ability to access the library and search for an appropriate textbook. Therefore, an easily accessible (internet) reference tool would provide an ideal opportunity with which to overcome this potential stumbling block. The aim of the proposed project was to develop an internet-based tool to assist undergraduate students learn ‘applied’ statistical analysis of data (relevant to typical construction problems) not just statistics per se. Such a tool would facilitate students, who actively seek to enhance their general mathematical and statistical knowledge as well as gain an insight into using commercially available statistical software simulation packages.
Citation:
CELT Learning and Teaching Projects 2001/02
Publisher:
University of Wolverhampton
Issue Date:
2002
URI:
http://hdl.handle.net/2436/3979
Additional Links:
http://www.wlv.ac.uk/celt
Type:
Book chapter
Language:
en
Description:
Report of a CELT project on supporting students through innovation and research.
ISBN:
0954211618
Appears in Collections:
Institute for Learning Enhancement (ILE)

Full metadata record

DC FieldValue Language
dc.contributor.authorNicholas, John-
dc.contributor.authorEdwards, David-
dc.date.accessioned2006-08-21T15:44:35Z-
dc.date.available2006-08-21T15:44:35Z-
dc.date.issued2002-
dc.identifier.citationCELT Learning and Teaching Projects 2001/02en
dc.identifier.isbn0954211618-
dc.identifier.urihttp://hdl.handle.net/2436/3979-
dc.descriptionReport of a CELT project on supporting students through innovation and research.en
dc.description.abstractBuilt Environment students (including construction management, quantity surveying and so forth) generally exhibit limited understanding of mathematics and statistics, both from a theoretical and practical perspective (cf. Johnson, 1998; Llewellyn, 1999; Mtenga and Spainhour, 2000). This statement is supported by the fact that over half of the first year students (2001/2 intake) who completed an Individual Learner Profile (ILP) admitted to exhibiting poor mathematical skill. In addition, fewer than one in forty students have gained a mathematical qualification higher than a GCSE. Hence, undergraduate students are faced with a huge task when initially conceptualising the analytical component of a dissertation. Consequently, students elect to avoid robust and rigorous analysis in preference for elementary and somewhat naïve statistical methods to interpret any gathered data. This problem is further exacerbated by the reference to many ‘introductory’ statistical texts that are written for persons who have an ‘above average’ mathematical knowledge. Due to their background, Built Environment students struggle in transferring their data into a format that can be analysed and interpreted by statistical software. To do so requires time and commitment of staff combined with student initiative and drive. The problem here is that over 50% of students in the School of Engineering and the Built Environment (SEBE) attend University on a part time basis. Hence, physical restrictions limit these students’ ability to access the library and search for an appropriate textbook. Therefore, an easily accessible (internet) reference tool would provide an ideal opportunity with which to overcome this potential stumbling block. The aim of the proposed project was to develop an internet-based tool to assist undergraduate students learn ‘applied’ statistical analysis of data (relevant to typical construction problems) not just statistics per se. Such a tool would facilitate students, who actively seek to enhance their general mathematical and statistical knowledge as well as gain an insight into using commercially available statistical software simulation packages.en
dc.format.extent103475 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.publisherUniversity of Wolverhamptonen
dc.relation.urlhttp://www.wlv.ac.uk/celten
dc.subjectDistance learningen
dc.subjectStudent supporten
dc.subjectMathematicsen
dc.subjectStatistical analysisen
dc.subjectUndergraduate studentsen
dc.subjectHigher educationen
dc.subjectConstruction managementen
dc.subjectBuilt environmenten
dc.subjectStudent empowermenten
dc.titleDistance learning and the empowerment of students: applied statistical analysis for students of the Built Environment.en
dc.typeBook chapteren
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