A new parameterization of Johnson's SB distribution with application to fitting forest tree diameter data

The SB distributional model of Johnson's 1949 paper was introduced by a transformation to normality, that is, z ~ N(0, 1), consisting of a linear scaling to the range (0, 1), a logit transformation, and an affine transformation, z = γ + δu. The model, in its original parameterization, has often been used in forest diameter distribution modelling. In this paper, we define the SB distribution in terms of the inverse transformation from normality, including an initial linear scaling transformation, u = γ′ + δ′z (δ′ = 1/δ and γ′ = �γ/δ). The SB model in terms of the new parameterization is derived, and maximum likelihood estimation schema are presented for both model parameterizations. The statistical properties of the two alternative parameterizations are compared empirically on 20 data sets of diameter distributions of Changbai larch (Larix olgensis Henry). The new parameterization is shown to be statistically better than Johnson's original parameterization for the data sets considered here.

SMARTFIRE: an integrated computational fluid dynamics code and expert system for fire field modelling

SMARTFIRE, an open architecture integrated CFD code and knowledge based system attempts to make fire field modeling accessible to non-experts in Computational Fluid Dynamics (CFD) such as fire fighters, architects and fire safety engineers. This is achieved by embedding expert knowledge into CFD software. This enables the 'black-art' associated with the CFD analysis such as selection of solvers, relaxation parameters, convergence criteria, time steps, grid and boundary condition specification to be guided by expert advice from the software. The user is however given the option of overriding these decisions, thus retaining ultimate control. SMARTFIRE also makes use of recent developments in CFD technology such as unstructured meshes and group solvers in order to make the CFD analysis more efficient. This paper describes the incorporation within SMARTFIRE of the expert fire modeling knowledge required for automatic problem setup and mesh generation as well as the concept and use of group solvers for automatic and manual dynamic control of the CFD code.

Experts on e-learning: insights gained from listening to the student voice!

The Student Experience of e-Learning Laboratory (SEEL) project at the University of Greenwich was designed to explore and then implement a number of approaches to investigate learners’ experiences of using technology to support their learning. In this paper members of the SEEL team present initial findings from a University-wide survey of nearly a 1000 students. A selection of 90 ‘cameos’, drawn from the survey data, offer further insights into personal perceptions of e-learning and illustrate the diversity of students experiences. The cameos provide a more coherent picture of individual student experience based on the totality of each person’s responses to the questionnaire. Finally, extracts from follow-up case studies, based on interviews with a small number of students, allow us to ‘hear’ the student voice more clearly. Issues arising from an analysis of the data include student preferences for communication and social networking tools, views on the ‘smartness’ of their tutors’ uses of technology and perceptions of the value of e-learning. A primary finding and the focus of this paper, is that students effectively arrive at their own individualised selection, configuration and use of technologies and software that meets their perceived needs. This ‘personalisation’ does not imply that such configurations are the most efficient, nor does it automatically suggest that effective learning is occurring. SEEL reminds us that learners are individuals, who approach learning both with and without technology in their own distinctive ways. Hearing, understanding and responding to the student voice is fundamental in maximising learning effectiveness. Institutions should consider actively developing the capacity of academic staff to advise students on the usefulness of particular online tools and resources in support of learning and consider the potential benefits of building on what students already use in their everyday lives. Given the widespread perception that students tend to be ‘digital natives’ and academic staff ‘digital immigrants’ (Prensky, 2001), this could represent a considerable cultural challenge.

The eLIDA CAMEL nomadic model of collaborative partnership for a community of practice in design for learning

A nomadic collaborative partnership model for a community of practice (CoP) in Design for Learning (D4L) can facilitate successful innovation and continuing appraisals of effective professional practice, stimulated by a 'critical friend' assigned to the project. This paper reports on e-learning case studies collected by the JISC-funded UK eLIDA CAMEL Design for Learning Project. The project implemented and evaluated learning design (LD) tools in higher and further education within the JISC Design for Learning pedagogic programme (2006-07). Project partners trialled professional user evaluations of innovative e-learning tools with learning design function, collecting D4L case studies and LD sequences in post-16/HE contexts using LAMS and Moodle. The project brought together learning activity sequences within a collaborative e-learning community of practice based on the CAMEL (Collaborative Approaches to the Management of e-Learning) model, contributing to international D4L developments. This paper provides an overview of project outputs in e-learning innovations, including evaluations from teachers and students. The paper explores intentionality in the development of a CoP in design for learning, reporting on trials of LD and social software that bridged tensions between formalised intra-institutional e-learning relationships and inter-institutional professional project team dynamic D4L practitioner interactions. Following a brief report of D4L case studies and feedback, the catalytic role of the 'critical friend' is highlighted and recommended as a key ingredient in the successful development of a nomadic model of communities of practice for managing professional e-learning projects. eLIDA CAMEL Partners included the Association of Learning Technology (ALT), JISC infoNet, three universities and five FE/Sixth Form Colleges. Results reported to JISC demonstrated D4L e-learning innovations by practitioners, illuminated by the role of the 'critical friend'. The project also benefited from formal case study evaluations and the leading work of ALT and JISC infoNet in the development of the CAMEL model.

Personalised e-learning, semantic web and learning ontologies

Kurzel(2004) points out that researchers in e-learning and educational technologists, in a quest to provide improved Learning Environments (LE) for students are focusing on personalising the experience through a Learning Management System (LMS) that attempts to tailor the LE to the individual (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez,2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman; 2003). According to Kurzel (2004) this tailoring can have an impact on content and how it’s accessed; the media forms used; method of instruction employed and the learning styles supported. This project is aiming to move personalisation forward to the next generation, by tackling the issue of Personalised e-Learning platforms as pre-requisites for building and generating individualised learning solutions. The proposed development is to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system’s processing engine. This paper will discuss some of our early work and ideas.

Semantic web and e-learning

With emergence of "Semantic Web" there has been much discussion about the impact of technologies such as XML and RDF on the way we use the Web for developing e-learning applications and perhaps more importantly on how we can personalise these applications. Personalisation of e-learning is viewed by many authors (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez, 2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman, 2003) as the key challenge for the learning technologists. According to Kurzel (2004) the tailoring of e-learning applications can have an impact on content and how it's accesses; the media forms used; method of instruction employed and the learning styles supported. This paper will report on a research project currently underway at the eCentre in University of Greenwich which is exploring different approaches and methodologies to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system's processing engine.

A case study of the effectiveness of the electronic survey as a research tool for measuring students' experience of e-learning

This paper uses a case study approach to consider the effectiveness of the electronic survey as a research tool to measure the learner voice about experiences of e-learning in a particular institutional case. Two large scale electronic surveys were carried out for the Student Experience of e-Learning (SEEL) project at the University of Greenwich in 2007 and 2008, funded by the UK Higher Education Academy (HEA). The paper considers this case to argue that, although the electronic web-based survey is a convenient method of quantitative and qualitative data collection, enabling higher education institutions swiftly to capture multiple views of large numbers of students regarding experiences of e-learning, for more robust analysis, electronic survey research is best combined with other methods of in-depth qualitative data collection. The advantages and disadvantages of the electronic survey as a research method to capture student experiences of e-learning are the focus of analysis in this short paper, which reports an overview of large-scale data collection (1,000+ responses) from two electronic surveys administered to students using surveymonkey as a web-based survey tool as part of the SEEL research project. Advantages of web-based electronic survey design include flexibility, ease of design, high degree of designer control, convenience, low costs, data security, ease of access and guarantee of confidentiality combined with researcher ability to identify users through email addresses. Disadvantages of electronic survey design include the self-selecting nature of web-enabled respondent participation, which tends to skew data collection towards students who respond effectively to email invitations. The relative inadequacy of electronic surveys to capture in-depth qualitative views of students is discussed with regard to prior recommendations from the JISC-funded Learners' Experiences of e-Learning (LEX) project, in consideration of the results from SEEL in-depth interviews with students. The paper considers the literature on web-based and email electronic survey design, summing up the relative advantages and disadvantages of electronic surveys as a tool for student experience of e-learning research. The paper concludes with a range of recommendations for designing future electronic surveys to capture the learner voice on e-learning, contributing to evidence-based learning technology research development in higher education.