An evaluation of pedagogically informed parameterised questions for self assessment

Self-assessment is a crucial component of learning. Learners can learn by asking themselves questions and attempting to answer them. However, creating effective questions is time-consuming because it may require considerable resources and the skill of critical thinking. Questions need careful construction to accurately represent the intended learning outcome and the subject matter involved. There are very few systems currently available which generate questions automatically, and these are confined to specific domains. This paper presents a system for automatically generating questions from a competency framework, based on a sound pedagogical and technological approach. This makes it possible to guide learners in developing questions for themselves, and to provide authoring templates which speed the creation of new questions for self-assessment. This novel design and implementation involves an ontological database that represents the intended learning outcome to be assessed across a number of dimensions, including level of cognitive ability and subject matter. The system generates a list of all the questions that are possible from a given learning outcome, which may then be used to test for understanding, and so could determine the degree to which learners actually acquire the desired knowledge. The way in which the system has been designed and evaluated is discussed, along with its educational benefits

An improved functional link neural network for data classification

The goal of classification is to assign the pre-specified group or class to an instance based on the observed features related to that instance. The implementation of several classification models is challenging as some only work well when the underlying assumptions are satisfied. In order to generate the complex mapping between input and output space to build the arbitrary complex non-linear decision boundaries, neural networks has become prominent tool with wide range of applications. The recent techniques such as Multilayer Perceptron (MLP), standard Functional Link Neural Network (FLNN) and Chebyshev Functional Link Neural Network (CFLNN) outperformed their existing regression, multiple regression, quadratic regression, stepwise polynomials, K-nearest neighbor (K-NN), Naïve Bayesian classifier and logistic regression. This research work explores the insufficiencies of well- known CFLNN model where CFLNN utilizes functional expansion with large number of degree and coefficient value for inputs enhancement which increase computational complexity of the network. Accordingly, two alternative models namely; Genocchi Functional Link Neural Network (GFLNN) and Chebyshev Wavelets Functional Link Neural Network (CWFLNN) are proposed. The novelty of these approaches is that, GFLNN presents the functional expansions with less degree and small coefficient values to make less computational inputs for training to overcome the drawbacks of CFLNN. Whereas, CWFLNN is capable to generate more number of small coefficient value based basis functions with same degree of polynomials as compared to other polynomials and it has orthonormality condition therefore it has more accurate constant of functional expansion and can approximate the functions within the interval. These properties of CWFLNN are used to overcome the deficiencies of GFLNN. The significance of proposed models is verified by using statistical tests such as Freidman test based on accuracy ranking and pairwise comparison test. Moreover, MLP, standard FLNN and CFLNN are used for comparison. For experiments, benched marked data sets from UCI repository, SVMLIB data set and KEEL data sets are utilized. The CWFLNN reveals significant improvement (due to its generating more numbers of basis function property) in terms of classification accuracy and reduces the computational work

A unified framework for building ontological theories with application and testing in the field of clinical trials

The objective of this research programme is to contribute to the establishment of the emerging science of Formal Ontology in Information Systems via a collaborative project involving researchers from a range of disciplines including philosophy, logic, computer science, linguistics, and the medical sciences. The re­searchers will work together on the construction of a unified formal ontology, which means: a general framework for the construction of ontological theories in specific domains. The framework will be constructed using the axiomatic-deductive method of modern formal ontology. It will be tested via a series of applications relating to on-going work in Leipzig on medical taxonomies and data dictionaries in the context of clinical trials. This will lead to the production of a domain-specific ontology which is designed to serve as a basis for applications in the medical field

Research based yet action oriented: Developing individual level enterprising competencies

This paper outlines an approach to teaching enterprising competencies in the university setting of Massey University, Auckland, New Zealand. It is characterised by two features. First, it has an experiential component in the form of developmental exercises; forms of practice which are devised by the students themselves. Second, the exercises are research-based: students study academic articles and book chapters that give clues about how to practice the various competencies. The method is inspired by Gibb’s (1993, 1998, 2002a, 2002b) ideas about simulating the essences of enterprise in the learning environment. The approach used at Massey is outlined at the end of the paper. The paper begins with offering the rationales for the course. First, it provides arguments as to why enterprising competencies are becoming increasingly important for our students. Second, it is argued why, out of three approaches to competency, the behavioural approach is deemed to be the most suitable for the approach employed at Massey. Third, in the debate about generic versus situation specific competencies, it argues for the relevance of generic competencies. The paper then describes entrepreneurship / small business (E/SB) research on competencies, and discusses why entrepreneurship research is often of little help for ‘how to’ approaches. Finally, the Massey approach is described in detail

Observation Centric Sensor Data Model

Management of sensor data requires metadata to understand the semantics of observations. While e-science researchers have high demands on metadata, they are selective in entering metadata. The claim in this paper is to focus on the essentials, i.e., the actual observations being described by location, time, owner, instrument, and measurement. The applicability of this approach is demonstrated in two very different case studies

Doctorateness: where should we look for evidence?

This chapter considers the possibility of an “institutional theory of artistic research”. It proposes four distinct quadrants in which one might look for evidence for such a theory, which needs to have the capacity to accommodate the diverse positions on artistic research in the literature. The quadrants ("explicit", "implicit", "generic", and "specific") form a Boolean square with which one may also consider the contested term “doctorateness” in any field. The chapter concludes in due course, artistic research will gain a voice that causes researchers to re-describe activity in other disciplines owing to the way in which artistic research will be described.Peer reviewe

Assessing the relevance of higher education courses

The establishment of the European Higher Education Area has involved specifying lists of professional competencies that programs are expected to develop, and with this the need for procedures to measure how every course within a higher education program is aligned with the program’s competencies. We propose an instrument for characterizing this alignment, a process that we call assessing the relevance of a course. Using information from the course syllabus (objectives, contents and assessment scheme), our instrument produces indicators for characterizing the syllabus in terms of a competence list and for assessing its coherence. Because assessment involves quality, the results obtained can also be used to revise and improve the course syllabus. We illustrate this process with an example of a methods course from a mathematics teacher education program at a Spanish university