Integrating synchronous and asynchronous internet distributed education for maximum effectiveness

Distributed education delivered via the Internet is a growing practice, with most institutions offering at least course websites and many expanding to full course offerings and even online degree progams. There are two schools of thought with regard to delivery mode: the larger group has focused on asynchronous delivery, accessible at any time via webpages and interactive tutorials and quizzes, while a smaller group advocates synchronous delivery where students are online and interact during class time. This paper summarizes the advantages and disadvantages of the two delivery modes and describes our successful and growing experience of more than a decade using an open source synchronous delivery tool blended with a variety of asynchronous capabilities and classroom instruction. We conclude that a synergistic combination of the two modes with in-person instruction, designed to provide maximum flexibility to the student within the constraints of the subject, offers the best support for student learning. www:     

The brachistochrone

The brachistochrone problem posed by Bernoulli and its solution highlights one of the most famous experiments in physics which illustrates the variational principle. This pedagogical study is designed to ignite a classroom discussion on the variational problem. We overview the Euler–Lagrange formalism of the variational principle and obtain the solution to the brachistochrone problem. We demonstrate the success of the variational method using brachistochrone models which were fabricated specially for this purpose.     

Allies in learning: critical insights into the importance of staff–student interactions in university education

Discussions of the quality of learning in university education often focus on curricula. Less attention is paid to the role of student–staff interactions. In a context in which a host of factors place pressure on the opportunities for students and staff to interact, it is important to use empirical insights to inform decisions about how to optimise learning. This paper uses data from a large survey of students and teaching staff in Australia to suggest that students and staff should be regarded as allies in learning. It investigates student reports to suggest that frequent interactions with those who teach them lead to higher levels of student engagement and satisfaction and lower attrition rates. The advantages do not only flow in one direction. Teaching staff gain insights into students' learning experiences, providing them with clues to better target their teaching.     

Motives,attitudes and approaches to studying in distance education

This study investigated the relationships between demographic characteristics, motives and attitudes to studying, self-reported study behaviour and measures of outcome. Students taking courses by distance learning received a postal survey containing a short form of the Motivated Strategies and Learning Questionnaire (MSLQ) and the Revised Approaches to Studying Inventory (RASI). Path analysis was used to assess the causal relationships among 395 students’ age, gender and prior qualifications, their scores on the MSLQ and the RASI and their marks. Evidence was obtained for the causal efficacy of most of the paths among the main components. In particular, the causal link between variations in students’ motives and attitudes and variations in their study behaviour is bidirectional.     

A novel dependency language model for information retrieval

This paper explores the application of term dependency in information retrieval (IR) and proposes a novel dependency retrieval model. This retrieval model suggests an extension to the existing language modeling (LM) approach to IR by introducing dependency models for both query and document. Relevance between document and query is then evaluated by reference to the Kullback-Leibler divergence between their dependency models. This paper introduces a novel hybrid dependency structure, which allows integration of various forms of dependency within a single framework. A pseudo relevance feedback based method is also introduced for constructing query dependency model. The basic idea is to use query-relevant top-ranking sentences extracted from the top documents at retrieval time as the augmented representation of query, from which the relationships between query terms are identified. A Markov Random Field (MRF) based approach is presented to ensure the relevance of the extracted sentences, which utilizes the association features between query terms within a sentence to evaluate the relevance of each sentence. This dependency retrieval model was compared with other traditional retrieval models. Experiments indicated that it produces significant improvements in retrieval effectiveness.