Is E-learning replacing the traditional lecture?

Purpose – The purpose of this paper is to review some of the learning technologies associated with teaching and learning in Higher Education (HE). It looks at E-learning and Information Technology (IT) as tools for replacing the traditional learning experience in HE, i.e. the ‘chalk and talk’ lecture and seminar. HE is on the threshold of being transformed through the application of learning technologies. Are we on the brink of a new way of learning in HE after a tried and tested formula over eight hundred years? Design/methodology/approach – Adopting a case based approach, the fieldwork for this research took place at two UK Higher Education Institutes (HEI’s). A number of units that included IT based learning were identified. All units included a web site that was aimed at supporting students’ learning. The data was collected through unstructured discussion with the lecturer and a questionnaire to students. Findings – This paper considers and highlights the key findings from the sample linking them to the literature with the purpose of testing the aim/title of this paper. Evidence suggested the implications for HEI’s are they cannot assume that presenting new technologies automatically makes their institutions “youth friendly”; this new generation would like to see some concrete benefits of technology. Originality/value – From this small-scale investigation this paper attempts to investigate which direction the threshold may go. There has been eight hundred years of learning in the UK, is this generation wanting a new chapter. Evidence from this research suggests not, it will only play a bit part. They can help free up time in order to engage and support students in new and interesting ways

Machine Transliteration

PACLIC 20 / Wuhan, China / 1-3 November, 200

The Choice of Tense in Translation into the Second Language

English tense is widely believed as one of the most problematic areas in the “interlanguage”, which includes non-native English speakers’ English writing and translations into the translator’s second language. This study aims to investigate the relationships between the tense choice in translation, the tense in the Chinese source text, and the translation competence of translators. A small Chinese-English parallel corpus has been built with 127 translations of Chinese press editorials by experienced native English speaking translators, experienced native Chinese speaking translators, and novice native Chinese speaking translators. Cross-tabulate analyses of this study have shown that the three groups of translators differ from one another significantly in their handling of marked Chinese past tense verbs, while they do not when translating Chinese sentences with contextually marked tense. This study suggests that in order to improve their translation quality, (1) experienced native Chinese speaking translators need to increase the percentages of Present Simple, Present Progress, Present Perfect, and Past Simple, and reduce the percentages of Past Perfect in their translation; (2) novice native Chinese speaking translators need to increase the percentages of Present Simple, and Present Progress, and reduce the percentages of Past Perfect, Past Simple, and Present Perfect in their translation

The infusion of emerging technologies in complex higher education settings

In the context of an increasing reliance on, and integration of, Information and Communication Technologies (ICTs) into the Higher Education (HE) sector, innovative approaches are being sought in response to infrastructural and resource limits, and mounting pressures to increase participation and throughput rates. This is particularly evident in South Africa, given its history of exclusion and marginalisation. Here, the potential of eLearning has been recognised in expanding access to educational opportunities and in equipping university staff and students with the eSkills and ePedagogy needed to make full use of emerging technologies. At the University of the Western Cape, the Centre for Innovative Education and Communication Technologies (CIECT) was established in 2005 to champion the adoption of emerging technologies at that institution in support of teaching-and-learning practices, and to provide support and training to staff and students in their use. After nearly a decade of experience and refinement, the Centre’s activities are structured according to a systemic framework that drives the infusion of emerging technologies into its particular complex higher education setting. The framework encompasses the areas of Teaching-and-Learning, Research, Community Engagement, and Collaboration, and aligns all eLearning activities with institutional and national policy. The goal of this case study is to share these activities in a complex HE setting, since in order to successfully drive the adoption of emerging eLearning technologies, a systemic framework aligned to institutional and national policy goals is required

Sentence Level N-Gram Context Feature in Real-Word Spelling Error Detection and Correction: Unsupervised Corpus Based Approach

Spell checking is the process of finding misspelled words and possibly correcting them. Most of the modern commercial spell checkers use a straightforward approach to finding misspellings, which considered a word is erroneous when it is not found in the dictionary. However, this approach is not able to check the correctness of words in their context and this is called real-word spelling error. To solve this issue, in the state-of-the-art researchers use context feature at fixed size n-gram (i.e. tri-gram) and this reduces the effectiveness of model due to limited feature. In this paper, we address the problem of this issue by adopting sentence level n-gram feature for real-word spelling error detection and correction. In this technique, all possible word n-grams are used to learn proposed model about properties of target language and this enhance its effectiveness. In this investigation, the only corpus required to training proposed model is unsupervised corpus (or raw text) and this enables the model flexible to be adoptable for any natural languages. But, for demonstration purpose we adopt under-resourced languages such as Amharic, Afaan Oromo and Tigrigna. The model has been evaluated in terms of Recall, Precision, F-measure and a comparison with literature was made (i.e. fixed n-gram context feature) to assess if the technique used performs as good.  The experimental result indicates proposed model with sentence level n-gram context feature achieves a better result: for real-word error detection and correction achieves an average F-measure of 90.03%, 85.95%, and 84.24% for Amharic, Afaan Oromo and Tigrigna respectively. Keywords: Sentence level n-gram, real-word spelling error, spell checker, unsupervised corpus based spell checker DOI: 10.7176/JIEA/10-4-02 Publication date:September 30th 202

Toward a Corpus of Cantonese Verbal Comments and their Classification by Multi-dimensional Analysis

The information explosion in modern days across various media calls for effective opinion mining for timely digestion of public views and appropriate follow-up actions. Current studies on sentiment analysis have primarily focused on uncovering aspects like subjectivity, sentiment and credibility from written data, while spoken data are less addressed. This paper reports on our pilot work on constructing a corpus of Cantonese verbal comments and making use of multi-dimensional analysis to characterise different opinion types therein. Preliminary findings on the dimensions identified and their association with various communicative functions are presented, with an outlook on their potential application in subjectivity analysis and opinion classification.

Vowel Sound Disambiguation for Intelligible Korean Speech Synthesis

PACLIC 19 / Taipei, taiwan / December 1-3, 200