Developing interest to share and craft based on the Technology Acceptance Model

The Malaysian Ministry of Education aims to increase interest in learning Science, Technology, Engineering and Mathematics, through Science2Action. Among these initiatives in Science2Action, is the use of Art(s). By combining the Internet, technology and crafts, e-crafting is formed. This e-crafting project aims to increase awareness about what interests the audience through sharing of and development of craft, hopefully towards possibilities of ideation and mixing crafts, extending from the original craft such as origami. Designed based on the Technology Acceptance Model, findings are positive

Universal Global Imprints of Genome Growth and Evolution – Equivalent Length and Cumulative Mutation Density

BACKGROUND: Segmental duplication is widely held to be an important mode of genome growth and evolution. Yet how this would affect the global structure of genomes has been little discussed. METHODS/PRINCIPAL FINDINGS: Here, we show that equivalent length, or L(e), a quantity determined by the variance of fluctuating part of the distribution of the k-mer frequencies in a genome, characterizes the latter's global structure. We computed the L(e)s of 865 complete chromosomes and found that they have nearly universal but (k-dependent) values. The differences among the L(e) of a chromosome and those of its coding and non-coding parts were found to be slight. CONCLUSIONS: We verified that these non-trivial results are natural consequences of a genome growth model characterized by random segmental duplication and random point mutation, but not of any model whose dominant growth mechanism is not segmental duplication. Our study also indicates that genomes have a nearly universal cumulative "point" mutation density of about 0.73 mutations per site that is compatible with the relatively low mutation rates of (1-5) x 10(-3)/site/Mya previously determined by sequence comparison for the human and E. coli genomes

A large calcium-imaging dataset reveals a systematic V4 organization for natural scenes

The visual system evolved to process natural scenes, yet most of our understanding of the topology and function of visual cortex derives from studies using artificial stimuli. To gain deeper insights into visual processing of natural scenes, we utilized widefield calcium-imaging of primate V4 in response to many natural images, generating a large dataset of columnar-scale responses. We used this dataset to build a digital twin of V4 via deep learning, generating a detailed topographical map of natural image preferences at each cortical position. The map revealed clustered functional domains for specific classes of natural image features. These ranged from surface-related attributes like color and texture to shape-related features such as edges, curvature, and facial features. We validated the model-predicted domains with additional widefield calcium-imaging and single-cell resolution two-photon imaging. Our study illuminates the detailed topological organization and neural codes in V4 that represent natural scenes.Comment: 39 pages, 14 figure

2018-2019 Master Class - Lynn Chang (Violin)

https://spiral.lynn.edu/conservatory_masterclasses/1176/thumbnail.jp

2016-2017 Dean\u27s Showcase No. 3

https://spiral.lynn.edu/conservatory_deansshowcase/1004/thumbnail.jp

2016-2017 Master Class - Elmar Oliveira (Violin)

https://spiral.lynn.edu/conservatory_masterclasses/1005/thumbnail.jp

Adopting Automated Essay Scoring Feedback In Malaysia: A Review Of The Literature

Assessing essays and providing feedback to learners is undoubtedly a daunting, time consuming task for language teachers especially for formative assessment. Formative assessment requires feedbacks that indicate learning gaps that inform ideas for further improvement. Although providing high quality feedback is important, teachers are often in dilemma to beat the deadline and hold accountable to huge class size despite the need for iterative and frequent practice. The laboriousness of essay marking often limits the occurrence of essay writing in classroom. A possible solution is to make use of an Automated Essay Scorer (AES) system that could score and generate feedback immediately. The purpose of this paper is to review on the importance of feedback and the feasibility of adopting an automated mechanism to help Malaysian English teachers to mark essays and provide feedbacks instantly. Features of good feedback, commercially available AES, reasons in favour of automated feedback based on the Malaysian context and some limitations of the system are examined. Our findings suggest that relevant and effective automated feedback mechanism can be possible through home-grown AES supplemented with properly phrased feedbacks. It can lead to self-regulated learning that empowers them for sustainable development. It is a laborious but attainable task with the cooperation and supports all parties. Hence, introducing Automated Essay Scoring Feedback (AESF), a home-grown AES is a feasible and highly anticipated tool for the Malaysian classroom

Developing an Automated Essay Scorer with Feedback (AESF) for Malaysian University English Test (MUET) : A Design-based Research Approach

This paper presents the development of an automated essay scoring mechanism based on the Malaysian University English Test essay marking criteria using the Design-based research (DBR). It is a learning intervention to facilitate students in their essay writing process and at the same time, serves as a tool for teachers to mark essay. DBR is the most commonly used method for conducting research in technological enhanced learning context especially for solving real classroom problem. The development of the automated scoring system is presented step by step following the four phases in DBR model. In each phase, data collection procedure, research instrument and the lessons learnt that lead to further iterations are discussed in order to produce a workable and effective automated essay grader. The outcome resulted from the five iterations lead to the present intervention, Automated Essay Scorer with Feedback (AESF). This system allows teachers to collect samples of marked essays to be trained to grade newly entered essays. Then the teacher can set task and keep track of students’ progress and provide additional feedback as well as rectify the scores generated. For students, they can practice writing essays and demand for feedback at any point of their essays writing process for the system to provide scores by paragraph as well as the whole essay. The system was tested by 24 teachers from 5 schools in real-classroom context with favorable comment