Social and Behavioral Sciences Commons^™

Towards A More Effective Bidirectional Lstm-Based Learning Model For Human-Bacterium Protein-Protein Interactions, Huaming Chen, Jun Shen, Lei Wang, Yaochu Jin

Faculty of Engineering and Information Sciences - Papers: Part B

The identification of protein-protein interaction (PPI) is one of the most important tasks to understand the biological functions and disease mechanisms. Although numerous databases of biological interactions have been published in debt to advanced high-throughput technology, the study of inter-species protein-protein interactions, especially between human and bacterium pathogens, remains an active yet challenging topic to harness computational models tackling the complex analysis and prediction tasks. In this paper, we comprehensively revisit the prediction task of human-bacterium protein-protein interactions (HB-PPI), which is a first ever endeavour to report an empirical evaluation in learning and predicting HB-PPI based on machine learning models. …

Utilizing Qr Codes To Verify The Visual Fidelity Of Image Datasets For Machine Learning, Yang-Wai Chow, Willy Susilo, Jianfang Wang, Richard Buckland, Joon Sang Baek, Jongkil Kim, Nan Li

Faculty of Engineering and Information Sciences - Papers: Part B

Machine learning is becoming increasingly popular in modern technology and has been adopted in various application areas. However, researchers have demonstrated that machine learning models are vulnerable to adversarial examples in their inputs, which has given rise to a field of research known as adversarial machine learning. Potential adversarial attacks include methods of poisoning datasets by perturbing input samples to mislead machine learning models into producing undesirable results. While such perturbations are often subtle and imperceptible from the perspective of a human, they can greatly affect the performance of machine learning models. This paper presents two methods of verifying the …

"A Big Influence On My Teaching Career And My Life": A Longitudinal Study Of Learning To Teach English Pronunciation, Michael S. Burri, Amanda Ann Baker

Faculty of Social Sciences - Papers (Archive)

Inquiry into learning to teach pronunciation is a growing area within the second language teacher education research paradigm. To what extent this learning process extends into instructors' early years of teaching pronunciation has yet to be explored. This article is a response to this need by exploring the 3.5-year trajectory of five teachers learning to teach English pronunciation. The study was conducted in two phases. In Phase 1, pre- and post-course questionnaires, weekly observations of the lectures, focus groups interviews, final post-course interviews, and the participants' final assessment task were triangulated to examine the development of participants' cognitions during a …

Learning To Dance, Skye Playsted

Faculty of Social Sciences - Papers (Archive)

No abstract provided.

Automatic Ventricular Nuclear Magnetic Resonance Image Processing With Deep Learning, Binbin Yong, Chen Wang, Jun Shen, Fucun Li, Hang Yin

Faculty of Engineering and Information Sciences - Papers: Part A

Cardiovascular diseases (CVD) seriously threaten the health of human beings, and they have caused widespread concern in recent years. At present, the diagnosis of CVD is mainly conducted by computed tomography (CT), echocardiography and nuclear magnetic resonance (NMR) technologies. NMR imaging technology is widely used in medical applications owing to its characteristics of high resolution and very low radiation. However, manual NMR image segmentation is time-consuming and error-prone, which has led to the research on automatic NMR image segmentation technologies. Researchers tend to explore the ventricular NRM image segmentation to improve the accuracy of CVD diagnosis. In this study, based …

Using Cost-Sensitive Learning And Feature Selection Algorithms To Improve The Performance Of Imbalanced Classification, Fang Feng, Kuan-Ching Li, Jun Shen, Qingguo Zhou, Xuhui Yang

Faculty of Engineering and Information Sciences - Papers: Part A

Imbalanced data problem is widely present in network intrusion detection, spam filtering, biomedical engineering, finance, science, being a challenge in many real-life data-intensive applications. Classifier bias occurs when traditional classification algorithms are used to deal with imbalanced data. As already known, the General Vector Machine (GVM) algorithm has good generalization ability, though it does not work well for the imbalanced classification. Additionally, the state-of-the-art Binary Ant Lion Optimizer (BALO) algorithm has high exploitability and fast convergence rate. Based on these facts, we have proposed in this paper a Cost-sensitive Feature selection General Vector Machine (CFGVM) algorithm based on GVM and …

Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin

Faculty of Engineering and Information Sciences - Papers: Part A

As an emerging pedagogy, micro learning aims to make use of people’s fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains showed …

From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen

Faculty of Engineering and Information Sciences - Papers: Part B

The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people’s daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners’ fragmented time to carry out personalized learning activities through online education resources. The whole workflow of a micro learning system can be separated into three processing stages: micro learning material generation, learning materials annotation and personalized learning materials delivery. Our micro learning framework is firstly introduced in this paper from a higher perspective. Then we will review representative segmentation …

Apex2s: A Two-Layer Machine Learning Model For Discovery Of Host-Pathogen Protein-Protein Interactions On Cloud-Based Multiomics Data, Huaming Chen, Jun Shen, Lei Wang, Chi-Hung Chi

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Evolutionary Learner Profile Optimization Using Rare And Negative Association Rules For Micro Open Learning, Geng Sun, Jiayin Lin, Jun Shen, Tingru Cui, Dongming Xu, Huaming Chen

Faculty of Engineering and Information Sciences - Papers: Part B

The actual data availability, readiness and publicity has slowed down the research of making use of computational intelligence to improve the knowledge delivery in an emerging learning mode, namely adaptive micro open learning, which naturally has high demand in quality and quantity of data to be fed. In this study, we contribute a novel approach to tackle the current scarcity of both data and rules in micro open learning, by adopting evolutionary algorithm to produce association rules with both rare and negative associations taken into account. These rules further drive the generation and optimization of learner profiles through refinement and …

Deep Sequence Labelling Model For Information Extraction In Micro Learning Service, Jiayin Lin, Zhexuan Zhou, Geng Sun, Jun Shen, David Pritchard, Tingru Cui, Dongming Xu, Li Li, Ghassan Beydoun

Faculty of Engineering and Information Sciences - Papers: Part B

Micro learning aims to assist users in making good use of smaller chunks of spare time and provides an effective online learning service. However, to provide such personalized online services on the Web, a number of information overload challenges persist. Effectively and precisely mining and extracting valuable information from massive and redundant information is a significant preprocessing procedure for personalizing online services. In this study, we propose a deep sequence labelling model for locating, extracting, and classifying key information for micro learning services. The proposed model is general and combines the advantages of different types of classical neural network. Early …

Refinement And Augmentation For Data In Micro Learning Activity With An Evolutionary Rule Generators, Geng Sun, Jiayin Lin, Tingru Cui, Jun Shen, Dongming Xu, Mahesh Kayastha

Faculty of Engineering and Information Sciences - Papers: Part B

Improving both the quantity and quality of existing data are placed at the center of research for adaptive micro open learning. To cover this research gap, our work targets on the current scarcity of both data and rules that represent open learning activities. An evolutionary rule generator is constructed, which consists of an outer loop and an inner loop. The outer loop runs a genetic algorithm (GA) to produce association rules that can be effective in the micro open learning scenario from a small amount of available data sources; while the inner loop optimizes generated candidates by taking into account …

Ensemble Machine Learning Approaches For Webshell Detection In Internet Of Things Environments, Binbin Yong, Wei Wei, Kuan-Ching Li, Jun Shen, Qingguo Zhou, Marcin Wozniak, Dawid Polap, Robertas Damasevicius

Faculty of Engineering and Information Sciences - Papers: Part B

The Internet of things (IoT), made up of a massive number of sensor devices interconnected, can be used for data exchange, intelligent identification, and management of interconnected “things.” IoT devices are proliferating and playing a crucial role in improving the living quality and living standard of the people. However, the real IoT is more vulnerable to attack by countless cyberattacks from the Internet, which may cause privacy data leakage, data tampering and also cause significant harm to society and individuals. Network security is essential in the IoT system, and Web injection is one of the most severe security problems, especially …

Can Digital Media Affect The Learning Approach Of Medical Students?, Sonali Prashant Chonker, Hester Lau Chang Qi, Tam C. Ha, Melissa Lim, Mor Jack Ng, Kok Hian Tan

Faculty of Social Sciences - Papers (Archive)

Background: Students' learning approaches have revealed that deep learning approach has a positive impact on academic performance. There are suggestions of a waning interest in deep learning to surface learning. Aim: To assess if digital media can reduce the incidence of surface learning approach among medical students Method: A digital video introducing three predominant learning approaches (deep, strategic, surface) was shown to medical students between March 2015 and January 2017. The Approaches and Study Skills Inventory for Students (ASSIST), was administered at the beginning and end of their clinical attachment, to determine if there were any changes to the predominant …

Supporting Self-Regulated Learning In Online Learning Environments And Moocs: A Systematic Review, Jacqueline Wong, Martine Baars, Dan Davis, Tim Van Der Zee, Geert-Jan Houben, Fred Paas

Faculty of Social Sciences - Papers (Archive)

Massive Open Online Courses (MOOCs) allow learning to take place anytime and anywhere with little external monitoring by teachers. Characteristically, highly diverse groups of learners enrolled in MOOCs are required to make decisions related to their own learning activities to achieve academic success. Therefore, it is considered important to support self-regulated learning (SRL) strategies and adapt to relevant human factors (e.g., gender, cognitive abilities, prior knowledge). SRL supports have been widely investigated in traditional classroom settings, but little is known about how SRL can be supported in MOOCs. Very few experimental studies have been conducted in MOOCs at present. To …

Learning And Teaching In Culturally Diverse Classrooms, Skye Playsted

Faculty of Social Sciences - Papers (Archive)

No abstract provided.

Cooperative Secondary Voltage Control Of Static Converters In A Microgrid Using Model-Free Reinforcement Learning, Edward Smith, Duane A. Robinson, Ashish P. Agalgaonkar

Faculty of Engineering and Information Sciences - Papers: Part B

Agent-based secondary voltage regulation in an islanded MicroGrid is complicated by non-linear system dynamics, state couplings and uncertain communication network topology information. This paper proposes an off-policy learning algorithm for cooperative secondary voltage control which can synthesize an optimal feedback controller in real-time without knowledge of the system model. A simulation model has been developed using MATLAB/Simulink, which demonstrates a working controller. Results from the simulations are included, and practical considerations regarding implementation on a real system discussed.

Two Studies Of The Empirical Basis Of Two Learning Resource-Oriented Motivational Strategies For Gifted Educators, Anamaria Vladut, Wilma Vialle, Albert Ziegler

Faculty of Social Sciences - Papers (Archive)

Two learning resource-oriented motivational strategies for gifted educators are introduced: a homeostatic orientation that aims for balance and an allostatic orientation that aims at growth. In order to establish the empirical basis of these motivational strategies, two studies were conducted with samples of students from a specialized post-secondary business school who were enrolled in grades 11–13. Study 1 focused on the empirical basis of the homeostatic orientation. It was shown that the availability of learning resources is associated with two forms of balance within an actiotope: robustness and resilience. Furthermore, it could be shown that the effects of exogenous learning …

Meet Them Where They Are: Bringing The Learning Co-Op Into The Digital Space, Kristy Newton, Courtney A. Shalavin

Senior Deputy Vice-Chancellor and Deputy Vice-Chancellor (Education) - Papers

The University of Wollongong (UOW) Learning Co-Op developed an online portal to complement its physical services, providing support for the development of students’ academic, information, and digital literacies. A user-centred design process was used to identify student needs and create meaningful, relevant content. The project employed student partners to ensure the inclusion of a strong student voice, and integrated a peer-led design strategy where the student partners identified and advocated for the needs of other students. The project utilised a collaborative approach to the creation of resources and service models, working with UOW students and staff from multiple professional units.

What Is The Impact Of Professional Learning On Physical Activity Interventions Among Preschool Children? A Systematic Review, Michele Peden, Anthony D. Okely, Michelle J. Eady, Rachel A. Jones

Faculty of Social Sciences - Papers (Archive)

The purpose of this systematic review was to investigate professional learning models (length, mode, content) offered as part of objectively measured physical childcare-based interventions. A systematic review of eight electronic databases was conducted to June 2017. Only English, peer-reviewed studies that evaluated childcare-based physical activity interventions, incorporated professional learning and reported objectively measured physical activity were included. Study designs included randomized controlled trails, cluster randomized trials, experimental or pilot studies. The search identified 11 studies. Ten studies objectively measured physical activity using accelerometers; five studies used both accelerometer and direct observation tools and one study measured physical activity using direct …

The Predominant Learning Approaches Of Medical Students, Sonali P. Chonkar, Tam C. Ha, Sarah Chu, Ada X. Ng, Melissa Lim, Tat X. Ee, Mor J. Ng, Kok H. Tan

Faculty of Social Sciences - Papers (Archive)

Background By identifying medical students’ learning approaches and the factors that influence students’ learning approaches, medical schools and health care institutions are better equipped to intervene and optimize their learning experience. The aims of our study is to determine the predominant learning approach amongst medical students on a clinical posting in a hospital in Singapore and to examine the demographic factors that affect their learning approach. Methods The Approaches and Study Skills Inventory for Students (ASSIST) questionnaire was administered to 250 medical students from various medical schools on clinical attachment to the Obstetrics and Gynaecology (O&G) department of KK Women’s …

Towards Sustainable Technology-Enhanced Innovation In Higher Education: Advancing Learning Design By Understanding And Supporting Teacher Design Practice, Sue Bennett, Lori Lockyer, Shirley Agostinho

Faculty of Social Sciences - Papers (Archive)

Improving teacher design promises to be a scalable, sustainable approach to building capacity amongst a workforce faced with complex and evolving drivers of change in higher education worldwide. While design has long been recognised as a routine part of teaching, there has been renewed interest in supporting and understanding the design work that teachers do to foster innovation, particularly in technology-enhanced learning, at institutional scale by influencing teachers' practices. Re-framing teaching as design usefully emphasises the creative problem-solving needed to balance pedagogical, logistical and technical considerations within specific educational contexts, tailored to learners' needs. There is potential for this re-framing …

Fostering Effective Early Learning (Feel) Study: Final Report, Iram Siraj, Edward Melhuish, Steven J. Howard, Cathrine Marguerite Neilsen-Hewett, Denise Kingston, Marc De Rosnay, Elisabeth Duursma, Xiaoqi Feng, Betty Luu

Faculty of Social Sciences - Papers (Archive)

The 2018 Fostering Effective Early Learning (FEEL) study focuses on the importance of quality, and how to strengthen it in early childhood education and care (ECEC) settings. Extensive research demonstrates that the benefits of ECEC for children are increased when the service provider and educators are highly skilled and participate in professional development (PD), and the service is of high quality. Upskilling the workforce, including in-service professional development, is considered to be a key to improving quality, and can produce substantial and practical improvements for staff and children alike. Building on the existing body of international research, the findings of …

Employability In A Global Context: Evolving Policy And Practice In Employability, Work Integrated Learning, And Career Development Learning, Martin Smith, Kenton Bell, Dawn Bennett, Alan Mcalpine

Faculty of Social Sciences - Papers (Archive)

This research project was activated to explore trends emerging in the intersecting domains of employability, work-integrated learning, and career development learning. In late 2015, researchers, academics, and career practitioners from Australia, the United Kingdom and Canada gathered to attend an Employability Masterclass at the University of Wollongong. Attendees explored questions around employability in vocationally specific and non-vocationally specific degrees. The language and conversations highlighted the influence of global contexts on strategies and practices in transnational settings-specifically, how employability is defined and supported across the breadth of university activity.

Mlaas: A Cloud-Based System For Delivering Adapative Micro Learning In Mobile Mooc Learning, Geng Sun, Tingru Cui, Jianming Yong, Jun Shen, Shiping Chen

Faculty of Engineering and Information Sciences - Papers: Part B

No abstract provided.

Establishing A Framework For Learning To Teach English Pronunciation In An Australian Tesol Program, Michael S. Burri, Amanda Ann Baker, Honglin Chen

Faculty of Social Sciences - Papers (Archive)

A substantial number of studies have been conducted in various second language teacher education settings. Yet, evidence about the effectiveness of teacher preparation continues to be debated and research findings about the efficacy of preparing language teachers are still somewhat inconclusive. As a further complication, even though pronunciation has regained some of its prominence in second language teaching, only minimal understanding exists about the preparation of pronunciation instructors in teacher education. The aim of this paper is to address this gap and to advance our understanding of teacher learning by first combining the findings from four research-based articles on learning …

Identifying The Characteristics Of Support Australian University Teachers Use In Their Design Work: Implications For The Learning Design Field, Shirley Agostinho, Lori Lockyer, Sue Bennett

Faculty of Social Sciences - Papers (Archive)

Quality teaching is a strategic objective for universities; thus, there is an expectation that university teachers design high quality learning experience for their students. The field of learning design has developed over the past 15 years as a way to support teachers in their design work. There has been significant research and development work that has focused on creating support tools to help teachers plan, develop and deliver learning experiences. However, little is known about what supports teachers access and use when they design and overall how teachers undertake their design work. This paper presents the findings from a qualitative …

Ethnography In Work Integrated Learning Research, Bonnie Amelia Dean, Christopher S. Sykes, Jan Turbill

Senior Deputy Vice-Chancellor and Deputy Vice-Chancellor (Education) - Papers

This paper introduces and discusses ethnography as a methodological approach to investigate phenomena at the place of practice in WIL. The commensurability of ethnography for examining WIL 'in situ' is presented in order to delve deeper into WIL phenomena on placement through greater temporal and physical proximity. Part of the reason we haven't been able to fully understand student learning on placement, for example, is because of a lack of awareness and uptake of methodologies that employ direct observation in WIL spaces. Ethnography could open the door to investigating a range of research areas previously obscured or inaccessible by methodologies …

Retention In Enhanced Team Based Learning Course: Retain Or Refrain?, Janil Puthucheary, Sok H. Goh, Tam C. Ha, Doyle G. Graham, Sandy Cook

Faculty of Social Sciences - Papers (Archive)

Students’ ability to retain content in medical school has always been a concern. At Duke-NUS Medical School, we modified our Team-Based Learning (TBL) classes known as TeamLEAD, a learning strategy for first year basic science content, to include an open/closed-book option in the readiness assurance phase to engage teams in deeper discussion. We hypothesize that the open-book option allows students to engage in deeper learning in their teams, which leads to an improvement in retention ability for each individual student at the end of their first year basic science curriculum.

Methods: A total of 115 MCQs used throughout first year …

A Multidisciplinary Learning Experience Contributing To Mental Health Rehabilitation, Lorna Moxham, Christopher F. Patterson, Ellie K. Taylor, Dana J. Perlman, Susan Sumskis, Renee M. Brighton

Faculty of Science, Medicine and Health - Papers: part A

Purpose People who access health services often have a range of needs that require the involvement of members from a multidisciplinary team. Teaching future health professionals about the importance of a multidisciplinary approach can be challenging. The aim of this paper is to describe a project called Recovery Camp that enhanced multidisciplinary health education through experiential and immersive engagement with people experiencing mental illness.

Method Future health professionals and people with a lived experience of mental illness took part in Recovery Camp - an innovative five-day therapeutic recreation initiative in the Australian bush. Results are presented in a case study …