Digital Commons Network^™

Embodiment As A Pedagogical Tool To Enhance Learning, Myrto F. Mavilidi, Kim Ouwehand, Mirko Schmidt, Catarina Pesce, Phillip D. Tomporowski, Anthony D. Okely, Fred Paas

Faculty of Arts, Social Sciences and Humanities - Papers

This chapter focuses on practical implications of embodiment to facilitate learning in educational contexts. Starting from a brief historical overview of the scientific debate of action-perception that forms the genesis of embodiment, the chapter progresses to later influential theories. Contemporary trends are discussed in light of theories of embodied cognition, emphasising the importance of body movements in shaping higher-order cognitive processing and how embodied cognitive neuroscience links the brain, the body, and the broader environment. In reviewing the literature, empirical studies with movements are explored in relation to their type of embodiment (e.g., gestures, simulation, whole-body movements, physical activity), educational …

Editorial: Women And Leadership In Higher Education Learning And Teaching, Kerryn Butler-Henderson, Angela Carbone, Marcia Devlin, Rosalind Bull, Jo Coldwell-Neilson, Susan H. Fenton, Tanya Fitzgerald, Catherine Lang

Journal of University Teaching & Learning Practice

In this Special Issue Harvey and Jones state “It is time for women academics to accept the challenge – to rightfully claim their leadership”. We recognise the many women who have challenged the system, and those whose efforts have been thwarted. We encourage women and men to work together to break down the barriers of gender, race, culture, and religion, so that our current and next generation of female academics can rightfully claim their leadership. This Special Issue is an important step to bringing to light these challenges for women and the changes required to grow and support women in …

Investigating The Relationships Between The Feedback Practices Of Lecturers And Students In The Context Of Assessment And Learning Within A Postgraduate Business School, Mark David Middleton

University of Wollongong Thesis Collection 2017+

It is commonly agreed that feedback is a key component of higher education and critical for learning. Despite decades of research problems with feedback are still reported. Lecturers and students describe issues with feedback such as, timing, quality, usefulness, use of, effectiveness, and recipience. There are also differences between lecturers’ and students’ perceptions of feedback as well as among students and lecturers. The last two decades of research have repositioned feedback from something provided to students, to an ongoing dialogic process, with a focus on the development of feedback literacy. Whilst there is a growing body of research focusing on …

Using Deliberate Mistakes To Heighten Student Attention, Abey P. Philip, Dawn Bennett

Journal of University Teaching & Learning Practice

Attracting and retaining students’ attention is a concern for educators at every level of education, including those in higher education. Despite compelling evidence that student-centred pedagogies enhance attention, motivation and learning gain, exposition-centred delivery in forms such as lectures persists across higher education. Contemporary research on student attention suggests that student concentration in class begins to wane within 10 minutes; that neither tutorials or lectures tend to engage students effectively; and that the optimum length of a lecture is as little as 30 minutes. Where previous studies of student attention have focussed on the impacts of active listening, flipped classrooms …

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 …

Learning To Read Equine Agency: Sense And Sensitivity At The Intersection Of Scientific, Tacit And Situated Knowledges, Sanna Karkulehto, Nora Schuurman

Animal Studies Journal

The aim of this essay is to address the challenges and problems in communicating with horses and interpreting their communication in everyday handling and training situations. We seek ways to learn more about equine communication and agency in the prevention of cruelty against animals and in enhancing animal welfare. We ask how it would be possible to learn to read the subtle signs of equine communication and agency in a sensible, sensitive, and ethical way to increase the health and wellbeing of horses that humans interact with. We have placed this theoretical examination in a multidisciplinary framework that consists of …

"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 …

Deep Autoencoder For Mass Spectrometry Feature Learning And Cancer Detection, Qingguo Zhou, Binbin Yong, Qingquan Lv, Jun Shen, Xin Wang

Faculty of Engineering and Information Sciences - Papers: Part B

Cancer is still one of the most life threatening disease and by far it is still difficult to prevent, prone to recurrence and metastasis and high in mortality. Lots of studies indicate that early cancer diagnosis can effectively increase the survival rate of patients. But early stage cancer is difficult to be detected because of its inconspicuous features. Hence, convenient and effective cancer detection methods are urgently needed. In this paper, we propose to utilize deep autoencoder to learn latent representation of high-dimensional mass spectrometry data. Meanwhile, as a contrast, traditional particle swarm optimization (PSO) optimization algorithm are also used …

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 …

Evaluating Techniques For Mapping Island Vegetation From Unmanned Aerial Vehicle (Uav) Images: Pixel Classification, Visual Interpretation And Machine Learning Approaches, Sarah Hamylton, Rowena H. Morris, Rafael Cabral Carvalho, N Roder, P Barlow, K Mills, Lei Wang

Faculty of Science, Medicine and Health - Papers: Part B

We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a …

How Students Learn On Placement: Transitioning Placement Practices In Work-Integrated Learning, Bonnie Amelia Dean, Christopher S. Sykes

Faculty of Science, Medicine and Health - Papers: Part B

Examining learning in work-integrated learning (WIL) courses is complex. WIL traverses work and university spaces, which can be challenging for the way student learning is conceived, planned, supported, assessed and reported. This study strengthens our understanding of how students learn on placement by going directly to the source and observing learning unfold, in situ. Using an ethnographic methodology, this study adopts Schatzki’s (1996, 2010) practice-based lens to illuminate how students learn to embody and accomplish their assigned tasks on WIL placement. Findings suggest that students initially learn through performing an intermediary cluster of practices that enable them to orient, adapt …

5 Tips To Help Parents Navigate The Unique Needs Of Children With Autism Learning From Home, Amanda A. Webster

Faculty of Arts, Social Sciences and Humanities - Papers

Children on the autism spectrum will face unique challenges as they learn from home during the COVID-19 shutdown. These children process information and learn in different ways to their peers. They may find it more difficult to independently complete tasks and struggle with managing their time. They are also more likely to have difficulty in writing tasks or ones involving high amounts of language and communication with others. Children on the autism spectrum often associate specific tasks with locations. This might mean they resist doing schoolwork at home. Anxiety levels, which are often high in this group of students, may …

Leadership For Learning Frameworks, Kylie Lipscombe, Sue Bennett, Paul Andrew Kidson, Paul Gardiner, Ann Mcintyre

Faculty of Arts, Social Sciences and Humanities - Papers

The purpose of this report is to present the findings of a commissioned research study by the University of Wollongong (UOW) for the NSW DoE School Leadership Institute (SLI). The study is focused on examining the conceptualisation and design of three Leadership for Learning Frameworks implemented as part of the Aspiring Principals Leadership Program (APLP).

Conducting Qualitative Longitudinal Research On Learning To Teach English Pronunciation: Challenges, Pitfalls…Coffee, And Bubbles!, Michael S. Burri

Faculty of Arts, Social Sciences and Humanities - Papers

Inquiries into the impact of second language teacher education on the development of teachers' practices, beliefs, and knowledge have increased substantially in the last few years. However, most studies tend to investigate the process of second language teacher learning over a relatively short period of time, and only limited literature addresses methodological considerations in longitudinal research, making the design of this type of study potentially challenging for researchers. The aim of this paper is to first describe an ongoing project which explores the process of teachers learning to teach English pronunciation over a period of six years. Following an overview …

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 …

Courageous Collaboration In Co-Constructing Learning And Teaching Resources, Helen A. Pratt, Maria T. Mackay, Claudia Green, Gay Woodhouse, Kelly A. Marriott-Statham

Faculty of Science, Medicine and Health - Papers: Part B

Background: This paper describes the experiences of a group of academics in a metropolitan university who were invited to collaborate in the co-construction of a postgraduate nursing subject. The principles of practice development and person-centred practice informed our ways of working. This reflection was undertaken by unpacking shared assumptions, using Mezirow’s transformative model of critical reflection.

Aim: The aim of this reflection was to share the experiences of an academic team in collaboratively designing face-to-face learning opportunities for a masters of nursing subject and to invite others to consider this valuable way of working.

Conclusions: Three conclusions were realised within …

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.

Observational Research In Work-Integrated Learning, Bonnie Amelia Dean

Faculty of Science, Medicine and Health - Papers: Part B

Observational research has a long history in many disciplines, such as education and organizational studies, yet has had slow uptake in the scholarship of work-integrated learning (WIL). Observational research enables the researcher to journey inside workplace or community sites where actions and conversations unfold, to unpack the complexities of work, learning and practice. This paper looks at observational methodologies and their use in WIL research, highlighting practical methods for accessing and generating data, and discussing criteria for judging the quality of observational research. It introduces WIL researchers to alternative methods to elicit data, to consider making their bodies, thoughts and …