Learning kits as online learning guidelines in Master of Early Childhood education programme

The master degree programme in early childhood education is a postgraduate degree programme in Open University Malaysia (OUM) designed for adult students wishing to further their studies in early childhood online. The learning kit was organised to become a guide and companion to students learning adventure in this programme. Thus this paper discusses the use of learning kit as online learning guideline for students enrolled in the Master of Early Childhood Education (MECHE) programme in OUM. This paper will also describe how learning kit can be used to assist online students in their studies for one semester. In this study, a total of 20 students from MECHE programme were selected purposively. Quantitative data was taken from questionnaires and qualitative data was taken through interviews and open ended questions. The data was analysed using the thematic analysis. The result showed that the students found the learning kit easily accessible and helpful in guiding them to study in this course. (Abstract by authors

Classification Problem in Imbalanced Datasets

Classification is a data mining task. It aims to extract knowledge from large datasets. There are two kinds of classification. The first one is known as complete classification, and it is applied to balanced datasets. However, when it is applied to imbalanced ones, it is called partial classification or a problem of classification in imbalanced datasets, which is a fundamental problem in machine learning, and it has received much attention. Considering the importance of this issue, a large amount of techniques have been proposed trying to address this problem. These proposals can be divided into three levels: the algorithm level, the data level, and the hybrid level. In this chapter, we will present the classification problem in imbalanced datasets, its domains of application, its appropriate measures of performances, and its approaches and techniques

A Distributed Clustering Approach for Heterogeneous Environments Using Fuzzy Rough Set Theory

Vast majority of data mining algorithms have been designed to work on centralized data, unfortunately however, almost all of nowadays data sets are distributed both geographically and conceptually. Due to privacy and computation cost, centralizing distributed data sets before analyzing them is undoubtedly impractical. In this paper, we present a framework for clustering distributed data which takes into account privacy and computation cost. To do that, we remove uncertain instances and just send the label of the other instances to the central location. To remove the uncertain instances, we develop a new instance weighting method based on fuzzy and rough set theory. The achieved results on well-known data verify effectiveness of the proposed method compared to previous works

Teachers’ Perception of Technology Integration Easiness in Teaching Preschool Children

Despite the technology included in the National Preschool Standard-based Curriculum, teachers in Malaysian preschool are yet to fully integrate technology to enhance children’s learning in the classroom. Concerns such as how the preschool teacher perceived the easiness of technology integration became our main focus in this study. It is believed that teachers’ acceptance and readiness influenced the outcomes of the technology used in teaching and learning pre-schoolers. This study employed a quantitative approach and data collection through a survey to investigate the teacher’s perception towards technology integration in the preschool settings based on the Technology Acceptance Model (TAM). A total of 50 teachers in this survey were selected through random sampling from eight private preschools in Bandar Puteri, Puchong. Nevertheless, only 30 questionnaires were returned by the teachers. The survey was done through a questionnaire using a 5-point Likert scale. The data has been collected and analysed using the Statistical Package for Social Science (SPSS) to get the frequencies, percentages, and means of the teachers’ perception of technology integration in teaching and learning. This study found that teachers aged 30 to 39 have the highest perception of technology integration in teaching and learning, and Science and Technology is the most suitable area to teach children with technology

Multisensory Interactions of Visual and Tactile Modalities

Theorien und Modelle der multisensorischen Wahrnehmung haben in den letzten Jahren Aufmerksamkeit erregt. Das Verständnis der multisensorischen Wahrnehmung ist für Kognitionswissenschaftler von großem Interesse und für Ingenieure von entscheidender Bedeutung, um künstliche sensorische Geräte zu entwickeln. Das Berührungspotential für künstliche sensorische Geräte sowie die starke Verbindung zwischen Berührung und Sehen haben uns motiviert, die Wechselwirkungen zwischen Sehen und Berührung zu erforschen, wobei der Schwerpunkt auf Berührungsstimulationen mit einem speziell entwickelten künstlichen sensorischen Gerät liegt. Insbesondere untersuchten wir drei verschiedene Arten von Interaktionen in drei Studien: Die multisensorische Wahrnehmung und Kalibrierung für visuell-taktile Informationen in einer realistischen Umgebung (Studie 1), den multimodalen aufgabenunrelevanten Effekt (Studie 2) und schließlich das modalübergreifende Lernen und Integrieren von Sehen und Berühren unter neuartigen taktilen Erfahrungen (Studie 3). In Studie 1 wurde untersucht, wie sich die Teilnehmer unter verschiedenen Zuverlässigkeitsbedingungen an den Cue-Konflikt zwischen sensorischen Informationen anpassen würden. Unsere Ergebnisse zeigten, dass die Teilnehmer je nach Zuverlässigkeitsbedingung der sensorischen Informationen von einer Integrationsstrategie zu einer Auswahl oder zu einer Kalibrierungsstrategie wechselten. Unsere umfassende Simulation und Modellierung hat gezeigt, dass die optimale kausale Inferenz in einer Umgebung mit variierender Zuverlässigkeit nicht nur vom Ausmaß der multimodalen Diskrepanz abhängt, sondern auch von der relativen Zuverlässigkeit der Stimuli. Analysen der Vertrauensberichte zeigten, dass wir in Studie 2 untersucht haben, wie sich aufgabenunrelevante Informationen auf die Verarbeitung aufgabenrelevanter Informationen in einem multimodalen Setup auswirken. Insbesondere haben wir die bekannte Simon-Aufgabe auf die multimodale Ausgabe erweitert, in der aufgabenunrelevante Informationen aus zwei sensorischen Modalitäten hervorgehen können. Wir haben eine visuell-taktile und eine visuell-auditive Erweiterung der Simon-Aufgabe durchgeführt. Beide Experimente zeigten erwartete visuelle Kongruenzeffekte für aufgabenunrelevante Informationen, wie z. B. langsamere Reaktionen und geringere Genauigkeit bei inkongruenten als bei kongruenten Bedingungen. Wir beobachteten auch Kongruenzeffekte von taktilen aufgabenunrelevanten Informationen, obwohl die Effekte geringer waren als die visuellen aufgabenunrelevanten Informationen. Die Kongruenzeffekte auditorisch aufgabenunrelevanter Informationen waren jedoch unzureichend und vernachlässigbar. Es zeigte sich, dass bei gleichzeitiger Anwesenheit von visuellen und auditorischen räumlich aufgabenunrelevanten Informationen visuelle Informationen den auditorischen Kongruenzeffekt dominieren. Eine vorgeschlagene multimodale Erweiterung des Diffusionsmodells für Konfliktaufgaben (MDMC) wurde an die Ergebnisse beider Experimente angepasst. MDMC lieferte angemessene Anpassungen für die experimentellen Daten, während die echten Annahmen von DMC beibehalten wurden. In Studie 3 haben wir schließlich untersucht, ob und wie künstliche taktile Informationen von einem neuartigen nicht-invasiven Gerät gelernt und in visuelle Informationen integriert werden. Die Leistung der unimodalen taktilen Wahrnehmung wurde über sieben Trainingsblöcke verbessert und zeigte, dass die Teilnehmer die Assoziationen zwischen visuellen und taktilen Informationen lernten. Weitere Analysen zeigten, dass die Teilnehmer die unerfahrenen taktilen Informationen von Beginn des Trainings an mit erfahrenen visuellen Informationen kombinierten, obwohl die Genauigkeit der taktilen Modalität anfangs unter bestimmten Bedingungen geringer war als die visuelle Modalität. Vorgeschlagene Rechenmodelle zeigten, dass die Teilnehmer zunächst eine metakognitiv orientierte Entscheidungsintegrationspolitik anwendeten. Später wechselten sie jedoch zu einer optimalen Bayes'schen Integration sensorischer Eingaben. Wir glauben, dass unsere Ergebnisse das Gebiet der multisensorischen Wahrnehmung mit der Entwicklung künstlicher sensorischer Geräte verbindenTheories and models of multisensory perception have been drawing attention in the past decade. Understanding the multisensory perception is great of interest for cognitive scientists and is crucial for engineers to develop artificial sensory devices such as wearable and sensory substitution systems. The potential of touch for artificial sensory devices as well as the strong link between touch and vision motivated us to study the interactions of vision and touch with the focus on touch stimulations from a custom designed artificial sensory device. Specifically, we investigated three different type of interactions through three studies: The multisensory perception and calibration for visual-tactile information in a realistic environment (study 1), multimodal task-irrelevant effect (study 2), and finally cross-modal learning and integration of vision and touch under novel tactile experiences (study 3). Study 1 investigated how participants would adjust their perception to the discrepancy among sensory information under varying reliability conditions. Our findings showed participants switched from an integration strategy to a selection or to a calibration strategy according to reliability condition of the sensory information. Our comprehensive simulation and modelling revealed that the optimal causal inference not only depends on the amount of the cue conflict, but also on the relative reliability of stimuli across different modalities. We investigated, through study 2, how task irrelevant information affects the perception of task relevant information in a multimodal setup. Particularly, we extended the well-known Simon experiment to the multimodal edition, in which two source of information, from two modalities, deliver the task irrelevant information. We conducted a visual-tactile and a visual-auditory extension of Simon task. Both experiments showed expected visual congruency effects for task-irrelevant information, such as the slower responses and less accurcy in incongruent than congruent conditions. We additionally observed congruency effects of tactile task-irrelevant information, although the effects were smaller than the visual task-irrelevant information. However, the congruency effects of auditory task-irrelevant information were insufficient and negligible. It revealed that in the co-presence of visual and auditory spatial task-irrelevant information, visual information dominates the auditory congruency effect. A proposed multimodal extension of the Diffusion Model for Conflict Tasks (MDMC) was fitted to the results of both experiments. MDMC provided reasonable fits for the experimental data while keeps the genuine assumptions of DMC. We finally investigated, through study 3, whether and how tactile information from a non invasive sensory feedback device can be learned or even integrated with visual perception. The performance of unimodal tactile perception was improved over seven blocks of training, showed that participants learned the associations between the visual and tactile information. Further analyses showed that participants integrated the unexperienced tactile information with experienced visual information from the very beginning of the training, despite of the fact that the accuracy of tactile modality was initially lower than the visual modality in some conditions. Proposed computational models revealed that participants initially employed a metacognitive oriented decision integration policy. However, they later switched to an optimal Bayesian integration of sensory inputs. We believe our findings connects the topic of multisensory perception to the artificial sensory feedback devices

High Performance and Optimal Configuration of Accurate Heterogeneous Block-Based Approximate Adder

Approximate computing is an emerging paradigm to improve power and performance efficiency for error-resilient application. Recent approximate adders have significantly extended the design space of accuracy-power configurable approximate adders, and find optimal designs by exploring the design space. In this paper, a new energy-efficient heterogeneous block-based approximate adder (HBBA) is proposed; which is a generic/configurable model that can be transformed to a particular adder by defining some configurations. An HBBA, in general, is composed of heterogeneous sub-adders, where each sub-adder can have a different configuration. A set of configurations of all the sub-adders in an HBBA defines its configuration. The block-based adders are approximated through inexact logic configuration and truncated carry chains. HBBA increases design space providing additional design points that fall on the Pareto-front and offer better power-accuracy trade-off compared to other configurations. Furthermore, to avoid Mont-Carlo simulations, we propose an analytical modelling technique to evaluate the probability of error and Probability Mass Function (PMF) of error value. Moreover, the estimation method estimates delay, area and power of heterogeneous block-based approximate adders. Thus, based on the analytical model and estimation method, the optimal configuration under a given error constraint can be selected from the whole design space of the proposed adder model by exhaustive search. The simulation results show that our HBBA provides improved accuracy in terms of error metrics compared to some state-of-the-art approximate adders. HBBA with 32 bits length serves about 15% reduction in area and up to 17% reduction in energy compared to state-of-the-art approximate adders.Comment: Submitted to the IEEE-TCAD journal, 16 pages, 16 figure

Application of virtual learning environment in the teaching of engineering drawing to enhance students' mental rotation skills

Virtual learning environment seems to transform education process in a more flexible way as compared to other modes of learning and have great potential in ensuring successful learning. This study investigates the effectiveness of virtual learning environment in teaching engineering drawing in order to enhance mental rotation skills. A quasi- experimental design study was used involving engineering students in Universiti Teknologi Malaysia. The intervention group in this study was exposed to virtual learning environment courseware. Students in this study were given a pre-test before the intervention and a post-test prior to the intervention. The result of this research indicates that there are significant improvements in the mental rotation skills of the students who were being exposed to the virtual learning environment. This study also investigates the gender differences in visualization skills. Thus, this study shows that using courseware in the teaching of engineering drawing can act as a catalyst in enhancing productivity and quality of engineering drawing. As a result, students are capable of enhancing their visualization skills which is vital in engineering drawing

The Private Preschool Teachers’ Perception of ICT Integration Usefulness in Teaching and Learning During MCO

In the 21st century, one of the modern pedagogical approaches is integrating information and Communication Technology (ICT) in the early childhood curriculum. The purpose of this study is to investigate the private preschool teachers’ perception of integrating ICT and internet usage in teaching and learning during MCO in private preschools. This study employed a quantitative approach, and data collection was gathered through a survey method. A total of 44 private preschool teachers from private preschools located in the Klang Valley were selected through snowball sampling. The survey was done through questionnaires using a 5-point Likert Scale. Quantitative data were analysed through a descriptive method using the Statistical Package for The Social Science (SPSS) software. The study results indicated that young teachers have high perception of ICT integration usefulness, whereas senior teachers need to be given courses that will help them be more confident to handle children learning activities using ICT tools during MCO