Implementing Aproiri Algorithm for Predicting Result Analysis

University or Higher Learning Institution is aplatform to train students in specific domain area that willbecome an asset for a country. One of the critical issues inUniversity is to avoid dropout students. Educational DataMining (EDM) is an emergent discipline in developing methodsto explore the unique types of data from the educationalcontext. One of the techniques applied in EDM is an AssociationRules (AR) which is to find a pattern of one element influencingother element. In this paper, AR technique has been utilized topredict students’ results based on a group of the previousstudents results. Clustering method has been used to classify thespecific subject category. Finally, a system known as ResultPrediction System (REPS) has been developed to performautomatically the AR analysis on the academic data using PHPand MYSQL databases

CONCEPTUAL FRAMEWORK OF EDUTAINMENT ANIMATED SERIES FOR CHILDREN: A PIOUS STORY

ABSTRACT The objective of this study was to develop a conceptual framework for edutainment animated series for children taking into consideration a pious story. The conceptual framework has been designed and considered as the first step to ensure attainment of the edutainment animated series. Nowadays, multimedia technology plays an important role to deliver the desired information. Animation is one of the ways used to educate children. Most animations have been brought in which implicitly deliver negative values such as violence and aggressiveness. Due to this factor, local animated series is crucial to be produced to suit with the local moral values. The pious story has been selected and designed to provide the children with the good moral values to be practiced by a good Muslim. Expert review has been conducted with two experts to validate the component in the conceptual framework. The instrument used is questionnaire with 5.00 point Likert scale. The result shows the elements in the conceptual framework are successfully implemented with overall means are above 4.00 of Likert Scale score. The designed framework could be serving as a catalyst to promote good moral value for animated series which could be used worldwide to develop Islamic edutainment

Motivasi Pembelajaran Kendiri Bahasa Arab dalam Kalangan Pelajar Sekolah Rendah melalui Teknologi: EZ-Arabic sebagai Aplikasi dan Penilaian

As attached in the research repor

Framework Of Extrinsic Feedback Evaluation Using Motion Capture For Martial Arts

Capturing and analysing human motion using the motion capture (MoCap) technique is a rapidly growing research area due to a large number of potential applications and its inherent complexity. In martial arts (MAs), MoCap is used widely to evaluate human performance. MoCap normally requires motion recognition (MoRec) to translate the movements executed into meaningful forms. MoRec can be used to produce intrinsic and extrinsic feedback (EF) to evaluate MAs. MAs promote a sense of identity and culture, and as such are considered part of the national heritage in certain countries. However, the evaluation systems using MoCap for MAs are scarce due to the absence of a complete framework of evaluation systems for MAs. Furthermore, common approaches to MoRec require very large training and validation sets. MoRec using Gesture Description Language (GDL) and Reverse-GDL (R-GDL) approaches is insufficient to evaluate MAs techniques because both approaches are not designed to produce results in the form of EF. Therefore, a framework for evaluating EF using MoCap for MAs called EFE-MoCap has been developed. The framework comprises designs of templates, Frames-Based Rules-Ranges (FBRR) and Score Rubric Assessment (SRA) to create the MAs motion templates; create rules-ranges for the created motion templates for publishing EF, and evaluate the framework for a traditional Malay MAs

Evaluating Extrinsic Feedback of Martial Art Techniques Using Minimal Values of Rules in Frame-Based Rules Ranges

Martial arts (MAs) can be considered as a preserved heritage. The evaluations of MAs which are normally in form of extrinsic feedback (EF) such as existence of the technique patterns, speed of accomplishing the techniques and level of confidence however are still focusing on conventional method due to there is a few research on EF for MAs evaluation using advanced technologies. Even Frame-Based Rules Ranges (FBRR) approach using motion capture technology have been implemented to measure the sequence of steps in MA techniques, the remaining rules in the sequence are diverse which make it difficult to determine the existence of steps and to produce EF. Therefore, a standardised minimal value for each rule (MinRule) of FBRR has been proposed in this paper to become as a main reference for measuring the existence of steps in the sequence. TEN MA performers have been involved to test MinRule by executing FOUR selected techniques in SSCM. The MinRule for the FOUR techniques have been successfully produced, evaluated and compared. Using FBRR approach with the produced MinRule, its' accuracy has achieved very high result, thus can be used to measure the sequence of steps as well as to produce EF for MA

Developing new robust motion templates of martial art techniques using R-GDL approach: a case study of SSCM

Martial art (MA) is considered a conserved heritage primarily for promoting certain level of identities and cultures. With the technology advancement, motion capture has been widely used in MA to capture and evaluate human performance. However, methods to create motion templates (templates) of MA techniques from scratch are rarely exposed because there is no complete evaluation system framework suggested for MA. This paper presents in detaile how to create the MA templates using framework of extrinsic feedback-based evaluation system generally and R-GDL specifically. To create more robust templates, GDL has been used in validation tests. SSCM becomes the case study in this research. The main contribution in this paper is introduction of new datasets of templates for SSCM techniques. Evaluation of trainees' performance will be done using the datasets for future works. The datasets are believed to promise MAs' authenticity and originality and to preserve this valuable cultural heritage

The development concept of enhanced visualization-based augmented reality applications in education

This concept paper discusses the proposed design and development of augmented reality (AR) applications based on enhanced visualization. Previous development studies used marker-based techniques in developing applications. Development studies involving marker less techniques and three-dimensional (3D) object recognition in education are still understudied. This study will develop an application based on enhanced visualization through the use of 3D object recognition techniques. The theories and models underlying the study consist of constructivist learning theory, behaviourist learning theory, user experience (UX) design process models, and enhanced visualization. In order to evaluate the usability of the developed application, the UX component evaluation model is used. The design and development of AR applications using 3D object recognition techniques is expected to achieve the value of expert agreement through the Fuzzy Delphi method and provide a different experience to users through a more dynamic process without targeting two-dimensional (2D) images as markers while being able to meet the evaluation of UX components which includes product perception, consumer emotions, consequences of use and overall product evaluation

Measuring the sequence of steps in martial art techniques using frame-based rules ranges of the motion templates

Martial arts (MAs) can be considered as a preserved heritage. Motion capture (MoCap) techniques have been used in various applications of MAs preservation, such as: producing 3D models; performance testing results; and system platforms development. MoCap requires motion recognition (MoRec) technique to translate the motions executed into meaningful forms. MoRec measures accuracy of rules towards certain movements which is in perspective of machine learning algorithm without emphasizing aspects to be assessed in MA perspective. Sequence of steps is one of the important aspects in measuring the effectiveness of MA techniques. The sequence of steps may reflect certain MA technique due to the accuracy of consecutive steps being executed. Incorrect steps in MA technique may cause harm and even fatal injuries. In this paper, Frame-Based Rules-Ranges (FBRR) approach is proposed to measure the sequence of steps in MA technique. Implementation and evaluation of FBRR for templates of MA techniques are discussed by experimenting FOUR SSCM techniques. The results show that the templates with FBRR have reduced redundant and irrelative rules in the sequence that leads to a better measurement of the sequence of steps. These templates with FBRR are ready to be tested to the other MA practitioners including trainers and trainees in order to validate and verify their techniques