International Journal of Modern Education and Computer Science (IJMECS)

IJMECS Vol. 5, No. 5, May. 2013

Cover page and Table of Contents: PDF (size: 734KB)

Table Of Contents

REGULAR PAPERS

Student Learning Ability Assessment using Rough Set and Data Mining Approaches

By A. Kangaiammal R. Silambannan C. Senthamarai M.V. Srinath

DOI: https://doi.org/10.5815/ijmecs.2013.05.01, Pub. Date: 8 May 2013

All learners are not able to learn anything and everything complete. Though the learning mode and medium are different in e-learning mode and in classroom learning, similar activities are required in both the modes for teachers to observe and assess the learner(s). Student performance varies considerably depending upon whether a task is presented as a multiple-choice question, an open-ended question, or a concrete performance task [3]. Due to the dominance of e-learning, there is a strong need for an assessment which would report the learning ability of a learner based on the learning skills under various stages. This paper focuses on assessment through multiple choice questions at the beginning and at the end of learning. The learning activities of the learner are tracked during the learning phase through a Continuous Assessment test to realize the understanding level of the learner. The scores recorded in the database is analyzed using a Rough Set Approach based Decision System. The effectiveness of teaching learning process indicates the learning ability of the learner, presented in a Graphical form. It is evident from the results that the entry behavior and the behavior while learning determine the actual learning. Students generate internal opinion as they monitor their engagement with learning activities and tasks and also assess progress towards goals. Those who are effective at self-regulation, however, produce better feedback or are able to use the self-opinion they generate to achieve their desired goals. The tool developed assists the teacher to be aware of the learning ability of learners before preparing the content and the presentation structure towards complete learning. In other words, the developed tool helps the learner to self-assess the learning ability and thereby identify and focus to gain the lacking skills.

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Question Answering for Collaborative Learning with Answer Quality Predictor

By Kohei Arai Anik Nur Handayani

DOI: https://doi.org/10.5815/ijmecs.2013.05.02, Pub. Date: 8 May 2013

The increasing advances of Internet Technologies in all application domains have changed life styles and interactions. With the rapid development of E-Learning, collaborative learning is an important for teaching, learning methods and strategies. Studies over the years shown that students had actively and more interactively involved in a classroom discussion to gain their knowledge. Students can ask their questions to the classroom discussion when they want to collaborate with others, asking one another for information, evaluating one another’s ideas. Therein, the activity allowing one question has many answer or information that should be selected. Every answer has a weighting and its very subjective to select it. In this paper, we introduce question answering for collaborative learning with answer quality predictor. By using answer quality predictor the quality of the information could be determined. Through the process of collaborative learning, the knowledge base will be enriched for future question answering. Further, not only the student could get answers form others but also provided by the system.

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An Analysis on Performance of Decision Tree Algorithms using Student‟s Qualitative Data

By T. Miranda Lakshmi A. Martin R.Mumtaj Begum V. Prasanna Venkatesan

DOI: https://doi.org/10.5815/ijmecs.2013.05.03, Pub. Date: 8 May 2013

Decision Tree is the most widely applied supervised classification technique. The learning and classification steps of decision tree induction are simple and fast and it can be applied to any domain. In this research student qualitative data has been taken from educational data mining and the performance analysis of the decision tree algorithm ID3, C4.5 and CART are compared. The comparison result shows that the Gini Index of CART influence information Gain Ratio of ID3 and C4.5. The classification accuracy of CART is higher when compared to ID3 and C4.5. However the difference in classification accuracy between the decision tree algorithms is not considerably higher. The experimental results of decision tree indicate that student’s performance also influenced by qualitative factors.

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Analysis of PV-FC Hybrid System Operation Considering Sale Electricity

By Amirali Shahkoomahalli

DOI: https://doi.org/10.5815/ijmecs.2013.05.04, Pub. Date: 8 May 2013

This paper presents a hybrid power generation system modeling and simulation with the objective of electricity sale to distribution network (DN) which consists of photovoltaic (PV) module, proton exchange membrane (PEM) fuel cell (FC), hydrogen storage tank (HST) and electrolyzer (EL).Since last researches in optimal FC and PV application aimed in power electronic approach, In this paper the application between FC and PV is considered with the aim of maximizing profit gained due to electricity sale revenue to DN. The revenue from electricity sale to DN considering electricity price in low load, shoulder load and peak load hours is considered as the system profit. Also in a sensitivity analysis the impact of technical parameters of hybrid system components is investigated on system profit. The results showed that the system saves the electricity by hydrogen storage in HST in low load hours and sale it with more prices in shoulder load hours to DN. Also the obtained results show that several technical parameters of PV and PEM FC have considerable impact on system operation and profit.

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Evaluating the Project based Organizational Teaching-Learning Process

By S. Justus Mohammed Sirajudin

DOI: https://doi.org/10.5815/ijmecs.2013.05.05, Pub. Date: 8 May 2013

Organizational Training and Learning are among the 22 key process areas in CMM. These two processes are subject for improvement based on its framework and execution. In this paper, we have worked on project-based frameworks for organizational training and learning and have attempted to validate them in the software developmental organizations and in an institution teaching software engineering.
The empirical validation is carried out with those case studies and significant results are obtained in assessing the improvement in the two process areas. Moreover, this work is also extended to accommodate improvement in the regular conventional OTL processes.

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Design and Development MIPS Processor Based on a High Performance and Low Power Architecture on FPGA

By Tina Daghooghi

DOI: https://doi.org/10.5815/ijmecs.2013.05.06, Pub. Date: 8 May 2013

This paper presents the design and development of a high performance and low power MIPS microprocessor and implementation on FPGA. In this method we for achieving high performance and low power in the operation of the proposed microprocessor use different methods including, unfolding transformation (parallel processing), C-slow retiming technique, and double edge registers are used to get even reduce power consumption. Also others blocks designed based on high speed digital circuits. Because of feedback loop in the proposed architecture C-slow retiming can enhance designs that contain feedback loops. The C-slow retiming is well-known for optimization and high performance technique, it automatically rebalances the registers in the proposed design. The proposed high performance microprocessor is modeled and verified using FPGA and simulation results. The proposed methods in microprocessor have been successfully synthesized and implemented in Quartus II 9.1 and Stratix II FPGA, to target device EP2S15F484C3, and power is analyzed with Xpower analyzer. Results demonstrate that the proposed method has high performance.

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Activity Recognition with Multi-tapeFuzzy Finite Automata

By H. Karamath Ali D. I. George Amalarethinam

DOI: https://doi.org/10.5815/ijmecs.2013.05.07, Pub. Date: 8 May 2013

Recognizing the activities performed by the user in an unobtrusive manner is one of the important requisites of pervasive computing. Users perform a number of activities during their day to day life. Tracking and deciding what a user is doing at a given time involves a number of challenges. The lack of a precise pattern in doing an activity at different times is one among them. The number, order, and duration of the different steps involved in an activity vary significantly, even when the activity is done by the same user at different times. To overcome these challenges, a number of simultaneous inputs have to be handled with provisions for handling variations in number, order and duration of these inputs. This paper explains how multi-tape fuzzy finite state automata can be used to effectively recognize human activities. The method explained is found to give good results when tested using publicly available activity datasets collected in a smart home environment.

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All-Optical Parity Circuits Using Nonlinear Directional Coupler

By Leily A.Bakhtiar E. Yaghoubi A. Adami S. M. Hamidi M. Hosseinzadeh

DOI: https://doi.org/10.5815/ijmecs.2013.05.08, Pub. Date: 8 May 2013

Since in the previous existing optical designs, the electronic-optic-electronic conversion has not been completely eliminated. Construction of the optical circuits with nonlinear waveguides can overcome this drawback. We have developed a nonlinear directional coupler theory to describe novel all-optical parity circuits. By using three channels, appropriate adjusting of the refractive indices, and selecting the correct length for coupling event, even/odd parity circuits can be obtained. The operation of these circuits is simulated with the aid of RSoft CAD-Layout (BeamPROP) simulator. Towards the end of the work, we compared the speed of our proposed novel circuit with the existing optical designs and also electronic structure of which we have a better result.

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