Instant messaging clients - Relaxed, free & enjoyable English learning and training tools

In a demanding world of using English as a second language, computer technology and the internet are being dominantly used as they provide an incredible boost to language learning environment. At present, we can experience a more exciting way of learning a language by taking the advantages of the Instant Messaging Networks widely available online. This latest incarnation of the online chat is one of the communication methods that has proven to be a very good complement to the ways in which we communicate, both privately and professionally. These brilliantly invented instruments such as Skype, Yahoo Messenger and et cetera are a godsend to those who like to seek knowledge and to improve their English. This paper aims to examine the effectiveness of these so called ‘eclectic communicators’ in second language learning; focusing more on their functions as relaxing, and enjoyable language learning tools in a higher educational setting. This qualitative paper begins by highlighting current literature in the area of computer mediated communication (CMC) learning environments in second language use and development. It also discusses some of the issues and challenges related to this matter. In conclusion, this paper provides an overview of the benefits and drawbacks of instant messaging in educational settings especially in second language learning environment

The relationship between the use of Meta-cognitive Self Regulated Learning Strategies (Meta-SRLS) and achievement in English language learning

This study provides a detailed description of Meta-cognitive Self Regulated Learning (Meta-SRL) strategies employed by one hundred and seventy (170) undergraduate students majoring in different Engineering courses at one local university in the northern part of Malaysia. The findings revealed that the proposed Meta-SRLS framework can be used as a basis for a development of assessment instruments and teaching curricula that measure and develop a systematic Meta-cognitive Self Regulated Learning ability among ESL learners. The findings also indicated the use of a wide range of Meta-cognitive Self Regulated Learning Strategies (Meta-SRLS) by the participants in their English language learning. Moreover, the results of Pearson correlation test also revealed a positive relationship between the use of Meta-SRL strategies and the participants‟ level of English language proficiency. The results affirmed the findings of previous studies that language learners with advanced proficiency level tend to utilize more strategies than those with low proficiency level (e.g., Magogwe & Oliver, 2007); Hong-Nam & Leave ll, 2006; Wharton, 2000; Oxford & Nyikos, 1989; O‟Malley & Chamot, 1985). The study employed a multiphase mixed method research design to investigate the use of Metacognitive Self Regulated Learning Strategies in second language learning context via five phases of investigation.A systematic review of literature was conducted to develop aMeta-SRLS framework that may be used to assess metacognitive self regulatory behaviors and assist language instructors in promoting autonomous learning in the second language classrooms. In addidtion, a group of experts participated in the interviews to validate and iievaluatethe proposed Meta-SRLS framework. In order to examine the use of strategies by the participants, a newly adapted Meta-Cognitive Self Regulated Learning Strategies Questionnaire (Meta-SRLSQ) was used to collect the data. The questionnaire was re-designed based on the previous literature (Flavell, 1979; Brown et al, 1983; Flavell, 1987; Anderson, 2002; Mokhtari & Richard, 2002; Danuwong, 2006; Azizah, 2012). This study has yielded findings that make an original contribution to both the theory and the practice of Self Regulated learningespecially in the context of language teaching and learning. In the context of second language education in Malaysia, this study provides new insights in the area of metacognition and self regulation. The pedagogical implications of this study will further lead to a systematic teaching of Meta-cognitive self regulated learning strategies in the L2 classrooms and increase the proficiency level of L2 learners especiall

Pengelompokan Data Kaji Cuaca Menggunakan Teknik Engelompokan Hierarki Agglomerative Bagi Peramalan Taburan Hujan

Kertas kerja ini melaporkan penggunaan teknik pengelompokan hierarki Agglomerative bagi melakukan peramalan taburan hujan. Tujuan utama kajian ini adalah untuk melihat keberkesanan serta prestasi algoritma yang terdapat di dalam teknik pengelompokan hierarki. Kertas kerja ini bermula dengan penerangan ke atas pengelompokan hierarki yang memfokus kepada algoritma Single Link, Average Link dan Complete Link. Melalui penggunaan algoritma-algoritma tersebut, kelompok dihasilkan berdasarkan pembentukan susunan skema pengelompokan dengan mengurangkan jumlah kelompok bagi setiap proses. Kelompok yang dihasilkan, diperolehi daripada gabungan kelompok-kelompok yang terhampir (sama) kepada satu kelompok. Kelompok-kelompok yang dihasilkan melalui ketiga-tiga algoritma tersebut akan digunakan sebagai input bagi melakukan peramalan taburan hujan. Langkah-langkah yang terlibat di dalam proses pengelompokan ini akan diterangkan dengan lebih jelas di dalam bahagian metodologi kajian. Seterusnya, kertas kerja ini akan menerangkan mengenai eksperimen yang dilakukan ke atas kelompok-kelompok yang dihasilkan dengan menggunakan ketiga-tiga algoritma di atas. Pengukuran prestasi pengelompokan dibuat berdasarkan hasil pengelompokan ialah nilai ralat min punca kuasa dua (RMS) dan nilai pekali kolerasi yang dihasilkan di dalam setiap eksperimen yang telah dijalankan. Hasil kajian menunjukkan bahawa peramalan taburan hujan yang terbaik diperolehi melalui penggunaan algoritma Complete-Link

The relationship between the use of Meta-cognitive Self Regulated Learning Strategies (Meta-SRLS) and achievement in English language learning

This study provides a detailed description of Meta-cognitive Self Regulated Learning (Meta-SRL) strategies employed by one hundred and seventy (170) undergraduate students majoring in different Engineering courses at one local university in the northern part of Malaysia. The findings revealed that the proposed Meta-SRLS framework can be used as a basis for a development of assessment instruments and teaching curricula that measure and develop a systematic Meta-cognitive Self Regulated Learning ability among ESL learners. The findings also indicated the use of a wide range of Meta-cognitive Self Regulated Learning Strategies (Meta-SRLS) by the participants in their English language learning. Moreover, the results of Pearson correlation test also revealed a positive relationship between the use of Meta-SRL strategies and the participants‟ level of English language proficiency. The results affirmed the findings of previous studies that language learners with advanced proficiency level tend to utilize more strategies than those with low proficiency level (e.g., Magogwe & Oliver, 2007); Hong-Nam & Leave ll, 2006; Wharton, 2000; Oxford & Nyikos, 1989; O‟Malley & Chamot, 1985). The study employed a multiphase mixed method research design to investigate the use of Metacognitive Self Regulated Learning Strategies in second language learning context via five phases of investigation.A systematic review of literature was conducted to develop aMeta-SRLS framework that may be used to assess metacognitive self regulatory behaviors and assist language instructors in promoting autonomous learning in the second language classrooms. In addidtion, a group of experts participated in the interviews to validate and iievaluatethe proposed Meta-SRLS framework. In order to examine the use of strategies by the participants, a newly adapted Meta-Cognitive Self Regulated Learning Strategies Questionnaire (Meta-SRLSQ) was used to collect the data. The questionnaire was re-designed based on the previous literature (Flavell, 1979; Brown et al, 1983; Flavell, 1987; Anderson, 2002; Mokhtari & Richard, 2002; Danuwong, 2006; Azizah, 2012). This study has yielded findings that make an original contribution to both the theory and the practice of Self Regulated learningespecially in the context of language teaching and learning. In the context of second language education in Malaysia, this study provides new insights in the area of metacognition and self regulation. The pedagogical implications of this study will further lead to a systematic teaching of Meta-cognitive self regulated learning strategies in the L2 classrooms and increase the proficiency level of L2 learners especiall

Feasibility study of fuzzy clustering techniques in chemical database for compound classification

Compound selection methods are important in drug discovery especially in lead identification process. Finding the best method in compound selection has become a need to the pharmaceutical industry because of the increasing number of chemical compound to be screened. One of the best and widely used methods in compound selection is cluster-based selection where the compound datasets are grouped into clusters and representative compounds are selected from each cluster. Non-overlapping methods, such as Ward’s clustering method, have been widely used and it was agreed as the most efficient clustering method in compound selection. However, little focus has been given to overlapping method in compound selection or even in lead identification process. The research focused on the fuzzy c-means clustering where the effectiveness of the clusters produced with regard to compound selection is analyzed and compared with other conventional cluster-based compound selection method. Fuzzy c-means have been chosen because it produces clusters by identifying the cluster centroid and their corresponding degree of membership, therefore the compounds may belong to more than one cluster. The results from fuzzy c-means method are compared to Ward’s clustering method and also to the results from the fuzzification of Ward’s cluster. The analysis shows that fuzzy c-means clustering gives the best result in intermolecular dissimilarity; however it shows poor results of separation of active/inactive structure

Pengelompokan data kajicuaca menggunakan teknik peraturan kesatuan

Penganalisaan data merupakan satu tugas yang penting bagi pihak Jabatan Perkhidmatan Kajicuaca Malaysia (JPKM), di mana ianya digunakan untuk membuat peramalan taburan hujan pada masa akan datang. Pengekstrakan maklumat yang berguna daripada pangkalan data di JPKM bagi tujuan penganalisaan ini menjadi sukar ekoran pertambahan jumlah data kajicuaca yang disimpan. Peramalan taburan hujan boleh diaplikasikan melalui operasi perlombongan data iaitu pengelompokan data. Kajian ini memberikan penumpuan kepada operasi pengelompokan data kajicuaca di mana hasil dari pengelompokan ini akan digunakan untuk melakukan peramalan taburan hujan. Hasil kajian ini menunjukkan pengelompokan data kajicuaca dengan menggunakan teknik peraturan kesatuan dapat membantu pihak peramal di JPKM untuk melakukan peramalan taburan hujan. Selain daripada itu, hasil kajian juga mendapati bahawa penggunaan kelompok data kajicuaca yang berlainan sebagai data input kepada proses peramalan taburan hujan telah memberikan prestasi peramalan yang lebih baik berbanding dengan penggunaan kelompok data kajicuaca yang sama

Study of clustering trechniques in data mining for climate data

The acquisition of useful information from meteorological data dumps is difficult due to the increase in the amount of data stored in JPKM. This is because the parameters and amount of meteorological data are increasing from time to time. This large amount of data has made it difficult to analyze the meteorological data for the purpose of forecasting the rainfall. In the process of forecasting the rain distribution, it is unreasonable to use all the meteorological parameters to do the forecasting. Therefore, one of the ways to identify which parameter gives an impact to the accuracy or performance of the rainfall distribution forecasting is to group the meteorological data. The purpose of this study is to study and compare between two grouping techniques, namely partial and hierarchical method to carry out grouping of meteorological data for the purposes of forecasting of rainfall. The results of this study found that partial groupings were more suitable for use in grouping of meteorological data than hierarchical grouping. In addition, the use of meteorological data attributes within different groups provides better forecasting performance than the use of meteorological data attributes within the same group

Penggunaan kaedah statistik di dalam pengelompokan data kajicuaca bagi meramal taburan hujan

Meramal cuaca merupakan satu tugas yang kompleks dan sukar bagi pihak Jabatan Perkhidmatan Kajicuaca Malaysia (JPKM) ekoran pertambahan data kajicuaca di dalam pangkalan data. Di antara parameter-parameter data kajicuaca yang disimpan, taburan hujan merupakan parameter yang paling sukar diramal kerana ia melibatkan pelbagai parameter data kajicuaca seperti taburan hujan, suhu, kelajuan angin, tekanan, kelembapan dan sebagainya. Salah satu cara yang boleh diaplikasikan untuk meramal taburan hujan adalah melalui pengelompokan parameter data kajicuaca dengan menggunakan kaedah statistik. Kajian ini memberikan penumpuan kepada operasi pengelompokan data kajicuaca di mana hasil dari pengelompokan ini akan digunakan sebagai input untuk meramal taburan hujan. Hasil kajian ini menunjukkan pengelompokan data kajicuaca dengan menggunakan kaedah statistik dapat membantu pihak peramal di JPKM untuk melakukan peramalan taburan hujan. Di samping itu, hasil kajian juga telah mendapati bahawa penggunaan kelompok data kajicuaca yang berlainan sebagai data input kepada proses peramalan taburan hujan telah memberikan prestasi peramalan yang lebih baik berbanding dengan penggunaan kelompok data kajicuaca yang sama

Pengelompokan Data Kaji Cuaca Menggunakan Algoritma K-Means Bagi Peramalan Taburan Hujan

Pengelompokan merupakan salah satu teknik utama di dalam perlombongan data di mana set entiti dibahagikan kepada beberapa subkelas. Tujuan utama proses pengelompokan adalah untuk mengenalpasti corak sesebuah kumpulan, yang membolehkan persamaan serta perbezaan yang wujud antara kumpulan dikenalpasti. Terdapat pelbagai kaedah di dalam pengelompokan di mana setiap satunya berfungsi mengikut cara tersendiri dan mengeluarkan keputusan yang berlainan. Kajian ini menekankan kepada proses pengelompokan data kaji cuaca dengan menggunakan algoritma K-Means. Di dalam kajian ini, beberapa algoritma K-Means yang dihasilkan oleh penulis yang berlainan, dibincangkan secara umum. Penulis juga telah memfokuskan kajian kepada pengelompokan parameter data kaji cuaca kepada beberapa kelompok yang berlainan. Kelompok-kelompok ini dihasilkan melalui pembangunan algoritma K-Means dengan menggunakan program Borland C. Hanya beberapa wakil parameter sahaja diambil daripada setiap kelompok yang telah dihasilkan), akan digunakan bagi melakukan proses peramalan taburan hujan. Hasil yang diperolehi di dalam kajian menunjukkan proses pengelompokan dapat memudahkan proses peramalan taburan hujan