Search results for: Decision Tree learning

Authors: Chechen Liao, Chin Yi Yang

Abstract:

Although several factors that affect learning to program have been identified over the years, there continues to be no indication of any consensus in understanding why some students learn to program easily and quickly while others have difficulty. Seldom have researchers considered the problem of how to help the students enhance the programming learning outcome. The research had been conducted at a high school in Taiwan. Students participating in the study consist of 330 tenth grade students enrolled in the Basic Computer Concepts course with the same instructor. Two types of training methods-instruction-oriented and exploration-oriented were conducted. The result of this research shows that the instruction-oriented training method has better learning performance than exploration-oriented training method.

Keywords: Learning performance, programming learning, TDD, training method.

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Authors: Evgeny Pyshkin, Maxim Mozgovoy, Vladislav Volkov

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The paper follows a discourse on computer-assisted language learning. We examine problems of foreign language teaching and learning and introduce a metamodel that can be used to define learning models of language grammar structures in order to support teacher/student interaction. Special attention is paid to the concept of a virtual language lab. Our approach to language education assumes to encourage learners to experiment with a language and to learn by discovering patterns of grammatically correct structures created and managed by a language expert.

Keywords: Computer-assisted instruction, Language learning, Natural language grammar models, HCI.

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Authors: Mikel Alonso López

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This paper explores, in depth, the idea that emotions are present in all consumer decision making processes, meaning that purchase decisions have never been purely cognitive or as they traditionally have been defined, rational. Human beings, in all kinds of decisions, has "always" used neural systems related to emotions along with neural systems related to cognition, regardless of the type of purchase or the product or service in question. Therefore, all purchase decisions are, at the same time, cognitive and emotional. This paper presents an analysis of the main contributions of researchers in this regard.

Keywords: Emotions, decision making, consumer behavior.

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Authors: C. Ardil

Abstract:

This paper presents a multiple criteria evaluation analysis for airline quality rating using the preference analysis for reference ideal solution (PARIS) and the technique for order of preference by similarity to ideal solution (TOPSIS) approaches. The airline quality rating was developed as an objective method for assessing airline quality on combined multiple performance criteria and the importance weights of criteria. The selected multiple performance criteria were determined as on-time arrivals, mishandled baggage, involuntary denied boardings, and consumer complaints. The multiple criteria decision making analysis results show that the alternative ( a2) airline is the best-rated airline.

Keywords: airline quality rating, multiple criteria decision making, multiple criteria decision making analysis, entropy weight, MCDMA, PARIS, TOPSIS

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Authors: Teodora Bakardjieva, Galya Gercheva

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In this paper an open agent-based modular framework for personalized and adaptive curriculum generation in e-learning environment is proposed. Agent-based approaches offer several potential advantages over alternative approaches. Agent-based systems exhibit high levels of flexibility and robustness in dynamic or unpredictable environments by virtue of their intrinsic autonomy. The presented framework enables integration of different types of expert agents, various kinds of learning objects and user modeling techniques. It creates possibilities for adaptive e-learning process. The KM e-learning system is in a process of implementation in Varna Free University and will be used for supporting the educational process at the University.

Keywords: agents, e-Learning, knowledge management, knowledge sharing, artificial intelligence

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Authors: E. Bruno, F. Lacarbonara, M. C. Placentino, D. Gramegna

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Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

Keywords: Multi-criteria decision analysis, Hazardous wastemanagement, Asbestos.

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Authors: Md. Anwar Hossain Masud, Xiaodi Huang

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The massive proliferation of affordable computers, Internet broadband connectivity and rich education content has created a global phenomenon in which information and communication technology (ICT) is being used to transform education. Therefore, there is a need to redesign the educational system to meet the needs better. The advent of computers with sophisticated software has made it possible to solve many complex problems very fast and at a lower cost. This paper introduces the characteristics of the current E-Learning and then analyses the concept of cloud computing and describes the architecture of cloud computing platform by combining the features of E-Learning. The authors have tried to introduce cloud computing to e-learning, build an e-learning cloud, and make an active research and exploration for it from the following aspects: architecture, construction method and external interface with the model.

Keywords: Architecture, Cloud Computing, E-learning, Information Technology

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Authors: Damith Senanayake, Lakmal Muthugama, Laksheen Mendis, Tiroshan Madushanka

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Customer churn prediction is one of the most useful areas of study in customer analytics. Due to the enormous amount of data available for such predictions, machine learning and data mining have been heavily used in this domain. There exist many machine learning algorithms directly applicable for the problem of customer churn prediction, and here, we attempt to experiment on a novel approach by using a cognitive learning based technique in an attempt to improve the results obtained by using a combination of supervised learning methods, with cognitive unsupervised learning methods.

Keywords: Growing Self Organizing Maps, Kernel Methods, Churn Prediction.

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Authors: Yinggan Tang, Xinping Guan

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Color image segmentation can be considered as a cluster procedure in feature space. k-means and its adaptive version, i.e. competitive learning approach are powerful tools for data clustering. But k-means and competitive learning suffer from several drawbacks such as dead-unit problem and need to pre-specify number of cluster. In this paper, we will explore to use competitive and cooperative learning approach to perform color image segmentation. In competitive and cooperative learning approach, seed points not only compete each other, but also the winner will dynamically select several nearest competitors to form a cooperative team to adapt to the input together, finally it can automatically select the correct number of cluster and avoid the dead-units problem. Experimental results show that CCL can obtain better segmentation result.

Keywords: Color image segmentation, competitive learning, cluster, k-means algorithm, competitive and cooperative learning.

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Authors: Aseela Alhinaai, Suliman Abdullah, Adil Albusaidi

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Knowledge has been considered an important asset in private and public organizations. It is utilized in the libraries sector to run different operations of technical services and administrative works. This study aims to identify the impact of the knowledge-sharing factors (technology, collaboration, management support) to improve decision-making at Sultan Qaboos University Libraries. This study conducted a quantitative method using a questionnaire instrument to measure the impact of technology, collaboration, and management support on knowledge sharing that lead to improved decision-making. The study population is the Sultan Qaboos University (SQU) libraries (Main Library, Medical Library, College of Economic and Political Science Library, and Art Library). The results showed that management support, collaboration, and technology use have a positive impact on the knowledge-sharing process, and knowledge sharing positively affects decision making process.

Keywords: Knowledge sharing, decision making, information technology, management support, corroboration, Sultan Qaboos University.

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Authors: S. Housseno, A. Simonet, M. Simonet

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Semantic query optimization consists in restricting the search space in order to reduce the set of objects of interest for a query. This paper presents an indexing method based on UB-trees and a static analysis of the constraints associated to the views of the database and to any constraint expressed on attributes. The result of the static analysis is a partitioning of the object space into disjoint blocks. Through Space Filling Curve (SFC) techniques, each fragment (block) of the partition is assigned a unique identifier, enabling the efficient indexing of fragments by UB-trees. The search space corresponding to a range query is restricted to a subset of the blocks of the partition. This approach has been developed in the context of a KB-DBMS but it can be applied to any relational system.

Keywords: Index, Range query, UB-tree, Space Filling Curve, Query optimization, Views, Database, Integrity Constraint, Classification.

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Authors: Fahri Benli, Sitalakshmi Venkatraman, Ye Wei, Fiona Wahr

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A flipped classroom which is a form of blended learning shifts the focus from a teacher-centered approach to a learner-centered approach. However, not all learners are ready to take the active role of knowledge and skill acquisition through a flipped classroom and they continue to delve in a passive mode of learning. This challenges educators in designing, scaffolding and facilitating in-class activities for students to have active learning experiences in a flipped classroom environment. Experiential learning theories have been employed by educators in the past in physical classrooms based on the principle that knowledge could be actively developed through direct experience. However, with more of online teaching witnessed recently, there are inherent limitations in designing and simulating an experiential learning activity for an online environment. In this paper, we explore enhancing experiential learning using smart digital tools that could be employed in a flipped classroom within a higher education setting. We present the use of smart collaborative tools online to enhance the experiential learning activity to teach higher-order cognitive concepts of business process modeling as a case study.

Keywords: Experiential learning, flipped classroom, smart software tools, online learning higher-order learning attributes.

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Authors: R. Ferdous

Abstract:

Power, responsibility sharing, and democratic decision-making are the central ethos to co-management. It is assumed that involving local community in the decision-making process can create a sense of ownership and responsibility of that community and motivate the community towards collective action. But this paper demonstrated that the process to involve local community is not simple and straightforward as it is influenced by structural aspects, power relations among the actors, and social embedded institutions. These factors shape the process in that way who will participate, how they will participate and how the local community maneuvers their agency in the decision-making process. To grasp the complexities that materialize in the process of participation and to understand the inclusionary and exclusionary nature of participation, this paper examines the subjective understanding of different stakeholders concerning participation and furthermore observes the enabling or constraining factors that affect the community to exercise their agency.

Keywords: Participation, social embeddedness, power, structure.

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Authors: José M. Merigó, Pilar López-Jurado, M.Carmen Gracia, Montserrat Casanovas

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We present a method for the selection of students in interdisciplinary studies based on the hybrid averaging operator. We assume that the available information given in the problem is uncertain so it is necessary to use interval numbers. Therefore, we suggest a new type of hybrid aggregation called uncertain induced generalized hybrid averaging (UIGHA) operator. It is an aggregation operator that considers the weighted average (WA) and the ordered weighted averaging (OWA) operator in the same formulation. Therefore, we are able to consider the degree of optimism of the decision maker and grades of importance in the same approach. By using interval numbers, we are able to represent the information considering the best and worst possible results so the decision maker gets a more complete view of the decision problem. We develop an illustrative example of the proposed scheme in the selection of students in interdisciplinary studies. We see that with the use of the UIGHA operator we get a more complete representation of the selection problem. Then, the decision maker is able to consider a wide range of alternatives depending on his interests. We also show other potential applications that could be used by using the UIGHA operator in educational problems about selection of different types of resources such as students, professors, etc.

Keywords: Decision making, Selection of students, Uncertainty, Aggregation operators.

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Authors: Ali Serhan Koyuncugil, Nermin Ozgulbas

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In this paper, a data mining model to SMEs for detecting financial and operational risk indicators by data mining is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. In addition, this paper is based on a project which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK).

Keywords: Risk Management, Financial Risk, Operational Risk, Financial Early Warning System, Data Mining, CHAID Decision Tree Algorithm, SMEs.

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Authors: El Falaki Brahim, Khalidi Idrissi Mohammed, Bennani Samir

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E-learning is not restricted to the use of new technologies for the online content, but also induces the adoption of new approaches to improve the quality of education. This quality depends on the ability of these approaches (technical and pedagogical) to provide an adaptive learning environment. Thus, the environment should include features that convey intentions and meeting the educational needs of learners by providing a customized learning path to acquiring a competency concerned In our proposal, we believe that an individualized learning path requires knowledge of the learner. Therefore, it must pass through a personalization of diagnosis to identify precisely the competency gaps to fill, and reduce the cognitive load To personalize the diagnosis and pertinently measure the competency gap, we suggest implementing the formative assessment in the e-learning environment and we propose the introduction of a pre-regulation process in the area of formative assessment, involving its individualization and implementation in e-learning.

Keywords: Competency-Based-Approach, E-learning, Formative assessment, learner model, Modeling, pre-regulation process

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Authors: Jaflah H. Al-Ammary

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The increasing recognition of the need for education to be closely aligned with team playing, project based learning and problem solving approaches has increase the interest in collaborative learning among university and college instructors. Using online collaboration learning in learning can enhance the outcome and achievement of students as well as improve their communication, critical thinking and personnel skills. The current research aims at examining the effect of OCL on the student's achievement at Kingdom of Bahrain. Numbers of objectives were set to achieve the aim of the research include: investigating the current situation regarding the collaborative learning and OCL at the Kingdom of Bahrain by identifying the advantages and effectiveness of OCL as a learning tool over traditional learning, examining the factors that affect OCL as well as examining the impact of OCL on the student's achievement. To achieve these objectives, quantitative method was adopted. Two hundred and thirty one questionnaires were distributed to students in different local and private universities at Kingdom of Bahrain. The findings of the research show that most of the students prefer to use FTFCL in learning and that OCL is already adopted in some universities especially in University of Bahrain. Moreover, the most factors affecting the adopted OCL are perceived readiness, and guidance and support.

Keywords: Collaborative learning, perceived readiness, student achievement.

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Authors: Heba Mustafa Abdullah

Abstract:

The research aimed at examining the effect of using a suggested blended learning (BL) strategy on developing EFL pre- intermediate students. The study adopted the quasi-experimental design. The sample of the research consisted of a group of 26 EFL pre- intermediate students. Tools of the study included a listening comprehension checklist and a pre-post listening comprehension test. Results were discussed in relation to several factors that affected the language learning process. Finally, the research provided beneficial contributions in relation to manipulating BL strategy with respect to language learning process in general and oral language learning in particular.

Keywords: Blended learning, English as a foreign language, listening comprehension, oral language instruction.

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Authors: Burcu Karabina, Lynn Long, Amanda Garcia

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Augmented reality (AR) and virtual reality (VR) applications were offered as supplemental learning experiences to a second-year multivariable calculus class. A framework of research-informed best practices was used to guide selection and application of AR and VR learning technologies. Student feedback indicated that both AR and VR enhanced learning, both would be of value to future students, and learning may be most enhanced when AR and VR are used as complementary learning tools. The simpler technology, AR, was generally preferred, but for specific topics, students felt that the more immersive VR learning experience was especially beneficial. Immersion in the virtual learning environment minimized distractions, allowed students to feel more connected to their learning, and enhanced their ability to visualize and interact with 3D objects. Resolution of identified accessibility concerns could improve students’ overall experience with VR. Future research will explore ways to optimize the complementary effects of the two technologies. Application of research-informed framework of best practices was modelled throughout the study. Results and key resources informed revision and refinement of the framework.

Keywords: Accessibility, augmented reality, best practices, pedagogy, virtual reality.

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Authors: A. Braeken, L. Sterckx, A. Touhafi, Y. Verbelen

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When studying electronics, hands-on experience is considered to be very valuable for a better understanding of the concepts of electricity and electronics. Students lacking sufficient time in the lab are often put at disadvantage. A way to overcome this, is by using interactive multimedia in a virtual environment. Instead of proposing another new ad-hoc simulator for e-learning, we propose in this paper an e-learning platform integrating the SPICE simulator as a web service. This enables to make use of all the functions of the de-facto standard simulator SPICE inelectronics when developing new simulations.

Keywords: E-learning, SPICE, virtual experiments, web service.

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Authors: Sylvia Tumelo Nthutang, Nehemiah Mavetera

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Educational institutions are under pressure from their competitors. Regulators and community groups need educational institutions to adopt appropriate business and organizational practices. Globally, educational institutions are now using e-learning as the best teaching and learning approach. E-learning is becoming the center of attention to the learning institutions, educational systems and software inventors. North-West University (NWU) is currently using eFundi, a Learning Management System (LMS). LMS are all information systems and procedures that adds value to students learning and support the learning material in text or any multimedia files. With various e-learning tools, students would be able to access all the materials related to the course in electronic copies. The study was tasked with identifying the e-learning components at the NWU, Mafikeng campus. Quantitative research methodology was considered in data collection and descriptive statistics for data analysis. The Activity Theory (AT) was used as a theory to guide the study. AT outlines the limitations amongst e-learning at the macro-organizational level (plan, guiding principle, campus-wide solutions) and micro-organization (daily functioning practice, collaborative transformation, specific adaptation). On a technological environment, AT gives people an opportunity to change from concentrating on computers as an area of concern but also understand that technology is part of human activities. The findings have identified the university’s current IT tools and knowledge on e-learning elements. It was recommended that university should consider buying computer resources that consumes less power and practice e-learning effectively.

Keywords: E-learning, information and communication technology, teaching, and virtual learning environment.

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Authors: Uttam Vijay, Nitin Gupta

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Due to heavy energy constraints in WSNs clustering is an efficient way to manage the energy in sensors. There are many methods already proposed in the area of clustering and research is still going on to make clustering more energy efficient. In our paper we are proposing a minimum spanning tree based clustering using divide and conquer approach. The MST based clustering was first proposed in 1970’s for large databases. Here we are taking divide and conquer approach and implementing it for wireless sensor networks with the constraints attached to the sensor networks. This Divide and conquer approach is implemented in a way that we don’t have to construct the whole MST before clustering but we just find the edge which will be the part of the MST to a corresponding graph and divide the graph in clusters there itself if that edge from the graph can be removed judging on certain constraints and hence saving lot of computation.

Keywords: Algorithm, Clustering, Edge-Weighted Graph, Weighted-LEACH.

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Authors: Muhammad Y.K. Barozai, Ifthikhar A. Baloch, M. Din

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MicroRNAs (miRNAs) are small, non-coding and regulatory RNAs about 20 to 24 nucleotides long. Their conserved nature among the various organisms makes them a good source of new miRNAs discovery by comparative genomics approach. The study resulted in 21 miRNAs of 20 pre-miRNAs belonging to 16 families (miR156, 157, 158, 164, 165, 168, 169, 172, 319, 390, 393, 394, 395, 400, 472 and 861) in evergreen spruce tree (Picea). The miRNA families; miR 157, 158, 164, 165, 168, 169, 319, 390, 393, 394, 400, 472 and 861 are reported for the first time in the Picea. All 20 miRNA precursors form stable minimum free energy stem-loop structure as their orthologues form in Arabidopsis and the mature miRNA reside in the stem portion of the stem loop structure. Sixteen (16) miRNAs are from Picea glauca and five (5) belong to Picea sitchensis. Their targets consist of transcription factors, growth related, stressed related and hypothetical proteins.

Keywords: BLAST, Comparative Genomics, Micro-RNAs, Spruce

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Authors: Jin Myoung Kim, Tae Ho Cho

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Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.

Keywords: Heuristic search, key management, security, sensor network.

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Authors: Junyou Shi, Weiwei Cui

Abstract:

Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective.

Keywords: BIT, fault detection, fault isolation, testability modeling.

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Authors: S.Pancucci

Abstract:

The purpose of this paper is to describe the process of setting up a learning community within an elementary school in Ontario, Canada. The description is provided through reflection and examination of field notes taken during the yearlong training and implementation process. Specifically the impact of teachers- capacity on the creation of a learning community was of interest. This paper is intended to inform and add to the debate around the tensions that exist in implementing a bottom-up professional development model like the learning community in a top-down organizational structure. My reflections of the process illustrate that implementation of the learning community professional development model may be difficult and yet transformative in the professional lives of the teachers, students, and administration involved in the change process. I conclude by suggesting the need for a new model of professional development that requires a transformative shift in power dynamics and a shift in the view of what constitutes effective professional learning.

Keywords: Learning community model, professionaldevelopment, teacher capacity, teacher leadership.

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Authors: Salina Budin, Shaira Ismail

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Students learn effectively in a learning environment with a suitable teaching approach that matches their learning preferences. The main objective of the study is to examine the learning preferences amongst the students in the Science and Technology (S&T), and Social Science (SS) fields of study at the Universiti Teknologi Mara (UiTM), Pulau Pinang. The measurement instrument is based on the Dunn and Dunn Learning Styles which measure five elements of learning styles; environmental, sociological, emotional, physiological and psychological. Questionnaires are distributed amongst undergraduates in the Faculty of Mechanical Engineering and Faculty of Business Management. The respondents comprise of 131 diploma students of the Faculty of Mechanical Engineering and 111 degree students of the Faculty of Business Management. The results indicate that, both S&T and SS students share a similar learning preferences on the environmental aspect, emotional preferences, motivational level, learning responsibility, persistent level in learning and learning structure. Most of the S&T students are concluded as analytical learners and the majority of SS students are global learners. Both S&T and SS students are concluded as visual learners, preferred to be in an active mobility in a relaxing and enjoying mode with some light of refreshments during the learning process and exhibited reflective characteristics in learning. Obviously, the S&T students are considered as left brain dominant, whereas the SS students are right brain dominant. The findings highlighted that both categories of students exhibited similar learning preferences except on psychological preferences.

Keywords: Learning preferences, Dunn and Dunn learning style, teaching approach, science and technology, social science.

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Authors: Hong Choon Ong

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Naïve Bayes classifiers are simple probabilistic classifiers. Classification extracts patterns by using data file with a set of labeled training examples and is currently one of the most significant areas in data mining. However, Naïve Bayes assumes the independence among the features. Structural learning among the features thus helps in the classification problem. In this study, the use of structural learning in Bayesian Network is proposed to be applied where there are relationships between the features when using the Naïve Bayes. The improvement in the classification using structural learning is shown if there exist relationship between the features or when they are not independent.

Keywords: Bayesian Network, Classification, Naïve Bayes, Structural Learning.

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Authors: Karoliina Nisula, Samuli Pekkola

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Business education has been criticized for being too theoretical and distant from business life. Different types of experiential learning environments ranging from manual role-play to computer simulations and enterprise resource planning (ERP) systems have been used to introduce the realistic and practical experience into business learning. Each of these learning environments approaches business learning from a different perspective. The implementations tend to be individual exercises supplementing the traditional courses. We suggest combining them into a business skills laboratory resembling an actual workplace. In this paper, we present a concrete implementation of an ERP-supported business learning environment that is used throughout the first year undergraduate business curriculum. We validate the implementation by evaluating the learning outcomes through the different domains of Bloom’s taxonomy. We use the role-play oriented practice enterprise model as a comparison group. Our findings indicate that using the ERP simulation improves the poor and average students’ lower-level cognitive learning. On the affective domain, the ERP-simulation appears to enhance motivation to learn as well as perceived acquisition of practical hands-on skills.

Keywords: Business simulations, experiential learning, ERP systems, learning environments.

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Authors: M. Mamatha, H. B. Aravinda, E. T. Puttaiah, S. Manjappa

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One of the causes of water pollution is the presence of heavy metals in water. In the present study, an adsorbent prepared from the raw bark of the Pongamia pinnata tree is used for the removal of ferrous or ferric ions from aqueous and waste water containing heavy metals. Adsorption studies were conducted at different pH, concentration of metal ion, amount of adsorbent, contact time, agitation and temperature. The Langmuir and Freundlich adsorption isotherm models were applied for the results. The Langmuir isotherms were best fitted by the equilibrium data. The maximum adsorption was found to 146mg/g in waste water at a temperature of 30°C which is in agreement as comparable to the adsorption capacity of different adsorbents reported in literature. Pseudo second order model best fitted the adsorption of both ferrous and ferric ions.

Keywords: Adsorption, Adsorption isotherms, Heavy metals, Industrial effluents.

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