Forthcoming articles

 


International Journal of Knowledge and Learning

 

These articles have been peer-reviewed and accepted for publication in IJKL, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

 

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International Journal of Knowledge and Learning (10 papers in press)

 

Regular Issues

 

  • ViewpointS: capturing formal data and informal contributions into an adaptive knowledge graph   Order a copy of this article
    by Philippe Lemoisson, Guillaume Surroca, Clement Jonquet, Stefano A. Cerri 
    Abstract: Formal data is supported by means of specific languages from which the syntax and semantics have to be mastered, which represents an obstacle for collective intelligence. In contrast, informal knowledge relies on weak/ambiguous contributions e.g., I like. Reconciling the two forms of knowledge is a big challenge. We propose a brain-inspired knowledge representation approach called ViewpointS where formal data and informal contributions are merged into an adaptive knowledge graph which is then topologically, rather than logically, explored and assessed. We firstly illustrate within a mock-up simulation, where the hypothesis of knowledge emerging from preference dissemination is positively tested. Then we use a real-life web dataset (MovieLens) that mixes formal data about movies with user ratings. Our results show that ViewpointS is a relevant, generic and powerful innovative approach to capture and reconcile formal and informal knowledge and enable collective intelligence.
    Keywords: knowledge representation; knowledge graph; semantic Web; social Web; collective intelligence; nature-inspired computational model; formal/informal knowledge; serendipitous learning.

  • Modelling Wisdom in Learning and Decision Making   Order a copy of this article
    by Muhammad Asim Qayyum 
    Abstract: There is a growing interest in understanding application of wisdom but abstract and intangible personal factors make it difficult to design and achieve practical learning of wisdom. The purpose of this research is to identify the key concepts of wisdom and their relationships to create a learning and decision making model, or a Wise Action Model (WAM) for organizational knowledge workers. A review of relevant models, theories, and related literatures from various disciplines was undertaken, which identified prior knowledge and its comprehension and understanding as the significant concepts of wisdom. The resulting WAM conceptual framework defines relationships between these key concepts and the impacting factors, such as, motivations, reliance on embedded cues and signs in the environment, and the values (especially the moral values) needed to recognize and remember project stakeholders. This studys contribution is significant as wisdom needs more attention in the knowledge management literature and findings of this study are expected to influence the theory and practices in this field.
    Keywords: knowledge management; wisdom; prior knowledge; Learning wisdom; wise decision making; wise actions.

  • University teachers beliefs and constructivist teaching practices in blended learning courses in Tanzanian universities   Order a copy of this article
    by Haruni Machumu, Chang Zhu, Koen  
    Abstract: The study examines the relationship between university teachers beliefs and constructivist teaching practices (CTP) in blended learning environment (BLE) courses in Tanzanian universities. The study collects data from 211 teachers in BLE courses. The analyses involved descriptive statistics, correlational, the Mann-Whitney U-test, Kruskal-Wallis H-test and multiple linear regression. The findings revealed threefold. First, explicit engagement, supportive teaching and interactions were important aspects of CTP in BLE courses. Second, there were no statistically significant differences in teachers beliefs about gender, academic rank, educational level and teaching experiences in BLE courses. And, third, there was a significant relationship between teachers beliefs and CTP in BLE courses. Moreover, the findings indicate that teachers beliefs predict their explicit engagement and supportive teaching are predictors of the beliefs of teachers who teach BLE courses. This study provides important implications and empirical evidence about the beliefs of the university teachers who teach BLE courses and their CTP.
    Keywords: Teachers’ beliefs; constructivist teaching; constructivist teaching practices; blended learning; blended learning environments; blended learning courses.

  • The relationship between emotional intelligence and organizational learning   Order a copy of this article
    by Abdollah Babaeinesami, Peiman Ghasemi 
    Abstract: This research is devoted to study the relationship between emotional intelligence and organizational learning among Pazargad non-Industrial Operation Company. 120 people of staff of Pazargad non-Industrial Operation Company were chosen randomly. Templeton organizational learning questionnaire and Bradberry and Greeues questionnaire were applied. There is a significant relationship between all the elements of emotional intelligence (self-awareness, self-management, social awareness, relationship management) and organizational learning (awareness, communication, performance assessment, intellectual cultivation, environmental adaptability, social learning, intellectual capital management and organizational grafting). Considering that emotional intelligence is the ability to use emotions and feelings of oneself and others in individual and group behavior in order to obtain maximum results with maximum satisfaction in the organization, therefore, the integration of managerial knowledge and emotional abilities in management can be useful in pushing people towards achieving the goal and will increase the efficiency and effectiveness of the organization. Hence, the contribution of this paper can be summarized as follows: To study the relationship between emotional intelligence and organizational learning among staff in Pazargad non-Industrial Operation Company.
    Keywords: Organizational learning; Emotional intelligence; Templeton's learning factors; Intellectual cultivation; organizational grafting.

  • The impact of e-learning usage on students achievements: a case study   Order a copy of this article
    by Khaled Maabreh 
    Abstract: Abstract: E-learning, an important Internet-based tool, can be implemented using communication methods and storage media that support different data types. As a virtual learning environment, e-learning has emerged in the field of higher education in countries throughout the world, including Jordan, a developing country. To evaluate the effectiveness of the e-learning program implemented in Jordan, a sample study is presented in this paper to examine the students perceptions and attitudes related to the courses offered at the Faculty of Information Technology in Zarqa University. This study aims to evaluate the students satisfaction and measure the influence of using an e-learning system (Moodle) on their achievements. Statistical analysis showed that the use of e-learning technology had a major effect on the students achievements.
    Keywords: Keywords: e-learning; moodle; education; internet; jordan.

  • Effective Question Modeling and Intelligent Question Bank Storage Engine: An Adaptive Graph Based Approach   Order a copy of this article
    by Rayan Goudar, Abhijeet Singh, Saurabh Srivastava, Vijay Krishan 
    Abstract: In the changing present competitive scenario, intelligent development of question model is indispensible for intellectual growth of students and also to fulfill learning objectives of the course (Blooms Taxonomy). There are several computer based question paper generators but they typically use random selection from question bank. Also these databases (question bank) are not rich enough to avoid recalling (repetition of questions). This paper deals with the empiric and pragmatic essence of the Adaptive Question Bank Development and Management System(AQBDMS) that is generating good and balanced combinations of questions intelligently as per the inputs or parameters provided by the question paper designer (QPD) in the beginning. After that, the adaptive management system uses concept map developed on graph database that uses hierarchical knowledge of a particular domain for fetching a good set of questions generated in former part. The concept map integrated with question bank (question database) will ensure the question modeling process based on degree of certain criteria like Blooms Taxonomy, difficulty level, marking scheme etc. The question storage engine (QSE) of AQBDMS is intelligent enough to avert the redundant questions using the existential information retrieval schemes. The paper presents the implementation aspects of such system as well as it shows the efficient and novel utilization of graph database. The evaluation of generated question model will provide a feedback to check students overall level of understanding and this will be an advantage for an organization for enhancing the growth of their students. In sum, the proposed system would be great aid for the organization in effective question modeling and its assessment.
    Keywords: Question modelling; Question paper designer engine; Question storage engine; Question bank (Database); Concept map.

  • Factors Affecting the Motivation and Intention to Become an Entrepreneur among Business University Students   Order a copy of this article
    by Syed Ali Raza, Nida Shah 
    Abstract: The purpose of this study is to explore how the variables of the theory of planned behavior and motivation and ability model affect the intention to become an entrepreneur among business university students. For this purpose, data were collected from 267 students of different business schools of Pakistan. PLS-SEM was used as a statistical tool to analyze the data. The result revealed that the variables, i.e., Subjective norm, opportunity, attitude, perceived behavioral control has a positive and significant effect on the motivation, and motivation also has a significant positive effect on the students intention to become an entrepreneur, however, ability has a positive but insignificant on motivation. From this study it can be concluded that the only financial resources are not enough to start a business, behavioral factors also play the critical role. This research gives valuable insights for the policy implications.
    Keywords: Intention to become Entrepreneur; Theory of planned behavior; Business students; Pakistan.

  • Plagiarism Detection Based on Semantic Analysis
    by Indrajit Mukherjee, Bipul Kumar, Samarth Singh, Kishan Sharma 
    Abstract: Plagiarism means copy and paste for a text or change in some words or makes use of synonymous or near synonymous words without citing the source. Plagiarism is on rise especially in the academic and research field due the availability of the digital text documents in the internet which can easily be copied and pasted. Existing approaches for detecting the plagiarism have either ignored or made limited use of information about semantic similarities between the words. The proposed method to measure the semantic similarity between the documents by mapping keywords (verbs, adverbs, adjectives, descriptors, etc.) with the nouns and then finding the similarity between the mapped words that can rectify the existing shortcomings. The efficiency of the algorithm is evaluated on the dataset (corpus of Plagiarized Short Answers). The experiments showed that the proposed algorithm gives significantly accurate results in detecting semantic based similarity between the documents and found to outperform previously published methods.
    Keywords: Semantic Similarity, Plagiarism Detection, NLP, WordNet and LDA.

  • Correlation between Teaching Evaluation and Learning
    by Abid Ali Khan, Kashif Mehmood, Taimur Shams, Sumaira Khan, M Arif Ashraf 
    Abstract: Grade Points Average (GPA), is an assessment tool used for evaluation of student’s academic achievement by the teachers. It relates acquired percentages into letter grades that are clustered and later converted into numerical values. Different systems of assigning GPAs are being followed by the institutions worldwide. Over the period of time, grade inflation, that is award of higher grades to students not conforming to their academic standing, has been reported as a serious concern worldwide. Over the time, researchers have identified the factors that result in grade inflation and proposed different schemes to address the processes of determining a true academic standing of students. The authors have evaluated the impact of higher-class average percentage score on the grade awards. Higher percentage scores are associated with higher student aptitude that influences instructor’s decision towards inflated evaluation. In the present work, original students’ grades for different batches with different class average percentage scores were normalized for inflation effects based on published and proposed normalization schemes. The outcomes were analyzed, which revealed that the proposed scheme effectively addresses the issue of inflated evaluation without affecting the student aptitude parameter.
    Keywords: Grade Point Average; Class Average Percentages; Grades Inflation; Grades Normalization; Assessment Schemes

  • Accuracy Assessment of Rough Set based SVM Technique for Spatial Image Classifi cation
    by D N VASUNDHARA, M Seetha 
    Abstract: There exist many traditional spatial image classification techniques which are developed over past years and exists in literature. Today, expert systems along with machine learning methods are getting universality in this area due to effective classification. This paper presents Rough set based Support vector machine classification (RS-SVM) method. In this technique, Rough set (RS) is used as a feature selection mathematical tool which eliminates the redundant features. Further, this reduced dimensionality data set is given to Support vector machine (SVM) classifier. This process improves the classification accuracy and performance. We have performed experiments using standard geospatial images for above-proposed method for classification.
    Keywords: Feature Extraction; Classification; Rough sets; Artificial neural network; Support vector machines