International Journal of Knowledge and Learning (8 papers in press)

Regular Issues

• Individual study work and lecturer support as predictors of students academic success  
  by Nazmi Xhomara 
  Abstract: The purpose of the study is to investigate the relationships between individual study work and lecturer support, and students academic success, as well as the influence of individual study work and lecturer support on students academic success. The mixed approach is the method used in the study. A random cluster sample of students and a purposive sample of lecturers, a structured questionnaire, and a semi-structured interview were selected to be used in the study. The study demonstrated that individual study work influences strongly students academic success, meanwhile lecturer support doesnt influence it. At the same time, students academic success has been explained strongly by individual study work and lecturer support. This study is one of a very small number of studies reporting similar results.
  Keywords: individual study work; lecturer support; students’ academic success.
  
  
• Understanding Entrepreneurial Intention among Indian Youth Aspiring for SelfEmployment  
  by Yasir Arafat, Imran Saleem, Amit Kumar Dwivedi 
  Abstract: Purpose - The main aim of this study is to confirm whether Entrepreneurial Intention Models (EIM) explain the entrepreneurial phenomenon when applied to India.rnrnDesign/methodology/approach We have tested the Ajzens theory of planned behavior (TPB) framework for testing entrepreneurial intention (EI) in Indian setting. The data has been collected by administering Entrepreneurial Intention Questionnaire (EIQ) among the students of Aligarh Muslim University, Aligarh, India who are aspiring to take up self-employment as their career option. The paper employs a linear regression model to examine the determinants of entrepreneurial intention (EI) based on the theory of planned behavior (TPB).rnrnFindings Results obtained partially support the theory of planned behavior. The construct Social Norms (SN) found to be insignificant in predicting entrepreneurial intention (EI). Moreover, Perceived Behavioral Control (PBC) or Self-efficacy explains highest variance than other variables which indicates that entrepreneurial behavior is not under volitional control; hence, India has a less munificent environment for entrepreneurs than other nations. rnrnOriginality/value This is one of the few studies to provide evidence for Entrepreneurial Intention Models (EIM) in India based on the TPB framework. In addition, it checks the robustness of the TPB in explaining EI in India and confirm the some of the previous findings.rn
  Keywords: Entrepreneurship; Entrepreneurial Intention; Theory of Planned Behavior; Students; Intention models; Start-up; Venture creation.
  
  
• Open Assessment Methodology Based Decision Support System in Blended Learning Environments  
  by Shivanagowda G M, Rayan Goudar, Umakanth Kulkarni 
  Abstract: Personalizing the education is one of the 16 grand challenges as per the National Academy of Engineering (NAE), USA. Measuring the outcomes of education and the progress of learning has an essential role in generating personalized feedbacks and recommendations in personalized learning. The data obtained by traditional assessment tools like written and oral examinations, mass assignments do not reflect the real state of the students knowledge and progress of learning. Also, in such a setup students learning activities outside the classroom are not observable leading to imprecise recommendations. As a solution, this paper share one of our assessment practice called Open-Assessment Method(OAM) developed and practiced during 2012-2015 along with the design of decision support system (DSS). The DSS built around CAS (Class Activity Sheet) with Google technologies, enhances the observability of the student's learning activities. This technological adaption leads to significant improvement in students participation in the learning activities. Increased students participation generates a good amount of rarely seen data useful for composing recommendations on a personal basis through the DSS with teachers interventions.
  Keywords: Open-Assessment Method; Teaching Practices; Decision Support System; Students Modelling; Personalised Recommendation; Blended Learning Environments.
  
  
• Why Do Students Fall Into Webtoon Viewing While They Give Up Mathematics? An fMRI Study  
  by Seung-Hyuk Kwon, Yeong-Ji Lee, Yong-Ju Kwon 
  Abstract: The purpose of this study was to identify brain activation regions related to flow and motivation during mathematics problem solving and webtoon viewing based on brain imaging technology. Researchers measured brain activation using functional magnetic resonance imaging (fMRI) and investigated flow and motivation through questionnaires. Significant differences between mathematics problem solving and webtoon viewing were found in high school students brain activation regions. Based on the functions of these brain activation regions, result-oriented reward pursuit could play an important role in students motivation-inducing during mathematics problem solving. However, investigation of flow and motivation from webtoon viewing were ascertained to be caused from pleasure from new information presented in the story and picture. Results of this study could help devise a specific strategy for mathematics problem solving instruction.
  Keywords: flow experience; functional magnetic resonance imaging; mathematics problem solving; motivation; webtoon viewing.
  
  
• Students' Psychological Characteristics and its Relationship with Exhaustion, Cynicism, and Academic Inefficacy  
  by Mahtab Pouratashi, Asghar Zamani 
  Abstract: This paper highlights the relationship between students psychological characteristics with exhaustion, cynicism, and academic inefficacy. A sample of 247 students from Iranian Colleges of agriculture participated in this study. A questionnaire was used to obtain information on studied variables including demographic characteristics, goal orientation, intelligence beliefs, general self-efficacy beliefs, and so on. Reliability and validity of instrument were determined through opinions of professors and application of Cronbach's Alpha. The findings revealed that there were significant correlations between students psychological characteristics with exhaustion, cynicism, and academic inefficacy. Finally, the findings showed that the most dominant determinant of exhaustion was general self-efficacy belief with a total effect of -.400. Incremental intelligence belief and entity intelligence belief had the most effects on cynicism and academic inefficacy, with a total effect of -.437 and .448, respectively. The findings have implications for professors to use teaching methods that encourage effective engagement of students in learning and for counselors to give useful educational and psychological advices to students.
  Keywords: learning; student; higher education; exhaustion; cynicism; academic inefficacy; intelligence beliefs; goal orientation; general self-efficacy belief.
  
  
• A Semantic Assessment Framework for E-Learning Systems  
  by Thair Khdour 
  Abstract: Semantic Web Technologies are applied in a wide spectrum of applications including search engines, Web services discovery and composition, semantic tags and Electronic assessment of E-learning systems. Recently, the field of electronic assessment has grabbed the attention of many researchers. Electronic assessment is a real challenge taking to consideration the diversity of question types. E-assessment of answers to open questions has created new challenges regarding extracting students� answers using natural language processing techniques and infer new knowledge using description logic reasoning. To be able to automate the process of assessing the students� answers, they have to be annotated with semantics. This paper presents a thorough survey of significant research efforts that adopt semantic annotation to enhance the process of e-assessment. Moreover, in this paper we propose a semantic-based framework that automates the process of electronically assessing the answers of questions on e-learning systems based on their semantic descriptions.
  Keywords: e-assessment; e-learning; semantics annotation; ontology.
  
  
• Organizational learning and knowledge creation research: A hotel typologies according to the manager perceptions  
  by MARIA SOLEDAD CELEMIN-PEDROCHE, MIROSLAVA KOSTOVA KARABOYTCHEVA, LUIS RUBIO-ANDRADA, JOSE-MIGUEL RODRIGUEZ-ANTON 
  Abstract: This study aims to analyze the relationship between organizational learning and organizational performance, establishing a typology of hotels that give origin of a series of competitive advantages linked to the organizational learning process and deepening the knowledge creation model. In order to achieve the results, a questionnaire has been distributed among the hotel establishments in the Community of Valencia in Spain, performing both an exploratory factorial analysis and a cluster analysis. The results show that hotels which facilitate more organizational learning gain more clients loyalty and that outsourcing is the most used process by hotels that are related to the knowledge creation. The study has only been applied in the Valencian Community and the information collected comes from the perceptions of senior managers of hotel establishments. Considering the achieved results, it is recommendable that hotels learn from customers' expectations during their stays.
  Keywords: organisational learning; knowledge creation; organisational performance; hotels; contingent factors.
  
  
• A new Text categorization strategy: Prototype design and Experimental analysis  
  by N. Venkata Sailaja, L. Padma Sree, N. Mangathayaru 
  Abstract: Since a decade, ample amount of text data is being generated through various web sources in online or offline scenarios. This huge amount of data is mainly inconsistent and non-structured format, so hard to process through computing machines available. With the advent of computers and the information age, statistical and analytical problems have also grown both in size and complexity. Text categorization involves a learning methodology whose applications are in the areas like - language identification, information retrieval, opinion mining, spam filtering, and email routing etc. Text categorization can also be thought as the mechanism to give labels to various natural corpus text documents. Text classification using various Machine Learning mechanisms encounter the difficulty of the high dimensionality of attributes vector. Therefore, a feature selection technique is very much required to discard irrelevant as well as noisy attributes from the feature set vector so that the ML algorithms can work efficiently. In this paper, Rough Set Theory (RST) based attribute selection methodology is applied to achieve Text classification goal. A hybrid method based on RST is proposed for text documents classification. Further, proposed method's performance is evaluated on standard datasets. The experiments are performed on various Reuters categories corpus i.e. acq, corn, crude, earn, interest, ship, trade. We have also performed an experimental analysis on 20 Newsgroups dataset. We opted "bydate" version of the dataset containing 18941 documents, since the cross-experiment comparison is easier. Through our experiments, we attempted to explore the various performance measures i.e. Accuracy(Cohen's Kappa measure), Optimal matching rules set, Precision, Recall, F1 score etc. It is observed that proposed procedure takes less computational time with better categorization accuracy as compare to some existing approaches.
  Keywords: Text Classification; Rough sets; Information Retrieval Feature selection; Machine learning; Evaluation; 20 Newsgroups; Reuters 21578.