Search results for: student enrollment

Authors: B. Bergström, A. Ladd, A. Jones, L. Rosso, P. Michael

Abstract:

Attitudes toward treatment manuals serve as a meaningful predictor of general attitudes toward evidence-based practice. Despite demonstrating high effectiveness in treating many mental disorders, manualized treatments have been underutilized by practitioners. Thus, one can assess the state of the field regarding the adoption of evidence-based practices by surveying practitioner attitudes towards manualized treatments. This study is an adapted replication that assesses psychology graduate student attitudes towards manualized treatments, as a general marker for attitudes towards evidence-based practice. Training programs provide future clinicians with the foundation for critical skills in clinical practice. Research demonstrates that post-graduate continuing education has little to no effect on clinical practice; thus, graduate programs serve as the primary, and often final platform for all future practice. However, there are little empirical data identifying the attitudes and training of graduate students in utilizing manualized treatments. The empirical analysis of this study indicates an increase in positive attitudes among graduate student attitudes towards manualized treatments (within the United States), when compared to past surveys of professional psychologists. Findings from this study may inform graduate programs of barriers for students in developing positive attitudes toward manualized treatments and evidence-based practice. This study also serves as a preliminary predictor of the state-of-the field, in regards to professional psychologists attitudes towards evidence-based practice, if attitudes remain stable. This study indicates that the attitudes toward utilizing evidence-based practices, such as treatment manuals, has become more positive since year 2000.

Keywords: Evidence based treatment, Future of clinical science, Manualized treatment, Student attitudes towards evidence based treatments.

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Authors: Duangkamol Thitivesa

Abstract:

This paper explores the use of project work in a content-based instruction in a Rajabhat University, Thailand. The use of project is to promote kinds of learning expected of student teachers as stated by Thailand Quality Framework: TQF. The kinds of learning are grouped into five domains: Ethical and moral development, knowledge, cognitive skill, interpersonal skills and responsibility, and analytical and communication skills. The content taught in class is used to lead the student teachers to relate their previously-acquired linguistic knowledge to meaningful realizations of the language system in passages of immediate relevance to their professional interests, teaching methods in particular. Two research questions are formulate to guide this study: 1) To what degree are the five domains of learning expected of student teachers after the use of project in a content class?, and 2) What is the academic achievement of the students’ writing skills, as part of the learning domains stated by TQF, against the 70% attainment target after the use of project to enhance the skill? The sample of the study comprised of 38 fourth-year English major students. The data was collected by means of a summative achievement test, student writing works, an observation checklist, and project diary. The scores in the summative achievement test were analyzed by mean score, standard deviation, and t-test. Project diary serves as students’ record of the language acquired during the project. List of structures and vocabulary noted in the diary has shown students’ ability to attend to, recognize, and focus on meaningful patterns of language forms.

Keywords: Thailand Quality Framework, Project Work, Writing skill.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed elearning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: E-learning environments, intelligent agents, user modeling, Bayesian Networks, computational intelligence.

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Authors: Konstantinos Sofianos, Michael Stefanidakis

Abstract:

Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at anytime, anywhere, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: Intelligent learning systems, e-learning, music education, ontology, semantic web.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed e-learning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: Computational Intelligence, E-learning Environments, Intelligent Agents, User Modelling, Bayesian Networks.

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

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The present digital world poses many challenges to various stakeholders in the education sector. In particular, lecturers of higher education (HE) are faced with the problem of ensuring that students are able to achieve the required learning outcomes despite rapid changes taking place worldwide. Different strategies are adopted to retain student engagement and commitment in classrooms to address the differences in learning habits, preferences and styles of the digital generation of students recently. Further, with the onset of coronavirus disease (COVID-19) pandemic, online classroom has become the most suitable alternate mode of teaching environment to cope with lockdown restrictions. These changes have compounded the problems in the learning engagement and short attention span of HE students. New Agile methodologies that have been successfully employed to manage projects in different fields are gaining prominence in the education domain. In this paper, we present the application of Scrum as an agile methodology to enhance student learning and engagement in an online smart classroom environment. We demonstrate the use of our proposed approach using a case study to teach key topics in information technology that require students to gain technical and business-related data analytics skills.

Keywords: Agile methodology, Scrum, online learning, smart classroom environment, student engagement, active learning.

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Authors: L. A. Muhammad, M. S. Argungu

Abstract:

Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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Authors: PeiWen Liao, Tsung Hau Jen

Abstract:

This study was conducted to explore the effects of two countries model comparison program in Taiwan and Singapore in TIMSS database. The researchers used Multi-Group Hierarchical Linear Modeling techniques to compare the effects of two different country models and we tested our hypotheses on 4,046 Taiwan students and 4,599 Singapore students in 2007 at two levels: the class level and student (individual) level. Design quality is a class level variable. Student level variables are achievement and self-confidence. The results challenge the widely held view that retention has a positive impact on self-confidence. Suggestions for future research are discussed.

Keywords: Teaching approach, self-confidence, achievement, multi-group HLM.

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Authors: Ikmal Hisyam Mohamad Paris, Lilly Suriani Affendey, Norwati Mustapha

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In this paper we compare the accuracy of data mining methods to classifying students in order to predicting student-s class grade. These predictions are more useful for identifying weak students and assisting management to take remedial measures at early stages to produce excellent graduate that will graduate at least with second class upper. Firstly we examine single classifiers accuracy on our data set and choose the best one and then ensembles it with a weak classifier to produce simple voting method. We present results show that combining different classifiers outperformed other single classifiers for predicting student performance.

Keywords: Classification, Data Mining, Prediction, Combination of Multiple Classifiers.

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Authors: Ewa. M. Sztendur, Neil T. Diamond

Abstract:

Random Forests are a powerful classification technique, consisting of a collection of decision trees. One useful feature of Random Forests is the ability to determine the importance of each variable in predicting the outcome. This is done by permuting each variable and computing the change in prediction accuracy before and after the permutation. This variable importance calculation is similar to a one-factor-at a time experiment and therefore is inefficient. In this paper, we use a regular fractional factorial design to determine which variables to permute. Based on the results of the trials in the experiment, we calculate the individual importance of the variables, with improved precision over the standard method. The method is illustrated with a study of student attrition at Monash University.

Keywords: Random Forests, Variable Importance, Fractional Factorial Designs, Student Attrition.

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Authors: P. Valdiviezo, G. Riofrio, R. Reategui

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This article describes the implementation of an intelligent agent that provides recommendations for educational resources in a virtual learning environment (VLE). It aims to support pending (undeveloped) student learning activities. It begins by analyzing the proposed VLE data model entities in the recommender process. The pending student activities are then identified, which constitutes the input information for the agent. By using the attribute-based recommender technique, the information can be processed and resource recommendations can be obtained. These serve as support for pending activity development in the course. To integrate this technique, we used an ontology. This served as support for the semantic annotation of attributes and recommended files recovery.

Keywords: Learning activities, educational resource, recommender agent, recommendation technique, ontology.

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Authors: Mohammed Salem Alzahrani

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In this paper, student admission process is studied to optimize the assignment of vacant seats with three main objectives. Utilizing all vacant seats, satisfying all programs of study admission requirements and maintaining fairness among all candidates are the three main objectives of the optimization model. Seat Assignment Method (SAM) is used to build the model and solve the optimization problem with help of Northwest Coroner Method and Least Cost Method. A closed formula is derived for applying the priority of assigning seat to candidate based on SAM.

Keywords: Admission Process Model, Assignment Problem, Hungarian Method, Least Cost Method, Northwest Corner Method, Seat Assignment Method (SAM).

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Authors: Suleiman Obeidat, Adnan Bashir, Wisam Abu Jadayil

Abstract:

The affect of the attendance percentage, the overall GPA and the number of credit hours the student is enrolled in at specific semester on the grade attained in specific course has been studied. This study has been performed on three courses offered in industrial engineering department at the Hashemite University in Jordan. Study has revealed that the grade attained by a student is strongly affected by the attendance percentage and his overall GPA with a value of R2 of 52.5%. Another model that has been investigated is the relation between the semester GPA and the attendance percentage, the number of credit hours enrolled in at specific semester, and the overall GPA. This model gave us a strong relationship between the semester GPA and attendance percentage and the overall GPA with a value of R2 of 76.2%.

Keywords: Attendance in classes, GPA, Industrial Engineering, Grade

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Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

Abstract:

For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: High-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network.

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Authors: Said C. Fares, Mary A. Fares

Abstract:

It is well documented that introductory computer programming courses are difficult and that failure rates are high. The aim of this project was to reduce the high failure and withdrawal rates in learning to program. This paper presents a number of changes in module organization and instructional delivery system in teaching CS1. Daily out of class help sessions and tutoring services were applied, interactive lectures and laboratories, online resources, and timely feedback were introduced. Five years of data of 563 students in 21 sections was collected and analyzed. The primary results show that the failure and withdrawal rates were cut by more than half. Student surveys indicate a positive evaluation of the modified instructional approach, overall satisfaction with the course and consequently, higher success and retention rates.

Keywords: Failure Rate, Interactive Learning, Student engagement, CS1.

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Authors: Zhihan Li

Abstract:

Nowadays, most universities use the course enrollment system considering students’ registration orders. However, the students’ preference level to certain courses is also one important factor to consider. In this research, the possibility of applying a preference-first system has been discussed and analyzed compared to the order-first system. A bipartite graph is applied to resemble the relationship between students and courses they tend to register. With the graph set up, we apply Ford-Fulkerson (F.F.) Algorithm to maximize parings between two sets of nodes, in our case, students and courses. Two models are proposed in this paper: the one considered students’ order first, and the one considered students’ preference first. By comparing and contrasting the two models, we highlight the usability of models which potentially leads to better designs for school course registration systems.

Keywords: Bipartite graph, Ford-Fulkerson Algorithm, graph theory, maximum matching.

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Authors: Tahseen Ahmed Jilani, Syed Muhammad Aqil Burney, C. Ardil

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In the last 15 years, a number of methods have been proposed for forecasting based on fuzzy time series. Most of the fuzzy time series methods are presented for forecasting of enrollments at the University of Alabama. However, the forecasting accuracy rates of the existing methods are not good enough. In this paper, we compared our proposed new method of fuzzy time series forecasting with existing methods. Our method is based on frequency density based partitioning of the historical enrollment data. The proposed method belongs to the kth order and time-variant methods. The proposed method can get the best forecasting accuracy rate for forecasting enrollments than the existing methods.

Keywords: Fuzzy logical groups, fuzzified enrollments, fuzzysets, fuzzy time series.

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Authors: Dag A.H. Samuelsen, Olaf H. Graven

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Introducing Electromagnetic Interference and Electromagnetic Compatibility, or “The Art of Black Magic", for engineering students might be a terrifying experience both for students and tutors. Removing the obstacle of large, expensive facilities like a fully fitted EMC laboratory and hours of complex theory, this paper demonstrates a design of a laboratory setup for student exercises, giving students experience in the basics of EMC/EMI problems that may challenge the functionality and stability of embedded system designs. This is done using a simple laboratory installation and basic measurement equipment such as a medium cost digital storage oscilloscope, at the cost of not knowing the exact magnitude of the noise components, but rather if the noise is significant or not, as well as the source of the noise. A group of students have performed a trial exercise with good results and feedback.

Keywords: EMC, EMI, engineering project, student laboratory.

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Authors: José L. Jiménez

Abstract:

The use of technology in the classroom is an issue that is constantly evolving. Digital age students learn differently than their teachers did, so now the teacher should be constantly evolving their methods and teaching techniques to be more in touch with the student. In this paper a case study presents how were used some of these technologies by accompanying a classroom course, this in order to provide students with a different and innovative experience as their teacher usually presented the activities to develop. As students worked in the various activities, they increased their digital skills by employing unknown tools that helped them in their professional training. The twenty-first century teacher should consider the use of Information and Communication Technologies in the classroom thinking in skills that students of the digital age should possess. It also takes a brief look at the history of distance education and it is also highlighted the importance of integrating technology as part of the student's training.

Keywords: Digital tools, on-line learning, social networks, technology.

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Authors: Proud Arunrangsiwed

Abstract:

This study analyzes the crisis management and image repair strategies during the crisis of Mahidol Wittayanusorn School (MWIT) library burning. The library of this school was burned by a 16-year-old-male student on June 6th, 2010. This student blamed the school that the lesson was difficult, and other students were selfish. Although no one was in the building during the fire, it had caused damage to the building, books and electronic supplies around 130 million bahts (4.4 million USD). This event aroused many discourses arguing about the education system and morality. The strategies which were used during crisis were denial, shift the blame, bolstering, minimization, and uncertainty reduction. The results of using these strategies appeared after the crisis. That was the numbers of new students, who registered for the examination to get into this school in the later years, have remained the same.

Keywords: School, crisis management, violence, image repair strategies, uncertainty, burn.

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Authors: Kafuko M. Maria, Namisango Fatuma, Byomire Gorretti

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Mobile learning (m-learning) is steadily growing and has undoubtedly derived benefits to learners and tutors in different learning environments. This paper investigates the variation in benefits derived from enhanced classroom learning through use of m-learning platforms in the context of a developing country owing to the fact that it is still in its initial stages. The study focused on how basic technology-enhanced pedagogic innovation like cell phone-based learning is enhancing classroom learning from the learners’ perspective. The paper explicitly indicates the opportunities presented by enhanced learning to a conventional learning environment like a physical classroom. The findings were obtained through a survey of two universities in Uganda in which data was quantitatively collected, analyzed and presented in a three banded diagram depicting the variation in the obtainable benefits. Learners indicated that a smartphone is the most commonly used device. Learners also indicate that straight lectures, student to student plus student to lecturer communication, accessing learning material and assignments are core activities. In a TEL environment support by smartphones, learners indicated that they conveniently achieve the prior activities plus discussions and group work. Learners seemed not attracted to the possibility of using TEL environment to take lectures, as well as make class presentations. The less attractiveness of these two factors may be due to the teacher centered approach commonly applied in the country’s education system.

Keywords: Technology enhanced learning, mobile learning classroom learning, perceived benefits.

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Authors: Yaşar Baykul, Musa Gürsel, Hacı Sulak, Erhan Ertekin, Ersen Yazıcı, Osman Dülger, Yasin Aslan, Kağan Büyükkarcı

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The reliability of the tools developed to learn the learning styles is essential to find out students- learning styles trustworthily. For this purpose, the psychometric features of Grasha- Riechman Student Learning Style Inventory developed by Grasha was studied to contribute to this field. The study was carried out on 6th, 7th, and 8th graders of 10 primary education schools in Konya. The inventory was applied twice with an interval of one month, and according to the data of this application, the reliability coefficient numbers of the 6 sub-dimensions pointed in the theory of the inventory was found to be medium. Besides, it was found that the inventory does not have a structure with 6 factors for both Mathematics and English courses as represented in the theory.

Keywords: Learning styles, Grasha-Riechmann, reliability, validity.

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Authors: Elizabeth M. Hodge, Sharon K. Collins, Eric Kisling

Abstract:

Virtual environments are a hot topic in academia and more importantly in courses offered via distance education. Today-s gaming generation view virtual worlds as strong social and interactive mediums for communicating and socializing. And while institutions of higher education are challenged with increasing enrollment while balancing budget cuts, offering effective courses via distance education become a valid option. Educators can utilize virtual worlds to offer students an enhanced learning environment which has the power to alleviate feelings of isolation through the promotion of communication, interaction, collaboration, teamwork, feedback, engagement and constructivists learning activities. This paper focuses on the use of virtual environments to facilitate interaction in distance education courses so as to produce positive learning outcomes for students. Furthermore, the instructional strategies were reviewed and discussed for use in virtual worlds to enhance learning within a social context.

Keywords: Virtual Environments, Second Life, Instructional Strategies and Technology

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Authors: Amudha Kadirvelu, Sivalal Sadasivan

Abstract:

While the problem based learning (PBL) approach promotes unsupervised self-directed learning (SDL), many students experience difficulty juggling the role of being an information recipient and information seeker. Logbooks have been used to assess trainee doctors but not in other areas. This study aimed to determine the effectiveness of logbook for assessing SDL during PBL sessions in first year medical students. The log book included a learning checklist and knowledge and skills components. Comparisons with the baseline assessment of student performance in PBL and that at semester end after logbook intervention showed significant improvements in student performance (31.5 ± 8 vs. 17.7 ± 4.4; p<0.001) with a large effect size of 3.93. The learner-s log for PBL has played an important role in enhancing SDL in first year medical students. Learner-s log could be a good self-assessment tool for the undergraduate medical students.

Keywords: Problem based learning, self-directed learning, logbook, self-assessment.

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf, .doc, .ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: Education technology, learning management system, decentralized applications, blockchain.

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Authors: Hazem M. El-Bakry, Ahmed A. Saleh, Taghreed T. Asfour

Abstract:

Adaptive e-learning today gives the student a central role in his own learning process. It allows learners to try things out, participate in courses like never before, and get more out of learning than before. In this paper, an adaptive e-learning model for logic design, simplification of Boolean functions and related fields is presented. Such model presents suitable courses for each student in a dynamic and adaptive manner using existing database and workflow technologies. The main objective of this research work is to provide an adaptive e-learning model based learners' personality using explicit and implicit feedback. To recognize the learner-s, we develop dimensions to decide each individual learning style in order to accommodate different abilities of the users and to develop vital skills. Thus, the proposed model becomes more powerful, user friendly and easy to use and interpret. Finally, it suggests a learning strategy and appropriate electronic media that match the learner-s preference.

Keywords: Adaptive learning, Learning styles, Teaching strategies.

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Authors: Shatha Ghareeb, Rawaa Al-Jumeily, Thar Baker

Abstract:

In Abu Dhabi, there are many different education curriculums where sector of private schools and quality assurance is supervising many private schools in Abu Dhabi for many nationalities. As there are many different education curriculums in Abu Dhabi to meet expats’ needs, there are different requirements for registration and success. In addition, there are different age groups for starting education in each curriculum. In fact, each curriculum has a different number of years, assessment techniques, reassessment rules, and exam boards. Currently, students that transfer curriculums are not being placed in the right year group due to different start and end dates of each academic year and their date of birth for each year group is different for each curriculum and as a result, we find students that are either younger or older for that year group which therefore creates gaps in their learning and performance. In addition, there is not a way of storing student data throughout their academic journey so that schools can track the student learning process. In this paper, we propose to develop a computational framework applicable in multicultural countries such as UAE in which multi-education systems are implemented. The ultimate goal is to use cloud and fog computing technology integrated with Artificial Intelligence techniques of Machine Learning to aid in a smooth transition when assigning students to their year groups, and provide leveling and differentiation information of students who relocate from a particular education curriculum to another, whilst also having the ability to store and access student data from anywhere throughout their academic journey.

Keywords: Admissions, algorithms, cloud computing, differentiation, fog computing, leveling, machine learning.

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Authors: Svitov David, Alyamkin Sergey

Abstract:

The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax.

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Authors: J. L. Andrade-Pineda, J.M. León-Blanco, M. Calle, P. L. González-R

Abstract:

The enrollment in current Master's degree programs usually pursues gaining the expertise required in real-life workplaces. The experience we present here concerns the learning process of "Project Management Methodology (PMM)", around a cooperative/collaborative mechanism aimed at affording students measurable learning goals and providing the teacher with the ability of focusing on the weaknesses detected. We have designed a mixed summative/formative evaluation, which assures curriculum engage while enriches the comprehension of PMM key concepts. In this experience we converted the students into active actors in the evaluation process itself and we endowed ourselves as teachers with a flexible process in which along with qualifications (score), other attitudinal feedback arises. Despite the high level of self-affirmation on their discussion within the interactive assessment sessions, they ultimately have exhibited a great ability to review and correct the wrong reasoning when that was the case.

Keywords: Cooperative-collaborative learning, educational management, formative-summative assessment, leadership training.

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Authors: Guo Yanru, Zhu Xiaobo, Lee Chu Keong

Abstract:

This paper maps the structure of the social network of the 2011 class ofsixty graduate students of the Masters of Science (Knowledge Management) programme at the Nanyang Technological University, based on their friending relationships on Facebook. To ensure anonymity, actual names were not used. Instead, they were replaced with codes constructed from their gender, nationality, mode of study, year of enrollment and a unique number. The relationships between friends within the class, and among the seniors and alumni of the programme wereplotted. UCINet and Pajek were used to plot the sociogram, to compute the density, inclusivity, and degree, global, betweenness, and Bonacich centralities, to partition the students into two groups, namely, active and peripheral, and to identify the cut-points. Homophily was investigated, and it was observed for nationality and study mode. The groups students formed on Facebook were also studied, and of fifteen groups, eight were classified as dead, which we defined as those that have been inactive for over two months.

Keywords: Facebook, friending relationships, Social network analysis, social network sites, structural position

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