Analyzing the effects of the personality traits on the success of online collaborative groups

The purpose of this study is to analyze how efficient online study groups can be formed among students based on their personality traits. A survey consisting of Ten Item Personality Inventory (TIPI) was conducted among the undergraduate students in a well-known university. Eighty-two students who did not know each other were assigned to 35 small online groups based on their personality characteristics. The group members were then asked to study collaboratively on a task by communicating via the university's learning management system (LMS) forums. It was found that other factors (such as gender) were more effective than personality traits on the group success, and groups with lower degrees of Emotional Stability scores obtained higher grades over the task. This study is one of the first examples that hierarchically show different factors affecting the success of online groups with data mining techniques. The findings of the study will contribute to the field of online collaborative learning that is one of the most prominent subject in distance education. (C) 2016 The Authors. Published by Elsevier Ltd

A Dimension Reduction Approach to Player Rankings in European Football

Player performance evaluation is a challenging problem with multiple dimensions. Football (soccer) is the largest sports industry in terms of monetary value and it is paramount that teams can assess the performance of players for both financial and operational reasons. However, this is a difficult task, not only because performance differs from position to position, but also it is based on competition, time played and team play-styles. Because of this, raw player statistics are not comparable across players and must be processed to facilitate a fair performance evaluation. Furthermore, teams may have different requirements and a generic player performance evaluation does not directly serve the particular expectations of different clubs. In this study, we provide a generic framework for estimating player performance and performing player-fit-to-criteria assessment, under different objectives, for left and right backs from competitions worldwide. The results show that the players who have ranked high have increased their transfer values and they have moved to suitable teams. Global nature of the proposed methodology expands the analyzed player pool, facilitating the search for outstanding players from all available competitions

Impact of individual differences on the use of mobile phones and applications

Many studies examining the relation between mobile phone use and the personality traits of individual users have concluded that a significant relationship exists with extraversion standing out as a common trait in this context. In addition, innovativeness plays a key role in the users' adoption of technology and this has been studied within the domain of information systems including the adoption of mobile commerce. This study investigates the relationship between innovativeness, extraversion, mobile phone use and mobile applications, for the first time in the literature. A structured survey was administered to 343 university students. The results showed that mobile phone use features are predominantly related with the trait of extraversion whereas mobile application use features are mostly related with the innovativeness of the user

Dış Mekan Gözetleme İçin Olağandışı Olay Tespiti

Projenin amacı birbiri ile ilişkili davranışları olan birçok nesneyi içeren karmaşık davranışların sergilendiği kalabalık alanlarda olağandışı olayları tespit etmek için bir çerçeve oluşturmaktır. Karmaşık davranışlar ve alanlar için otomatik olay tespiti özellikle davranış gösterim şeklinin ve model yapısının seçimi ile ilgili zorluklar içermektedir. Özellikle pek çok nesne içeren kalabalık ortamlarda bu nesnelerin ayrı ayrı takibi mümkün olamamaktadır ve bu nedenle nesneler arasındaki ilişkiler ve olağandışı durumların tespiti güçtür. Son zamanlarda nesnelerin ayrı ayrı takibi yerine öğrenme tabanlı yöntemler öne çıkmaktadır. Bu yöntemler beklenen davranışları verilen örneklerden öğrenir. Daha sonra beklenen davranışlardan sapan örüntüleri tespit etmeyi hedefler. Bu projede, dış mekan videolarındaki olağandışı olayların belirlenmesi için bir çerçeve oluşturmak amaçlanmaktadır. Sistem öncelikle trafik videoları üzerinde denenerek olağandışı (kural ihlali ve kazalar gibi) hareketlerin tespiti için denenecektir. Bu projede hem belirgin hem de hemen göze çarpmayan olağandığı dışı durumların bulunduğu durumlar için bir model önerilmesi hedeflenmektedir. Bu model aşağıdaki durumlar için uyarlanır olacaktır: • Belirgin ve hemen göze çarpmayan olağandışı durumlar içeren kalabalık ve karmaşık sahneler, • Karmaşık davranışlar gösteren nesneler, • Birbirleriyle etkileşimde bulunan pek çok nesne. Bu projede Loy ve diğerlerinin[1] çalışması temel alınacaktır. [1] C.C. Loy, T. Xiang and S. Gong. Detecting and Discriminating Behavioural Anomalies. Pattern Recognition, 44(1):117-132, 2011

Clustering of Local Behaviour in Crowd Videos

Surveillance cameras are playing more important role in our daily life with the increasing number of human population and surveillance cameras. While there are a myriad of methods for video analysis, they are generally designed for low-density areas. Running of these algorithms in crowded areas would not give expected results and results in high number of false alarms giving rise to a need for different approaches for crowded area surveillance. Due to occlusions and images of individuals having a low resolution, holistic approaches have started to be preferred rather than detection and tracking of individuals. In this work, a method based on detection of regional behaviors in high density crowds is proposed. The method clusters the crowd behavior in different areas of the scene and can be used as a basis for anomaly detection

The Impacts of Persuasive Messages on Students Motivation and Learning Management System Use

Persuasive messaging is used to change individuals' behaviours in a specific way, which are effective mechanisms in decision making and are mainly created based on persuasion strategies. Persuasive messaging has been applied in numerous contexts such as e-health, fund-raising. In this study, the effects of Cialdini's six persuasion principles (authority, scarcity, commitment, liking, consensus, reciprocation) in education context were studied via persuasive messaging for the first time in the literature. An experimental study was conducted with 147 students in an introductory IT course. To collect data, initially students filled motivated strategies for learning questionnaire (to measure motivation), Big Five Inventory (to measure personality) and susceptibilities to persuasion strategies scale (to measure persuadability). Treatment and control groups were created according to personality scores, motivation scores, persuadability scores obtained from the pre-survey, class type (online class or blended class) and departments of the students to form homogenous groups. One treatment and one control group were created for each class type making a total of 4 groups. During 12-week trimester, the treatment groups were sent messages including persuasive cues while the control groups were sent messages without persuasive cues or no messages. The messages included midterm reminders, assignment reminders, online quizzes, online discussions and related shares. At the end of the experiment, the students' Learning Management System (LMS) use and motivation (all of which refers to general attendance to the course) differences in control and treatment groups were compared. Additionally, students' opinions about the messages were explored. The results showed that there is no significant difference between the two student groups' LMS uses and motivations. However, the students' opinions about the messages in the treatment groups were more positive than the students in the control groups which show that persuasive messages are more effective. This study suggests that adoption of persuasive cues in messages should be considered if the instructors want to take their students attention to their announcements or course related messages especially in online learning environments

The impact of individual differences on influence strategies

Persuasion and its applications aim at positively changing human behavior and they work the best when they are tailored to individuals. Recent studies show that individuals could give different responses to the same persuasion strategies which lead to personalization of persuasion strategies for better effectiveness. This study investigates what persuasion strategies are more effective for whom. More specifically, the relationship between the Big Five Personality traits (extraversion, neuroticism, agreeableness, conscientiousness and openness) and six persuasion strategies (authority, reciprocation, scarcity, liking, commitment and consensus) is explored. This study was conducted with 381 university students. A structured questionnaire comprising the Big Five Inventory Personality Trait scale and the Susceptibility to Persuasion Strategies scale was used to collect data. The Bayesian estimation was employed to reveal causal relationships. The results show that there are significant relations between personality traits and influence strategies

A Hadoop solution for ballistic image analysis and recognition

The importance of ballistic applications has been recently recognized due to the increasing crime and terrorism threats and incidents around the world. Ballistic image analysis is one of the application areas which requires immediate response with high precision from large databases. Here, the microscopic markings on cartridge case of a bullet obtained in a crime scene are compared with that of images on ballistic databases for similarity in order to find out whether it is fired from any of the firearms within the database. In this paper, we have implemented a MapReduce solution using Hadoop for ballistic image comparison which is a high data and computation intensive task. MapReduce, a programming model developed by Google, provides a scalable, flexible and QoS guaranteed IT infrastructure particularly for embarrassingly parallel data oriented computational tasks. Our results have shown that we can effectively utilize the computing resources and gain significant increases in performance. Furthermore, we will share our experiences in programming and tuning a Hadoop cluster in the paper