Teaching chemical bonding through jigsaw cooperative learning

This study examined the effectiveness of jigsaw cooperative learning in teaching chemical bonding at tertiary level. This study was carried out in two different classes in the Department of Primary Science Education of Atatürk University during the 2005–2006 academic year. One of the classes was the non‐jigsaw group (control) and the other was the jigsaw group (experimental). Students in the jigsaw group were divided into four ‘home groups’ since chemical bonding is divided into four subtopics (Modules A, B, C and D). Each of these home groups consisted of four students. The subjects covered were ionic bonding (Module A), covalent bonding (Module B), hydrogen bonding and van der Waals (Module C) and basic concepts about bonds (Module D). The main instrument for obtaining data was the Chemical Bonding Achievement Test (CBAT), which was applied to both groups. The CBAT was divided into four modules (A, B, C and D), in which each module consisted of five questions (four multiple‐choice and one open‐ended). The data obtained indicated that the students in the jigsaw group were more successful than those in the non‐jigsaw group.     

沈阳市少年运动员意志品质研究

目的：探讨沈阳市少年运动员的意志品质特点,并比较业余体校、专业少年运动员和普通少年学生在意志品质上的差异。方法：主要采用问卷法对沈阳市70名少年运动员和70名普通少年学生进行调查。结果：（1）女运动员在坚韧性上显著优于男运动员,在果敢性上不如男运动员;（2）业余与专业少年运动员的意志品质不存在显著差异;（3）少年运动员在意志品质的综合水平、自制性、果敢性、独立性等因素上显著优于普通少年学生。结论：少年运动员整体意志水平较高。     

DistanceRank: An intelligent ranking algorithm for web pages

A fast and efficient page ranking mechanism for web crawling and retrieval remains as a challenging issue. Recently, several link based ranking algorithms like PageRank, HITS and OPIC have been proposed. In this paper, we propose a novel recursive method based on reinforcement learning which considers distance between pages as punishment, called “DistanceRank” to compute ranks of web pages. The distance is defined as the number of “average clicks” between two pages. The objective is to minimize punishment or distance so that a page with less distance to have a higher rank. Experimental results indicate that DistanceRank outperforms other ranking algorithms in page ranking and crawling scheduling. Furthermore, the complexity of DistanceRank is low. We have used University of California at Berkeley’s web for our experiments.     

Seminal plasma levels of free 8-isoprostane and its relationship with sperm quality parameters

There is growing evidence that damage to spermatozoa by reactive oxygen species play a key role in male infertility. The aim of this study was to assess seminal plasma free 8-Isoprostane levels in men with asthenozoospermia, asthenoteratozoospermia and oligoasthenoteratozoospermia compared to normozoospermic males and its correlation with seminal parameters. The case group consisted of men with asthenozoospermia (n=15), asthenoteratozoospermia (n=16) and oligoasthenoteratozoospermia (n=15). The control group consisted of 16 males with normozoospermia. After Purification of Free 8-Isoprostane by affinity column, its concentration was measured by enzyme immunoassay method. Free 8-Isoprostane evaluation showed significantly greater values in the total case group (n=46) versus control group (18.23±3.56 vs 2.6±0.38 ng/ml). In each case group free 8-Isoprostane also showed a significant increasing compared to normozoospermic males. Free 8-Isoprostane showed an inversely significant correlation with sperm motility and sperm morphology. Lipid peroxidation could have significant role in etiology of sperm abnormalities. Measurement of 8-Isoprostane can be used as a specific biomarker for assessing lipid peoxidation in sperm.     

Vocational Schools in Turkey: An Administrative and Organizational Analysis

The data used in this paper were derived from a larger project which had the aim of critically evaluating the Turkish vocational education system on a number of different levels. This article examines the administrative and organisational practices in a selected group of secondary vocational schools in Turkey from the point of view of school administrators, teachers and industrial managers. The results indicate that the Turkish vocational education system is characterised by a centralised, top-down bureaucracy, which inhibits innovative capacity. The authors argue that a degree of decentralisation is necessary at various levels of the system.     

Temporal expert profiling: With an application to T-shaped expert finding

Cost optimization continues to be a critical concern for many human resources departments. The key is to balance between costs and business value. In particular, computer science organizations prefer to hire people who are expert in only one skill area and have a slight superficial knowledge in other areas that gives them the ability to collaborate across different aspects of project. Community Question Answering networks provide good platforms for people and organizations to share knowledge and find experts. An important issue in expert finding is that an expert has to constantly update his knowledge after being saturated in his field of expertise to still be identified as expert. A person who fails to preserve his expertise is likely to lose his expertise. This work justifies this question that does take the concept of time into account improve the quality of expertise retrieval. We propose a new method for T-shaped expert finding that is based on temporal expert profiling. The proposed method takes the temporal property of expertise into account to mine the shape of expertise for each candidate expert based on his profile. To this end, for each candidate expert, we take snapshots of his expertise trees at regular time intervals and learn the relation between temporal changes in different expertise trees and candidates’ profile. Finally, we use a filtering technique that is applied on top of the profiling method, to find shape of expertise for candidate experts. Experimental results on a large test collection show the superiority of the proposed method in terms of quality of results in comparison with state-of-the-art.     

The reflection of offline activities on users’ online social behavior: An observational study

The ever increasing presence of online social networks in users’ daily lives has led to the interplay between users’ online and offline activities. There have already been several works that have studied the impact of users’ online activities on their offline behavior, e.g., the impact of interaction with friends on an exercise social network on the number of daily steps. In this paper, we consider the inverse to what has already been studied and report on our extensive study that explores the potential causal effects of users’ offline activities on their online social behavior. The objective of our work is to understand whether the activities that users are involved with in their real daily life, which place them within or away from social situations, have any direct causal impact on their behavior in online social networks. Our work is motivated by the theory of normative social influence, which argues that individuals may show behaviors or express opinions that conform to those of the community for the sake of being accepted or from fear of rejection or isolation. We have collected data from two online social networks, namely Twitter and Foursquare, and systematically aligned user content on both social networks. On this basis, we have performed a natural experiment that took the form of an interrupted time series with a comparison group design to study whether users’ socially situated offline activities exhibited through their Foursquare check-ins impact their online behavior captured through the content they share on Twitter. Our main findings can be summarised as follows (1) a change in users’ offline behavior that affects the level of users’ exposure to social situations, e.g., starting to go to the gym or discontinuing frequenting bars, can have a causal impact on users’ online topical interests and sentiment; and (2) the causal relations between users’ socially situated offline activities and their online social behavior can be used to build effective predictive models of users’ online topical interests and sentiments.     

The impact of deep learning on document classification using semantically rich representations

This paper presents a semantically rich document representation model for automatically classifying financial documents into predefined categories utilizing deep learning. The model architecture consists of two main modules including document representation and document classification. In the first module, a document is enriched with semantics using background knowledge provided by an ontology and through the acquisition of its relevant terminology. Acquisition of terminology integrated to the ontology extends the capabilities of semantically rich document representations with an in depth-coverage of concepts, thereby capturing the whole conceptualization involved in documents. Semantically rich representations obtained from the first module will serve as input to the document classification module which aims at finding the most appropriate category for that document through deep learning. Three different deep learning networks each belonging to a different category of machine learning techniques for ontological document classification using a real-life ontology are used.Multiple simulations are carried out with various deep neural networks configurations, and our findings reveal that a three hidden layer feedforward network with 1024 neurons obtain the highest document classification performance on the INFUSE dataset. The performance in terms of F1 score is further increased by almost five percentage points to 78.10% for the same network configuration when the relevant terminology integrated to the ontology is applied to enrich document representation. Furthermore, we conducted a comparative performance evaluation using various state-of-the-art document representation approaches and classification techniques including shallow and conventional machine learning classifiers.     

Emotions Management Skills and Barriers with Library Staff: A Correlational Survey of Agriculture Students

The literature has identified barriers with library staff as one of the important barriers affecting academic activities of students and also recognized the relationship of various academic and demographic characteristics of students with it. The emotions management skills of students may be one of the possible correlates of the barriers with library staff. This study was designed to investigate the levels of barriers with library staff and emotions management skills as well as their possible correlation using two standardized scales. The data were collected from the final year undergraduate agriculture students. The results confirmed the existence of barriers with library staff among the participants of both genders experiencing the same level of anxiety. The participants scored 3.75 (average) on the emotions management scale. The results also revealed significantly negative correlation between emotions management skills and barriers with library staff among these students. These results have many practical implications in the sphere of academic librarianship.