Understanding MOOCs as an Emerging Online Learning Tool: Perspectives From the Students

This study examined participants’ learning experiences in the context of a six-week massive open online course (MOOC) in journalism with five thousand students from 137 countries. Three research questions were asked: (1) Who are the students and why are they enrolled in this MOOC?, (2) How much time have the students spent in taking this MOOC and have they completed all the assignments?, and, (3) What have they learned and what aspects of this MOOC do the students find most helpful? Four hundred and nine students responded to a survey and forty-four responded to interview questions. The main findings showed 84% of the participants were working professionals and only 28.9% were from a journalism background. Of those who did not complete the course, lack of time was the top reason. Most participants reported a positive learning experience, but lack of feedback and/or poor quality were reported as negative experiences. The discussion forum was the least liked aspect of the course.     

The effects of transport by pneumatic tube system on blood cell count,erythrocyte sedimentation and coagulation tests

Introduction:

Today, the pneumatic tube transport system (PTS) is used frequently because of its advantages related to timing and speed. However, the impact of various types of PTS on blood components is unknown. The aim of this study was to examine the influence of PTS on the quality of routine blood cell counts, erythrocyte sedimentation, and certain blood coagulation tests.

Materials and methods:

Paired blood samples were obtained from each of 45 human volunteers and evaluated by blood cell count, erythrocyte sedimentation, and several coagulation tests, including prothrombin time (PT) and activated partial thromboplastin time (aPTT). Blood samples were divided into 2 groups: Samples from group 1 were transported to the laboratory via the PTS, and samples from group 2 were transported to the laboratory manually. Both groups were evaluated immediately by the tests listed above.

Results:

The blood sample test results from groups 1 and 2 were evaluated and compared. No statistically significant differences were observed (P = 0.069–0.977).

Conclusion:

The PTS yielded no observable effects on blood cell counts, erythrocyte sedimentation, or PT and aPTT test results. We concluded that the PTS can be used to transport blood samples and yield reliable results for blood cell counts, erythrocyte sedimentation, and several coagulation tests.     

Powerful Actor and Hesitant Institutionalization: The State in the History of Turkish Football

We examine the validity of the assumptions of the new institutional theory about the state over the history of national football league as an institutional field in Turkey. The state is not out of the field, on the contrary, at the centre of the field, and is not an ordinary actor but the most important one although the intensity of the state’s impact changes from time to time. Sometimes, the state founds the football clubs and administrates them directly, decides who will be the champion; and sometimes, authorizes the regulative agency and gives autonomy. However, despite the state’s coercive power on the ground, the Turkish football field is still far from being fully institutionalized with its fluctuating structure.     

The glue that makes it “hang together”: A framework for identifying how metadiscourse facilitates uncertainty navigation during knowledge building discussions

Classroom discussions have become a centerpiece of reform efforts in science education because talk mediates the joint co-constructing of knowledge in science classrooms. Although decades of research underscore the importance of talk in supporting science learning, the science education community continues to grapple with how to support teachers and students in navigating the uncertainty that is associated with doing knowledge building work. To address these challenges, we must examine not just what gets constructed (the scientific ideas), but how knowledge is co-constructed by teachers and students (the process of building those ideas) amidst uncertainty. In this study, we propose a conceptual tool for identifying organizational, epistemic, and interpretive metadiscourse markers (MDMs) in science talk. We highlight how teachers and students use these three types of MDMs as they navigate uncertainty while connecting ideas within and across multiple turns of talk, leveraging resources for knowledge building, and making interpretations about one another's ideas. We conclude with a set of suggestions for how researchers and teachers can utilize this framework to attend to the ways that MDMs index the organizational, epistemic, and interpretive dimensions of uncertainty in the knowledge building process.     

Formation of ots self-assembled monolayer on glass surface investigated by AFM

The whole process of octadecyltrichlorosilane (OTS) self-assembled monolayer formation on glass surface was clearly revealed by using Atomic Force Microscope (AFM). The growth regularity pattern of OTS self-assembled monolayer on glass substrate was obtained by analyses of the AFM images and the average surface mean roughness (R _avg) of the sample surfaces. The adsorption feature of OTS molecules on the substrate surface during the initial reaction period was probed through a comparison experiment. Project supported by the Scientific Research Foundation for Retured Overseas Chinese Scholar, State Education Committee.     

WSVR-based fuzzy neural network with annealing robust algorithm for system identification

This paper proposes a fuzzy neural network (FNN) based on wavelet support vector regression (WSVR) approach for system identification, in which an annealing robust learning algorithm (ARLA) is adopted to adjust the parameters of the WSVR-based FNN (WSVR-FNN). In the WSVR-FNN, first, the WSVR method with a wavelet kernel function is used to determine the number of fuzzy rules and the initial parameters of FNN. After initialization, the adjustment for the parameters of FNNs is performed by the ARLA. Combining the self-learning ability of neural networks, the compact support of wavelet functions, the adaptive ability of fuzzy logic, and the robust learning capability of ARLA, the proposed FNN has the superiority among the several existed FNNs. To demonstrate the performance of the WSVR-FNN, two nonlinear dynamic plants and a chaotic system taken from the extant literature are considered to illustrate the system identification. From the simulation results, it shows that the proposed WSVR-FNN has the superiority over several presented FNNs even the number of training parameters is considerably small.     

Asymmetric Missing-data Problems: Overcoming the Lack of Negative Data in Preference Ranking

In certain classification problems there is a strong a asymmetry between the number of labeled examples available for each of the classes involved. In an extreme case, there may be a complete lack of labeled data for one of the classes while, at the same time, there are adequate labeled examples for the others, accompanied by a large body of unlabeled data. Since most classification algorithms require some information about all classes involved, label estimation for the un-represented class is desired. An important representative of this group of problems is that of user interest/preference modeling where there may be a large number of examples of what the user likes with essentially no counterexamples.Recently, there has been much interest in applying the EM algorithm to incomplete data problems in the area of text retrieval and categorization. We adapt this approach to the asymmetric case of modeling user interests in news articles, where only labeled positive training data are available, with access to a large corpus of unlabeled documents. User modeling is here equivalent to that of user-specific document ranking. EM is used in conjunction with the Naive Bayes model while its output is also utilized by a Support Vector Machine and Rocchio's technique.Our findings demonstrate that the EM algorithm can be quite effective in modeling the negative class under a number of different initialization schemes. Although primarily just the negative training examples are needed, a natural question is whether using all of the estimated labels (i.e., positive and negative) would be more (or less) beneficial. This is important considering that, in this context, the initialization of the negative class for EM is likely not to be very accurate. Experimental results suggest that EM output should be limited to negative label estimates only.     

Combining evidence with a probabilistic framework for answer ranking and answer merging in question answering

Question answering (QA) aims at finding exact answers to a user’s question from a large collection of documents. Most QA systems combine information retrieval with extraction techniques to identify a set of likely candidates and then utilize some ranking strategy to generate the final answers. This ranking process can be challenging, as it entails identifying the relevant answers amongst many irrelevant ones. This is more challenging in multi-strategy QA, in which multiple answering agents are used to extract answer candidates. As answer candidates come from different agents with different score distributions, how to merge answer candidates plays an important role in answer ranking. In this paper, we propose a unified probabilistic framework which combines multiple evidence to address challenges in answer ranking and answer merging. The hypotheses of the paper are that: (1) the framework effectively combines multiple evidence for identifying answer relevance and their correlation in answer ranking, (2) the framework supports answer merging on answer candidates returned by multiple extraction techniques, (3) the framework can support list questions as well as factoid questions, (4) the framework can be easily applied to a different QA system, and (5) the framework significantly improves performance of a QA system. An extensive set of experiments was done to support our hypotheses and demonstrate the effectiveness of the framework. All of the work substantially extends the preliminary research in Ko et al. (2007a). A probabilistic framework for answer selection in question answering. In: Proceedings of NAACL/HLT.     

Designing a business model for financial products for cultural heritage in the Korean market

There are many contingent valuation (CV) studies to estimate the economic benefits of cultural heritage, but few provided advice on the design of financial products for cultural heritage assets. This paper conducted conjoint and willingness-to-pay (WTP) analyses for providing the design implication of these financial products. We calculated WTP for each attribute. The result of conjoint analysis shows that people prefer a short period of investment, high-expected rate of return and small amount of money invested. Only the amount invested and the rate of return on investment are significant to estimate WTP for these financial products.