Some Guidance on Conducting and Reporting Qualitative Studies

This paper sets out to address the problem of the imbalance between the number of quantitative and qualitative articles published in highly ranked research journals, by providing guidelines for the design, implementation and reporting of qualitative research. Clarification is provided of key terms (such as quantitative and qualitative) and the interrelationships between them. The relative risks and benefits of using guidelines for qualitative research are considered, and the importance of using any such guidelines flexibly is highlighted. The proposed guidelines are based on a synthesis of existing guidelines and syntheses of guidelines from a range of fields

Research on ICT in K-12 schools e A review of experimental and survey-based studies in computers & education 2011 to 2015

International audienceWhat is the role of a journal? Is it to follow the research or lead it? For the former, it is to serve as an archival record of the scholarship in a field. It can serve to permit the research community to engage with each other via the written record. But, for the latter, it can serve the research community by pointing out gaps in the research based on the archival record. This review is intended to do just that

The Relationships among Chinese Practicing Teachers ’ Epistemic Beliefs, Pedagogical Beliefs and Their Beliefs about the Use of ICT

This study aimed to investigate the relationships among practicing teachers ’ epistemic beliefs, pedagogical beliefs and their beliefs about the use of ICT through survey methodology. Participants were 396 high school practicing teachers from mainland China. The path analysis results analyzed via structural equation modelling technique indicated that the systemic relationships among these three types of beliefs were nested. Specifically, teachers ’ sophisticated beliefs about the source of knowledge were aligned with constructivist pedagogical beliefs and constructivist use of ICT, with one belief highly related to another

Eighth graders' web searching strategies and outcomes: The role of task types, web experience and epistemological beliefs

Abstract This study reported an investigation of eighth graders' (14-year-olds) web searching strategies and outcomes, and then analyzed their correlations with students' web experiences, epistemological beliefs, and the nature of searching tasks. Eighty-seven eighth graders were asked to fill out a questionnaire for probing epistemological beliefs (from positivist to constructivist-oriented views) and finished three different types of searching tasks. Their searching process was recorded by screen capture software and answers were reviewed by two expert teachers based on their accuracy, richness and soundness. Five quantitative indicators were used to assess students' searching strategies: number of keywords, visited pages, maximum depth of exploration, refinement of keyword, and number of words used in the first keyword. The main findings derived from this study suggested that, students with richer web experiences could find more correct answers in ''closeended" search tasks. In addition, students with better metacognitive skills such as keyword refinement tended to achieve more successful searching outcomes in such tasks. However, in ''open-ended" tasks, where questions were less certain and answers were more elaborated, students who had more advanced epistemological beliefs, concurring with a constructivist view, had better searching outcomes in terms of their soundness and richness. This study has concluded that epistemological beliefs play an influential role in open-ended Internet learning environments

Thermodynamical Properties and Quasi-localized Energy of the Stringy Dyonic Black Hole Solution

In this article, we calculate the heat flux passing through the horizon $. {\bf TS}|_{r_h}$ and the difference of energy between the Einstein and M{\o}ller prescription within the region ${\cal M}$, in which is the region between outer horizon ${\cal H}_+$ and inner horizon ${\cal H}_-$, for the modified GHS solution, KLOPP solution and CLH solution. The formula . E_{\rm Einstein}|_{\cal M} = . E_{\rm M{\o}ller}|_{\cal M} - \sum_{\partial {\cal M}} {\bf TS}$ is obeyed for the mGHS solution and the KLOPP solution, but not for the CLH solution. Also, we suggest a RN-like stringy dyonic black hole solution, which comes from the KLOPP solution under a dual transformation, and its thermodynamical properties are the same as the KLOPP solution

Discovery of dominant and dormant genes from expression data using a novel generalization of SNR for multi-class problems

<p>Abstract</p> <p>Background</p> <p>The Signal-to-Noise-Ratio (SNR) is often used for identification of biomarkers for two-class problems and no formal and useful generalization of SNR is available for multiclass problems. We propose innovative generalizations of SNR for multiclass cancer discrimination through introduction of two indices, Gene Dominant Index and Gene Dormant Index (GDIs). These two indices lead to the concepts of dominant and dormant genes with biological significance. We use these indices to develop methodologies for discovery of dominant and dormant biomarkers with interesting biological significance. The dominancy and dormancy of the identified biomarkers and their excellent discriminating power are also demonstrated pictorially using the scatterplot of individual gene and 2-D Sammon's projection of the selected set of genes. Using information from the literature we have shown that the GDI based method can identify dominant and dormant genes that play significant roles in cancer biology. These biomarkers are also used to design diagnostic prediction systems.</p> <p>Results and discussion</p> <p>To evaluate the effectiveness of the GDIs, we have used four multiclass cancer data sets (Small Round Blue Cell Tumors, Leukemia, Central Nervous System Tumors, and Lung Cancer). For each data set we demonstrate that the new indices can find biologically meaningful genes that can act as biomarkers. We then use six machine learning tools, Nearest Neighbor Classifier (NNC), Nearest Mean Classifier (NMC), Support Vector Machine (SVM) classifier with linear kernel, and SVM classifier with Gaussian kernel, where both SVMs are used in conjunction with one-vs-all (OVA) and one-vs-one (OVO) strategies. We found GDIs to be very effective in identifying biomarkers with strong class specific signatures. With all six tools and for all data sets we could achieve better or comparable prediction accuracies usually with fewer marker genes than results reported in the literature using the same computational protocols. The dominant genes are usually easy to find while good dormant genes may not always be available as dormant genes require stronger constraints to be satisfied; but when they are available, they can be used for authentication of diagnosis.</p> <p>Conclusion</p> <p>Since GDI based schemes can find a small set of dominant/dormant biomarkers that is adequate to design diagnostic prediction systems, it opens up the possibility of using real-time qPCR assays or antibody based methods such as ELISA for an easy and low cost diagnosis of diseases. The dominant and dormant genes found by GDIs can be used in different ways to design more reliable diagnostic prediction systems.</p

The effects of rear-wheel camber on the kinematics of upper extremity during wheelchair propulsion

BACKGROUND: The rear-wheel camber, defined as the inclination of the rear wheels, is usually used in wheelchair sports, but it is becoming increasingly employed in daily propulsion. Although the rear-wheel camber can increase stability, it alters physiological performance during propulsion. The purpose of the study is to investigate the effects of rear-wheel cambers on temporal-spatial parameters, joint angles, and propulsion patterns. METHODS: Twelve inexperienced subjects (22.3±1.6 yr) participated in the study. None had musculoskeletal disorders in their upper extremities. An eight-camera motion capture system was used to collect the three-dimensional trajectory data of markers attached to the wheelchair-user system during propulsion. All participants propelled the same wheelchair, which had an instrumented wheel with cambers of 0°, 9°, and 15°, respectively, at an average velocity of 1 m/s. RESULTS: The results show that the rear-wheel camber significantly affects the average acceleration, maximum end angle, trunk movement, elbow joint movement, wrist joint movement, and propulsion pattern. The effects are especially significant between 0° and 15°. For a 15° camber, the average acceleration and joint peak angles significantly increased (p < 0.01). A single loop pattern (SLOP) was adopted by most of the subjects. CONCLUSIONS: The rear-wheel camber affects propulsion patterns and joint range of motion. When choosing a wheelchair with camber adjustment, the increase of joint movements and the base of support should be taken into consideration

Seismic behavior of pile in liquefiable soil ground by centrifuge shaking table tests

Dramatic failure of pile foundations caused by the soil liquefaction was founded and leading to many studies on the seismic behavior of pile. The failures were often accompanied with settlement, lateral displacement and tilting of superstructures. Therefore soil-structure interaction effects must be properly considered in the design of pile. Two centrifuge models were conducted by shaking table at an acceleration field of 80 g. The purpose of this study was to investigate the seismic response of piles attached with different tip mass and embedded in liquefied or non-liquefied deposits. From the results, it was found that the maximum bending moment of pile occurs at the depth of 4 m and 5 m for dry sand and saturated sand models, respectively. The more tip mass leads to the more permanent lateral displacement and the more residual bending moment

Deep Learning for Spin-Orbit Torque Characterizations with a Projected Vector Field Magnet

Spin-orbit torque characterizations on magnetic heterostructures with perpendicular anisotropy are demonstrated on a projected vector field magnet via hysteresis loop shift measurement and harmonic Hall measurement with planar Hall correction. Accurate magnetic field calibration of the vector magnet is realized with the help of deep learning models, which are able to capture the nonlinear behavior between the generated magnetic field and the currents applied to the magnet. The trained models can successfully predict the applied current combinations under the circumstances of magnetic field scans, angle scans, and hysteresis loop shift measurements. The validity of the models is further verified, complemented by the comparison of the spin-orbit torque characterization results obtained from the deep-learning-trained vector magnet system with those obtained from a conventional setup comprised of two separated electromagnets. The damping-like spin-orbit torque (DL-SOT) efficiencies (|$\xi_{DL}$|) extracted from the vector magnet and the traditional measurement configuration are consistent, where |$\xi_{DL}$| $\approx$ 0.22 for amorphous W and |$\xi_{DL}$| $\approx$ 0.02 for $\alpha$-W. Our work provides an advanced method to meticulously control a vector magnet and to conveniently perform various spin-orbit torque characterizations