Workshop: Training students to become better raters: Raising the quality of self- and peer-evaluations using a new feature of the CATME system

Author(s):  
Richard A. Layton ◽  
Misty L. Loughry ◽  
Matthew W. Ohland ◽  
Hal Pomeranz
Author(s):  
Cornelia Jareteg ◽  
Kristina Wärmefjord ◽  
Christoffer Cromvik ◽  
Rikard Söderberg ◽  
Lars Lindkvist ◽  
...  

Geometrical variation and deviation in all the manufacturing processes affect the quality of the final product. Therefore, geometry assurance is an important tool in the design phase of a new product. In the automotive and aviation industries where the use of composite parts is increasing drastically, new tools within variation simulations are needed. Composite parts tend to deviate more from nominal specification compared to metal parts. Methods to simulate the manufacturing process of composites have been developed before. In this paper, we present how to combine the process variation simulation of composites with traditional variation simulations. The proposed method is demonstrated on a real complex subassembly, representing part of an aircraft wing-box. Since traditional variation simulation methods are not able to capture the spring-in and the special deviation behavior of composites, the proposed method adds a new feature and reliability to the geometry assurance process of composite assemblies.


2020 ◽  
Vol 44 (2) ◽  
pp. 203-209
Author(s):  
Olivia S. Anderson ◽  
Noura El Habbal ◽  
Dave Bridges

Peer evaluation skills are not typically taught to students, yet they are expected to provide high-quality feedback to their peers. Gameful learning, a pedagogy supporting student-driven learning, can further reinforce the development of peer evaluation skills, if students are motivated to improve upon them. To better understand the effects of a peer evaluation training on the quality of student-generated peer evaluations, we scored peer evaluations from two cohorts taking a graduate-level nutritional sciences class using gameful learning pedagogy. The intervention group completed a peer evaluation training before engaging in peer reviews, while the control group did not. The training included two readings, a video, and reflection questions. The peer evaluations submitted by both the intervention and control groups were assessed on a validated rubric. The peer evaluation training had a positive effect on the quality of the submitted peer evaluations. The intervention group had a 10.8% higher score on its first submitted peer evaluation compared with controls ( P = 0.003). The intervention group improved the quality of its future submissions by a further 8.9%, whereas the controls did not continue to improve substantially ( P < 0.001). Overall, peer review training enhanced the quality of peer evaluations and allowed students to develop professional skills that they can utilize in any biomedical profession. Our results highlight the importance of peer evaluation training in combination with repeated practice and student-driven learning brought forth by gameful learning pedagogy in improving the quality of evaluations and developing professional skills.


Author(s):  
Albert Bruch

Abstract Taking advantage of the unparallel quantity and quality of high cadence Kepler light curves of several dwarf novae, the strength of the flickering and the high frequency spectral index of their power spectra are investigated as a function of magnitude around the outburst cycle of these systems. Previous work suggesting that the flickering strength (on a magnitude scale) is practically constant above a given brightness threshold and only rises at fainter magnitudes is confirmed for most of the investigated systems. As a new feature, a hysteresis in the flickering strength is seen in the sense that at the same magnitude level flickering is stronger during decline from outburst than during the rise. A similar hysteresis is also seen in the spectral index. In both cases, it can qualitatively be explained under plausible assumptions within the DIM model for dwarf nova outbursts.


The increasing usage of internet, online stores and social media has provided the users to express their opinion, attitude and views without any reluctance and fear on the World Wide Web. These opinions expressed by the users can be related to a product or service as well as any global issues. The colossal growth of the web technology has offered the consumers to know more about the products they intend to buy from the existing customer’s reviews. This paper focuses on analyzing the opinion by splitting the positive and negative opinion and then guides the user about the ground truth regarding the performance and quality of the product. The important idea here is to categorize the important features of the product and then accordingly provide the feature wise computation instead of roughly promoting a product as good or bad.


Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1358
Author(s):  
Airam Curtidor ◽  
Tetyana Baydyk ◽  
Ernst Kussul

This article describes and analyzes the new feature extraction technique, Random Local Descriptor (RLD), that is used for the Permutation Coding Neural Classifier (PCNC), and compares it with Local Binary Pattern (LBP-based) feature extraction. The paper presents a model of face feature detection using local descriptors, and describes an improvement on the PCNC for the recognition of plane rotated and small displaced face images, as applied to three databases, i.e., ORL, FRAV3D and FEI. All databases are described along with the recognition results that were obtained. We also include a comparison of our classifier with the Support Vector Machine (SVM) and Iterative Closest Point (ICP). The ORL database was selected to compare our RLDs with LBP-based algorithms. The PCNC with the RLDs demonstrated the best recognition rate, i.e., 97.49%, in comparison with 90.49% for LBPs. For the FEI image database, we obtained the best recognition rate, i.e., 93.57%, in comparison with 66.74% for LBPs. Using the RLDs and rotating the original images for FRAV3D, we improved the recognition rate by decreasing by approximately twice the number of errors. In addition, we analyzed the influence of different RLD parameters on the quality of facial recognition.


2021 ◽  
Vol 12 (1) ◽  
pp. 69-76
Author(s):  
Elmira Jafari Navimipour ◽  
Fatemeh Pournagi Azar ◽  
Sarvin Kholafazade

Background and Objectives: Professional qualification-based dentist training plays an important role in providing the health services needed by the community. One of the most important steps in dentistry is choosing the color and matching the color of the tooth with the restoration. Color selection training in the curriculum of Iranian dental schools is provided to students as implicit training in some related courses such as restorations and prosthetics, and there is no separate practical unit for students to learn and practice more. The purpose of this study is to investigate the role of workshop training in the quality of tooth color selection by final year students of Tabriz Dental School in the academic year2019-2020. Material and Methods: In a quasi-experimeایntal study; Final year students of Tabriz Dental School entered the study. Students were randomly divided into experimental and control groups. In the experimental group, after selecting the primary color, through the workshop training strategy, color selection by Vitapan system in the right maxilla incisor 3 patients were taught simple, medium and complex method of workshop training and one week after training the correct color selection It was reviewed by these students. In the control group, color selection was done by students in exactly the same conditions as the case group who had received routine training. The data obtained from the study were analyzed using descriptive statistical methods (frequency-percentage) and Fisher's Exact test and statistical software SPSS.16. Results: In all three groups of simple, medium and complex patients, the quality of color selection in the intervention group was improved, which was significantly different from a dental point of view; however, there was no statistically significant difference between the intervention and control groups in all three groups of patients. Also, the effect of training in choosing complex colors was more significant. Conclusion: The results of the present study showed that workshop training had a positive effect on the color choice of dental students. Because dentistry is a procedure-based discipline and not all procedures are seen in the training curriculum. The dental professor can choose some procedures based on the pervasive need and teach in one workshop day. On the other hand, workshop training can be an proper educational strategy based on adult learning that learners show a lot of desire to learn according to their job needs.


2020 ◽  
Vol 10 (9) ◽  
pp. 3166 ◽  
Author(s):  
Cheng-Jian Lin ◽  
Cheng-Hsien Lin ◽  
Shiou-Yun Jeng

In recent years, convolutional neural networks (CNNs) have been successfully used in image recognition and image classification. General CNNs only use a single image as feature extraction. If the quality of the obtained image is not good, it is easy to cause misjudgment or recognition error. Therefore, this study proposes the feature fusion of a dual-input CNN for the application of face gender classification. In order to improve the traditional feature fusion method, this paper also proposes a new feature fusion method, called the weighting fusion method, which can effectively improve the overall accuracy. In addition, in order to avoid the parameters of the traditional CNN being determined by the user, this paper uses a uniform experimental design (UED) instead of the user to set the network parameters. The experimental results show that in the dual-input CNN experiment, average accuracy rates of 99.98% and 99.11% on the CIA and MORPH data sets are achieved, respectively, which is superior to the traditional feature fusion method.


Author(s):  
Daniel M. Ferguson ◽  
Matthew W. Ohland ◽  
Chad Lally ◽  
Hilda Ibriga Somnooma ◽  
Yuchen Cao

Author(s):  
Vyacheslav Kazarenkov ◽  
Bui Thuy ◽  
Tatyana Kazarenkova ◽  
Galina Kameneva

In educational science today, there are many studies on the factors associated with students' creativity using various research methods. A new feature of our current study is to use Q-methodology to explore the teacher's perspective on the factors influencing students' creativity in the teaching process. We investigated the views of 42 lecturers working at three universities in Vietnam including Hanoi National University of Education, Can Tho University of Medicine and Pharmacy, National University of Civil Engineering. Results of Q-sort implementation of participants are processed using a special software dedicated to Q-methodology – Ken-Q Analysis version 1.0.6. The results of the study indicated that there are two factors affecting the development of the students' creativity. Factor 1 extracted was named as the psychological characteristics of the students themselves. Factor 1 with an eigenvalue of 22.79 accounted for 54% of the study variance and consisted of 23  lecturers defining for this factor. Factor 2 was named as characteristics of the teaching activity of teachers. It accounted for 8% of the study variance with an eigenvalue of 3.38 and contained 19 lecturers. These factors accounted for 62% of the total study variance. The results are considered as important suggestions for teachers and students to achieve the purpose of developing creative personalities. Moreover, this also is an instruction for educational managers to improve the quality of education at universities. 


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