Wirkung von schriftlicher Fehlerkorrektur -Überzeugungen von Lehrenden und Ergebnisse empirischer Untersuchungen bei Lernenden im japanischen DaF-Kontext

Ohta, Tatsuya 한국독일어교육학회 2015 외국어로서의 독일어 Vol.37 No.-

This paper presents the results of a survey among German language teachers in Japan about their beliefs with regards to the effects of written corrective feedback. This survey is a complement to a prior, large-scale study on the effects of written corrective feedback. Therefore, this paper opens with a summary of the results of that study. The target group of the survey were teachers of German as a foreign language at Japanese universities. The survey was conducted online, the identity of the respondents was kept anonymous. The respondents were asked questions about their beliefs regarding teaching German, their opinions on the efficiency of various types of feedback and patterns of classroom interaction (individual work, pair work, group work etc.), as well as their actual behaviour when correcting. One of the main insights from this survey is that respondents regarded direct feedback as much less effective than indirect feedback (by applying error codes or by underlining). When comparing the answers of Japanese respondents with those of native speakers of German, it is obvious that among Japanese teachers, the tendency to emphasize accurate memorization of grammar rules was greater than among their non-Japanese colleagues. The native speakers of German, on the other hand, tended to place greater value on explorative learning than on teaching explicit grammar rules. Also, the non-Japanese group was notably less appreciative of outright error correction than of code marking errors or of underlining them. Peer feedback was highly appreciated by several of the respondents. Furthermore it was stated, that feedback depends on a number of factors such as the learners’ language ability, their learning goals, the text type, the type of error, and the available time frame. The question, if teachers’ self-reports match their actual behaviour when correcting, still needs to be investigated. But what can be said at this point is that in teacher training as well as in teacher professional development, fostering the capacity of reflection should become one of the central tenets. In der vorliegenden Arbeit werden die Ergebnisse einer Umfrage zu Überzeugungen (beliefs) von Deutschlehrenden in Japan in Bezug auf die Wirkung von schriftlicher Fehlerkorrektur vorgestellt. Die Befragung wurde als Ergänzung einer vorangehenden großangelegten Studie zum Thema Wirkung von schriftlicher Fehlerkorrektur durchgeführt, daher werden zuerst die Erkenntnisse dieser Studie (Ohta 2015) kurz zusammengefasst. Zielgruppe der Umfrage waren Deutschlehrende, die an Universitäten in Japan tätig sind. Die Befragung fand online und anonym statt. Gefragt wurde u. a. nach Überzeugungen zum Deutschunterricht, Meinungen zur Wirkung verschiedener Feedbacktypen und Sozialformen sowie zum konkreten Vorgehen bei der Korrektur. Dabei stellte sich heraus, dass direktes Feedback von den Befragten deutlich schlechter eingeschätzt wird als indirektes Feedback durch Fehlercodes oder Unterstreichung. Beim Vergleich zwischen den japanischen und muttersprachlichen Lehrenden ergab sich, dass die japanischen Lehrenden auf genaues Merken von Grammatikregeln größeren Wert legen als die muttersprachlichen. Die muttersprachlichen Lehrenden schätzen hingegen entdeckendes Lernen viel wichtiger ein als die explizite Erklärung von Grammatikregeln. Außerdem bewerten die muttersprachlichen Lehrenden die Wirkung direkter Berichtigung von Fehlern deutlich schlechter als das Versehen von Fehlerstellen mit Unterstreichungen und Fehlercodes. Peer-Feedback wird von einem Teil der Befragten sehr positiv eingeschätzt. Welches Feedback gegeben wird, kommt allerdings auf verschiedene Aspekte an, wie Sprachniveau der Lernenden, Typ der Fehler, Textsorte, Lernziel, die zur Verfügung stehende Zeit etc. Ob die Überzeugungen der Lehrenden und ihr tatsächliches Korrekturverhalten übereinstimmen, sollte jedoch empirisch überprüft werden. Lehrende zur Lehrkompetenz der Selbstreflexion anzuleiten, sollte eine der wichtigsten Aufgaben in zukünftigen Aus- und Fortbildungsprogrammen darstellen.

CHEMICAL AND OPTICAL PROPERTIES OF ATMOSPHERIC AEROSOLS IN JAPANESE AREA

Ohta, Sachio,Murao, Naoto,Yamagata, Sadamu,Kaneyasu, Naoki 대한원격탐사학회 1995 International Symposium on Remote Sensing Vol.11 No.1

Photo-based Desktop Virtual Reality System Implemented on a Web-browser

Ohta, Masaya,Otani, Hiroki,Yamashita, Katsumi The Institute of Electronics and Information Engin 2014 IEIE Transactions on Smart Processing & Computing Vol.3 No.2

This paper proposes a novel desktop virtual reality system. Based on the position of the user's face, the proposed system selects the most appropriate image of an object from a set of photographs taken at various angles, and simply "pastes" it onto the display at the appropriate location and scale. Using this system, the users can intuitively feel the presence of the object.

Two Dimensional Analysis of Staphylococcal Exoproteins for the Application in Epidemiological Study

Ohta, Michio,Kawano, Yasushi,Nakano, Miyo,Kawagishi, Mika,Hasegawa, Tadao The Korea Society for Microbiology 2000 大韓微生物學會誌 Vol.35 No.5

A comparative survey on SAR image segmentation using deep learning

Ohtae Jang,Sangho Jo,Sungho Kim 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11

Synthetic Aperture Radar (SAR) image is a radar system that observes topographic maps using microwaves as an active sensor. Due to the backscattering characteristics of SAR, speckle is distributed in the image, making it difficult to analyze. This paper investigates the classically used unsupervised method of SAR image segmentation that can easily recognize and analyze SAR images and the recently used deep learning algorithm, and compare the accuracy using performance metrics. Although the method using deep learning has the problem of insufficient dataset, it improves performance by 10-20% compared to unsupervised. Also, among deep learning algorithms, how the algorithms used in Electro Optical / Infrared (EO / IR) are used in SAR images and problems are investigated. In a recent study, the SAR image considered as a visible light image and applied it to a deep learning algorithm using eo to obtain results. In the future, more benchmark datasets for SAR images should be built, and research on deep learning algorithms using SAR data information will be conducted.

Parametric study of porous media as substitutes for flow-diverter stent

Ohta, Makoto,Anzai, Hitomi,Miura, Yukihisa,Nakayama, Toshio Techno-Press 2015 Biomaterials and biomedical engineering Vol.2 No.2

For engineers, generating a mesh in porous media (PMs) sometimes represents a smaller computational load than generating realistic stent geometries with computer fluid dynamics (CFD). For this reason, PMs have recently become attractive to mimic flow-diverter stents (FDs), which are used to treat intracranial aneurysms. PMs function by introducing a hydraulic resistance using Darcy's law; therefore, the pressure drop may be computed by test sections parallel and perpendicular to the main flow direction. However, in previous studies, the pressure drop parallel to the flow may have depended on the width of the gap between the stent and the wall of the test section. Furthermore, the influence of parameters such as the test section geometry and the distance over which the pressure drops was not clear. Given these problems, computing the pressure drop parallel to the flow becomes extremely difficult. The aim of the present study is to resolve this lack of information for stent modeling using PM and to compute the pressure drop using several methods to estimate the influence of the relevant parameters. To determine the pressure drop as a function of distance, an FD was placed parallel and perpendicular to the flow in test sections with rectangular geometries. The inclined angle method was employed to extrapolate the flow patterns in the parallel direction. A similar approach was applied with a cylindrical geometry to estimate loss due to pipe friction. Additionally, the pressure drops were computed by using CFD. To determine if the balance of pressure drops (parallel vs perpendicular) affects flow patterns, we calculated the flow patterns for an ideal aneurysm using PMs with various ratios of parallel pressure drop to perpendicular pressure drop. The results show that pressure drop in the parallel direction depends on test section. The PM thickness and the ratio of parallel permeability to perpendicular permeability affect the flow pattern in an ideal aneurysm. Based on the permeability ratio and the flow patterns, the pressure drop in the parallel direction can be determined.

Evaluation of Calcifying Tendinitis of the Shoulder by Arthroscopic Surgery

OHTA Satoru 대한견주관절의학회 2009 대한견주관절학회 학술대회논문집 Vol.2009 No.5

Fluorescence Behavior Associated with a Possible Intercolumnar Charge-transfer Interaction in the Crystalline State of a Dyad Consisting of Mesitylene and 1,4-Dicyano-2-methylnaphthalene Subunits

Ohta, Eisuke,Kobayashi, Hitoshi,Sakai, Atsushi,Matsui, Yasunori,Sato, Hiroyasu,Ikeda, Hiroshi Korean Society of Photoscience 2015 Rapid communication in photoscience Vol.4 No.2

Fluorescence (FL) properties of a novel donor-acceptor dyad, comprised of mesitylene and 1,4-dicyano-2-methylnaphthalene (DCMN) subunits connected by an ether linkage, were elucidated. The dyad in cyclohexane exhibits FL arising from an intramolecular exciplex. In the crystalline state, the dyad does not emit light from intra- and inter-molecular exciplexes but rather displays FL that is nearly equivalent to that of 2-methoxymethyl-substituted DCMN. However, the emission spectrum of the crystalline dyad contains a shoulder in the long wavelength region, suggesting that weak intercolumnar charge-transfer interactions take place between columns consisting of the mesitylene and DCMN subunits.

Three-Dimensional Structure-Activity Relationships and Receptor Mapping of N1-Substituents of Quinolone Antibacterials

Ohta, Masateru,Koga, Hiroshi 전남대학교 약품개발연구소 1996 약품개발연구지 Vol.4 No.1

Scene graph descriptors for visual place classification from noisy scene data

Ohta Tomoya,Tanaka Kanji,Yamamoto Ryogo 한국통신학회 2023 ICT Express Vol.9 No.6

In visual robot place recognition (VPR), a scene graph is a rich scene model that can describe the complex contexts in a scene such as the relationships between various types of visual contents including appearance, space, and semantics. However, training an efficient scene graph classifier is not straightforward. Existing approaches typically rely on exhaustive matching between query and database graphs and are not scalable to large-size VPR problems. Our research is motivated by a recent development of the graph convolutional neural network (GCN) as an efficient and discriminative classifier for graph data, and it aims to explore the potential of the GCN as a scene graph classifier. However, unlike several existing GCN applications, no valid scene graph descriptor for a GCN classifier on noisy scene data exists. To address this issue, herein, we propose to train the GCN model in a teacher-to-student knowledge transfer scheme by employing an existing state-of-the-art single-view VPR system as the teacher model. The proposed approach is implemented within a practical VPR framework by combining the best of the following three independent fields: multimodal information retrieval, rank matching, and similarity-based pattern recognition. Experiments using the public NCLT dataset validate the effectiveness of the proposed approach.