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The prevalence and adverse effects of learning burnout are a major concern in higher education. Based upon JD-R and COR theories, this study modeled the associations among social support that teachers and peers provide in class, academic buoyancy, learning burnout, and class level with respect to the degree of English proficiency. A sample of 1955 Chinese EFL learners in higher education participated in the cross-sectional survey. Structural equation modelling via partial least squares technique was utilized for statistical analysis. The results corroborated the protecting role that social support in class played against EFL students' learning burnout. In particular, the findings revealed that academic buoyancy both mediated and moderated the nexus between social support on EFL learners' burnout. Moreover, this study found that class level with respect to English proficiency moderated the relation between academic buoyancy and learning burnout and that the negative impact of academic buoyancy on burnout increased in classes in which students had lower English proficiency. Based upon the findings, certain targeted suggestions for educational practice were provided. [ABSTRACT FROM AUTHOR]

This study examined the frequent cognitive strategies used by Jordanian undergraduate EFL students and how these cognitive strategies are related to students' class levels and Grade Point Averages (GPAs). The study used the quantitative research design. Sixty-two EFL students in an academic reading course at a public university in Jordan were randomly selected to respond to a questionnaire which was adapted from Oxford (1990). Data were analysed using descriptive statistics, independent samples t-test, One-Way ANOVA, and Scheffe test. The study revealed that the top four frequent cognitive strategies used by EFL students are inferencing, prediction, elaboration, and paraphrasing. In other words, this study revealed that these cognitive strategies are useful techniques for EFL students to use in academic reading courses. The study also showed that there are no significant differences between students' use of cognitive strategies and their class level. In addition, One-Way ANOVA and Scheffe tests revealed that there are significant differences between three cognitive strategies which are sounds, prediction, and paraphrasing and students' GPAs, in favour of students with excellent GPAs. Thus, in EFL contexts, teachers of academic reading courses need to train students to use cognitive strategies effectively for better academic reading comprehension. This can be enhanced through designing reading activities and tasks that should involve the use of cognitive strategies in order to help EFL students practice these strategies. [ABSTRACT FROM AUTHOR]

The goal of this study is to investigate undergraduate students' attitudes toward learning English based on their academic major, class level, and gender. A total of 150 undergraduate students (65 males and 85 females) distributed in different class levels and different colleges and departments were surveyed using a Likert-type scale. Statistical differences indicated that students had a mixed bag of attitudes about the English language, with some being positive and others being negative. The findings revealed that students in science-related majors and Kindergarten Education had a higher interest in learning English than other students; all students in science-related majors believed that learning English is beneficial; felt more confident and had more positive attitudes toward their English instructors than those in Education-related ones. In addition, juniors were more enthusiastic about learning English as a second language and had more positive attitudes toward it than freshmen. Likewise, female students obtained more positive attitudes in terms of interest and instructor subscales. However, ANOVA analysis of indicated no significant differences in self-confidence and usability subscales between male and female students. In light of the research's conclusions, some practical implications are explored to assist students in adopting a positive attitude toward English language learning.

The goal of this study is to investigate undergraduate students' attitudes toward learning English based on their academic major, class level, and gender. A total of 150 undergraduate students (65 males and 85 females) distributed in different class levels and different colleges and departments were surveyed using a Likert-type scale. Statistical differences indicated that students had a mixed bag of attitudes about the English language, with some being positive and others being negative. The findings revealed that students in science-related majors and Kindergarten Education had a higher interest in learning English than other students; all students in science-related majors believed that learning English is beneficial; felt more confident and had more positive attitudes toward their English instructors than those in Education-related ones. In addition, juniors were more enthusiastic about learning English as a second language and had more positive attitudes toward it than freshmen. Likewise, female students obtained more positive attitudes in terms of interest and instructor subscales. However, ANOVA analysis of indicated no significant differences in self-confidence and usability subscales between male and female students. In light of the research's conclusions, some practical implications are explored to assist students in adopting a positive attitude toward English language learning. [ABSTRACT FROM AUTHOR]

Piano practicing habits are one of the most important factors that affect the process of how to play the piano and the performances of music students. The study aims to examine the piano practicing habits and attitudes of vocal students towards piano lessons by comparing them according to gender and class variables. In addition, the aim is to put forward relations between piano practicing habits and attitudes towards piano classes. This study was conducted on 120 vocal students studying at Marmara University, Burdur Mehmet Akif Ersoy University, Necmettin Erbakan University, Erciyes University, Kırşehir Ahi Evran University, Nevşehir Hacı Bektaş Veli University, Giresun University, Trabzon University, Atatürk University, Muğla Sıtkı Koçman University, Balıkesir University, Ağrı İbrahim Çeçen University, Van, Yüzüncü Yıl University, Dicle University, Afyon Kocatepe University, Sivas Cumhuriyet University, Zonguldak Bülent Ecevit University, Mersin University, Ordu University, Kahramanmaraş Sütçü İmam University. In the collection of research data, piano practicing habits and piano class attitude scales have been used. According to research results, it has been observed that the practicing habits of the vocal students in instrumental technique, preparation, and warm-up habits are at a medium level and a high level in other dimensions. It was found that the general piano practicing habits of the participants were at a high level. Piano practicing habits of the students differed according to gender and class level variables. Besides significant relations between piano practicing habits and attitudes towards piano classes were found. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the level of understanding and perceptions of climate change using the variables of major, gender, and class level with a sample of undergraduate college students. Using a Likert-type questionnaire, data were collected from a randomly selected sample in a Midwest college in the United States. The study found that students in the tourism major were similar in their understanding and perceptions of climate change when compared to non-tourism majors. Males and females differed in their overall climate change knowledge and perceptions regarding climate change. In addition, class level (year 1–4) had a significant impact on students' climate change perceptions and understanding of climate change knowledge. These and other findings from the study have important implications for tourism education and curriculum development relative to climate change issues, particularly at the post-secondary and college levels. [ABSTRACT FROM AUTHOR]

Copyright of Erciyes Universitesi Sosyal Bilimler Dergisi is the property of Erciyes Universitesi Sosyal Bilimler Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Gazi University Journal of Gazi Educational Faculty (GUJGEF) is the property of Gazi University Journal of Gazi Educational Faculty (GUJGEF) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Mehmet Akif Ersoy University Journal of Education Faculty is the property of Mehmet Akif Ersoy Universitesi Egitim Fakultesi Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Landscape metrics are useful tools in investigating spatial structure and in describing the heterogeneity of landscapes, but are sensitive to grain size. Thus, it is necessary to determine the appropriate grain size before researching landscape patterns. However, there have been few large-scale investigations in high-precision research about the effect of grain size on landscape patterns, especially in arid valleys in China. Thus, we selected three representative sample areas according to the basic characteristics of arid valleys, and we chose 22 grain sizes from 15 to 450 m to calculate twelve landscape metrics at the landscape level and six landscape metrics at the class level to analyze the most appropriate grain size for the arid valleys. All basins in the study area were converted to an appropriate-sized grid to analyze the landscape patterns. Our results showed that the effect of grain size on landscape metrics can be categorized as: no law, increasing, decreasing, or no change. The majority of the fitted landscape index curves were good, with high R² values. The most appropriate grain size at both levels was 75 m. The landscape pattern of arid valleys was scale-dependent. At the landscape level, arid valley landscape patterns changed from northwest to southeast due to topography and hydrothermal conditions. While the value of aggregation for different size classes was high, the other metrics showed significant differences due to area and degree of human activity at the class level. [ABSTRACT FROM AUTHOR]

Copyright of Ilkogretim Online is the property of Ilkogretim Online and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quality assurance activities include software testing, verification, validation, fault proneness and fault prediction. Most of existing model predicts faults based on historical data (Within-project) through intellectual analysis. This paper instanced on defect prediction using cross-projects and mixed-project prediction because of the unpredictability in selection of software attributes by analogy based approach that deliver imprecise and ambiguous solution. Cross project delivers momentous results by focussing on selection of training data. Combination of cross project data with regression techniques improves effectiveness of prediction by extracting similar features impacted by all datasets. Feature extraction with similarity based approach creates training model that constitute more accurate prediction. We proposed two experiments with method-level and class level datasets on 23 open source projects with different scenario that shows improvement in accuracy, probability of prediction and probability of false alarm with the involvement of cross project and mixed project combinations. Major outcomes from our experiment conclude that cross project prediction provide better prediction by selecting dataset either by iterative versions of historical information or addition of limited within project data to cross project data. [ABSTRACT FROM AUTHOR]

This study examined the foreign language (FL) reading anxiety level of learners of Chinese as a FL (n = 76) in the United States.Data from an FL reading anxiety survey,a background information survey and a face-to-face interview indicated that there was no significant difference in reading anxiety level among four course levels.In general,Chinese L2 learners experienced a medium level of reading anxiety.100-and 400-level students experienced higher levels of reading anxiety compared to 200- and 300-level students.A regression model with background variables such as years of learning Chinese,heritage learner status,the number of foreign languages learned,and time spent in China significantly predicted learners'reading anxiety levels and explained 15% of the variance in their reading anxiety. Worries relating to comprehension, unfamiliar topics, unknown pronunciation,and feeling uncomfortable reading aloud were identified as major sources of FL reading anxiety [ABSTRACT FROM AUTHOR]

The prevalence and adverse effects of learning burnout are a major concern in higher education. Based upon JD-R and COR theories, this study modeled the associations among social support that teachers and peers provide in class, academic buoyancy, learning burnout, and class level with respect to the degree of English proficiency. A sample of 1955 Chinese EFL learners in higher education participated in the cross-sectional survey. Structural equation modelling via partial least squares technique was utilized for statistical analysis. The results corroborated the protecting role that social support in class played against EFL students' learning burnout. In particular, the findings revealed that academic buoyancy both mediated and moderated the nexus between social support on EFL learners' burnout. Moreover, this study found that class level with respect to English proficiency moderated the relation between academic buoyancy and learning burnout and that the negative impact of academic buoyancy on burnout increased in classes in which students had lower English proficiency. Based upon the findings, certain targeted suggestions for educational practice were provided., Competing Interests: Competing interestsThe author(s) proclaims there exists no conflict of interests., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Copyright of Journal of Theoretical Educational Science / Kuramsal Eğitimbilim Dergisi is the property of Afyon Kocatepe University, Faculty of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Conventional zero‐shot learning (ZSL) methods usually use class‐level attribute, which corresponds to a batch of images of same category. This setting is not reasonable since the images even though belong to same category still have variances in their attribute items. To alleviate this phenomenon, the authors propose a novel method namely attribute relaxation (AR) to extend attributes from class level to instance level by adding a small variance matrix, which is more reasonable than traditional ZSL methods such as Semantic AutoEncoder that projects features from multi to one. Extensive experiments on four popular datasets show that AR can significantly improve the method using only class‐level attributes, and verifies that AR can make the projected features in attribute space more discriminative. [ABSTRACT FROM AUTHOR]

Multidimensional (coupled land use, soil properties, and topography) landscape effects on stream water nitrogen (N) are complex and scale-dependent. However, studies that identify critical buffer zones that explain large variations in riverine N, and estimate specific thresholds of multidimensional landscape patterns at the class level, result in a sudden changes in riverine N pollution, are still limited. Here, a new multidimensional landscape metric that combined land use, soil properties, and topography effects was applied to various riparian buffer zones and sub-watershed scales, and their relationships to riverine N levels were investigated. We used stream water ammonium−N, nitrate−N, and total−N concentrations datasets, from 2010 to 2017, in the nine subtropical sub-watersheds in China. The results of model selection and model averaging in ordinary least squares regressions, indicated that the riparian buffer zone with widths of 400 m, had more pronounced influence on water NH 4 –N and TN levels than at other scales. Within the 400 m buffer zone, the key landscape metrics for NH 4 –N, NO 3 –N and TN concentrations in stream water were different, and explained up to 43.35%–76.55% (adjusted R2) of the total variation in river N levels. When ENN_MN Class17 below 39–56 m, PD Class8 above 4.63–6.55 n/km2, PLAND Class27 above 23–29%, and CONTIG_MN Class42 below 0.35–0.37% within the 400 m buffer zone, riverine NH 4 –N and TN would be abruptly increased. This study provided practical ideas for regulation regarding landscape management linked to watershed structure, and identified reference thresholds for multidimensional landscape metrics, which should help reduce riverine N pollution in subtropical China. • Multidimensional landscape patterns affect riverine N at watershed outlets. • The 400 m riparian buffer zone has the strongest influence on riverine NH 4 –N and TN concentrations. • The ENN_MN Class17 , PD Class8 , PLAND Class27 , and CONTIG_MN Class42 are important metrics to characterize riverine N. • There exist change points in riverine N along a gradient of multidimensional landscape metrics. [ABSTRACT FROM AUTHOR]

Copyright of Pegem Journal of Education & Instruction / Pegem Egitim ve Ögretim is the property of Pegem Journal of Education & Instruction / Pegem Egitim ve Ogretim and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this research was to investigate the primary education second level students' motivations towards science learning in terms of various factors. Within the research, the variation of the total motivational scores in science learning according to the gender, class, socio-economic levels, success in science-technology course and variables of science-technology scores were investigated. The sample of the research was composed of 413 second level students of public primary schools in the city center of Ankara and Adana who were selected randomly. The "Motivational Learning Environment" and the "Personal Information Form" were used as data collection tools throughout the study as survey models. As a consequence of the research, it was confirmed that there was a meaningful difference between the scores that the students got from the REAL version & IDEAL version of the scale and this difference was in favor of the scores that were gained from the 'IDEAL' version. Moreover, students' total motivational scores in science learning (REAL version & IDEAL version) displayed a meaningful difference in favor of the female students. It was also observed that students' total motivational scores in science learning exposed a significant difference according to the class level and this difference was in favor of the 6th and 7th grade students. On the other hand, students' total motivational scores in science learning (REAL version & IDEAL version) revealed a significant difference according to the socio-economic factors. Another result was that, students' total motivational scores in science learning (REAL version & IDEAL version) were in favor of the students who were successful in science-technology whose course scores varied between "85-100". [ABSTRACT FROM AUTHOR]

Abstract: To improve the class separability of Fisher linear discriminant analysis (FDA) for large category problems, we investigate the weighted Fisher criterion (WFC) by integrating weighting functions for dimensionality reduction. The objective of WFC is to maximize the sum of weighted distances of all class pairs. By setting larger weights for the most confusable classes, WFC can improve the class separation while the solution remains an eigen-decomposition problem. We evaluate five weighting functions in three different weighting spaces in a typical large category problem of handwritten Chinese character recognition. The weighting functions include four based on existing methods, namely, FDA, approximate pairwise accuracy criterion (aPAC), power function (POW), confused distance maximization (CDM), and a new one based on K-nearest neighbors (KNN). All the weighting functions can be calculated in the original feature space, low-dimensional space, or fractional space. Our experiments on a 3,755-class Chinese handwriting database demonstrate that WFC can improve the classification accuracy significantly compared to FDA. Among the weighting functions, the KNN method in the original space is the most competitive model which achieves significantly higher classification accuracy and has a low computational complexity. To further improve the performance, we propose a nonparametric extension of the KNN method from the class level to the sample level. The sample level KNN (SKNN) method is shown to outperform significantly other methods in Chinese handwriting recognition such as the locally linear discriminant analysis (LLDA), neighbor class linear discriminant analysis (NCLDA), and heteroscedastic linear discriminant analysis (HLDA). [Copyright &y& Elsevier]

Copyright of Journal of Elementary Education / Revija za Elementarno Izobraževanje is the property of University of Maribor, Faculty of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Elementary Education / Revija za Elementarno Izobraževanje is the property of University of Maribor, Faculty of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Kirsehir Education Faculty is the property of Journal of Kirsehir Education Faculty and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The landscape grain effect reflects the spatial heterogeneity of a landscape and it is used as a research core of landscape ecology. The landscape grain effect can be used to not only explore spatiotemporal variation characteristics of a landscape pattern, but also to disclose variation laws of ecological structures and functions of landscapes. In this study, the sensitivity of landscape pattern indexes to grain sizes 50-1000 m was studied based on landscape data in Yancheng Coastal Wetland acquired in 1991, 2000, 2008, and 2017. Response of the grain effect to landscape changes was analyzed and an optimal grain size for analysis in the study area was determined. Results indicated that: (1) among 27 indexes (12 in a class level and 15 in a landscape level), eight indexes were highly sensitive to grains, ten indexes presented moderate sensitivity, eight indexes presented low sensitivity, and one was unresponsive. It was shown that the area-margin index and the shape index were more sensitive to the different grain sizes. The aggregation index had some differences in the grain size change, and the diversity index had a low response degree to the grain size. (2) Landscape indexes showed six different responses to different grains, including slow reduced response, fast reduced and then slow reduced response, monotonically increased response, fluctuating reduced response, up-down responses, and stable response, which indicated that the landscape index was closely related to the spatial grain. (3) From 1991 to 2017, variation curves of the landscape grain size of different landscape types could be divided into four types: fluctuation rising type, fluctuation type, monotonous decreasing type, and monotonous rising type. Different grain size curves had different interpretations of landscape changes, but in general, Yancheng Coastal Wetland's landscape tended to be fragmented and complicated, internal connectivity was weakened, and dominant landscape area was reduced. Natural wetlands were more sensitive to grain size effects than artificial wetlands. (4) The landscape index at the 50 m grain size had a strong response to different grain size changes, and the loss of landscape information was the smallest. Therefore, it was determined that the optimal landscape grain size in the study area was 50 m.