检索结果-内蒙古大学图书馆

Body appreciation around the world: Measurement invariance of the Body Appreciation Scale-2 (BAS-2) across 65 nations, 40 languages, gender identities, and age

引用

Body image 2023年 46卷 449-466页

作者： Viren Swami Ulrich S Tran Stefan Stieger Toivo Aavik Hamed Abdollahpour Ranjbar Sulaiman Olanrewaju Adebayo Reza Afhami Oli Ahmed Annie Aimé Marwan Akel Hussam Al Halbusi George Alexias Khawla F Ali Nursel Alp-Dal Anas B Alsalhani Sara Álvares-Solas Ana Carolina Soares Amaral Sonny Andrianto Trefor Aspden Marios Argyrides John Jamir Benzon R Aruta Stephen Atkin Olusola Ayandele Migle Baceviciene Radvan Bahbouh Andrea Ballesio David Barron Ashleigh Bellard Sóley Sesselja Bender Kerime Derya Beydağ Gorana Birovljević Marie-Ève Blackburn Teresita Borja-Alvarez Joanna Borowiec Miroslava Bozogáňová Solfrid Bratland-Sanda Matthew H E M Browning Anna Brytek-Matera Marina Burakova Yeliz Çakır-Koçak Pablo Camacho Vittorio Emanuele Camilleri Valentina Cazzato Silvia Cerea Apitchaya Chaiwutikornwanich Trawin Chaleeraktrakoon Tim Chambers Qing-Wei Chen Xin Chen Chin-Lung Chien Phatthanakit Chobthamkit Bovornpot Choompunuch Emilio J Compte Jennifer Corrigan Getrude Cosmas Richard G Cowden Kamila Czepczor-Bernat Marcin Czub Wanderson Roberto da Silva Mahboubeh Dadfar Simon E Dalley Lionel Dany Jesus Alfonso D Datu Pedro Henrique Berbert de Carvalho Gabriel Lins de Holanda Coelho Avila Odia S De Jesus Sonia Harzallah Debbabi Sandesh Dhakal Francesca Di Bernardo Donka D Dimitrova Jacinthe Dion Barnaby Dixson Stacey M Donofrio Marius Drysch Hongfei Du Angel M Dzhambov Claire El-Jor Violeta Enea Mehmet Eskin Farinaz Farbod Lorleen Farrugia Leonie Fian Maryanne L Fisher Michał Folwarczny David A Frederick Matthew Fuller-Tyszkiewicz Adrian Furnham Antonio Alías García Shulamit Geller Marta Ghisi Alireza Ghorbani Maria Angeles Gomez Martinez Sarah Gradidge Sylvie Graf Caterina Grano Gyöngyvér Gyene Souheil Hallit Motasem Hamdan Jonathan E Handelzalts Paul H P Hanel Steven R Hawks Issa Hekmati Mai Helmy Tetiana Hill Farah Hina Geraldine Holenweger Martina Hřebíčková Olasupo Augustine Ijabadeniyi Asma Imam Başak İnce Natalia Irrazabal Rasa Jankauskiene Ding-Yu Jiang Micaela Jiménez-Borja Verónica Jiménez-Borja Evan M Johnson Veljko Jov School of Psychology and Sport Science Anglia Ruskin University Cambridge United Kingdom Centre for Psychological Medicine Perdana University Kuala Lumpur Malaysia. Electronic address: viren.swami@aru.ac.uk. Department of Cognition Emotion and Methods in Psychology Faculty of Psychology University of Vienna Vienna Austria. Department of Psychology and Psychodynamics Karl Landsteiner University of Health Sciences Krems an der Donau Austria. Institute of Psychology University of Tartu Tartu Estonia. Department of Psychology Koç University Istanbul Turkiye. Department of Psychology and Behavioural Studies Ekiti State University Ado-Ekiti Nigeria. Department of Art Studies Tarbiat Modares University Tehran Iran. Department of Psychology University of Chittagong Chattogram Bangladesh. Department of Psychoeducation and Psychology Université du Québec en Outaouais Saint-Jérôme Canada. INSPECT-LB: National Institute of Public Health Clinical Epidemiology and Toxicology Beirut Lebanon School of Pharmacy Lebanese International University Beirut Lebanon. Department of Management Ahmed Bin Mohammad Military College Doha Qatar. Faculty of Psychology Panteion University of Social and Political Sciences Athens Greece. Royal College of Surgeons Ireland-Bahrain Adliya Bahrain. Department of Midwifery Faculty of Health Sciences Munzur University Tunceli Turkiya. Department of Oral Medicine and Diagnostic Sciences Vision College of Dentistry and Nursing Vision Colleges Riyadh Saudi Arabia. Facultad de Ciencias de la Vida Universidad Regional Amazónica Ikiam Muyuna Ecuador. Federal Institute of Education Science and Technology of Southeast Minas Gerais Barbacena Brazil. Department of Psychology Universitas Islam Indonesia Yogyakarta Indonesia. Department of Psychology Aberystwyth University Ceredigion United Kingdom. Department of Psychology Neapolis University Pafos Paphos Cyprus. Department of Psychology De La Salle University Phillippines. Department of Gen

The Body Appreciation Scale-2 (BAS-2) is a widely used measure of a core facet of the positive body image construct. However, extant research concerning measurement invariance of the BAS-2 across a large number of nations remains limited. Here, we utilised the Body Image in Nature (BINS) dataset - with data collected between 2020 and 2022 - to assess measurement invariance of the BAS-2 across 65 nations, 40 languages, gender identities, and age groups. Multi-group confirmatory factor analysis indicated that full scalar invariance was upheld across all nations, languages, gender identities, and age groups, suggesting that the unidimensional BAS-2 model has widespread applicability. There were large differences across nations and languages in latent body appreciation, while differences across gender identities and age groups were negligible-to-small. Additionally, greater body appreciation was significantly associated with higher life satisfaction, being single (versus being married or in a committed relationship), and greater rurality (versus urbanicity). Across a subset of nations where nation-level data were available, greater body appreciation was also significantly associated with greater cultural distance from the United States and greater relative income inequality. These findings suggest that the BAS-2 likely captures a near-universal conceptualisation of the body appreciation construct, which should facilitate further cross-cultural research.

关键词： Body appreciation Body appreciation Scale-2 (BAS-2) Cross-cultural Measurement invariance Multi-group confirmatory factor analysis (MG-CFA) Psychometrics Structural analysis

来源：评论

学校读者我要写书评

暂无评论

“I’m Just Guiding You”: An Exploration of Software design Mentorship within a Software Engineering Firm

引用

Journal of Software Engineering and Applications 2018年第6期11卷 299-317页

作者： Leshell Hatley Maha Al-Freih Brenda Bannan Department of Mathematics & Computer Science Coppin State University Baltimore USA Department of Educational Technology Princess NourahBint Abdulrahman University Riyadh Saudi Arabia Instructional Technology/Learning Technologies Design Research George Mason University Fairfax USA

The case study presented here uses an interpretivist (qualitative, humanistic) approach to illustrate and describe a range of interactions and behaviors that occur during design meetings where mentoring and design simultaneously occur within a software engineering firm, during a portion of the design phase for a software project. It attempts to examine the interaction between two design team members (one novice and one expert) and describes how these observations intersect with the theoretical and applied literature and actual design processes. Taking cues from two theoretical descriptions of the design process, the study presented here suggests that modes and models of mentorship should be added, when applicable, as a descriptive portion of the design process.

关键词： Software design Mentorship design Meeting Collaboration

来源：评论

学校读者我要写书评

暂无评论

An evaluation framework for engineering design projects for gender bias, domain relatedness, and ambiguity: Development

An evaluation framework for engineering design projects for ...

引用

2018 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2018

作者： Khoje, Shubham Günay, Elcin Kremer, Gül E. Park, Kijung Jackson, Kathy L. Wu, Xinli Department of Industrial and Manufacturing Systems Engineering Iowa State University AmesIA50011 United States Department of Industrial and Management Engineering Incheon National University Incheon22012 Korea Republic of Teaching and Learning with Technology Pennsylvania State University University ParkPA16802 United States School of Engineering Design Technology and Professional Programs Pennsylvania State University University ParkPA16802 United States

Engineering design learning is one of the key components for an engineering degree;thus engineering design projects are commonly included in engineering curricula to help students cultivate design thinking and creative problem-solving skills. However, an engineering design project is prone to the following issues if it is not appropriately provided to engineering students. First, gender bias can occur when the design project is perceived to be more skewed to one gender in comparison to the other. Second, domain bias can occur when the discipline of the design project is not related to the chosen major and interest areas of a student. Third, ambiguity can arise from the lack of clarity on design objectives and the scope. These issues can lead to diminished engagement and self-efficacy for engineering students. In order to tackle these issues, this study performs a preliminary work to build a framework that appropriately assesses engineering design projects. The evaluation framework is based on a measurement system that helps educators to evaluate the appropriateness of the design projects through designated questionnaires. The framework for design projects proposed in this study would help engineering educators to better prepare and revise their design projects, so that the engineering design projects can improve student engagement and learning performance. © 2018 Institute of Industrial Engineers (IIE). All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Pruning by explaining: A novel criterion for deep neural network pruning

arXiv

引用

arXiv 2019年

作者： Yeom, Seul-Ki Seegerer, Philipp Lapuschkin, Sebastian Binder, Alexander Wiedemann, Simon Müller, Klaus-Robert Samek, Wojciech Machine Learning Group Technische Universität Berlin Berlin10587 Germany BIFOLD – Berlin Institute for the Foundations of Learning and Data Berlin Germany Department of Artificial Intelligence Fraunhofer Heinrich Hertz Institute Berlin10587 Germany ISTD Pillar Singapore University of Technology and Design Singapore487372 Singapore Department of Informatics University of Oslo Oslo0373 Norway Department of Artificial Intelligence Korea University Seoul136-713 Korea Republic of Max Planck Institut für Informatik Saarbrücken66123 Germany Aignostics GmbH Berlin10557 Germany Nota AI GmbH Berlin10117 Germany

The success of convolutional neural networks (CNNs) in various applications is accompanied by a significant increase in computation and parameter storage costs. Recent efforts to reduce these overheads involve pruning and compressing the weights of various layers while at the same time aiming to not sacrifice performance. In this paper, we propose a novel criterion for CNN pruning inspired by neural network interpretability: The most relevant units, i.e. weights or filters, are automatically found using their relevance scores obtained from concepts of explainable AI (XAI). By exploring this idea, we connect the lines of interpretability and model compression research. We show that our proposed method can efficiently prune CNN models in transfer-learning setups in which networks pre-trained on large corpora are adapted to specialized tasks. The method is evaluated on a broad range of computer vision datasets. Notably, our novel criterion is not only competitive or better compared to state-of-the-art pruning criteria when successive retraining is performed, but clearly outperforms these previous criteria in the resource-constrained application scenario in which the data of the task to be transferred to is very scarce and one chooses to refrain from fine-tuning. Our method is able to compress the model iteratively while maintaining or even improving accuracy. At the same time, it has a computational cost in the order of gradient computation and is comparatively simple to apply without the need for tuning hyperparameters for pruning. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

An autonomous UAV-UGV system for eradication of invasive weed prosopis juliflora

An autonomous UAV-UGV system for eradication of invasive wee...

引用

2017 IEEE International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2017

作者： Baskaran, Balaji Radhakrishnan, Karthikeyan Muthukrishnan, G. Prasath, R Nagendra Balaji, Kamal P. Pandian, Shunmugham R. Department of Mechatronics Sri Krishna College of Engineering and Technology Coimbatore India Teaching Learning Centre for Design and Manufacturing Department of Electronics Engineering Indian Institute of Information Technology Design and Manufacturing-Kancheepuram Chennai India

ISBN: (纸本)9781538618660

Prosopis juliflora is a small weed tree, native to Central and South America, and the Caribbean, which has become a major invasive weed in Asia, including India, Latin America, Africa and Australia. It has major detrimental impact on scarce, underground water resources, takes over the local flora ecosystems and affects the soil environment. Manual removal of saplings is time-consuming and expensive. Presently, the removal of the weed is performed manually which is time-consuming, or using very expensive commercial heavy equipment. In this paper, an affordable and innovative unmanned aerial vehicle (UAV) - unmanned ground vehicle (UGV) system is designed and developed for autonomous identification and removal of the weed seedlings and saplings. Results of implementation of a proof-of-concept prototype system using mainly commercial off-the-shelf components, open source hardware and free open source software, are presented to illustrate the effectiveness of the proposed approach. © 2017 IEEE.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Teaching in the Age of Covid-19—The New Normal

引用

Postdigital Science and Education 2022年第3期4卷 877-1015页

作者： Jandrić, Petar Martinez, Ana Fuentes Reitz, Charles Jackson, Liz Grauslund, Dennis Hayes, David Lukoko, Happiness Onesmo Hogan, Michael Mozelius, Peter Arantes, Janine Aldous Levinson, Paul Ozoliņš, Jānis John Kirylo, James D. Carr, Paul R. Hood, Nina Tesar, Marek Sturm, Sean Abegglen, Sandra Burns, Tom Sinfield, Sandra Stewart, Georgina Tuari Suoranta, Juha Jaldemark, Jimmy Gustafsson, Ulrika Monzó, Lilia D. Kokić, Ivana Batarelo Kihwele, Jimmy Ezekiel Wright, Jake Kishore, Pallavi Stewart, Paul Alexander Bridges, Susan M. Lodahl, Mikkel Bryant, Peter Kaur, Kulpreet Hollings, Stephanie Brown, James Benedict Steketee, Anne Prinsloo, Paul Hazzan, Moses Kayode Jopling, Michael Mañero, Julia Gibbons, Andrew Pfohl, Sarah Humble, Niklas Davidsen, Jacob Ford, Derek R. Sharma, Navreeti Stockbridge, Kevin Pyyhtinen, Olli Escaño, Carlos Achieng-Evensen, Charlotte Rose, Jennifer Irwin, Jones Shukla, Richa SooHoo, Suzanne Truelove, Ian Buchanan, Rachel Urvashi, Shreya White, E. Jayne Novak, Rene Ryberg, Thomas Arndt, Sonja Redder, Bridgette Mukherjee, Mousumi Komolafe, Blessing Funmi Mallya, Madhav Devine, Nesta Sattarzadeh, Sahar D. Hayes, Sarah Zagreb University of Applied Sciences Zagreb Croatia University of Wolverhampton Wolverhampton UK University West Trollhättan Sweden Kansas City Kansas Community College Kansas City USA Education University of Hong Kong Hong Kong China University College of Northern Denmark (UCN) Aalborg Denmark Further Education Worcester UK Institute of Development Studies University of Dar Es Salaam Dar es Salaam Tanzania School of Psychology National University of Ireland Galway Galway Ireland Mid Sweden University Östersund/Stockholm Sweden Victoria University Melbourne Australia Fordham University New York City USA College of Philosophy and Theology University of Notre Dame Australia Fremantle Australia Faculty of History and Philosophy University of Latvia Riga Latvia University of South Carolina Columbia USA Département des sciences de l’éducation Université du Québec en Outaouais Gatineau Canada Faculty of Education and Social Work University of Auckland Auckland New Zealand School of Architecture Planning and Landscape University of Calgary Calgary Canada Centre for Professional and Educational Development London Metropolitan University London UK Auckland University of Technology Auckland New Zealand Faculty of Social Sciences Tampere University Tampere Finland Department of Education Mid Sweden University Sundsvall Sweden Department of Applied Educational Science Umeå University Umeå Sweden Attallah College of Educational Studies Chapman University Orange USA Department of Pedagogy Faculty of Humanities and Social Sciences University of Split Split Croatia Department of Education Mzumbe University Morogoro Tanzania Center for Learning Innovation University of Minnesota Rochester Rochester USA Jindal Global Law School O.P. Jindal Global University Sonipat India MIMA School of Art and Design Teesside University Middlesbrough UK The University of Hong Kong Hong Kong China Dania Academy Randers Denmark University of Sydney Sydney Australia J

来源：评论

学校读者我要写书评

暂无评论

The role of artificial intelligence in achieving the Sustainable Development Goals

arXiv

引用

arXiv 2019年

作者： Vinuesa, Ricardo Azizpour, Hossein Leite, Iolanda Balaam, Madeline Dignum, Virginia Domisch, Sami Felländer, Anna Langhans, Simone Tegmark, Max Nerini, Francesco Fuso Linné FLOW Centre KTH Mechanics StockholmSE-100 44 Sweden School of Electrical Engineering and Computer Science KTH Royal Institute Of Technology Stockholm Sweden Division of Robotics Perception and Learning School of EECS KTH Royal Institute Of Technology Stockholm Sweden Division of Media Technology and Interaction Design KTH Royal Institute of Technology Lindstedtsvägen 3 Stockholm Sweden Responsible AI Lab Umeå University UmeåSE-90358 Sweden Leibniz-Institute of Freshwater Ecology and Inland Fisheries Müggelseedamm 310 Berlin12587 Germany Division of Media Technology and Interaction Design KTH Royal Institute of Technology Lindstedtsvägen 3 Stockholm Sweden Leioa Spain Department of Zoology University of Otago 340 Great King Street Dunedin9016 New Zealand Center for Brains Minds & Machines Massachusetts Institute of Technology CambridgeMA02139 United States KTH Royal Institute of Technology Brinellvagen 68 StockholmSE-100 44 Sweden

The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors across the society requires an assessment of its effect on sustainable development. Here we analyze published evidence of positive or negative impacts of AI on the achievement of each of the 17 goals and 169 targets of the 2030 Agenda for Sustainable Development. We find that AI can support the achievement of 128 targets across all SDGs, but it may also inhibit 58 targets. Notably, AI enables new technologies that improve efficiency and productivity, but it may also lead to increased inequalities among and within countries, thus hindering the achievement of the 2030 Agenda. The fast development of AI needs to be supported by appropriate policy and regulation. Otherwise, it would lead to gaps in transparency, accountability, safety and ethical standards of AI-based technology, which could be detrimental towards the development and sustainable use of AI. Finally, there is a lack of research assessing the medium- and long-term impacts of AI. It is therefore essential to reinforce the global debate regarding the use of AI and to develop the necessary regulatory insight and oversight for AI-based technologies. Copyright © 2019, The Authors. All rights reserved.

关键词： Planning

来源：评论

学校读者我要写书评

暂无评论

Investigating the Development of Reasoning Abilities among Bruneian Physics Students after 1 Year Exposure to Cambridge International Advanced Level Program 2

Investigating the Development of Reasoning Abilities among B...

引用

2nd Mathematics, Informatics, Science and Education International Conference, MISEIC 2018

作者： Marlizayati, J. Nor'Arifahwati, A.H. Rahiman, A.P. Science Education Academic Group Sultan Hassanal Bolkiah Institute of Education University Brunei Darussalam Jalan Tungku Link Brunei DarussalamBE 1410 Brunei Learning Sciences and Technology Sultan Hassanal Bolkiah Institute of Education University Brunei Darussalam Jalan Tungku Link Brunei DarussalamBE 1410 Brunei Design and Creative Industries Department Faculty of Arts and Social Sciences University Brunei Darussalam Jalan Tungku Link Brunei DarussalamBE 1410 Brunei

The aim of this study is to investigate the development of different reasoning abilities among Bruneian physics students after undergoing one year of Cambridge International Advanced level ('A' level) programme. This particular study administered pre and post questionnaires, namely, verbal critical reasoning, spatial ability and abstract reasoning. These questionnaires were distributed among 'A' level physics students from four out of six, sixth form centres. There were 173 students (73 male and 100 female students) who participated in the study. Non-parametric tests (i.e. Wilcoxon Signed-Rank Test and Mann Whitney U) were conducted on the pre-test and post-test scores of verbal critical reasoning, spatial ability and abstract reasoning and their corresponding gain scores due to violation of normality and presence of outliers in the data. Wilcoxon Signed-Rank Test revealed that there were significant differences in the spatial reasoning score and abstract reasoning score from pre-test to post-test. Meanwhile Mann Whitney U test indicated that male students outperformed female students in abstract reasoning during pre-test and post-test. Thus for this particular sample, there is an increase in students' abstract reasoning abilities and spatial reasoning abilities. A further investigation might be needed in exploring the reasoning abilities scores of the students with their 'A' level results to make a stronger claim for this study. © Published under licence by IOP Publishing Ltd.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Resolving challenges in deep learning-based analyses of histopathological images using explanation methods

arXiv

引用

arXiv 2019年

作者： Hagele, Miriam Seegerer, Philipp Lapuschkin, Sebastian Bockmayr, Michael Samek, Wojciech Klauschen, Frederick Muller, Klaus-Robert Binder, Alexander Technical University of Berlin Machine Learning Group Berlin10587 Germany Fraunhofer Heinrich Hertz Institute Department of Video Coding and Analytics Berlin10587 Germany Charite University Hospital Institute of Pathology Berlin10117 Germany University Medical Center Hamburg-Eppendorf Department of Pediatric Hematology and Oncology Hamburg20251 Germany Korea University Department of Brain and Cognitive Engineering Anam-dong Seongbuk-gu Seoul02841 Korea Republic of Max-Planck-Institute for Informatics Campus E1 4 Saarbrücken66123 Germany Singapore University of Technology and Design ISTD Pillar Singapore487372 Singapore

Deep learning has recently gained popularity in digital pathology due to its high prediction quality. However, the medical domain requires explanation and insight for a better understanding beyond standard quantitative performance evaluation. Recently, explanation methods have emerged, which are so far still rarely used in medicine. This work shows their application to generate heatmaps that allow to resolve common challenges encountered in deep learning-based digital histopathology analyses. These challenges comprise biases typically inherent to histopathology data. We study binary classification tasks of tumor tissue discrimination in publicly available haematoxylin and eosin slides of various tumor entities and investigate three types of biases: (1) biases which affect the entire dataset, (2) biases which are by chance correlated with class labels and (3) sampling biases. While standard analyses focus on patch-level evaluation, we advocate pixel-wise heatmaps, which offer a more precise and versatile diagnostic instrument and furthermore help to reveal biases in the data. This insight is shown to not only detect but also to be helpful to remove the effects of common hidden biases, which improves generalization within and across datasets. For example, we could see a trend of improved area under the receiver operating characteristic curve by 5% when reducing a labeling bias. Explanation techniques are thus demonstrated to be a helpful and highly relevant tool for the development and the deployment phases within the life cycle of real-world applications in digital pathology. Copyright © 2019, The Authors. All rights reserved.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

Teaching in the Age of Covid-19—1 Year Later

引用

Postdigital Science and Education 2021年第3期3卷 1073-1223页

作者： Jandrić, Petar Hayes, David Levinson, Paul Christensen, Line Lisberg Lukoko, Happiness Onesmo Kihwele, Jimmy Ezekiel Brown, James Benedict Reitz, Charles Mozelius, Peter Nejad, Harry G. Martinez, Ana Fuentes Arantes, Janine Aldous Jackson, Liz Gustafsson, Ulrika Abegglen, Sandra Burns, Tom Sinfield, Sandra Hogan, Michael Kishore, Pallavi Carr, Paul R. Batarelo Kokić, Ivana Prinsloo, Paul Grauslund, Dennis Steketee, Anne Achieng-Evensen, Charlotte Komolafe, Blessing Funmi Suoranta, Juha Hood, Nina Tesar, Marek Rose, Jennifer Humble, Niklas Kirylo, James D. Mañero, Julia Monzó, Lilia D. Lodahl, Mikkel Jaldemark, Jimmy Bridges, Susan M. Sharma, Navreeti Davidsen, Jacob Ozoliņš, Jānis (John) Bryant, Peter Escaño, Carlos Irwin, Jones Kaur, Kulpreet Pfohl, Sarah Stockbridge, Kevin Ryberg, Thomas Pyyhtinen, Olli SooHoo, Suzanne Hazzan, Moses Kayode Wright, Jake Hollings, Stephanie Arndt, Sonja Gibbons, Andrew Urvashi, Shreya Forster, Daniella J. Truelove, Ian Mayo, Peter Rikowski, Glenn Stewart, Paul Alexander Jopling, Michael Stewart, Georgina Tuari Buchanan, Rachel Devine, Nesta Shukla, Richa Novak, Rene Mallya, Madhav Biličić, Eva Sturm, Sean Sattarzadeh, Sahar D. Philip, Abey P. Redder, Bridgette White, E. Jayne Ford, Derek R. Allen, Quaylan Mukherjee, Mousumi Hayes, Sarah Zagreb University of Applied Sciences Zagreb Croatia University of Wolverhampton Wolverhampton UK Further Education Worcester UK Fordham University New York City USA Department of Communication and Psychology Aalborg University Aalborg Denmark Institute of Development Studies University of Dar es Salaam Dar es Salaam Tanzania Department of Education Mzumbe University Morogoro Tanzania Umeå School of Architecture Umeå University Umeå Sweden Kansas City Kansas Community College Kansas City USA Department of Computer and System Science (DSV) Mid Sweden University Östersund/Stockholm Sweden Jindal Institute of Behavioural Sciences O. P. Jindal Global University Haryana India Katedralskolan (Lund)/University West Trollhättan Sweden Victoria University Melbourne Australia Education University of Hong Kong Hong Kong China Department of Applied Educational Science Umeå University Umeå Sweden School of Architecture Planning and Landscape University of Calgary Calgary Canada Centre for Professional and Educational Development London Metropolitan University London UK School of Psychology National University of Ireland Galway Galway Ireland Jindal Global Law School O.P. Jindal Global University Sonipat India Département des sciences d l’éducation Université du Québec en Outaouais Gatineau Canada Department of Pedagogy Faculty of Humanities and Social Sciences University of Split Split Croatia University of South Africa Pretoria South Africa University College of Northern Denmark (UCN) Aalborg Denmark School of Education Millikin University Decatur Il USA Attallah College of Educational Studies Chapman University Orange USA Science Education Department Adekunle Ajasin University Ondo Nigeria Curriculum and Pedagogy College of Teacher Education Zhejiang Normal University Jinhua China Faculty of Social Sciences Tampere University Tampere Finland Faculty of Education University of Auckland Auckland New Zealand School of Social Science Education and

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：