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Thematische Bibliographien / Explainer / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Explainer“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 26. Juli 2025

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1

Li, Qiaomei, Rachel Cummings, and Yonatan Mintz. "Optimal Local Explainer Aggregation for Interpretable Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (2022): 12000–12007. http://dx.doi.org/10.1609/aaai.v36i11.21458.

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A key challenge for decision makers when incorporating black box machine learned models into practice is being able to understand the predictions provided by these models. One set of methods proposed to address this challenge is that of training surrogate explainer models which approximate how the more complex model is computing its predictions. Explainer methods are generally classified as either local or global explainers depending on what portion of the data space they are purported to explain. The improved coverage of global explainers usually comes at the expense of explainer fidelity (i.

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2

Asgotraa, Sonal, and Paras Loomba. "Explained in 60 Seconds: Creating Sustainable Livelihoods Through Astrostays." Communicating Astronomy with the Public Journal 14, no. 1 (2020): 4. https://doi.org/10.5281/zenodo.14977914.

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3

Daniels, Sebastian. "Explained in 60 Seconds: Jupiter Descending." Communicating Astronomy with the Public Journal 10, no. 3 (2016): 4. https://doi.org/10.5281/zenodo.14974127.

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4

Ingall, Benji. "Explainer." Stolen Tools 2, no. 1 (2024): 35–36. http://dx.doi.org/10.59745/st.v2i1.37.

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5

Fuge, Lauren, and Hannah Dalgleish. "Explained in 60 Seconds: What has the Cassini Mission Taught Us?" Communicating Astronomy with the Public Journal 11, no. 1 (2017): 4. https://doi.org/10.5281/zenodo.14974384.

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6

Heinz, Jay. "Explained in 60 Seconds: Fulldomeq." Communicating Astronomy with the Public Journal 7, no. 1 (2013): 4. https://doi.org/10.5281/zenodo.14891134.

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7

Canas, Lina, and Sze-Leung Cheung. "Explained in 60 Seconds: The IAU National Outreach Coordinators (NOCs) Network." Communicating Astronomy with the Public Journal 14, no. 2 (2020): 4. https://doi.org/10.5281/zenodo.14978161.

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8

Bradac, Marusa. "Explained in 60 seconds: Dark matter." Communicating Astronomy with the Public Journal 1, no. 1 (2007): 4. https://doi.org/10.5281/zenodo.14842406.

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9

Hughes, David W., and Grijs Richard de. "The Top Ten Astronomical "Breakthroughs" of the 20th Century." Communicating Astronomy with the Public Journal 1, no. 1 (2007): 11–17. https://doi.org/10.5281/zenodo.14842849.

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Astronomy was revolutionized in the 20th century. The electron was discovered in 1897 and this transformed spectroscopy and introduced plasma and magnetohydrodynamic physics and astro-chemistry. Einstein’s E = mc^2, solved the problem of stellar energy generation and spawned the study of elemental nuclear synthesis. Large telescopes led to a boom in astronomical spectroscopic and photometric data collection, leading to such cornerstones as the Hertzprung-Russell diagram and the mass-luminosity relationship, and to the realization that the Universe contained a multitude of galaxies and wa

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Turner, Michael S. "Explained in 60 seconds: Dark energy." Communicating Astronomy with the Public Journal 2, no. 1 (2008): 4. https://doi.org/10.5281/zenodo.14848171.

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11

Marshall, Phil. "Explained in 60 seconds: Gravitational Lenses." Communicating Astronomy with the Public Journal 2, no. 2 (2008): 4. https://doi.org/10.5281/zenodo.14862062.

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12

Murayama, Hitoshi. "Explained in 60 seconds: Standard Model." Communicating Astronomy with the Public 2, no. 3 (2008): 4. https://doi.org/10.5281/zenodo.14862815.

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13

Schwarz, John H. "Explained in 60 Seconds: String Theory." Communicating Astronomy with the Public 3, no. 1 (2009): 4. https://doi.org/10.5281/zenodo.14863091.

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14

Tucker, Wallace. "It Is not Just a Theory, It Is a Theory!" Communicating Astronomy with the Public 3, no. 1 (2009): 9–10. https://doi.org/10.5281/zenodo.14863143.

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A theory is not some hunch, or half-baked idea that you come up with while taking a shower, or being under the influence of something or other. A theory, as scientists understand the meaning of the word, is a scientifically tested principle or body of principles that incorporates and explains a significant body of evidence.

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15

Pullen, Lee. "Explained in 60 seconds: The End of the Sun." Communicating Astronomy with the Public 3, no. 3 (2009): 4. https://doi.org/10.5281/zenodo.14868343.

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16

Holbrook, Jarita C. "Explained in 60 Seconds: Cultural Astronomy." Communicating Astronomy with the Public 4, no. 2 (2010): 4. https://doi.org/10.5281/zenodo.14880662.

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17

Trodden, Mark. "Explained in 60 Seconds: The Big Bang." Communicating Astronomy with the Public Journal 5, no. 1 (2011): 31. https://doi.org/10.5281/zenodo.14890682.

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18

Bernstein, Joe. "Explained in 60 Seconds: Redshift." Communicating Astronomy with the Public Journal 6, no. 1 (2012): 4. https://doi.org/10.5281/zenodo.14890752.

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19

Beck, Paul G. "Explained in 60 Seconds: Timescales of Stellar Oscillations." Communicating Astronomy with the Public Journal 8, no. 2 (2014): 4. https://doi.org/10.5281/zenodo.14928605.

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20

Rosenfield, Phil, Justin Gaily, Oliver Fraser, and John Wisniewski. "The University of Washington Mobile Planetarium: A Do-It-Yourself Guide." Communicating Astronomy with the Public Journal 8, no. 2 (2014): 35–39. https://doi.org/10.5281/zenodo.14929043.

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The University of Washington mobile planetarium project is a student-driven effort to bring astronomy to secondary schools, and the community, in Seattle, USA. This paper presents the solution that was designed and built in order to use the World- Wide Telescope — a computer program created by Microsoft that displays the astronomical sky as maps, the 3D  Universe, and earth science data — from a laptop and an off-the-shelf high-definition (HD) projector located in an inflatable planetarium.In the first six months of operation, undergraduates at the University of Washington pre

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21

Cheetham, Clementine. "Explained in 60Sseconds: The Event Horizon and the Fate of Fish." Communicating Astronomy with the Public Journal 8, no. 3 (2014): 4. https://doi.org/10.5281/zenodo.14935258.

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22

Jenner, Nicky. "Explained in 60 Seconds: Windy with a Chance of Flares." Communicating Astronomy with the Public Journal 9, no. 1 (2015): 4. https://doi.org/10.5281/zenodo.14942465.

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23

Marshall, Chris. "Explained in 60 Seconds: Why is Pluto not a Planet?" Communicating Astronomy with the Public Journal 9, no. 2 (2015): 4. https://doi.org/10.5281/zenodo.14942505.

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24

Bladon, Georgia. "Explained in 60 Seconds: The Ripples on Everyone's Lips." Communicating Astronomy with the Public Journal 10, no. 2 (2016): 4. https://doi.org/10.5281/zenodo.14959160.

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25

Orton, Glenn S. "Explained in 60 Seconds: Juno Surveys Jupiter's Great Red Spot and the Citizen-led Approach to Imaging." Communicating Astronomy with the Public Journal 12, no. 1 (2018): 4. https://doi.org/10.5281/zenodo.14977304.

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26

Cui, Chenzhou. "Explained in 60 Seconds: Virtual Observatory." Communicating Astronomy with the Public Journal 12, no. 2 (2018): 4. https://doi.org/10.5281/zenodo.14977457.

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27

Batalha, Natalie. "Explained in 60 Seconds: The Diversity of Distant Worlds." Communicating Astronomy with the Public Journal 13, no. 1 (2019): 4. https://doi.org/10.5281/zenodo.14977559.

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28

Hada, Kazuhiro. "Explained in 60 Seconds: The First Ever Image of a Black Hole." Communicating Astronomy with the Public Journal 13, no. 2 (2019): 4. https://doi.org/10.5281/zenodo.14977745.

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29

Walker, Constance E. "Explained in 60 Seconds: Impact of Satellite Constellations in Astronomy." Communicating Astronomy with the Public Journal 15, no. 1 (2021): 4. https://doi.org/10.5281/zenodo.14978423.

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30

Marshall, Genevieve. "Explained in 60 Seconds: Getting Started in Fundraising for Astronomy Outreach." Communicating Astronomy with the Public Journal 15, no. 2 (2021): 4. https://doi.org/10.5281/zenodo.14980039.

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31

Pössel, Markus, and Carolin Liefke. "Explained in 60 Seconds: Astronomy Outreach and Education, Overlap and Differences." Communicating Astronomy with the Public Journal 16, no. 1 (2022): 4. https://doi.org/10.5281/zenodo.14984800.

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32

Kubheka, Duduzile, and Sally Macfarlane. "Explained in 60 Seconds: Community Engagement at the XXXII IAU General Assembly." Communicating Astronomy with the Public Journal 18, no. 2 (2024): 4–5. https://doi.org/10.5281/zenodo.14986837.

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In August 2024, the International Astronomical Union General Assembly will take place on the African continent for the first time in the organisation’s 105-year history. To celebrate this historic event, the National Organising Committee’s education and public outreach team is planning a series of events to encourage students and the general public across the continent to explore and engage with astronomy. This article describes how we will engage the African public before, during and after the conference.

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33

da Costa, Antonio Gomes. "The Cheshire explainer. Musings about the training of explainers." Journal of Science Communication 15, no. 04 (2016): C06. http://dx.doi.org/10.22323/2.15040306.

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The profession of explainer is still pretty much undefined and underrated and the training of explainers is many times deemed to be a luxury. In the following pages we make the argument that three main factors contribute to this state of affairs and, at the same time, we try to show why the training of explainers should really be at the core of any science communication institution. These factors are: an erroneous perception of what a proper scientific training means for explainers; a lack of clear definition of the aptitudes and role of explainers required by institutions that are evolving an

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34

Griffiths, Martin, and Carlos Oliveira. "The Big Bang – A hot Issue in Science Communication." Communicating Astronomy with the Public 4, no. 3 (2010): 7–11. https://doi.org/10.5281/zenodo.14881240.

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The Big Bang theory is one of the cornerstones of modern cosmology, drawing on a wealth of observational, experimental and theoretical data to underpin one of the most successful theories science has constructed. Why then is it under attack in the public domain? This paper will examine the theory and look at the perceived public problems that arise when it is communicated by following the dominant model of communicating science. This paper then examines whether in public perception, replacing a more traditional faith-based worldview by the Big Bang theory results in a loss of purpose, philosop

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35

Ekayana, Anak Agung Gde. "Development of Microlearning-Oriented Explainer Videos on Robotics Learning in Higher Education." Jurnal Ilmu Pendidikan (JIP) STKIP Kusuma Negara 15, no. 1 (2023): 69–83. http://dx.doi.org/10.37640/jip.v15i1.1788.

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The digital era triggers innovation in the learning process where currently, students prefer to find and learn learning resources through the internet/online technology. Microlearning-oriented explainer video media is one solution to accommodate changes in the current way of learning. This research aims to develop and implement microlearning-oriented explainer videos in robotics courses in higher education on a limited scale. The research used the Plomp development model to create explainer videos. The resulting explainer video media is tested for validity, practicality, and effectiveness. The

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36

Krämer, Andreas, and Sandra Böhrs. "How Do Consumers Evaluate Explainer Videos? An Empirical Study on the Effectiveness and Efficiency of Different Explainer Video Formats." Journal of Education and Learning 6, no. 1 (2016): 254. http://dx.doi.org/10.5539/jel.v6n1p254.

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There is a significant rise in the use of videos. More and more people use videos not only as a source of information but also as learning tool. This article explores the future potential of explainer videos, a format that conveys complex facts to a target group within a very short time. The findings are based on an empirical study representative for the German and U.S. population (18+ years). In the first step, the status quo of the use of e-learning in general and explainer videos in particular is presented. Subsequently, the effectiveness and efficiency of five different explainer video for

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Balbin, Karen Joy, and Marymina Odiem. "Unveiling the Impact of Explainer Videos on Grade 4 Science Learning: A Quasi-Experimental Analysis." International Journal of Advances in Education, Social Sciences and Innovation 2 (June 5, 2023): 1–6. https://doi.org/10.5281/zenodo.11194947.

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This research looked into the use of explainer video as a science learning intervention for Grade 4 learners of Liwan West Elementary School. The study utilized the quantitative type of research employing a quasi-experimental research design through the use of experimental and control groups with pre-test and post-test approaches to determine the effectiveness of utilizing video explainers in improving pupils’ academic performance in Science. Data was gathered from 32 Grade 4 pupils. It was analyzed using the Paired Sample T-Test and Independent Sample T-Test. Findings revealed that the

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38

Handoko, Handoko, Angela Angela, and Gunawan Gunawan. "Pembekalan Explainer Video bagi Siswa dalam Menghadapi Era Revolusi Industri 4.0." Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal 4, no. 3 (2021): 217–24. http://dx.doi.org/10.33330/jurdimas.v4i3.967.

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Abstract: The 4.0 Industrial Revolution is marked by rapid advances and technological changes in various fields, including education. To welcome the era of the 4.0 Industrial Revolution, learning curriculum in schools must follow the technological advancement. Teachers generally provide group assignments to be presented by students. The main obstacle faced is that students are less capable to create and deliver presentation content. Therefore, it is necessary to provide insight about presentation ability and the use of technology to make presentations. The activity began by compiling a trainin

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Fajar, Ahmad, and Seliwati Ginting. "PEMBUATAN VIDEO EXPLAINER TENTANG TRIPUTRA DNA SEBAGAI MEDIA INFORMASI KARYAWAN DAYA MOTOR ASIA AFRIKA." INFOKOM (Informatika & Komputer) 10, no. 2 (2023): 1–9. http://dx.doi.org/10.56689/infokom.v10i2.964.

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In this digital era, finding various things on the internet is effortless, especially finding information in form of explainer video. Explainer video in this digital era are quite important, it makes messages or information easy to convey with visuals that look neat and organized. This final project aims to deliver information about Triputra DNA's Guiding Values through explainer video. The author uses multi panel layout in making explainer video to produce a neat and organized visual. From the video that has been made and the results of the questionnaire received, messages or information is e

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Huang, Rundong, Farhad Shirani, and Dongsheng Luo. "Factorized Explainer for Graph Neural Networks." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 11 (2024): 12626–34. http://dx.doi.org/10.1609/aaai.v38i11.29157.

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Graph Neural Networks (GNNs) have received increasing attention due to their ability to learn from graph-structured data. To open the black-box of these deep learning models, post-hoc instance-level explanation methods have been proposed to understand GNN predictions. These methods seek to discover substructures that explain the prediction behavior of a trained GNN. In this paper, we show analytically that for a large class of explanation tasks, conventional approaches, which are based on the principle of graph information bottleneck (GIB), admit trivial solutions that do not align with the no

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41

Wu, Shuaimin. "Explainer on GNN-based segmentation networks." Journal of Physics: Conference Series 2711, no. 1 (2024): 012009. http://dx.doi.org/10.1088/1742-6596/2711/1/012009.

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Abstract Graph Neural Networks (GNN) are powerful tools for deep learning. Similar to other neural networks, GNNs are complex models, in which humans can’t understand the decision-making procedures of the models. Therefore, it brings the need to explainability of GNNs. Explainability is critical for deep learning to support its predictions. In this paper, we will investigate the Grad-Cam and Integrated-Gradients explaining methods. The Grad-Cam applies a global average pooling over the feature activation mapping, and then which was followed by a ReLU activation to obtain an attribution. The In

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42

Stephenson, David B., Andrew Garrett, and Dario Domingo. "Extreme weather: A climate change explainer." Significance 22, no. 3 (2025): 13–15. https://doi.org/10.1093/jrssig/qmaf022.

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Abstract In the second of an occasional series of explainers on the statistics and data underpinning our understanding of climate change, David B. Stephenson, Andrew Garrett and Dario Domingo explain why a small increase in the global mean temperature can lead to a disproportionate increase in extreme events

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43

Bobek, Szymon, and Grzegorz J. Nalepa. "Local Universal Rule-based eXplainer (LUX)." SoftwareX 30 (May 2025): 102102. https://doi.org/10.1016/j.softx.2025.102102.

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44

Baldwin, Emily. "Explained in 60 Seconds: Why Visit a Comet?" Communicating Astronomy with the Public Journal 10, no. 1 (2016): 4. https://doi.org/10.5281/zenodo.14959900.

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45

Hu, Tan, and Tieru Wu. "An evaluation method with convolutional white-box models for image attribution explainers." Journal of Physics: Conference Series 2637, no. 1 (2023): 012004. http://dx.doi.org/10.1088/1742-6596/2637/1/012004.

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Abstract Research in the explanation of models has developed rapidly in recent years. However, research in the evaluation of explainers is still limited, with most evaluation strategies centered around perturbation. This approach may produce incorrect evaluations when the relationship between features gets complicated. In this research, we present a ground-truth-based evaluation method for feature attribution explainers on image tasks. We design three perspectives to evaluate. The input perspective evaluates whether the explainers accurately represent the inputs that the model detects. The fea

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46

Pullen, Lee. "Explained in 60 seconds: Astronomy Matters." Communicating Astronomy with the Public 4, no. 1 (2010): 4. https://doi.org/10.5281/zenodo.14868949.

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47

Sagge, Jr. Roberto G., and Jr. Salvador P. Bacio. "Video explainer, e-module, or both: which is better to improve statistics performance of graduate students?" International Journal of Evaluation and Research in Education (IJERE) 13, no. 5 (2024): 3194–201. https://doi.org/10.11591/ijere.v13i5.28945.

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Technology is an essential component of modern education, and teachers use various types of technology to improve classroom performance. Meanwhile, statistics is one of the seemingly difficult courses according to students across levels. This study experimental aimed to determine if video explainer and e-module improve students’ performance in statistics. There were 78 graduate school students participated and used video explainer, e-module, or both as an intervention. A 100-item performance test in statistics was used. The statistical techniques employed were mean, standard deviation an

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48

Amelia, Tiara Pia, Sukesi Sukesi, Dwi Wahyu Wulan Sulistyowati, and Dina Isfentiani. "EFFECTIVENESS OF EXPLAINER VIDEO-BASED ANEMIA PREVENTION EDUCATION ON PREGNANT WOMEN’S KNOWLEDGE AND ATTITUDES." Journal Midwifery Jurusan Kebidanan Politeknik Kesehatan Gorontalo 10, no. 2 (2024): 137. https://doi.org/10.52365/jm.v10i2.1078.

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Anemia in pregnant women is a global health issue, often caused by a lack of knowledge and awareness regarding its prevention. Health education is one approach to improving the knowledge and attitudes of pregnant women toward anemia prevention. This study aims to evaluate the effectiveness of health education using explainer videos on the knowledge and attitudes of pregnant women. The research used a quasi-experimental method with a population of 76 primigravida pregnant women and a sample of 44 respondents selected through Simple Random Sampling. The independent variable was health education

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49

Thayaparan, Mokanarangan, Marco Valentino, Deborah Ferreira, Julia Rozanova, and André Freitas. "Diff-Explainer: Differentiable Convex Optimization for Explainable Multi-hop Inference." Transactions of the Association for Computational Linguistics 10 (2022): 1103–19. http://dx.doi.org/10.1162/tacl_a_00508.

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Abstract This paper presents Diff-Explainer, the first hybrid framework for explainable multi-hop inference that integrates explicit constraints with neural architectures through differentiable convex optimization. Specifically, Diff- Explainer allows for the fine-tuning of neural representations within a constrained optimization framework to answer and explain multi-hop questions in natural language. To demonstrate the efficacy of the hybrid framework, we combine existing ILP-based solvers for multi-hop Question Answering (QA) with Transformer-based representations. An extensive empirical eva

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Leslie, David. "Isaac Asimov: centenary of the great explainer." Nature 577, no. 7792 (2020): 614–16. http://dx.doi.org/10.1038/d41586-020-00176-4.

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