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548 results on '"Murray, Tom"'

1. Imagen 3

Author

Imagen-Team-Google, Baldridge, Jason, Bauer, Jakob, Bhutani, Mukul, Brichtova, Nicole, Bunner, Andrew, Castrejon, Lluis, Chan, Kelvin, Chen, Yichang, Dieleman, Sander, Du, Yuqing, Eaton-Rosen, Zach, Fei, Hongliang, de Freitas, Nando, Gao, Yilin, Gladchenko, Evgeny, Colmenarejo, Sergio Gómez, Guo, Mandy, Haig, Alex, Hawkins, Will, Hu, Hexiang, Huang, Huilian, Igwe, Tobenna Peter, Kaplanis, Christos, Khodadadeh, Siavash, Kim, Yelin, Konyushkova, Ksenia, Langner, Karol, Lau, Eric, Lawton, Rory, Luo, Shixin, Mokrá, Soňa, Nandwani, Henna, Onoe, Yasumasa, Oord, Aäron van den, Parekh, Zarana, Pont-Tuset, Jordi, Qi, Hang, Qian, Rui, Ramachandran, Deepak, Rane, Poorva, Rashwan, Abdullah, Razavi, Ali, Riachi, Robert, Srinivasan, Hansa, Srinivasan, Srivatsan, Strudel, Robin, Uria, Benigno, Wang, Oliver, Wang, Su, Waters, Austin, Wolff, Chris, Wright, Auriel, Xiao, Zhisheng, Xiong, Hao, Xu, Keyang, van Zee, Marc, Zhang, Junlin, Zhang, Katie, Zhou, Wenlei, Zolna, Konrad, Aboubakar, Ola, Akbulut, Canfer, Akerlund, Oscar, Albuquerque, Isabela, Anderson, Nina, Andreetto, Marco, Aroyo, Lora, Bariach, Ben, Barker, David, Ben, Sherry, Berman, Dana, Biles, Courtney, Blok, Irina, Botadra, Pankil, Brennan, Jenny, Brown, Karla, Buckley, John, Bunel, Rudy, Bursztein, Elie, Butterfield, Christina, Caine, Ben, Carpenter, Viral, Casagrande, Norman, Chang, Ming-Wei, Chang, Solomon, Chaudhuri, Shamik, Chen, Tony, Choi, John, Churbanau, Dmitry, Clement, Nathan, Cohen, Matan, Cole, Forrester, Dektiarev, Mikhail, Du, Vincent, Dutta, Praneet, Eccles, Tom, Elue, Ndidi, Feden, Ashley, Fruchter, Shlomi, Garcia, Frankie, Garg, Roopal, Ge, Weina, Ghazy, Ahmed, Gipson, Bryant, Goodman, Andrew, Górny, Dawid, Gowal, Sven, Gupta, Khyatti, Halpern, Yoni, Han, Yena, Hao, Susan, Hayes, Jamie, Heek, Jonathan, Hertz, Amir, Hirst, Ed, Hoogeboom, Emiel, Hou, Tingbo, Howard, Heidi, Ibrahim, Mohamed, Ike-Njoku, Dirichi, Iljazi, Joana, Ionescu, Vlad, Isaac, William, Jana, Reena, Jennings, Gemma, Jenson, Donovon, Jia, Xuhui, Jones, Kerry, Ju, Xiaoen, Kajic, Ivana, Ayan, Burcu Karagol, Kelly, Jacob, Kothawade, Suraj, Kouridi, Christina, Ktena, Ira, Kumakaw, Jolanda, Kurniawan, Dana, Lagun, Dmitry, Lavitas, Lily, Lee, Jason, Li, Tao, Liang, Marco, Li-Calis, Maggie, Liu, Yuchi, Alberca, Javier Lopez, Lorrain, Matthieu Kim, Lu, Peggy, Lum, Kristian, Ma, Yukun, Malik, Chase, Mellor, John, Mensink, Thomas, Mosseri, Inbar, Murray, Tom, Nematzadeh, Aida, Nicholas, Paul, Nørly, Signe, Oliveira, João Gabriel, Ortiz-Jimenez, Guillermo, Paganini, Michela, Paine, Tom Le, Paiss, Roni, Parrish, Alicia, Peckham, Anne, Peswani, Vikas, Petrovski, Igor, Pfaff, Tobias, Pirozhenko, Alex, Poplin, Ryan, Prabhu, Utsav, Qi, Yuan, Rahtz, Matthew, Rashtchian, Cyrus, Rastogi, Charvi, Raul, Amit, Rebuffi, Sylvestre-Alvise, Ricco, Susanna, Riedel, Felix, Robinson, Dirk, Rohatgi, Pankaj, Rosgen, Bill, Rumbley, Sarah, Ryu, Moonkyung, Salgado, Anthony, Salimans, Tim, Singla, Sahil, Schroff, Florian, Schumann, Candice, Shah, Tanmay, Shaw, Eleni, Shaw, Gregory, Shillingford, Brendan, Shivakumar, Kaushik, Shtatnov, Dennis, Singer, Zach, Sluzhaev, Evgeny, Sokolov, Valerii, Sottiaux, Thibault, Stimberg, Florian, Stone, Brad, Stutz, David, Su, Yu-Chuan, Tabellion, Eric, Tang, Shuai, Tao, David, Thomas, Kurt, Thornton, Gregory, Toor, Andeep, Udrescu, Cristian, Upadhyay, Aayush, Vasconcelos, Cristina, Vasiloff, Alex, Voynov, Andrey, Walker, Amanda, Wang, Luyu, Wang, Miaosen, Wang, Simon, Wang, Stanley, Wang, Qifei, Wang, Yuxiao, Weisz, Ágoston, Wiles, Olivia, Wu, Chenxia, Xu, Xingyu Federico, Xue, Andrew, Yang, Jianbo, Yu, Luo, Yurtoglu, Mete, Zand, Ali, Zhang, Han, Zhang, Jiageng, Zhao, Catherine, Zhaxybay, Adilet, Zhou, Miao, Zhu, Shengqi, Zhu, Zhenkai, Bloxwich, Dawn, Bordbar, Mahyar, Cobo, Luis C., Collins, Eli, Dai, Shengyang, Doshi, Tulsee, Dragan, Anca, Eck, Douglas, Hassabis, Demis, Hsiao, Sissie, Hume, Tom, Kavukcuoglu, Koray, King, Helen, Krawczyk, Jack, Li, Yeqing, Meier-Hellstern, Kathy, Orban, Andras, Pinsky, Yury, Subramanya, Amar, Vinyals, Oriol, Yu, Ting, and Zwols, Yori

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We introduce Imagen 3, a latent diffusion model that generates high quality images from text prompts. We describe our quality and responsibility evaluations. Imagen 3 is preferred over other state-of-the-art (SOTA) models at the time of evaluation. In addition, we discuss issues around safety and representation, as well as methods we used to minimize the potential harm of our models.

Published
2024

2. PopSparse: Accelerated block sparse matrix multiplication on IPU

Author

Li, Zhiyi, Orr, Douglas, Ohan, Valeriu, Da costa, Godfrey, Murray, Tom, Sanders, Adam, Beker, Deniz, and Masters, Dominic

Subjects
Computer Science - Machine Learning
Abstract

Reducing the computational cost of running large scale neural networks using sparsity has attracted great attention in the deep learning community. While much success has been achieved in reducing FLOP and parameter counts while maintaining acceptable task performance, achieving actual speed improvements has typically been much more difficult, particularly on general purpose accelerators (GPAs) such as NVIDIA GPUs using low precision number formats. In this work we introduce PopSparse, a library that enables fast sparse operations on Graphcore IPUs by leveraging both the unique hardware characteristics of IPUs as well as any block structure defined in the data. We target two different types of sparsity: static, where the sparsity pattern is fixed at compile-time; and dynamic, where it can change each time the model is run. We present benchmark results for matrix multiplication for both of these modes on IPU with a range of block sizes, matrix sizes and densities. Results indicate that the PopSparse implementations are faster than dense matrix multiplications on IPU at a range of sparsity levels with large matrix size and block size. Furthermore, static sparsity in general outperforms dynamic sparsity. While previous work on GPAs has shown speedups only for very high sparsity (typically 99\% and above), the present work demonstrates that our static sparse implementation outperforms equivalent dense calculations in FP16 at lower sparsity (around 90%). IPU code is available to view and run at ipu.dev/sparsity-benchmarks, GPU code will be made available shortly.

Published
2023

3. Extreme Acceleration of Graph Neural Network-based Prediction Models for Quantum Chemistry

Author

Helal, Hatem, Firoz, Jesun, Bilbrey, Jenna, Krell, Mario Michael, Murray, Tom, Li, Ang, Xantheas, Sotiris, and Choudhury, Sutanay

Subjects
Computer Science - Machine Learning, Computer Science - Hardware Architecture, Physics - Chemical Physics
Abstract

Molecular property calculations are the bedrock of chemical physics. High-fidelity \textit{ab initio} modeling techniques for computing the molecular properties can be prohibitively expensive, and motivate the development of machine-learning models that make the same predictions more efficiently. Training graph neural networks over large molecular databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. This paper demonstrates a novel hardware-software co-design approach to scale up the training of graph neural networks for molecular property prediction. We introduce an algorithm to coalesce the batches of molecular graphs into fixed size packs to eliminate redundant computation and memory associated with alternative padding techniques and improve throughput via minimizing communication. We demonstrate the effectiveness of our co-design approach by providing an implementation of a well-established molecular property prediction model on the Graphcore Intelligence Processing Units (IPU). We evaluate the training performance on multiple molecular graph databases with varying degrees of graph counts, sizes and sparsity. We demonstrate that such a co-design approach can reduce the training time of such molecular property prediction models from days to less than two hours, opening new possibilities for AI-driven scientific discovery.

Published
2022

4. Affect Behavior Prediction: Using Transformers and Timing Information to Make Early Predictions of Student Exercise Outcome

Author

Yu, Hao, Allessio, Danielle A., Rebelsky, William, Murray, Tom, Magee, John J., Arroyo, Ivon, Woolf, Beverly P., Bargal, Sarah Adel, Betke, Margrit, Hartmanis, Juris, Founding Editor, Goos, Gerhard, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Olney, Andrew M., editor, Chounta, Irene-Angelica, editor, Liu, Zitao, editor, Santos, Olga C., editor, and Bittencourt, Ig Ibert, editor

Published
2024
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5. Measurements and Interventions to Improve Student Engagement Through Facial Expression Recognition

Author

Lee, Will, Allessio, Danielle, Rebelsky, William, Satish Gattupalli, Sai, Yu, Hao, Arroyo, Ivon, Betke, Margrit, Bargal, Sarah, Murray, Tom, Sylvia, Frank, Woolf, Beverly P., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sottilare, Robert A., editor, and Schwarz, Jessica, editor

Published
2022
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8. HIF activation enhances FcγRIIb expression on mononuclear phagocytes impeding tumor targeting antibody immunotherapy

Author

Hussain, Khiyam, Liu, Rena, Smith, Rosanna C. G., Müller, Kri T. J., Ghorbani, Mohammadmersad, Macari, Sofia, Cleary, Kirstie L. S., Oldham, Robert J., Foxall, Russell B., James, Sonya, Booth, Steven G., Murray, Tom, Dahal, Lekh N., Hargreaves, Chantal E., Kemp, Robert S., Longley, Jemma, Douglas, James, Markham, Hannah, Chee, Serena J., Stopforth, Richard J., Roghanian, Ali, Carter, Matthew J., Ottensmeier, Christian H., Frendéus, Bjorn, Cutress, Ramsey I., French, Ruth R., Glennie, Martin J., Strefford, Jonathan C., Thirdborough, Stephen M., Beers, Stephen A., and Cragg, Mark S.

Published
2022
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9. Affective Teacher Tools: Affective Class Report Card and Dashboard

Author

Gupta, Ankit, Menon, Neeraj, Lee, William, Rebelsky, William, Allesio, Danielle, Murray, Tom, Woolf, Beverly, Whitehill, Jacob, Arroyo, Ivon, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Roll, Ido, editor, McNamara, Danielle, editor, Sosnovsky, Sergey, editor, Luckin, Rose, editor, and Dimitrova, Vania, editor

Published
2021
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10. Measuring and Integrating Facial Expressions and Head Pose as Indicators of Engagement and Affect in Tutoring Systems

Author

Yu, Hao, Gupta, Ankit, Lee, Will, Arroyo, Ivon, Betke, Margrit, Allesio, Danielle, Murray, Tom, Magee, John, Woolf, Beverly P., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sottilare, Robert A., editor, and Schwarz, Jessica, editor

Published
2021
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15. Progress Report--Microsoft Office 2003 Lynchburg College Tutorials

Author

Murray, Tom

Abstract

For the past several years Lynchburg College has developed Microsoft tutorials for use with academic classes and faculty, student and staff training. The tutorials are now used internationally. Last year Microsoft and Verizon sponsored a tutorial web site at http://www.officetutorials.com. This website recognizes ASCUE members for their wonderful efforts in spreading the tutorials throughout higher and K-12 education. Because of this effort, the tutorials became a 2003 Microsoft Model Professional Development Award recipient. Since our last meeting, the Office 2003 tutorials have been created, and are available, through the website. One of our ASCUE members, Bernadette Ortiz-Brewster, is translating the tutorials into Spanish. Karen Fraser of Hendrix College, Arkansas is MACing the tutorials. Several other ASCUE members have also published tutorials, from their institutions, on this website. Currently, a Microsoft Producer tutorial is being created. As this is being written, the tutorials are being considered by the National Forum on Information Literacy, the Department of the Navy Information Literacy Toolkit, the Virginia Department of Education, and the Teaching, Learning, Technology Roundtable. This presentation will furnish an update on all of these initiatives, as well as some others, which are "unfolding" at this time. [For complete proceedings, see ED490093.]

Published
2004

19. COVES: A Cognitive-Affective Deep Model that Personalizes Math Problem Difficulty in Real Time and Improves Student Engagement with an Online Tutor

Author

Yu, Hao, primary, Allessio, Danielle A., additional, Lee, Will, additional, Rebelsky, William, additional, Sylvia, Frank, additional, Murray, Tom, additional, Magee, John J., additional, Arroyo, Ivon, additional, Woolf, Beverly P., additional, Bargal, Sarah Adel, additional, and Betke, Margrit, additional

Published
2023
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23. Coordinating the Complexity of Tools, Tasks, and Users: On Theory-Based Approaches to Authoring Tool Usability

Author

Murray, Tom

Abstract

Intelligent Tutoring Systems authoring tools are highly complex educational software applications used to produce highly complex software applications (i.e. ITSs). How should our assumptions about the target users (authors) impact the design of authoring tools? In this article I first reflect on the factors leading to my original 1999 article on the state of the art in ITS authoring tools and consider some challenges facing authoring tool researchers today. Then, in the bulk of the paper, I propose some principled foundations for future authoring tool design, focusing on operationalizing the construct of complexity--for tool, task, and user. ITS authoring tools are major undertakings and to redeem this investment it is important to anticipate actual user needs and capacities. I propose that one way to do this is to match the complexity of tool design to the complexity of authoring tasks and the complexity capacity of users and user communities. Doing so entails estimating the complexity of the mental models that a user is expected to build in order to use a tool as intended. The goal is not so much to support the design of more powerful authoring tools as it is to design tools that meet the needs of realistic user audiences. This paper presents some exploratory ideas on how to operationalize the concept of complexity for tool, task, and user. The paper draws from the following theories and frameworks to weave this narrative: Complexity Science, Activity Theory, Epistemic Forms and Games, and adult cognitive developmental theory (Hierarchical Complexity Theory). This exploration of usability and complexity is applicable to the design of any type of complex authoring application, though the application area that motivated the exploration is ITS authoring.

Published
2016
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29. ATL-BP: A Student Engagement Dataset and Model for Affect Transfer Learning for Behavior Prediction

Author

Ruiz, Nataniel, primary, Yu, Hao, additional, Allessio, Danielle A., additional, Jalal, Mona, additional, Joshi, Ajjen, additional, Murray, Tom, additional, Magee, John J., additional, Delgado, Kevin Manuel, additional, Ablavsky, Vitaly, additional, Sclaroff, Stan, additional, Arroyo, Ivon, additional, Woolf, Beverly P., additional, Bargal, Sarah Adel, additional, and Betke, Margrit, additional

Published
2023
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30. Building a Foundation: How Technology-Rich Project-Based Learning Transformed Talladega County Schools. Case Study

Author

Alliance for Excellent Education, Jones, Rachel, Hall, Sara White, Thigpen, Kamila, Murray, Tom, and Loschert, Kristen

Abstract

This report demonstrates how one predominantly low-income school district dramatically improved student engagement in the classroom and increased high school graduation rates through project-based learning (PBL) and the effective use of technology. The report, which includes short video segments with educators and students, focuses on Talladega County Schools in Alabama, where technology is an important component that builds students' abilities to solve real-world problems; master college- and career-ready academic standards; and develop skills in communication, collaboration, critical thinking, and other deeper learning competencies. "Building a Foundation" describes how Talladega implemented a PBL model using a digital learning framework to engage students with an extended inquiry learning process that paired complex questions with carefully designed tasks. It also identifies key factors that supported the county's transformation and includes several recommendations for schools and school districts interested in changing their own learning models. [Contains endnotes.]

Published
2015

32. Morphological Response of Submerged Structures on a Highly Dynamic Wave Dominated Beach.

Author

Strauss, Darrell, Vieira da Silva, Guilherme, Murray, Tom, Mingyuan Ma, Faivre, Gaëlle, Angenent, Evanne, and Alvarez, Fernando

Subjects
COASTAL engineering, COASTAL development, METEOROLOGY, WAVES (Physics)
Abstract

Multi-purpose submerged coastal protection structures are increasingly being considered on sandy wave dominated coasts for their relatively low impact on visual and beach amenity compared to traditional emerged structural works such as breakwaters. However, knowledge of submerged coastal protection structure attributes, with respect to their impact on morphological responses, is scarce, mainly due to the difficulty in predicting outcomes in dynamic environments and a reliance on expensive laboratory or numerical modelling experiments combined with a general lack of in-situ monitoring data. The design and performance of multi-purpose submerged coastal protection structures for coastal protection and surf amenity is assessed here using a process-based model. The model is supported by field measurements used to calibrate models of two existing Gold Coast artificial reefs and nearshore beach nourishments and their morphological evolution. Twenty-five scenarios with varying crest width, shape, depth and distance offshore were tested to identify key physical parameters for the effective and efficient design of submerged nearshore protection structures. The open coast beach of the northern Gold Coast was used as a case study site however this research methodology can be used to inform coastal protection strategies for other wave-dominated, sandy beach coastlines with similar geology, geomorphology, tide and wave climate. The impacts of the submerged structures on nearshore waves, hydrodynamics and morphology were determined in several key areas such as the lee of the structure, updrift and downdrift active profile regions. The results demonstrate that validated morphological models can be applied with increasing confidence to develop evidence-based guidelines for defining the key planning, design, and structural parameters of nearshore coastal protection structures to achieve effective coastal protection and enhanced recreational amenity outcomes. [ABSTRACT FROM AUTHOR]

Published
2023

37. Supporting Social Deliberative Skills Online: The Effects of Reflective Scaffolding Tools

Author

Murray, Tom, Stephens, Lynn, Woolf, Beverly Park, Wing, Leah, Xu, Xiaoxi, Shrikant, Natasha, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ozok, A. Ant, editor, and Zaphiris, Panayiotis, editor

Published
2013
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38. An Exploration of Text Analysis Methods to Identify Social Deliberative Skill

Author

Murray, Tom, Xu, Xiaoxi, Woolf, Beverly Park, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Lane, H. Chad, editor, Yacef, Kalina, editor, Mostow, Jack, editor, and Pavlik, Philip, editor

Published
2013
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40. Recognizing Dialogue Content in Student Collaborative Conversation

Author

Dragon, Toby, Floryan, Mark, Woolf, Beverly, Murray, Tom, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Aleven, Vincent, editor, Kay, Judy, editor, and Mostow, Jack, editor

Published
2010
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42. Coaching Within a Domain Independent Inquiry Environment

Author

Dragon, Toby, Woolf, Beverly Park, Marshall, David, Murray, Tom, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ikeda, Mitsuru, editor, Ashley, Kevin D., editor, and Chan, Tak-Wai, editor

Published
2006
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43. Is Adaptation to Task Complexity Really Beneficial for Performance?

Author

Pieschl, Stephanie, Stahl, Elmar, and Murray, Tom

Abstract

Theories of self-regulated learning assume that learners flexibly adapt their learning process to external task demands and that this is positively related to performance. In this study, university students (n = 119) solved three tasks that greatly differed in complexity. Their learning processes were captured in detail by task-specific questionnaires and computer-generated log files. Results indicate that students adapted almost all learning processes significantly to task complexity. For example, students accessed more hypertext pages for complex tasks than for simple tasks. However, this kind of adaptation was not consistently related to performance. For variables capturing learners' self-regulation, such as the number of accessed hypertext pages, more pronounced adaptation was significantly and positively related to performance even when learners' general processing depth was statistically controlled. Results were less consistent for variables capturing learners' self-monitoring, such as their judged task complexity. (Contains 3 tables and 2 figures.)

Published
2012
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45. Web-Based Intelligent Multimedia Tutoring for High Stakes Achievement Tests

Author

Arroyo, Ivon, Beal, Carole, Murray, Tom, Walles, Rena, Woolf, Beverly P., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lester, James C., editor, Vicari, Rosa Maria, editor, and Paraguaçu, Fábio, editor

Published
2004
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46. Lessons Learned from Authoring for Inquiry Learning: A Tale of Authoring Tool Evolution

Author

Murray, Tom, Woolf, Beverly, Marshall, David, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lester, James C., editor, Vicari, Rosa Maria, editor, and Paraguaçu, Fábio, editor

Published
2004
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47. Supporting Social Deliberative Skills in Online Classroom Dialogues: Preliminary Results Using Automated Text Analysis

Author

Murray, Tom, Woolf, Beverly Park, Xu, Xiaoxi, Shipe, Stefanie, Howard, Scott, Wing, Leah, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Cerri, Stefano A., editor, Clancey, William J., editor, Papadourakis, Giorgos, editor, and Panourgia, Kitty, editor

Published
2012
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