Phoster

Research and Development

Computer-aided and Automated Educational Scientific Reasoning and Discovery

Educational Research

Educational Research: An Introduction by Meredith D. Gall, Walter R. Borg and Joyce P. Gall, Introduction to Research in Education by Donald Ary, Lucy C. Jacobs, Christine K. Sorensen and David Walker, Research Methods in Education by Louis Cohen, Lawrence Manion and Keith Morrison, Design-based Research Methods for Studying Learning in Context: Introduction by William A. Sandoval and Philip Bell and Research Design: Qualitative, Quantitative, and Mixed Methods Approaches by John W. Creswell.

Scientific Reasoning and Discovery

The Computer-aided Discovery of Scientific Knowledge by Pat Langley, Principles of Human—computer Collaboration for Knowledge Discovery in Science by Raúl E. Valdés-Pérez, The Computational Support of Scientific Discovery by Pat Langley, Towards the Automation of Scientific Method by Oliver Ray, Amanda Clare, Maria Liakata, Larisa Soldatova, Ken Whelan and Ross D. King, The Automation of Science by Ross D. King, Jem Rowland, Stephen G. Oliver, Michael Young, Wayne Aubrey, Emma Byrne, Maria Liakata, Magdalena Markham, Pınar Pir, Larisa N. Soldatova, Andrew Sparkes, Kenneth E. Whelan and Amanda Clare, Exploring Science: The Cognition and Development of Discovery Processes by David Klahr, Scientific Discovery and the Psychology of Problem Solving by Herbert A. Simon, The Ubiquity of Discovery by Douglas B. Lenat, Scientific Discovery: Computational Explorations of the Creative Processes by Pat Langley, Data-driven Approaches to Empirical Discovery by Pat Langley and Jan M. Zytkow, Automated Discovery of Empirical Laws by Jan M. Zytkow, Enhancing the Plausibility of Law Equation Discovery by Takashi Washio, Hiroshi Motoda and Yuji Niwa, Scientific Knowledge Discovery using Inductive Logic Programming by Stephen Muggleton, Discovering Dynamics: From Inductive Logic Programming to Machine Discovery by Saso Dzeroski and Ljupco Todorovski, Machine Discovery by Herbert A. Simon, Towards a Mathematical Theory of Machine Discovery from Facts by Yasuhito Mukouchi and Setsuo Arikawa, Scientific Discovery Learning with Computer Simulations of Conceptual Domains by Ton De Jong and Wouter R. Van Joolingen, Automatic Construction of Accurate Models of Physical Systems by Elizabeth Bradley and Reinhard Stolle, Multimodal Reasoning for Automatic Model Construction by Reinhard Stolle and Elizabeth Bradley, The Need for Qualitative Reasoning in Automated Modeling: A Case Study by Antonio C. Capelo, Liliana Ironi and Stefania Tentoni, Learning Qualitative Models in the Presence of Noise by George M. Coghill, Simon M. Garrett and Ross D. King, A Computational Model of Scientific Insight by Pat Langley and Randolph Jones, Computational Models of Scientific Discovery and Theory Formation by Jeff Shrager and Pat Langley, An Integrated Framework for Empirical Discovery by Bernd Nordhausen and Pat Langley, Generating Predictions to Aid the Scientific Discovery Process by Randy Jones, Artificial Intelligence Methods for Theory Representation and Hypothesis Formation by Peter D. Karp, Automated Hypothesis Generation Using Extended Inductive Resolution by Charles O. Morgan, An Algorithm for Constructing and Searching Spaces of Alternative Hypotheses by Christopher Griffin, Kelly Testa and Stephen Racunas and On Comparing and Evaluating Scientific Theories edited by Adam Jonkisz and Leon Koj.

Scientific Experimentation

Experimentation in Machine Discovery by Deepak Kulkarni and Herbert A. Simon, The Processes of Scientific Discovery: The Strategy of Experimentation by Deepak Kulkarni and Herbert A. Simon, Experimenting and Theorizing in Theory Formation by Bruce W. Koehn and Jan M. Zytkow, The Design of Discrimination Experiments by Shankar A. Rajamoney, Towards Automatic Experimentation of Educational Knowledge by Yun-En Liu, Travis Mandel, Emma Brunskill and Zoran Popović, Trading Off Scientific Knowledge and User Learning with Multi-armed Bandits by Yun-En Liu, Travis Mandel, Emma Brunskill and Zoran Popović, Building Behavioral Experimentation Engines by Yun-En Liu, Learning Experiments Using AB Testing at Scale by Christopher Chudzicki, David E. Pritchard and Zhongzhou Chen, The Role of A/B Tests in the Study of Large-scale Online Learning by Alexander Savi, Joseph J. Williams, Gunter Maris and Han van der Maas, A Methodology for Discovering How to Adaptively Personalize to Users Using Experimental Comparisons by Joseph J. Williams and Neil Heffernan, Using Randomized Experiments as a Methodological and Conceptual Tool for Improving the Design of Online Learning Environments by Joseph J. Williams and Betsy A. Williams and Using and Designing Platforms for In Vivo Educational Experiments by Joseph J. Williams, Korinn Ostrow, Xiaolu Xiong, Elena Glassman, Juho Kim, Samuel G. Maldonado, Na Li, Justin Reich and Neil Heffernan.