An evaluation of scanpath-comparison and machine-learning classification algorithms used to study the dynamics of analogy making

In recent years, eyetracking has begun to be used to study the dynamics of analogy making. Numerous scanpath-comparison algorithms and machine-learning techniques are available that can be applied to the raw eyetracking data. We show how scanpath-comparison algorithms, combined with multidimensional scaling and a classification algorithm, can be used to resolve an outstanding question in analogy making—namely, whether or not children’s and adults’ strategies in solving analogy problems are different. (They are.) We show which of these scanpath-comparison algorithms is best suited to the kinds of analogy problems that have formed the basis of much analogy-making research over the years. Furthermore, we use machine-learning classification algorithms to examine the item-to-item saccade vectors making up these scanpaths. We show which of these algorithms best predicts, from very early on in a trial, on the basis of the frequency of various item-to-item saccades, whether a child or an adult is doing the problem. This type of analysis can also be used to predict, on the basis of the item-to-item saccade dynamics in the first third of a trial, whether or not a problem will be solved correctly.

[1]  Seymour Geisser,et al.  The Predictive Sample Reuse Method with Applications , 1975 .

[2]  K. Holyoak,et al.  The Oxford handbook of thinking and reasoning , 2012 .

[3]  John R. Anderson,et al.  Integrating analogical mapping and general problem solving: the path-mapping theory , 2001, Cogn. Sci..

[4]  M. Stone.  Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .

[5]  G. Halford.  Children's Understanding: The Development of Mental Models , 1993 .

[6]  K. Holyoak.  Analogy and Relational Reasoning , 2012 .

[7]  Thierry Baccino,et al.  Methods for comparing scanpaths and saliency maps: strengths and weaknesses , 2012, Behavior Research Methods.

[8]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[9]  Sylvain Arlot,et al.  A survey of cross-validation procedures for model selection , 2009, 0907.4728.

[10]  Robert M. French,et al.  Visual Strategies in Analogical Reasoning Development: A New Method for Classifying Scanpaths , 2013, CogSci.

[11]  V. S. Ramachandran,et al.  Analogical Reasoning , 2012 .

[12]  John R. Anderson,et al.  Integrating Analogical Mapping and General Problem Solving , 2001 .

[13]  M. Just,et al.  Eye fixations and cognitive processes , 1976, Cognitive Psychology.

[14]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[15]  Marcus Nyström,et al.  A vector-based, multidimensional scanpath similarity measure , 2010, ETRA.

[16]  H. Deubel,et al.  Saccade target selection and object recognition: Evidence for a common attentional mechanism , 1996, Vision Research.

[17]  Robert M. French,et al.  In the Eyes of the Beholder: What Eye-Tracking Reveals About Analogy-Making Strategies in Children and Adults , 2011, CogSci.

[18]  Tilbe Göksun,et al.  The development of organized visual search. , 2013, Acta psychologica.

[19]  Per B Sederberg,et al.  A novel method for analyzing sequential eye movements reveals strategic influence on Raven's Advanced Progressive Matrices. , 2011, Journal of vision.

[20]  K. Holyoak,et al.  Children's development of analogical reasoning: insights from scene analogy problems. , 2006, Journal of experimental child psychology.

[21]  D. S. Wooding,et al.  Fixation sequences made during visual examination of briefly presented 2D images. , 1997, Spatial vision.

[22]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[23]  Vladimir I. Levenshtein,et al.  Binary codes capable of correcting deletions, insertions, and reversals , 1965 .

[24]  Rupert G. Miller.  The jackknife-a review , 1974 .

[25]  Heinz Hügli,et al.  Empirical Validation of the Saliency-based Model of Visual Attention , 2003 .

[26]  陳祉傑.  Children’s development of analogical reasoning , 2006 .

[27]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[28]  Stephanie Moser,et al.  Insight into analogies: Evidence from eye movements , 2007 .

[29]  Dedre Gentner,et al.  The Place of Analogy in Cognition , 2002 .

[30]  Kurt Hornik,et al.  Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.

[31]  Michael J. Fischer,et al.  The String-to-String Correction Problem , 1974, JACM.

[32]  Jean-Pierre Thibaut,et al.  The development of analogy making in children: cognitive load and executive functions. , 2010, Journal of experimental child psychology.

[33]  U. Goswami.  Analogical reasoning in children , 1993 .

[34]  D. Gentner.  Structure‐Mapping: A Theoretical Framework for Analogy* , 1983 .

[35]  W. Torgerson.  Multidimensional scaling: I. Theory and method , 1952 .

[36]  P. Lachenbruch.  An almost unbiased method of obtaining confidence intervals for the probability of misclassification in discriminant analysis. , 1967, Biometrics.

[37]  Robert M. French,et al.  Using eye-tracking to predict children's success or failure on analogy tasks , 2014, CogSci.

[38]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[39]  Ann L. Brown,et al.  Higher-order structure and relational reasoning: Contrasting analogical and thematic relations , 1990, Cognition.

[40]  Taylor R. Hayes.  A Novel Method for Analyzing Sequential Eye Movements Reveals the Relationship Between Learning and Strategy on Raven's Advanced Progressive Matrices , 2011 .

[41]  Alan C. Bovik,et al.  GAFFE: A Gaze-Attentive Fixation Finding Engine , 2008, IEEE Transactions on Image Processing.

[42]  Eileen Kowler,et al.  The role of saccades in the perception of texture patterns , 1992, Vision Research.

[43]  Robert M. French,et al.  Analogical reasoning, control and executive functions: A developmental investigation with eye-tracking , 2016 .

[44]  C. E. Bethell-Fox,et al.  Adaptive reasoning: Componential and eye movement analysis of geometric analogy performance ☆ , 1984 .

[45]  Michael C. Hout,et al.  Multidimensional Scaling , 2003, Encyclopedic Dictionary of Archaeology.

[46]  D. Gentner,et al.  Language and the career of similarity. , 1991 .

[47]  Jean-Pierre Thibaut,et al.  Cognitive load and semantic analogies: Searching semantic space , 2010, Psychonomic bulletin & review.