Psychology has changed a great deal during the more than 50 years I have been actively involved with it. In this essay, I try to trace these changes as I experienced them - a minor footnote to the history of psychology. This in no sense is a real history of psychology in the last 50 years - my experiences deal with only a small section of what is called psychology, and I don't even try to be fair and balanced. This is history as it happened to me. Some brief biographical data are given in an appendix, which are necessary to understand the twists and turns of my involvement with psychology.

Interest in "learning" has fluctuated more widely in the past decades than women's fashions. If my memory serves me right, I did not hear a single lecture or discussion on learning as a graduate student in Vienna in the 1950s. When I came to America, however, learning was almost the sole topic where I went to graduate school, and I quickly succumbed to the fascination of habit strength and drive–reward interactions. However, I had hardly graduated when all that became passé, and learning, together with my beloved Markov models, disappeared into history's storage closet. The students at Colorado during the past 10 years have heard about as much about "learning" as I had years ago at Vienna. What has happened? Has America caught up with Europe? Or have we relapsed into the dark ages?

The literature of complex problem solving and system control has focused on how to improve the adaptation of operators to new, unpredictable circumstances. The present work reviews the main methodologies and assumptions that are currently being used in complex, dynamic task to answer questions regarding the adaptability problem, i.e. the work on DuressII (Vicente and Collaborators) and on Firechief (Cañas and collaborators). Some methodological problems for Cañas et al. analysis assumptions that could have important consequences in the results obtained are discussed. This study proposes Latent Semantic Analysis (LSA) as an alternative that remedies some of the flaws and adds some interesting new possibilities of analysis, such as coherence measures to assess performance changes in a similar vein as the Within-trial Trajectory Deviation (WTD) used in continuous systems such as DuressII. The study uses an LSA corpus created from the experimental data generated by past experiments in Firechief on adaptation to unpredictable task changes to replicate and extend the results previously obtained. The new LSA approach and results obtained are discussed. The fact that results from both microworlds could be explained by LSA with no modifications in its basic assumptions promises a future common theory and method of complex problem solving.

A good qualitative account of word similarities may be obtained by adjusting the cosine between word vectors from latent semantic analysis for vector lengths in a manner analogous to the quantum geometric model of similarity.

In this essay, I explore how cognitive science could illuminate the concept of beauty. Two results from the extensive literature on aesthetics guide my discussion. As the term beauty is overextended in general usage, I choose as my starting point the notion of perfect form. Aesthetic theorists are in reasonable agreement about the criteria for perfect form. What do these criteria imply for mental representations that are experienced as beautiful? Complexity theory can be used to specify constraints on mental representations abstractly formulated as vectors in a high-dimensional space. A central feature of the proposed model is that perfect form depends both on features of the objects or events perceived and on the nature of the encoding strategies or model of the observer. A simple example illustrates the proposed calculations. A number of interesting implications that arise as a consequence of reformulating beauty in this way are noted.

LSA is a machine learning method that constructs a map of meaning that permits one to calculate the semantic similarity between words and texts. We describe an educational application of LSA that provides immediate, individualized content feedback to middle school students writing summaries.

We argue that word meanings are not stored in a mental lexicon but are generated in the context of working memory from long-term memory traces that record our experience with words. Current statistical models of semantics, such as latent semantic analysis and the Topic model, describe what is stored in long-term memory. The CI-2 model describes how this information is used to construct sentence meanings. This model is a dual-memory model, in that it distinguishes between a gist level and an explicit level. It also incorporates syntactic information about how words are used, derived from dependency grammar. The construction of meaning is conceptualized as feature sampling from the explicit memory traces, with the constraint that the sampling must be contextually relevant both semantically and syntactically. Semantic relevance is achieved by sampling topically relevant features; local syntactic constraints as expressed by dependency relations ensure syntactic relevance.

An fMRI Study of Strategic Reading Comprehension Jarrod Moss (jarrod.moss@msstate.edu) Department of Psychology, Mississippi State University, Mississippi State, MS 39762 USA Christian D. Schunn (schunn@pitt.edu) Walter Schneider (wws@pitt.edu) Learning Research and Development Center, University of Pittsburgh Pittsburgh, PA 15260 USA Danielle S. McNamara (dsmcnamara1@gmail.com) Department of Psychology, University of Memphis Memphis, TN 38152 USA Kurt VanLehn (kurt.vanlehn@asu.edu) School of Computing, Informatics and Decision Systems Engineering, Arizona State University Tempe, AZ 85287 USA Abstract While there have been neuroimaging studies of text comprehension, little is known about the brain mechanisms underlying strategic learning from text. It was hypothesized that reading strategies would involve areas of the brain that are normally involved in reading comprehension along with areas that are involved in strategic control processes because the readers are intentionally using a complex learning strategy. The present study was designed to answer the question of what brain areas are active during performance of complex reading strategies. Activation was found in both executive control and comprehension areas, and furthermore, learning gains were found to be associated with activation in the anterior prefrontal cortex (aPFC). Keywords: Reading Strategies; fl\/1R1; Cognitive Control Introduction The importance and difficulty of comprehending expository text is obvious to anyone who has tried to learn about a new field of science by reading a textbook. The complexity of text comprehension and learning processes results in large individual differences in the strategies that students engage in to understand texts and what students extract from texts (e.g., Chi, Bassok, Lewis, Reimann, & Glaser, 1989; McNamara, 2004). While there have been neuroimaging studies of text comprehension, these studies have not examined the differences in brain activity associated with different reading strategies. Thus, understanding the neural correlates of different types of strategic reading comprehension should help us to better understand both the brain mechanisms underlying comprehension as well as the way in which these strategies affect comprehension. There have been a number of neuroimaging studies that have investigated the brain areas involved in text comprehension (e.g., Xu, Kemeny, Park, Frattali, & Braun, 2005; Yarkoni, Speer, & Zacks, 2008). These studies show that a network of neural regions are used in text comprehension including inferior frontal and temporal areas associated with language comprehension and production as well as areas distributed throughout the temporal, parietal, and frontal cortices that appear to be associated with building coherent representations of texts. When contrasting sentence—level processing with narrative—level processing, Xu et al. (2005) identified a network of areas including the hippocampus, caudate, thalamus, prefrontal cortex, precuneus, posterior cingulate, and angular gyrus. Hippocampal areas are likely associated with memory formation and retrieval. They hypothesized that the caudate, thalamus, and prefrontal cortex were involved in the sequencing of higher—level processes associated with reading comprehension. Medial prefrontal cortex, precuneus, and posterior cingulate were hypothesized to be involved with linking text content with global themes and other information in memory, and the angular gyrus was hypothesized to be involved in the mental scanning of spatial representations built from the text. A number of the areas involved in discourse comprehension are also considered part of the brain's default network that is active when people are not engaged in an external task (Buckner, Andrews-Hanna, & Schacter, 2008). Some studies of discourse processing have noted this overlap between the default network and areas active during comprehension (e.g., Xu et al., 2005; Yarkoni, Speer, Balota, McAvoy, & Zacks, 2008). The default network has been associated with self—referential processing and the generation of coherent mental representations (Hassabis & Maguire, 2007). If the reader's goal is to form a coherent representation of the text, then these processes would be involved in all forms of comprehension including strategic reading comprehension. Reading comprehension strategies improve readers’ comprehension of text. Some readers use strategies naturally, and others benefit from being provided with strategy instruction. Self-explanation is one reading strategy 1319

This article explores the role of self-regulation in strategies that readers use to decide the order in which to read the different sections of a hypertext. This study explored 3 main strategies for link selection based on (a) link screen position, (b) link interest, and (c) the semantic relation of a link with the section just read. This study followed Winne's (1995, 2001) model of self-regulated learning to try to explain why some readers select hyperlinks based on strategies that lead to lower levels of comprehension (i.e., screen position and personal interest). Results from 2 studies revealed that readers with low prior knowledge base their decisions on what to read next on a default screen position or on link interest more often if they are instructed to set a low learning goal, if they regularly use shallow learning strategies (e.g., memorizing), or if they are poor at calibrating their comprehension. Readers' link selection strategies mediated the effect of the self-regulation variables studied on comprehension.