<p> How mental representations are constructed and how they evolve are central problems for cognitive science. Representation decisions help determine what computations are hard or easy. Structured, relational representations are a hallmark of human cognition. Developmental studies show that children do not perform as well as adults in tasks that require noticing relational similarity. What drives this development? Gentner and her colleagues have argued that comparison and language are two forces driving this change. This thesis explores these ideas further by presenting a computational model of forced choice tasks to illuminate the roles of comparison and language in driving representational change.</p><p> The model simulates the following roles of comparison. First, comparison can be used to make selections in forced-choice tasks. Second, comparisons from recent positive experiences are assimilated as <i>interim generalizations </i> which are retrieved for subsequent tasks and influence encoding by highlighting relevant structure. Third, comparisons suggest opportunities for re-representation. Finally, verifying candidate inferences resulting from a comparison provides a way to augment encodings with background knowledge, thus enriching representations. The model simulates the role of language in facilitating the creation and enrichment of generalizations as follows. When two objects are given the same label, the model compares them. This leads to an interim generalization associated with that label, enriched with commonalities from background knowledge.</p><p> We tested these hypotheses by extending the Companion cognitive architecture and simulating three developmental studies. To reduce tailorability, the visual stimuli were provided as sketches and the objects were labeled using simplified English. The model was evaluated by comparing its behavior and learning trajectory to that of children in the developmental studies. The performance of the model in the simulations provide evidence for the claims of this thesis.</p>

<p> To date, research on direct attention training (DAT) has focused primarily on adult populations with considerable gaps regarding DAT for children with attention-deficit/hyperactivity disorder (ADHD). The purpose of this study was to examine the effects of a DAT program, namely the Pay Attention! program, with a school-aged student with ADHD. The principle investigator hypothesized that this program would improve attention abilities on trained attention tasks, psychometric measures of attention, functional measures of attention, as well as improve reading comprehension abilities. A pre- and post-test single case study design was used to compare performance on impairment and participation-levels of attention, as well as measures of reading comprehension. Post-test results demonstrated improvement in accuracy or completion time on all impairment-level attention testing with some improvements noted on reading comprehension and measures at the participation level. These results contribute to existing research on DAT for children, as well as suggest that some generalization to participation-level activities and reading comprehension may be achieved.</p>

This thesis provides a conceptual and empirical analysis of implicit concept formation. A review of concept formation studies highlights the need for improving existing methodology in establish- ing the claim for implicit concept formation. Eight experiments are reported that address this aim. A review of theoretical issues highlights the need for computational modelling to elucidate the nature of implicit learning. Two chapters address the feasibility of different exemplar and Connectionist models in accounting for how subjects perform on tasks typically employed in the implicit learn- ing literature. The first five experiments use a concept formation task that involves classifying "computer people" as belonging to a particular town or income category. A number of manipulations are made of the underlying rule to be learned and of the cover task given subjects. In all cases, the knowledge underlying classification performance can be elicited both by free recall and by forced choice tasks. The final three experiments employ Reber's (e.g., 1989) grammar learning paradigm. More rigorous methods for eliciting the knowledge underlying classification performance are employed than have been used previously by Reber. The knowledge underlying clas- sification performance is not elicited by free recall, but is elicited by a forced-choice measure. The robustness of the learning in this paradigm is investigated by using a secondary task methodol- ogy. Concurrent random number generation interferes with all knowledge measures. A number of parameter-free Connectionist and exemplar models of artificial grammar learning are tested against the experimental data. The importance of different assumptions regarding the coding of features and the learning rule used is investigated by determin- ing the performance of the model with and without each assumption. Only one class of Connectionist model passes all the tests. Fur- ther, this class of model can simulate subject performance in a different task domain. The relevance of these empirical and theoretical results for understanding implicit learning is discussed, and suggestions are made for future research.

<p> There is an enormous educational disparity among schools in the United States. One reason for this disparity is the teachers employed by well-performing schools and low-performing schools. This study reports the factors and financial tradeoffs that would influence well-qualified teachers to work in low-performing schools. Teacher employment is viewed as a set of discrete choices made over time and based on a finite group of factors. This study uses a multinomial discrete choice experiment to determine how the school-related factors (alternative-specific variables) and teacher-related factors (case-specific variables) influence the willingness of experienced teachers in well-performing schools to transfer to low-performing schools. A discrete choice experiment (DCE) using an optimal, fractional factorial, experimental design (D-efficiency = 96.5 and A-efficiency = 92.9) with an adequate sample (<i>n</i> =111) was employed. The data are analyzed using alternative-specific conditional logistic regression, nested logistic regression, and latent class conditional logistic regression. The latent class conditional logistic regression with 3-classes was deemed the best fit and its results were interpreted. The first class has high job satisfaction and generally stays in their current school. The second class is most likely female and does not value salary, but rather better student behavior and school climate. The third and largest class has similar values with Latent Class 2, but fiscal incentives could impact their decision. This study shows that teachers are willing to work in low-performing schools, but school- and teacher-related factors impact the overall attractiveness to well-qualified teachers.</p>

The growing prevalence of computers, tablets, and educational apps in academic settings has prompted many researchers to investigate the potential benefits and drawbacks of this technology. One of the ways that this technology can influence learning in the classroom is through note-taking. Note-taking in the classroom is intended to facilitate learning through deeper processing/encoding of information and providing external storage. The incorporation of technology in the classroom has offered students the ability to take notes beyond the use of traditional pen and paper (e.g., via laptop, tablet, etc.). This change in the classroom has led researchers to question both the benefits and drawbacks of note-taking with technology versus with traditional methods, such as pen and paper. This dissertation will investigate whether note-taking using a computer may impair learning relative to taking notes in a handwritten fashion across three experiments. Experiments 1 and 2 asked students to take notes on 20 arithmetic facts. These facts were either presented in the same format across the study and assessment phases (Experiment 1) or in a different format (Experiment 2). Learning was measured at two points in time (i.e., an immediate and delayed post-test, one week later). The results of these Experiments 1 and 2 indicate that taking notes with pen and paper and typing both led to a comparable performance for factual information when controlling for two factors known to impact learning (i.e., word count and verbatim note-taking). Given these results, the goal of the prospective experiment (Experiment 3) is to contrast these findings using conceptual and factual questions after participants have taken notes on a series of Ted Talks about mathematical information. Furthermore, this experiment will require participants to complete a post-assessment questionnaire to evaluate the note-taking strategies that they used. / A Dissertation submitted to the Department of Psychology in partial fulfillment of the Doctor of Philosophy. / Spring Semester 2017. / April 10, 2017. / Implicit, Learning, Note-taking, Technology / Includes bibliographical references. / Gretchen L. Sunderman, University Representative; Wally R. Boot, Committee Member; Colleen M. Kelley, Committee Member; Arielle Borovsky, Committee Member.

This research investigated freshman college students' motivation beliefs and motivation regulation strategies (to manage their effort and persistence) in the context of an authentic college-level academic task such as studying for an exam. The unique elements of this research included the following: (a) studying exclusively freshmen students, (b) capturing their reported use of strategies in the context of a real academic task rather than hypothetical scenarios, (c) identifying whether students used different strategies while studying for their second test than their first test, and (d) identifying the most difficult motivational problems reported by students. The freshmen students' reported motivation beliefs (i.e., self-efficacy, task value, test anxiety), use of self-regulation (i.e., metacognitive) and motivation regulation strategies (i.e., Regulation of Performance, Environmental Structuring, Self-consequating, Regulation of Mastery Goals, Regulation of Value, Regulation of Situational Interest), and their end-of-course grades were gathered. This research was a Quantitative-Qualitative mixed-method (Creswell, 2003, 2008) study design with a time-series cross-sectional sampling of survey data. That is, I sampled multiple freshmen students (N=189) at two points in time to examine students' reported use of motivation regulation strategies (e.g., which ones were used, to what extent did they change their strategies). The quantitative data was analyzed by conducting descriptive, correlational, repeated measures t-tests, and hierarchical regression analyses. The purpose of the qualitative portion of the study design was to identify (a) additional strategies that students used, (b) their perceptions of motivational challenges with academic tasks, and (c) explanations of any changes made to exam studying behaviors. Overall, the goals of this mixed methodology study (quantitative and qualitative) were to address gaps in research findings related to (a) surveying more diverse populations; (b) measuring students' strategy use with an academic task, such as studying for an exam, rather than a hypothetical scenario; (c) replicating findings regarding relationships among a student's motivation beliefs (e.g., self-efficacy) and their use of self-regulated learning and motivation strategies; (d) adding findings regarding students' perceptions of the most difficult challenges to their studying; (e) adding findings about students changing strategy use between Time 1 and Time 2; and (f) replicating findings in relationships among motivation beliefs, self-regulated learning and motivation strategy use, and course grades. The results of this study added diversity of populations (freshmen only) and findings regarding strategy use while studying for an exam to the motivation regulation (MR) research. Freshmen students reported using motivation regulating strategies (MRSs) descriptively more frequently while studying for an exam than reported in hypothetical scenarios (Wolters & Benzon, 2013). Positive, strong and significant correlational relationships existed among students' self-efficacy beliefs, self-regulated learning (metacognitive) and MR strategy use; whereas, a weak yet significant, positive correlational relationships were found between students' reported test anxiety and their use of the following strategies: (a) self-regulated learning (metacognitive), (b) self-consequating, and (c) regulation of mastery goals. Students (72%) reported distractions in environment, time to study, or boredom as the most difficult challenges to overcome while studying. The repeated measures results indicated that students reported using strategies to regulate mastery goals less frequently from Time 1 to Time 2. The reasons given by students for changes in how they studied for Test 2 emphasized pursuing better grades for the test or course and improving their retention of the learned information. Lastly, the hierarchical linear regression analysis indicated that students' self-efficacy and use of regulating strategies for sustaining one's value of the content and mastery-oriented learning while studying were positive predictors of course grades. At least three implications for practice are appropriate for those who support student success. First, help students to identify their "performance" early in their freshman semester and year. Because a portion of the freshmen surveyed perceived grades on the first test as the primary stimulus for change in studying as well as sustaining motivation while studying, it would be effective for students to identify indicators of performance sooner rather than later. A second implication for practice is to help students to identify productive changes that will accomplish their desired test or course outcome. A third implication for practice is that increasing a students' belief in their ability to learn the content may be more likely to positively influence students' grade outcomes. An implication for research is to identify beliefs and study behaviors among more diverse student populations. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2018. / October 30, 2018. / Freshmen Study Behaviors, Metacognitive strategies, Motivational Beliefs, Motivation Research, Self-efficacy, Self-Regulated Learning / Includes bibliographical references. / Alysia Roehrig, Professor Directing Dissertation; Robert Schwartz, University Representative; Jeannine Turner, Committee Member; Yanyun Yang, Committee Member.

Thesis advisor: Elizabeth Kensinger / Thesis advisor: Katherine Mickley Steinmetz / Distractibility and impulsivity have long been thought of as two separate psychological processes; however, there is currently evidence that suggests otherwise. The aim of this study was to gain a better understanding on the behavioral level of the interaction between these two traits. I proposed a model in which some individuals have a higher than average threshold for activation of the top-down cognitive control resources that are important for directing and maintaining attention as well as for regulating impulsive behaviors. To test the strength of this model I used an experimental paradigm that combined two different types of tasks—a spatial working memory task and a delay discounting of a primary reward (juice) task. Participants were administered the Conners’ Adult ADHD Rating Scale in order to be classified in terms of their trait distractibility and trait impulsivity subscale scores. The results suggest that there is indeed an association between the traits of distractibility and impulsivity, and that they may be linked by a common mechanism involving a variable threshold of activation of top-down control resources to regulate these behaviors. / Thesis (BS) — Boston College, 2011. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: College Honors Program. / Discipline: Psychology.

<p>Prepositions are hard to learn ? even for the advanced language student (Celce- Murcia & Larson-Freeman, 1999). One reason these lexical items are particularly troublesome is that their meanings vary substantially across languages (Feist, 2008a; Levinson & Meira, 2003). In addition, prepositional meanings are complex, with their uses influenced by geometric, functional, and physical aspects of the scenes they describe (Coventry & Garrod, 2004; Feist 2000, 2008a; Vandeloise, 1991). In light of this complexity, the purpose of this study was to figure out what advanced ESL students understand about English prepositional meanings. In my first experiment, advanced ESL learners from ten different language backgrounds studying at the University of Louisiana at Lafayette were asked to look at images and choose the best fit preposition to describe each spatial scene (created by Feist, 2000). Students were given a choice of in or on to best describe spatial scenes which varied along geometric, functional, and physical parameters. Their responses were then analyzed to determine which factors influenced ESL learners? prepositional meanings. In addition, the pattern of influences on ESL learners? use of English prepositions was compared to the influence previously observed in native English speakers (Feist , 2000) to determine how the ESL students? prepositional meanings compared to those of native English speakers. This may help elucidate whether even advanced nonnative speakers are missing subtle influences in prepositional semantics or if they possess a complex understanding that is similar to native speakers. My second study, which was formed out of the discussion of the first, explored one potential strategy used by advanced nonnative speakers in prepositional selection. How do students choose one preposition over another? Understanding what students know about in and on can help researchers develop pedagogical practices which guide learners on a path toward more native-like understanding of prepositional semantics.

This study investigates the interaction of referential communication and the structure of perceptual features on the joint processes of inventing a referential lexicon for novel objects and discovering the functional significance of those objects during an indirect category learning activity. During the learning task, participants worked either individually or as cooperative dyads to learn four combinations of orthogonal functional features—nutritive vs. not nutritive and destructive vs. not destructive—that defined four categories of fictional extra-terrestrial creatures. These categories were not specifically identified or labeled; rather, participants had to infer them indirectly as they predicted the functions. Also, these functionally defined categories exhibited a complex perceptual structure: a unidimensional (simple) rule predicted one function, while a family resemblance (complex) sub-structure predicted the other function. The function-learning task yielded function prediction data. In addition, each learner worked individually to sort the creatures (pre- and post-function learning) and to predict their functions in an individual function prediction posttest that also yielded selective attention data. Together, the prediction data, sort data, and selective attention data supported three a priori hypotheses. Referential communication generates conceptual homogeneity (H3) and enhances indirect category learning (H1), though simple rules are learned earlier and better than complex relationships (H2). In explaining the learning advantages observed among dyadic learners, I argue that referential communication may highlight attention to relationships between features (perceptual and functional) and actions as well as render such relationships more memorable. Moreover, communication may foster greater motivation among collaborators and may allow them to take advantage of the differing expectations and heuristics each collaborator brings to the task. In explaining the simplicity advantages observed among dyadic learners, I argue that referential communication may provide explicit "rules" for otherwise implicit (and perhaps more difficult) judgements. Dyads appear to have established reference to simple rules earlier than they established reference to complex rules; thus, they could explicitly (and perhaps more easily) learn the simple rule earlier than the complex rule. Finally, in explaining the conceptual homogeneity between and within dyads, I consider whether communication pushes "public" conceptualizations and publicly-formed "private" conceptualizations towards a limited range of widely shareable conceptual structures.

Can action support cognition? Can direct touch support performance? Embodied interaction involving digital devices is based on the theory of grounded cognition. Embodied interaction with gestural interfaces involves more of our senses than traditional (mouse-based) interfaces, and in particular includes direct touch and physical movement, which are believed to help retain the knowledge that is being acquired. There is growing evidence that spontaneous gestures affect thought and possibly learning. The author was interested to explore whether designed gestures (for gestural interfaces) affect thought. It was hypothesized that the use of congruent gestures helps construct better mental representations and mental operations to solve problems (Gestural Conceptual Mapping). There is also evidence that physical manipulation of objects can benefit cognition and learning; it was therefore also hypothesized that manipulating objects through direct touch on the screen supports performance. These hypotheses were addressed by observing children's performance in arithmetic and numerical estimation. Arithmetic is a discrete task, and should be supported by discrete rather than continuous actions. Estimation is a continuous task, and should be supported by continuous rather than discrete actions. Children used either a gestural interface (multi-touch, e. g., iPad) or a traditional mouse interface. The actions either mapped congruently to the cognition (continuous action for estimation and discrete action for arithmetic), or not. If action supports cognition, children who use continuous actions for estimation or discrete actions for addition should perform better than children for whom the action-cognition mapping is less congruent. In addition, if manipulating the objects by touching them directly on the screen could yield a better performance, children who use a touch interface should perform better than children who use a mouse interface. The results confirmed the predictions.