MA, Kent State University, 2020, College of Arts and Sciences / Department of Psychological Sciences

Previous research has found that homophones cause processing difficulties during word recognition (Folk, 1999; Perfetti & Hart, 2001; Pexman, Lupker, & Jared, 2001; Unsworth & Pexman, 2003). The present study evaluated if lexical expertise, the ability to efficiently recognize words during reading, influenced participants' ability to learn novel homophones while reading. In two experiments novel homophones (e.g. `brale') and novel nonhomophones (e.g. `gloobs') were embedded in sentence frames containing context that indicated the meaning of the novel word. In Experiment 1, novel homophones had low-frequency real-world mates, and in Experiment 2, novel homophones had high-frequency real-world mates. After reading the sentences, participants' word learning was tested using surprise meaning recognition and spelling recognition tests. Lexical expertise was measured through tests of spelling and vocabulary knowledge. Although eye movement behavior during reading did not differ between novel homophones and nonhomophones, participants had more difficulty learning the spellings of the novel homophones. Regardless of the novel homophone's real-world mate's frequency, learning rates for the novel homophone spellings were at chance levels in Experiments 1 and 2. In contrast, participants only had difficulty learning the meaning of a novel homophone when the novel homophone had a low-frequency mate. Higher levels of lexical expertise were related to higher learning rates of novel homophone spellings, but only when the novel homophones had a high-frequency mate. These findings indicate that phonology is activated when novel words are encountered and can interfere with the acquisition of new spellings associated with the existing phonological representation regardless of homophone mate frequency.

Committee: Jocelyn Folk Ph.D. (Advisor); John Dunlosky Ph.D. (Committee Member); William Merriman Ph.D. (Committee Member); Jeffrey Ciesla Ph.D. (Committee Member) Subjects: Psychology

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2007, Communication Disorders/Speech-Language Pathology

Rapid learning of novel vocabulary is crucial to overall success in language acquisition. While the exact mechanisms underlying the acquisition of the lexicon remain under investigation, it is well known that children are able to form rapid initial associations between novel words and their referents during everyday experiences. This ability is referred to as incidental word learning, a process by which a learner makes a sparse initial representation of a word in lexical memory, following only a brief exposure. The cognitive abilities needed to succeed at this task were investigated, specifically by examining the role of working memory and phonological sensitivity in novel word learning by 4-year-olds who were typically developing. It evaluated two competing models, the phonological loop model proposed by Baddeley and colleagues (Baddeley & Hitch, 1974), and the lexical restructuring model of Metsala (Metsala & Walley, 1998; Metsala, 1999). Forty 4 year olds were administered a test of nonword repetition (to investigate phonological working memory), rhyming and phoneme alliteration tasks (to investigate phonological sensitivity), and an incidental word learning task, via a computer-based presentation of a cartoon story. A multiple regression analysis revealed that nonword repetition scores did not contribute significantly to incidental word learning. Phonological sensitivity scores were significant predictors of incidental word learning. These findings provide support for a model of lexical acquisition in which phonological knowledge plays an important role.

Committee: Lynne Hewitt (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2005, Physical Activity and Educational Services

Outcomes for secondary students whose writing skills are less than proficient are discouraging. Students with mild disabilities especially face significant challenges in their writing education, yet few interventions have been implemented (Englert, Raphael, Anderson, Anthony, & Stevens, 1991). Typically, these students write far less than their non-disabled counterparts and are less able to produce coherent, quality writing (Vallecross & Garriss, 1990). Writing output is often so sparse that it is difficult for teachers to identify deficits for remediation. Consequences for adults with poor writing skills include underemployment (College Board, 2004), restricted access to higher education, and extra time and expense in postsecondary education (Livingston & Wirt, 2004). Research indicates that with strategic support, students with disabilities can increase both the quantity and quality of their writing. Various supports have been explored in the research, including self-regulation (De La Paz, 1999), goal-setting (Page-Voth & Graham, 1999), and revision strategies (Wong, Butler, Ficzere, & Kuperis, 1996, 1997). Strategies are most likely to be used if they can be easily implemented by the teacher to more than one student at a time. This study proposed the use of an extended prompt containing supports for writing a 5-paragraph essay as a way to increase the length and quality of student writing. Eight African American high school students participated. Each week during the 12-week study, students completed a first draft essay. During the baseline condition, students wrote in response to a typical 1-page prompt that provided a topic, background, and brainstorming information. During the intervention condition, students wrote with an extended prompt, a 7-page packet containing the typical prompt, prewriting support, and guidance for writing an introduction, conclusion, and three body paragraphs. Students wrote a final essay using only the typical prompt. The results demo (open full item for complete abstract)

Committee: Ralph Gardner (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2024, Educational Studies

The purpose of this study was to examine the effects of a word box intervention with a self-monitoring component on the acquisition, maintenance, and generalization of real words read correctly for students identified with specific learning disabilities (SLD). A single-subject multiple probe experimental design across participants was used with four second-fourth grade students identified with SLD in a Midwestern urban school district. Students' acquisition and maintenance of real words read correctly was measured by the number of real words targeted in intervention read correctly and the number of correct letter-sound correspondences made in those words. Generalization measures involved reading untrained words correctly, correct letter-sound correspondences in those untrained words, and performance reading real words targeted in intervention in the context of decodable text. Maintenance of generalization effects were also examined by measuring untrained real words read correctly and correct letter-sound correspondences in those untrained words after intervention had ended. Visual analysis, percentage of nonoverlapping data, and TAU-U calculations were used to measure intervention effects. Results demonstrate that word box intervention with a self-monitoring component significantly improved the acquisition, maintenance, and generalization of real words read correctly for the four students identified with SLD. This study adds to previous research on explicit, systematic phonics instruction for students identified with SLD. Limitations of the current study, directions for future research, and implications for practitioners are discussed.

Committee: Laurice Joseph (Advisor); Sheila Alber-Morgan (Committee Member); Moira Konrad (Committee Member) Subjects: Education; Psychology

PHD, Kent State University, 2022, College of Arts and Sciences / Department of Psychological Sciences

Research indicates that readers break down complex words into their smallest, meaning-based units (morphemes) when spelling (e.g., Senechal, 2000). However, it remains unclear how morphemes are formed and whether newly formed morphological knowledge (i.e., knowledge of morphemes) is strong enough to support word learning. The current research proposes to address this gap in the literature by investigating how adult readers use recently acquired morphological knowledge when learning compound words. The first morpheme in each of the compound words was a novel non-word. Participants learned the meanings of the novel morphemes (e.g., breese = “fish”), and after a one-day delay, participants were re-exposed to those morphemes in novel compound words that contained the novel morpheme that had been learned the previous day (e.g., breesebin). The compound words were presented in sentence context that taught participants meanings to the compound words that either (1) were consistent with the meaning of the novel morpheme contained in the compound word (e.g., breesebin = “fish storage”); (2) were inconsistent with the meaning of the novel morpheme contained in the compound word (e.g., breesebin = “alleyway”); or (3) contained no contextual cues from which the meaning of the compound word could be derived. The current research found that participants were more successful at learning the novel compound words when they were able to use morphological knowledge from the novel word learned on day one to support their learning on day two. This was true for both learning the spellings of words and learning the meanings of words, despite participants receiving no instructions to consider the words' morphological knowledge. These findings support the body of literature that stress the importance of emphasizing morphology during language instruction.

Committee: Jocelyn Folk (Advisor); William Merriman (Committee Member); Mark Bracher (Committee Member); Jennifer Roche (Committee Member); Jeffrey Ciesla (Committee Member) Subjects: Cognitive Psychology; Psychology

PHD, Kent State University, 2022, College of Arts and Sciences / Department of Psychological Sciences

Even one-year-olds show the so-called disambiguation effect, which is a tendency to select a novel object rather than a familiar object as the referent of a novel label. The strength of this effect increases over the preschool years. This age trend may be due in part to advances in metacognition. The accuracy of preschoolers' lexical knowledge judgment mediates the association between age and strength of the disambiguation effect. Also, their judgments about object label knowledge accounted for why most 4-year-olds, but only a few 3-year-olds could predict the solution to a new disambiguation problem before hearing the novel label (Henning & Merriman, 2019). Study 1 tested whether more preschoolers could make this kind of prediction if they were told that the labels were ones “you have never heard before.” Results supported this hypothesis, but only for the younger children. Also, children's tendency to make these predictions was positively associated with their ability to give accurate reports of whether various words or pseudowords had known meanings. Study 2, which used an online rather than face-to-face testing procedure, demonstrated that 3-year-olds only learned how to solve the original prediction problem if they received direct rather than indirect feedback. When they receive helpful cues, most 3-year-olds can solve a disambiguation problem before hearing the novel label. Thus, most 3-year-olds can form metacognitive representations of the elements of the disambiguation problem and use these to draw inferences about the reference of a label.

Committee: William Merriman (Advisor); Maria Zaragoza (Committee Member); Bradley Morris (Committee Member); Jeffrey Ciesla (Committee Member) Subjects: Cognitive Psychology; Developmental Psychology; Psychology

PHD, Kent State University, 2019, College of Arts and Sciences / Department of Psychological Sciences

When shown a familiar and a novel object and asked to pick the referent of a novel label, even one-year-olds tend to favor the novel object (Halberda, 2003; Mervis & Bertrand, 1994). However, this so-called disambiguation effect becomes stronger as children develop through preschool age (Lewis & Frank, 2015). Advances in metacognition may play a role in this developmental trend. Preschoolers' awareness of their own lexical knowledge is associated with the strength of the disambiguation effect (Merriman & Schuster, 1991; Merriman & Bowman, 1989; Wall, Merriman, & Scofield, 2015). It is also associated with whether children can solve purely metacognitive forms of the disambiguation problem (Slocum & Merriman, 2018; Henning & Merriman, 2019). The current experiments tested the hypothesis that as the number of choices in a disambiguation problem increases, the frequency of correct response declines more sharply for children who lack awareness of lexical knowledge than for children who possessed it. The results of the first two experiments supported the main hypothesis. Two experiments also showed that awareness of lexical knowledge was associated with a more gradual increase in latency of correct solutions as number of choices increased. In Experiment 3, children's eye movements were recorded as they attempted to solve 3-, 4-, 5-, and 6-choice problems. Various aspects of children's eye movements were analyzed, including the number of familiar object foils checked, the number of revisits to the target, and the proportion of looking time spent on the target object. The current experiments advance our insight into why the “awareness-of-knowledge advantage” in solving disambiguation problems tends to increase as number of choices increases.

Committee: William Merriman PhD (Advisor); Clarissa Thompson PhD (Committee Member); Jeff Ciesla PhD (Committee Member); Bradley Morris PhD (Committee Member); Sarah Rilling PhD (Committee Member) Subjects: Cognitive Psychology; Developmental Psychology; Psychology

Doctor of Philosophy, The Ohio State University, 2019, Computer Science and Engineering

Machine learning is becoming an integral part of everyday life. Therefore, development of a high performance genre of machine learning algorithms is becoming increasingly significant from the perspectives of performance, efficiency, and optimization. The current solution is to use machine learning frameworks such as TensorFlow, PyTorch and CNTK, which enable us to utilize specialized architectures such as multi-core CPUs, GPUs, TPUs and FPGAs. However, many machine learning frameworks facilitate high productivity, but are not designed for high performance. There is a significant gap in the performance achievable by these frameworks and the peak compute capability of the current architectures. In order for machine learning algorithms to be accelerated for large-scale data, it is essential to develop architecture-aware machine learning algorithms. Since many machine learning algorithms are very computationally demanding, parallelization has garnered considerable interest. In order to achieve high performance, data locality optimization is extremely critical, since the cost of data movement from memory is significantly higher than the cost of performing arithmetic/logic operations on current processors. However, the design and implementation of new algorithms in machine learning has been largely driven by a focus on computational complexity. In this dissertation, the parallelization of three extensively used machine learning algorithms, Latent Dirichlet Allocation (LDA), Non-negative Matrix Factorization (NMF), and Word2Vec, is addressed by a focus on minimizing the data movement overhead through the memory hierarchy, using techniques such as 2D-tiling and rearrangement of data computation. While developing each parallel algorithm, a systematic analysis of data access patterns and data movements of the algorithm is performed and suitable algorithmic adaptations and parallelization strategies are developed for both multi-core CPU and GPU platforms. Experimental resul (open full item for complete abstract)

Committee: P. Sadayappan (Advisor); Srinivasan Parthasarathy (Committee Member); Eric Fosler-Lussier (Committee Member) Subjects: Computer Science

MA, Kent State University, 2019, College of Arts and Sciences / Department of Psychological Sciences

Past research on incidental vocabulary learning during reading found links between the development of orthographic (spelling) and semantic (meaning) knowledge, but the nature of this relationship remains unclear. The current study primarily investigated whether semantic knowledge benefits orthographic knowledge in a series of three experiments. Participants were exposed to 14 novel non-words embedded in sentences with either informative or uninformative context. Participants were exposed to each novel word multiple times in different sentences which either all converged on the same meaning (in the informative context) or which were all semantically neutral. Semantic and orthographic learning was assessed using orthographic and semantic posttests. In E1, participants were exposed to the novel words three times during the learning phase; the spelling frequency of the novel words was also manipulated (high x low). Results of E1 indicated that the relationship between context and orthographic accuracy was moderated by spelling frequency such that when a word had a less common--more difficult--spelling, participants were more likely to learn spellings to words when they also learned the meaning. In E2, participants were once again exposed to the novel words three times during the learning phase, but all of the novel words had low-frequency spelling bodies in an effort to demonstrate that words with more difficult spellings would be benefited by access to those words' meanings. The results of E2 did not show a main effect of access to meaning on learning spelling, but they did reveal a strong association between learning spelling and learning meaning. In E3, participants were exposed to the novel words two times during the learning phase in an effort to increase the task difficulty; the novel words all had low-frequency spelling bodies. As was the case for E2, there was no main effect of access to words' meaning on learning those words' spellings, but there were str (open full item for complete abstract)

Committee: Jocelyn Folk Dr. (Advisor) Subjects: Psychology

Doctor of Philosophy (PhD), Wright State University, 2018, Computer Science and Engineering PhD

Pictographs, commonly referred to as `emoji', have become a popular way to enhance electronic communications. They are an important component of the language used in social media. With their introduction in the late 1990's, emoji have been widely used to enhance the sentiment, emotion, and sarcasm expressed in social media messages. They are equally popular across many social media sites including Facebook, Instagram, and Twitter. In 2015, Instagram reported that nearly half of the photo comments posted on Instagram contain emoji, and in the same year, Twitter reported that the `face with tears of joy' emoji has been tweeted 6.6 billion times. As of 2017, Facebook and Facebook Messenger processed over 60 million and 6 billion messages with emoji per day, respectively. Emogi, an Internet marketing firm, reports that over 92% of all online users have used emoji at least once. Creators of the SwiftKey Keyboard for mobile devices report that they process 6 billion messages per day that contain emoji. Moreover, business organizations have adopted and now accept the use of emoji in professional communication. For example, Appboy, an Internet marketing company, reports that there has been a 777% year-over-year increase and 20% month-over-month increase in emoji usage for marketing campaigns by business organizations in 2016. These statistics leave little doubt that emoji are a significant and important aspect of electronic communication across the world. The ability to automatically process and interpret text fused with emoji will be essential as society embraces emoji as a standard form of online communication. In the same way that natural language is processed with sophisticated machine learning techniques and technologies for many important applications, including text similarity and word sense disambiguation, emoji should also be amenable to such analysis. Yet the pictorial nature of emoji, the fact that the same emoji may be used in different contexts to express di (open full item for complete abstract)

Committee: Amit Sheth Ph.D. (Advisor); Derek Doran Ph.D. (Committee Member); Krishnaprasad Thirunarayan Ph.D. (Committee Member); Wenbo Wang Ph.D. (Committee Member) Subjects: Artificial Intelligence; Computer Engineering; Computer Science; Sociolinguistics

Doctor of Philosophy, The Ohio State University, 2017, Computer Science and Engineering

Many state-of-the-art neural network models utilize a huge number of parameters, where a large number of labeled training examples are necessary for sufficient training of the models. Those models may not be properly trained if there are not enough training examples for target tasks. This dissertation focuses on transfer learning methods, which improve the performance of the target tasks in such situations by leveraging external resources or models from other tasks. Specifically, we introduce transfer learning methods for enriching word or sentence vector representations of neural network models by transferring linguistic knowledge. Usually, the first layer of the neural networks for Natural Language Processing (NLP) is a word embedding layer. Word embeddings represent each word as a real-valued vector, where semantically or syntactically similar words tend to have similar vector representations in vector spaces. The first part of this dissertation is mainly about word embedding enrichment, which is categorized as an inductive transfer learning methodology. We show that word embeddings can represent semantic intensity scales like "good" < "great" < "excellent" on vector spaces, and semantic intensity orders of words can be used as the knowledge sources to adjust word vector positions to improve the semantics of words by evaluating on word-level semantics tasks. Also, we show that word embeddings that are enriched with linguistic knowledge can be used to improve the performance of the Bidirectional Long Short-Term Memory (BLSTM) model for intent detection, which is a sentence-level downstream task especially when only small numbers of training examples are available. The second part of this dissertation concerns about sentence-level transfer learning for sequence tagging tasks. We introduce a cross-domain transfer learning model for dialog slot-filling, which is an inductive transfer learning method, and a cross-lingual transfer learning model for Part-of-Sp (open full item for complete abstract)

Committee: Eric Fosler-Lussier (Advisor); Alan Ritter (Committee Member); Michael White (Committee Member) Subjects: Artificial Intelligence; Computer Science

Doctor of Philosophy, The Ohio State University, 1972, Graduate School

Committee: Not Provided (Other) Subjects: Education

Doctor of Philosophy (PhD), Ohio University, 2016, Electrical Engineering & Computer Science (Engineering and Technology)

In software development, developers usually receive bug reports that describe the abnormal behaviors of the software products. When a new bug report is received, developers usually need to reproduce the bug and perform code reviews to find the cause, a process that can be tedious and time-consuming. To alleviate developers' manual efforts of finding the bug, this dissertation presents a learning-to-rank approach that ranks all the source code files for a given bug report automatically. To improve the ranking performance, this dissertation also introduces using word-embedding-based text similarities to bridge the lexical gap between natural languages in bug reports and code in source files. First, a tool for ranking all the source files with respect to how likely they are to contain the cause of the bug would enable developers to narrow down their search and improve productivity. This dissertation introduces an adaptive ranking approach that leverages project knowledge through functional decomposition of source code, API descriptions of library components, bug-fixing history, code change history, and the file dependency graph. Given a bug report, the ranking score of each source file is computed as a weighted combination of an array of features, where the weights are trained automatically on previously solved bug reports using a learning-to-rank technique. We evaluate the ranking system on six large-scale open source Java projects, using the before-fix version of the project for every bug report. The experimental results show that the learning-to-rank approach outperforms three recent state-of-the-art methods. In particular, our method makes correct recommendations within the top 10 ranked source files for over 70% of the bug reports in the Eclipse Platform and Tomcat projects. Second, we propose bridging the lexical gap by projecting natural language statements and code snippets as meaning vectors in a shared representation space. In the proposed architecture, (open full item for complete abstract)

Committee: Chang Liu (Advisor); Razvan Bunescu (Advisor) Subjects: Computer Science

Master of Arts, The Ohio State University, 2016, Speech Language Pathology

Word learning requires the ability to integrate auditory information (e.g., an object's name—the label) and visual information (e.g., an object itself—the referent). Previous research has shown that children with typical development preferentially weight auditory information when auditory-visual stimuli is placed into conflict and that this weighting is advantageous for word learning. Children with autism spectrum disorders (ASD) are described as visual learners; however, no comparable test has been administered to children with ASD. The purpose of this study is to determine whether children with ASD follow the same pattern of information processing as children who are typically developing. In the present study, four children with ASD and four typically-developing (TD) children matched to the children with ASD on the basis of receptive language abilities were tested on a computerized preferential looking task. During the computerized task, the children were presented with auditory-visual stimuli on a television screen and trained to look for an auditory-visual “prize” that appeared in specific locations corresponding with the stimulus presented. The children's eye gazes were recorded and coded frame-by-frame. Given the evidence of children with ASD's relative strength in visual processing, it was predicted that the children with ASD would differ from their receptive-vocabulary mates and give greater weight to the visual component of auditory-visual stimuli. Study findings did not support this prediction; the majority of participants with typical development weighted visual information, while participants with ASD demonstrated no stimulus preference as a group. These findings call into question the commonly held assumption that all children with ASD are “visual learners.” Additionally, the cognitive and linguistic profiles of the participants with ASD (determined via scores on standardized assessments of cognition and language) revealed that stronger cognitive (open full item for complete abstract)

Committee: Allison F. Bean Ellawadi PhD, CCC-SLP (Advisor); Rebecca J. McCauley PhD, CCC-SLP (Committee Member) Subjects: Developmental Psychology; Psychology; Speech Therapy

Doctor of Philosophy, The Ohio State University, 2015, Linguistics

Phonological processes such as vowel chain shifting result in complex systems of cross-category vowel variation across spoken varieties of a language (Labov, 1994). The experiments comprising this dissertation aimed to understand how listeners cope with such systemic pronunciation variation to recognize spoken words.

Committee: Cynthia Clopper (Advisor); Shari Speer (Committee Member); Mark Pitt (Committee Member) Subjects: Linguistics

Master of Science (MS), Bowling Green State University, 2014, Communication Disorders

Numerous studies have demonstrated that young children can learn new words without direct teaching (Rice, 1990; Hollich, Hirsh-Pasek, Golinkoff, Brand, Brown, Chung, Hennon, Rocroi, & Bloom, 2000; Halberda, 2003; Brackenbury & Pye, 2005; Brackenbury, Ryan, & Messenheimer, 2006; Carey, 2010). However, very few have examined the integration of novel words into children’s lexicons (e.g., Markman & Hutchinson, 1994). The present study assessed how and when preschool-aged children acquire novel words from stories, and connect them to familiar words that are related taxonomically and thematically. Testing was conducted immediately after hearing the stories and one week later with no further exposure. The children correctly identified all three types of lexical connections (i.e., phonological form, taxonomic associates, and thematic associates) at greater than chance levels, demonstrating that each type of lexical connection was accessed during novel word learning. Performances related to the time of testing and the interaction between time and connection type were not significantly different. These results suggest that children are accessing their current lexical knowledge when acquiring novel words and that the integration of newly learned words continues after the exposing event.

Committee: Tim Brackenbury Ph.D., CCC-SLP (Advisor); Virginia Dubasik Ph.D., CCC-SLP (Committee Member); Elizabeth Burroughs Ph.D., CCC-SLP (Committee Member) Subjects: Speech Therapy

Doctor of Philosophy (PhD), Ohio University, 2014, Speech-Language Science (Health Sciences and Professions)

Vocabulary is an important component of literacy, and its development is widely believed to be due to incidental encounters with unfamiliar words during reading. The extent to which incidental encounters contribute to overall vocabulary growth is an area in need of further exploration. Because derived words are common in academic contexts, the present study examined how children in grade 5 acquired semantic and syntactic knowledge of unfamiliar derived words in incidental reading contexts. The present study also explored the relationship and contribution of morphological knowledge (relational, syntactic, and distributional) and general syntactic knowledge to incidental derived word learning. Children were administered three measures of morphological knowledge, a standardized measure of general syntactic knowledge, and an incidental word learning measure. The incidental word learning measure required the children to read short stories containing a stimulus word and then identify the correct semantic and syntactic usage of the stimulus word within four new contexts. The results supported the theory that children learn new words in incidental encounters during reading. Although there were greater semantic gains in word knowledge overall, there was evidence that suffix knowledge provided an advantage to syntactic knowledge of an unfamiliar word. Furthermore, relational and syntactic knowledge had a relationship with and predicted incidental word learning. No relationship between distributional knowledge and incidental derived word learning was found. While there was a relationship between general syntactic knowledge and derived word learning, general syntactic knowledge did not predict derived word learning beyond the contributions of relational and distributional knowledge.

Committee: Sally Marinellie (Advisor) Subjects: Education; Language; Literacy

PhD, University of Cincinnati, 2011, Allied Health Sciences: Communication Sciences and Disorders

Graduated prompting is a method of dynamic assessment that is used to make predictions about a child's response to intervention (Gutierrez-Clellan & Pena, 2001). The purpose of this study was to use graduated prompting to assess the word learning ability of low-income fourth grade students when given context clues during a reading task. Twenty-eight fourth grade students were administered the Expressive One Word Picture Vocabulary Test (EOWPVT; Brownell, 2000) and were placed into Pass (85 and higher) and Non-Pass (below 85) groups based on standard EOWPVT scores. The participants were administered the three phases of the Dynamic Assessment of Vocabulary in Context (DAVIC): 1) Pretest, 2) Graduated Prompting, and 3) Transfer task. Scores on the DAVIC phases were analyzed by group and by EOWPVT score. The frequency of responses at each prompt level was compared to EOWPVT score. DAVIC pretest and DAVIC transfer task scores were compared. There was no significant difference between the scores of the Pass group (M=67.00, SD=14.502) and scores of the Non Pass group (M=64.57, SD=9.525) on the DAVIC graduated prompting phase t(26)=.524, p=.605, d=.19. Scores on EOWPVT and DAVIC pretest scores were significantly correlated, r=.599, p=0.01. EOWPVT scores were significantly correlated with Prompt 1, r=.429, (p=0.05) and Prompt 3, r= -.376, (p=0.05). There was not a significant correlation r=.184 p=.184, between scores on the EOWPVT and DAVIC transfer task scores. The participants scored significantly higher on the transfer task (M=62.32, SD=10.61) than on the pretest (M=37.96, SD=5.87); t=-10.73, p=<.001, d=2.84. Results of this study suggested that when assessing a child's vocabulary skills, Graduated Prompting may be more effective in determining a child's abilities than a standardized assessment alone.

Committee: Jo-Anne Prendeville EdD (Committee Chair); Beth O'Brien PhD (Committee Member); Nancy Creaghead PhD (Committee Member); Lesley Raisor PhD (Committee Member) Subjects: Speech Therapy

Master of Arts, The Ohio State University, 2011, Psychology

Validation has been hypothesized to impact the quality of therapeutic relationships and to have far-reaching consequences for treatment outcomes. Although there is some evidence that invalidation increases arousal and negative affect (Shenk, 2007), to date there are no known investigations of the role of invalidation in learning. The aim of the present study was to test the impact of validation and invalidation on mood and learning task performance. Participants were randomized to receive either validation or invalidation during disclosure of an angry personal event. Participants then completed an emotion-word card sorting test, followed by a paired-associates word recall test. Manipulation checks demonstrated significant differences in self-reported invalidation between conditions [F (2, 95) = 12.02, p < .001]. However, no difference was observed between the validation and invalidation groups on any learning task variable. We found a significant positive affect (PA) by condition interaction when comparing validation and invalidation separately [F (1, 64) = 7.67, p = .01], such that invalidated participants experienced significantly larger decreases in PA following recall of the angry story than did validated participants. No significant differences in self-reported negative affect were obtained [F (1, 64) = 0.002, p = .97]. These findings suggest that invalidating interactions may reduce PA, which is related to approach behavior and broadening of behavioral repertoires (Custers & Aarts, 2005; Fredrickson, 2001). It may be the case that reductions in PA, as opposed to disruptions in learning per se, might be related to poor therapeutic outcomes via decreased approach behaviors.

Committee: Jennifer Cheavens PhD (Advisor); Daniel Strunk PhD (Committee Member); Michael Vasey PhD (Committee Member) Subjects: Behavioral Psychology; Behavioral Sciences; Clinical Psychology; Psychology

Doctor of Philosophy, The Ohio State University, 2003, Physical Activity and Educational Services

Recent pedagogical standards voiced by the National Council of Teachers of Mathematics (2000) have increasingly stressed the development of students' strategic knowledge of mathematics. Such knowledge extends students' procedural and declarative understanding of mathematics and stretches their cognitive application of mathematics to greater conceptual and applied heights. The value of learning and applying mathematics strategically is often not appreciated by students who are learning disabled. Representing mathematical problems, deriving goals for solving such problems, choosing among appropriate strategies for problem-solving, and engaging in self-monitoring processes are of greater challenge to students with learning disabilities. Further, students with learning disabilities often experience lower self-efficacy toward mathematics and attribute their mathematical learning outcomes to forces external to their effort and behavior. This study assessed the efficacy of an intervention targeting the mathematical word problem-solving of middle school students with learning disabilities that is inclusive of cognitive, metacognitive, and motivational components. The intervention was based on the Mathematical Problem-Solving Model of Montague (1995, 1997, 2000) and taught students a strategy based on principles of self-regulated learning. Additionally, the intervention encouraged students to attribute their learning outcomes to the application of the strategy and sought to foster the development of self-efficacy through the promotion of the strategy's knowledge, use, and control. Results of the present investigation are meaningful in terms of each of the four research objectives. First, strategy instruction was efficacious in improving the mathematical word problem solving of students with learning disabilities. Second, important and significant gains were evidenced in the LD students' knowledge, use, and control of math word problem-solving strategies, such that their awar (open full item for complete abstract)

Committee: Antoinette Miranda (Advisor) Subjects: