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- Genre: Academic theses
Description
The need for improved mathematics education in many of America's schools that serve students from low income households has been extensively documented. This practical action research study, set in a suburban Title I school with a primarily Hispanic, non-native English speaking population, is designed to explore the effects of the progression through a set of problem solving solution strategies on the mathematics problem solving abilities of 2nd grade students. Students worked in class with partners to complete a Cognitively Guided Instruction-style (CGI) mathematics word problem using a dictated solution strategy five days a week for twelve weeks, three or four weeks for each of four solution strategies. The phases included acting out the problem using realia, representing the problem using standard mathematics manipulatives, modeling the problem using a schematic representation, and solving the problem using a number sentence. Data were collected using a five question problem solving pre- and post-assessment, video recorded observations, and Daily Answer Recording Slips or Mathematics Problem Solving Journals. Findings showed that this problem solving innovation was effective in increasing the problem solving abilities of all participants in this study, with an average increase of 63% in the number of pre-assessment to post-assessment questions answered correctly. Additionally, students increased the complexity of solutions used to solve problems and decreased the rate of guessing at answers to word problems. Further rounds of research looking into the direct effects of the MKO are suggested as next steps of research.
ContributorsSpilde, Amy (Author) / Zambo, Ronald (Thesis advisor) / Heck, Thomas (Committee member) / Nicoloff, Stephen J. (Committee member) / Arizona State University (Publisher)
Created2013
Description
This action research study explored what would happen if a principal network was created to provide time for collaboration about critical case studies of practice. The participants in this study were novice and experienced principals in an elementary school district in Arizona. Based on the underpinnings of the Wallace Foundation principal support programs, the study was designed to combat the limited professional development offerings for in-service principals. Modeling the use of cases from the legal and medical professions, this study utilized case studies as the base for peer collaboration to extend the principals' critical thinking skills of relevance, breadth, and depth.
The study design aligned with adult learning theory and focused on authentic problem solving. Participants read case studies, completed individual case analysis, collaborated, and wrote reflections. The cases were intentionally selected to match current problems of practice for the participants. This mixed methods study followed a sequential analysis process beginning with qualitative analysis using a grounded theory approach and moving to quantitative analysis.
The results of this study indicated that the participants' ability to think critically about the problem (relevance) and its complexity (breadth and depth) increased over time. The data also showed that the principals gained an increased awareness and appreciation for multiple perspectives. Lastly, the participants valued the time to collaborate together, gain insight from one another and reduce feelings of isolation in their role as administrators. Future research should continue to explore the use of critical case studies of practice as a in participatory action research with in-service principals.
The study design aligned with adult learning theory and focused on authentic problem solving. Participants read case studies, completed individual case analysis, collaborated, and wrote reflections. The cases were intentionally selected to match current problems of practice for the participants. This mixed methods study followed a sequential analysis process beginning with qualitative analysis using a grounded theory approach and moving to quantitative analysis.
The results of this study indicated that the participants' ability to think critically about the problem (relevance) and its complexity (breadth and depth) increased over time. The data also showed that the principals gained an increased awareness and appreciation for multiple perspectives. Lastly, the participants valued the time to collaborate together, gain insight from one another and reduce feelings of isolation in their role as administrators. Future research should continue to explore the use of critical case studies of practice as a in participatory action research with in-service principals.
ContributorsKubasko, Wendy Lynn (Author) / Rotheram-Fuller, Erin (Thesis advisor) / Dinn-You Liou, Daniel (Committee member) / Diaz, Rene (Committee member) / Arizona State University (Publisher)
Created2015
Description
The marketing and development of solutions has become an increasingly important concept in both marketing practice and theory. Recent conceptual work has defined solutions as sets of products and services that allow customers to achieve customized outcomes. Although the definition of a solution is becoming clearer, the process through which solution value is generated is still opaque. The purpose of this study was to add clarity to both marketing theory and practice by examining the solution value co-creation process in depth. Service-dominant logic, the relational view, service value co-creation, and theories of organizational learning and knowledge were the basis for this examination. Social capital was also examined to determine how these important relational concepts are involved in solution development. The study was conducted in four separate phases using a multi-method approach of quantitative surveys, qualitative surveys, and depth interviews. A large, multinational educational firm provided the context for the study which included access to their solution sales force and customer base. Quantitative data was collected from 97 key informants across 182 different customer opportunities for both new and existing solution engagements. Qualitative data was also collected from 71 respondents to provide a mixed-method triangulation of how solution value is created. Overall, the study provided strong support to the idea that knowledge sharing between solution providers and their customers plays a pivotal role in the co-creation of solution value.
ContributorsSellman, Collin (Author) / Hutt, Michael (Thesis advisor) / Kumar, Ajith (Committee member) / Walker, Beth (Committee member) / Arizona State University (Publisher)
Created2011
Description
The critical-thinking skill of problem solving needs to be part of the curriculum for all students, including those with learning disabilities living in poverty; yet, too often this is not the case. Too often students in poverty and students with learning disabilities are provided a curriculum that is watered down, focused on the basics, and aimed at managing their behaviors instead of helping them learn to think critically about their world. Despite their challenges, these students can learn to problem solve. Educators need to help students make connections between the critical-thinking skills learned in school and the problem-solving skills needed for life. One solution might be to use literature with characters facing similar problems, hold grand conversations, and teach them a problem solving method. Together, these three parts have the potential to motivate and lead students to better thinking. This action research study explored whether literature with characters facing similar problems to the study's participants, grand conversations, and the I SOLVE problem solving method would help students with disabilities living in poverty in the Southwestern United States develop the problem-solving skills they need to understand and successfully navigate their world. Data were collected using a mixed methods approach. The Motivation to Read Profile, I SOLVE problem-solving survey, thought bubbles, student journals, transcripts from grand conversations, and researcher's journal were tools used. To understand fully how and to what extent literature and grand conversations helped students gain the critical thinking skill of problem solving, data were mixed in a convergence model. Results show the I SOLVE problem-solving method was an effective way to teach problem-solving steps. Scores on the problem-solving survey rose pre- to post-test. Grand conversations focused on literature with character's facing problems led to an increase in students' motivation to read, and this population of students were able to make aesthetic connections and interpretations to the texts read. From these findings implications for teachers are provided.
ContributorsWells, Sheila (Author) / Zambo, Debby (Thesis advisor) / Hansen, Cory (Committee member) / Davidson, Carter (Committee member) / Arizona State University (Publisher)
Created2012
Description
Lots of previous studies have analyzed human tutoring at great depths and have shown expert human tutors to produce effect sizes, which is twice of that produced by an intelligent tutoring system (ITS). However, there has been no consensus on which factor makes them so effective. It is important to know this, so that same phenomena can be replicated in an ITS in order to achieve the same level of proficiency as expert human tutors. Also, to the best of my knowledge no one has looked at student reactions when they are working with a computer based tutor. The answers to both these questions are needed in order to build a highly effective computer-based tutor. My research focuses on the second question. In the first phase of my thesis, I analyzed the behavior of students when they were working with a step-based tutor Andes, using verbal-protocol analysis. The accomplishment of doing this was that I got to know of some ways in which students use a step-based tutor which can pave way for the creation of more effective computer-based tutors. I found from the first phase of the research that students often keep trying to fix errors by guessing repeatedly instead of asking for help by clicking the hint button. This phenomenon is known as hint refusal. Surprisingly, a large portion of the student's foundering was due to hint refusal. The hypothesis tested in the second phase of the research is that hint refusal can be significantly reduced and learning can be significantly increased if Andes uses more unsolicited hints and meta hints. An unsolicited hint is a hint that is given without the student asking for one. A meta-hint is like an unsolicited hint in that it is given without the student asking for it, but it just prompts the student to click on the hint button. Two versions of Andes were compared: the original version and a new version that gave more unsolicited and meta-hints. During a two-hour experiment, there were large, statistically reliable differences in several performance measures suggesting that the new policy was more effective.
ContributorsRanganathan, Rajagopalan (Author) / VanLehn, Kurt (Thesis advisor) / Atkinson, Robert (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2011
Description
Introductory programming courses, also known as CS1, have a specific set of expected outcomes related to the learning of the most basic and essential computational concepts in computer science (CS). However, two of the most often heard complaints in such courses are that (1) they are divorced from the reality of application and (2) they make the learning of the basic concepts tedious. The concepts introduced in CS1 courses are highly abstract and not easily comprehensible. In general, the difficulty is intrinsic to the field of computing, often described as "too mathematical or too abstract." This dissertation presents a small-scale mixed method study conducted during the fall 2009 semester of CS1 courses at Arizona State University. This study explored and assessed students' comprehension of three core computational concepts - abstraction, arrays of objects, and inheritance - in both algorithm design and problem solving. Through this investigation students' profiles were categorized based on their scores and based on their mistakes categorized into instances of five computational thinking concepts: abstraction, algorithm, scalability, linguistics, and reasoning. It was shown that even though the notion of computational thinking is not explicit in the curriculum, participants possessed and/or developed this skill through the learning and application of the CS1 core concepts. Furthermore, problem-solving experiences had a direct impact on participants' knowledge skills, explanation skills, and confidence. Implications for teaching CS1 and for future research are also considered.
ContributorsBillionniere, Elodie V (Author) / Collofello, James (Thesis advisor) / Ganesh, Tirupalavanam G. (Thesis advisor) / VanLehn, Kurt (Committee member) / Burleson, Winslow (Committee member) / Arizona State University (Publisher)
Created2011
Description
A sample of 127 high school Advanced Placement (AP) Calculus students from two schools was utilized to study the effects of an engineering design-based problem solving strategy on student performance with AP style Related Rate questions and changes in conceptions, beliefs, and influences. The research design followed a treatment-control multiple post-assessment model with three periods of data collection. Four high school calculus classes were selected for the study, with one class designated as the treatment and three as the controls. Measures for this study include a skills assessment, Related Rate word problem assessments, and a motivation problem solving survey. Data analysis utilized a mixed methods approach. Quantitative analysis consisted of descriptive and inferential methods utilizing nonparametric statistics for performance comparisons and structural equation modeling to determine the underlying structure of the problem solving motivation survey. Statistical results indicate that time on task was a major factor in enhanced performance between measurement time points 1 and 2. In the experimental classroom, the engineering design process as a problem solving strategy emerged as an important factor in demonstrating sustained achievement across the measurement time series when solving volumetric rates of change as compared to traditional problem solving strategies. In the control classrooms, where traditional problem solving strategies were emphasized, a greater percentage of students than in the experimental classroom demonstrated enhanced achievement from point 1 to 2, but showed decrease in achievement from point 2 to 3 in the measurement time series. Results from the problem solving motivation survey demonstrated that neither time on task nor instruction strategy produced any effect on student beliefs about and perceptions of problem solving. Qualitative error analysis showed that type of instruction had little effect on the type and number of errors committed, with the exception of procedural errors from performing a derivative and errors decoding the problem statement. Results demonstrated that students who engaged in the engineering design-based committed a larger number of decoding errors specific to Pythagorean type Related Rate problems; while students who engaged in routine problem solving did not sustain their ability to correctly differentiate a volume equation over time. As a whole, students committed a larger number of misused data errors than other types of errors. Where, misused data errors are the discrepancy between the data as given in a problem and how the student used the data in problem solving.
ContributorsThieken, John (Author) / Ganesh, Tirupalavanam G. (Thesis advisor) / Sloane, Finbarr (Committee member) / Middleton, James (Committee member) / Arizona State University (Publisher)
Created2012
Description
Design problem formulation is believed to influence creativity, yet it has received only modest attention in the research community. Past studies of problem formulation are scarce and often have small sample sizes. The main objective of this research is to understand how problem formulation affects creative outcome. Three research areas are investigated: development of a model which facilitates capturing the differences among designers' problem formulation; representation and implication of those differences; the relation between problem formulation and creativity.
This dissertation proposes the Problem Map (P-maps) ontological framework. P-maps represent designers' problem formulation in terms of six groups of entities (requirement, use scenario, function, artifact, behavior, and issue). Entities have hierarchies within each group and links among groups. Variables extracted from P-maps characterize problem formulation.
Three experiments were conducted. The first experiment was to study the similarities and differences between novice and expert designers. Results show that experts use more abstraction than novices do and novices are more likely to add entities in a specific order. Experts also discover more issues.
The second experiment was to see how problem formulation relates to creativity. Ideation metrics were used to characterize creative outcome. Results include but are not limited to a positive correlation between adding more issues in an unorganized way with quantity and variety, more use scenarios and functions with novelty, more behaviors and conflicts identified with quality, and depth-first exploration with all ideation metrics. Fewer hierarchies in use scenarios lower novelty and fewer links to requirements and issues lower quality of ideas.
The third experiment was to see if problem formulation can predict creative outcome. Models based on one problem were used to predict the creativity of another. Predicted scores were compared to assessments of independent judges. Quality and novelty are predicted more accurately than variety, and quantity. Backward elimination improves model fit, though reduces prediction accuracy.
P-maps provide a theoretical framework for formalizing, tracing, and quantifying conceptual design strategies. Other potential applications are developing a test of problem formulation skill, tracking students' learning of formulation skills in a course, and reproducing other researchers’ observations about designer thinking.
This dissertation proposes the Problem Map (P-maps) ontological framework. P-maps represent designers' problem formulation in terms of six groups of entities (requirement, use scenario, function, artifact, behavior, and issue). Entities have hierarchies within each group and links among groups. Variables extracted from P-maps characterize problem formulation.
Three experiments were conducted. The first experiment was to study the similarities and differences between novice and expert designers. Results show that experts use more abstraction than novices do and novices are more likely to add entities in a specific order. Experts also discover more issues.
The second experiment was to see how problem formulation relates to creativity. Ideation metrics were used to characterize creative outcome. Results include but are not limited to a positive correlation between adding more issues in an unorganized way with quantity and variety, more use scenarios and functions with novelty, more behaviors and conflicts identified with quality, and depth-first exploration with all ideation metrics. Fewer hierarchies in use scenarios lower novelty and fewer links to requirements and issues lower quality of ideas.
The third experiment was to see if problem formulation can predict creative outcome. Models based on one problem were used to predict the creativity of another. Predicted scores were compared to assessments of independent judges. Quality and novelty are predicted more accurately than variety, and quantity. Backward elimination improves model fit, though reduces prediction accuracy.
P-maps provide a theoretical framework for formalizing, tracing, and quantifying conceptual design strategies. Other potential applications are developing a test of problem formulation skill, tracking students' learning of formulation skills in a course, and reproducing other researchers’ observations about designer thinking.
ContributorsDinar, Mahmoud (Author) / Shah, Jami J. (Thesis advisor) / Langley, Pat (Committee member) / Davidson, Joseph K. (Committee member) / Lande, Micah (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2015
Description
Online learning platforms such as massive online open courses (MOOCs) and
intelligent tutoring systems (ITSs) have made learning more accessible and personalized. These systems generate unprecedented amounts of behavioral data and open the way for predicting students’ future performance based on their behavior, and for assessing their strengths and weaknesses in learning.
This thesis attempts to mine students’ working patterns using a programming problem solving system, and build predictive models to estimate students’ learning. QuizIT, a programming solving system, was used to collect students’ problem-solving activities from a lower-division computer science programming course in 2016 Fall semester. Differential mining techniques were used to extract frequent patterns based on each activity provided details about question’s correctness, complexity, topic, and time to represent students’ behavior. These patterns were further used to build classifiers to predict students’ performances.
Seven main learning behaviors were discovered based on these patterns, which provided insight into students’ metacognitive skills and thought processes. Besides predicting students’ performance group, the classification models also helped in finding important behaviors which were crucial in determining a student’s positive or negative performance throughout the semester.
intelligent tutoring systems (ITSs) have made learning more accessible and personalized. These systems generate unprecedented amounts of behavioral data and open the way for predicting students’ future performance based on their behavior, and for assessing their strengths and weaknesses in learning.
This thesis attempts to mine students’ working patterns using a programming problem solving system, and build predictive models to estimate students’ learning. QuizIT, a programming solving system, was used to collect students’ problem-solving activities from a lower-division computer science programming course in 2016 Fall semester. Differential mining techniques were used to extract frequent patterns based on each activity provided details about question’s correctness, complexity, topic, and time to represent students’ behavior. These patterns were further used to build classifiers to predict students’ performances.
Seven main learning behaviors were discovered based on these patterns, which provided insight into students’ metacognitive skills and thought processes. Besides predicting students’ performance group, the classification models also helped in finding important behaviors which were crucial in determining a student’s positive or negative performance throughout the semester.
ContributorsMandal, Partho Pratim (Author) / Hsiao, I-Han (Thesis advisor) / Davulcu, Hasan (Committee member) / Tong, Hanghang (Committee member) / Arizona State University (Publisher)
Created2017
Description
In the daily life of an individual problems of varying difficulty are encountered.
Each problem may include a different number of constraints placed upon the problem
solver. One type of problem commonly used in research are multiply-constrained
problems, such as the compound remote associates. Since their development they have
been related to creativity and insight. Moreover, research has been conducted to
determine the cognitive abilities underlying problem solving abilities. We sought to fully
evaluate the range of cognitive abilities (i.e., working memory, episodic and semantic
memory, and fluid and crystallized intelligence) linked to multiply-constrained problem
solving. Additionally, we sought to determine whether problem solving ability and
strategies (analytical or insightful) were task specific or domain general through the use
of novel problem solving tasks (TriBond and Location Bond). Results indicated that
multiply-constrained problem solving abilities were domain general, solutions derived
through insightful strategies were more often correct than analytical, and crystallized
intelligence was the only cognitive ability that provided unique predictive value.
Each problem may include a different number of constraints placed upon the problem
solver. One type of problem commonly used in research are multiply-constrained
problems, such as the compound remote associates. Since their development they have
been related to creativity and insight. Moreover, research has been conducted to
determine the cognitive abilities underlying problem solving abilities. We sought to fully
evaluate the range of cognitive abilities (i.e., working memory, episodic and semantic
memory, and fluid and crystallized intelligence) linked to multiply-constrained problem
solving. Additionally, we sought to determine whether problem solving ability and
strategies (analytical or insightful) were task specific or domain general through the use
of novel problem solving tasks (TriBond and Location Bond). Results indicated that
multiply-constrained problem solving abilities were domain general, solutions derived
through insightful strategies were more often correct than analytical, and crystallized
intelligence was the only cognitive ability that provided unique predictive value.
ContributorsEllis, Derek M (Author) / Brewer, Gene A. (Thesis advisor) / Homa, Donald (Committee member) / Goldinger, Stephen (Committee member) / Arizona State University (Publisher)
Created2019