Wong Ngai Ying. / Chinese title in romanization: Zi wo jian cha you qiang hua zuo yong dui jie nan biao xian di ying xiang. / Thesis (M.A.Ed.)--Chinese University of Hong Kong, 1987. / Bibliography: leaves 89-99.

In this study, I examined the relation between various construct relevant and irrelevant variables and a math problem solving assessment. I used independent performance measures representing the variables of mathematics content knowledge, general ability, and reading fluency. Non-performance variables included gender, socioeconomic status, language proficiency and special education qualification. Using a sequential regression and commonality analysis, I determined the amount of variance explained by each performance measure on the Oregon state math assessment in third grade. All variables were independently predictive of math problem solving scores, and used together, they explained 58% score variance. The math content knowledge measure explained the most variance uniquely (12%), and the measures of math content and general ability explained the most variance commonly (16%). In the second analysis, I investigated whether additional variance was explained once student demographic characteristics were controlled and how this affected the unique variance explained by each independent performance measure. By controlling for demographics, the model explained slightly more than 1% additional variance in math scores. The unique variance explained by each independent measure decreased slightly. This study highlighted the influence of various construct relevant and irrelevant variables on math problem solving scores, including the extent to which a language-free measure of general ability might help to inform likely outcomes. The use of variance partitioning expanded understanding of the unique and common underlying constructs that affect math problem solving assessment. Finally, this study provided more information regarding the influence demographic information has on outcomes related to state math assessments.

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Thesis (Sc.D.)--Massachusetts Institute of Technology, Dept. of Physics, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE / Bibliography: p. 424-432. / Sc.D.

While mathematical problem solving and problem posing are central to good mathematics teaching and mathematical learning, no criteria exist for what makes a good mathematics problem. This grounded theory study focused on defining attributes of good mathematics problems as determined by students, teachers, and mathematicians. The research questions explored the similarities and differences of the responses of these three populations. The data were analyzed using the grounded theory approach of the constant comparative method. Fifty eight students from an urban private school, 15 teachers of mathematics, and 7 mathematicians were given two sets of problems, one with 10 algebra problems and one with 10 number theory problems, and were asked choose which problems they felt were the “best” and the “least best”. Once their choices were made, they were asked to list the attributes of the problems that lead to their choices. Responses were coded and the results were compared within each population between the two different problem sets and between populations. The results of the study show that while teachers and mathematicians agree, for the most part, about what attributes make a good mathematics problem, neither of those populations agreed with the students. The results from this study may be useful for teachers as they write or evaluate problems to use in their classes.

After a negative consumption experience, consumers often like to muse about how their consumption might have turned out better. For example, a traveler who missed a flight may imagine that "if I had taken another transport to the airport, I might have caught the flight," or "I would have been enjoying my vacation if I had caught the flight." These imaginations, called counterfactual thoughts, have been documented to pose two effects on responses to negative consumptions. On one hand, they are functional because they provide corrective information that helps consumers solve problems associated with the consumption (Markman et al. 1993; Roese 1994). On the other hand, they are painful because they accentuate negative feelings about the consumption when they highlight the possibility that the consumption might have turned out better (Gleicher et al. 1990; Markman et al. 1993). Existing understanding on these two effects suggests that while people may learn a good lesson from their counterfactual thoughts, they have to contain the negative feelings induced by these thoughts. / In addition, this research also identifies the situational factors that promote the generation of process- and outcome-focused counterfactuals. Consumers are more likely to generate process-focused (versus outcome-focused) counterfactuals when they expect that the consumption is more likely to repeat. They are more likely to generate outcome-focused (versus process-focused) counterfactuals the closer they had missed a better-off consumption outcome. / In summary, this research contributes to the counterfactual literature by proposing thought focus as a new dimension to classify counterfactuals into process- and outcome-focused counterfactuals. It also advances existing understanding on the two effects of counterfactual generation and demonstrates that consumers may enjoy the problem-solving function of counterfactual generation without paying a psychological cost. Finally, this research provides managers insights into when promoting counterfactual generation is beneficial and when it is undesirable. / This research is motivated to tease out the problem-solving and affect accentuation effects of counterfactual generation, such that people may learn a lesson from counterfactual generation without paying incremental psychological cost. To start with, this research proposes thought focus as a new dimension to classify counterfactual thoughts into process- and outcome-focused counterfactuals. This classification is then used as a means to tease out the two effects of counterfactual generation. Specifically, it is argued that process- and outcome-focused counterfactuals pose differential consequences to consumers who experienced negative consumptions. Process-focused counterfactuals, which focus on the process leading to a better-off imagined outcome (e.g., taking another transport to airport), promote corrective behaviors in subsequent consumptions and reduce the chance of having negative experiences in the future. Outcome-focused counterfactuals, which focus on the benefits brought by a better-off outcome (e.g., enjoying the vacation), intensify the negative feelings (such as disappointment and unhappiness) about the current consumption. / Ho, Ka Yan. / Adviser: Jessica Y. Y. Kwong. / Source: Dissertation Abstracts International, Volume: 72-11, Section: A, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 70-73). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Since 2012, hundreds of companies have poured thousands of dollars into hackathons – finite events where creatives come together in small teams to design, build, and demo a new product of feature. The spectacle of the hackathon engages participants in a number of things: a transgressive ethos, disciplined play, and hacker’s literacies (Santo 2011). Based on my dissertation fieldwork at seven hackathons in three industries (journalism, healthcare, and e-government), I explore various types of play labor (Terranova 2000) based on the performances of eight teams. I show how teams creatively manage their peers’ affective and intellectual labor, and negotiate what appear to be industry-specific preferences for different technologies. In the process of competing for status and recognition, they engender distinct forms of play labor and making do. Hackathon participants directly embed resistance in their designs; some learn how to learn (Bateson 1972), giving them a strategic advantage over other classes of workers. They embody the characteristics of the new worker-subject required in the digital economy, as mutable, playful, and rapid.

The aim of this thesis is to adress the problem of capability brokering. A capability-brokering agent recieves capability advertisements from problem-solving agents and problem descriptions from problem-holding agents. The amin task for the broker is to find problem-solving agents that have the capabilities to address problems described to the broker by a problem-holding agent. Capability brokering poses two problems: for advertisements, and matching problems and capabilities, to find capable problem-solvers. For the representation part of the problem, there have been a number of representations in AI that address similar issues. We review various logical representations, action representations, and representations for models of problem solving and conclude that, while all of these areas have some positive features for the representation of capabilities, they also all have serious drawbacks. We describe a new capability description language, CDL, which shares the positive features of previous languages while avoiding their drawbacks. CDL is a decoupled action representation into which arbitrary state representations can be plugged, resulting in the expressiveness and flexibility needed for capability brokering. Reasoning over capability descriptions takes place on two levels. The outer level deals with agent communication and we have devloped the Knowledge Query and Manipulation Language (KQML) here. At the inner level the main task is to decide whether a capability description subsumes a problem description. In CDL thee subsumtion relation for achievable objectives is defined in terms of the logical entailment relation betwenn sentences in the state language used within CDL. The definition of subsumption for performable tasks in turn is based on this definition for achievable objectives. We describe algoritms in this thesis which have all been implemented and incorporated into he Java Agent Template where they proved sufficient to operationalise anumber of example scenarios. The two most important featues of CDL are its expressiveness and its flexibility. By expressiveness we mean the ability to express more than is possible in other representations. By flexibility we mean the possibility to delay decisions regarding the compromises that have to be made to knowledge representation time. The scenarions we ahve implemted illustrate the importance of the features and we have shown in this thesis that CDL indeed possess thease features. Thus, CDL is an expressive and flexible capability description language that can be used to address the problem of capability brokering.

This study examined parent engagement, child engagement, and quality of problem solving in a sample of families engaged in a trial of parent management training intervention. Data were collected for treatment and control groups at preintervention and 2, 4, and 6 months after the initial assessment. Variables in this study were measured utilizing a global coding scheme used to categorize parent-child behavioral observations. The coding scheme was developed by Forgatch, Knutson, and Mayne. Preliminary analyses led to scale changes due to lack of variance in observations. Results show that treatment group showed a gain in problem solving skills at T2; however those gains were not retained at T3. There was a gain between T3 and T4. The control group showed an increase at T4 from baseline in problem solving skills. Both parent and child engagement decreased for both groups, with the lowest time point occurring at T3.

No description available.