Matching Items (3)
Filtering by
- All Subjects: psychometrics
- Creators: Green, Samuel
Description
This study tested the effects of two kinds of cognitive, domain-based preparation tasks on learning outcomes after engaging in a collaborative activity with a partner. The collaborative learning method of interest was termed "preparing-to-interact," and is supported in theory by the Preparation for Future Learning (PFL) paradigm and the Interactive-Constructive-Active-Passive (ICAP) framework. The current work combined these two cognitive-based approaches to design collaborative learning activities that can serve as alternatives to existing methods, which carry limitations and challenges. The "preparing-to-interact" method avoids the need for training students in specific collaboration skills or guiding/scripting their dialogic behaviors, while providing the opportunity for students to acquire the necessary prior knowledge for maximizing their discussions towards learning. The study used a 2x2 experimental design, investigating the factors of Preparation (No Prep and Prep) and Type of Activity (Active and Constructive) on deep and shallow learning. The sample was community college students in introductory psychology classes; the domain tested was "memory," in particular, concepts related to the process of remembering/forgetting information. Results showed that Preparation was a significant factor affecting deep learning, while shallow learning was not affected differently by the interventions. Essentially, equalizing time-on-task and content across all conditions, time spent individually preparing by working on the task alone and then discussing the content with a partner produced deeper learning than engaging in the task jointly for the duration of the learning period. Type of Task was not a significant factor in learning outcomes, however, exploratory analyses showed evidence of Constructive-type behaviors leading to deeper learning of the content. Additionally, a novel method of multilevel analysis (MLA) was used to examine the data to account for the dependency between partners within dyads. This work showed that "preparing-to-interact" is a way to maximize the benefits of collaborative learning. When students are first cognitively prepared, they seem to make the most efficient use of discussion towards learning, engage more deeply in the content during learning, leading to deeper knowledge of the content. Additionally, in using MLA to account for subject nonindependency, this work introduces new questions about the validity of statistical analyses for dyadic data.
ContributorsLam, Rachel Jane (Author) / Nakagawa, Kathryn (Thesis advisor) / Green, Samuel (Committee member) / Stamm, Jill (Committee member) / Arizona State University (Publisher)
Created2013
Modeling motivation: examining the structural validity of the Sport Motivation Scale-6 among runners
Description
Two models of motivation are prevalent in the literature on sport and exercise participation (Deci & Ryan, 1991; Vallerand, 1997, 2000). Both models are grounded in self-determination theory (Deci & Ryan, 1985; Ryan & Deci, 2000) and consider the relationship between intrinsic, extrinsic, and amotivation in explaining behavior choice and outcomes. Both models articulate the relationship between need satisfaction (i.e., autonomy, competence, relatedness; Deci & Ryan, 1985, 2000; Ryan & Deci, 2000) and various cognitive, affective, and behavioral outcomes as a function of self-determined motivation. Despite these comprehensive models, inconsistencies remain between the theories and their practical applications. The purpose of my study was to examine alternative theoretical models of intrinsic, extrinsic, and amotivation using the Sport Motivation Scale-6 (SMS-6; Mallett et al., 2007) to more thoroughly study the structure of motivation and the practical utility of using such a scale to measure motivation among runners. Confirmatory factor analysis was used to evaluate eight alternative models. After finding unsatisfactory fit of these models, exploratory factor analysis was conducted post hoc to further examine the measurement structure of motivation. A three-factor structure of general motivation, external accolades, and isolation/solitude explained motivation best, although high cross-loadings of items suggest the structure of this construct still lacks clarity. Future directions to modify item content and re-examine structure as well as limitations of this study are discussed.
ContributorsKube, Erin (Author) / Thompson, Marilyn (Thesis advisor) / Tracey, Terence (Thesis advisor) / Green, Samuel (Committee member) / Arizona State University (Publisher)
Created2012
Description
The use of exams for classification purposes has become prevalent across many fields including professional assessment for employment screening and standards based testing in educational settings. Classification exams assign individuals to performance groups based on the comparison of their observed test scores to a pre-selected criterion (e.g. masters vs. nonmasters in dichotomous classification scenarios). The successful use of exams for classification purposes assumes at least minimal levels of accuracy of these classifications. Classification accuracy is an index that reflects the rate of correct classification of individuals into the same category which contains their true ability score. Traditional methods estimate classification accuracy via methods which assume that true scores follow a four-parameter beta-binomial distribution. Recent research suggests that Item Response Theory may be a preferable alternative framework for estimating examinees' true scores and may return more accurate classifications based on these scores. Researchers hypothesized that test length, the location of the cut score, the distribution of items, and the distribution of examinee ability would impact the recovery of accurate estimates of classification accuracy. The current simulation study manipulated these factors to assess their potential influence on classification accuracy. Observed classification as masters vs. nonmasters, true classification accuracy, estimated classification accuracy, BIAS, and RMSE were analyzed. In addition, Analysis of Variance tests were conducted to determine whether an interrelationship existed between levels of the four manipulated factors. Results showed small values of estimated classification accuracy and increased BIAS in accuracy estimates with few items, mismatched distributions of item difficulty and examinee ability, and extreme cut scores. A significant four-way interaction between manipulated variables was observed. In additional to interpretations of these findings and explanation of potential causes for the recovered values, recommendations that inform practice and avenues of future research are provided.
ContributorsKunze, Katie (Author) / Gorin, Joanna (Thesis advisor) / Levy, Roy (Thesis advisor) / Green, Samuel (Committee member) / Arizona State University (Publisher)
Created2013