Attitudes, Confidence, and Achievement of High-Ability Fifth Grade Math Students

In this action research study of my fifth grade high-ability mathematics class, I investigated student attitudes of mathematics and their confidence in mathematics. Student achievement was compared to two different confidence scales to identify a relationship between confidence and achievement. Six boys and eleven girls gave their consent to the study. I discovered there seems to be a connection between confidence and achievement and that boys are generally more confident than girls. Most students liked math and were comfortable sharing answers and methods of solving problems with other students. As a result of this study I plan to use my survey and interview questions at the beginning of the school year with my new class in order to assess their attitudes and confidence in math. I can use this information to identify potential struggles and better plan for student instruction.

Spatial modelling and prediction on river networks: up model, down model or hybrid?

Preservation of rivers and water resources is crucial in most environmental policies and many efforts are made to assess water quality. Environmental monitoring of large river networks are based on measurement stations. Compared to the total length of river networks, their number is often limited and there is a need to extend environmental variables that are measured locally to the whole river network. The objective of this paper is to propose several relevant geostatistical models for river modeling. These models use river distance and are based on two contrasting assumptions about dependency along a river network. Inference using maximum likelihood, model selection criterion and prediction by kriging are then developed. We illustrate our approach on two variables that differ by their distributional and spatial characteristics: summer water temperature and nitrate concentration. The data come from 141 to 187 monitoring stations in a network on a large river located in the Northeast of France that is more than 5000 km long and includes Meuse and Moselle basins. We first evaluated different spatial models and then gave prediction maps and error variance maps for the whole stream network.

Strategies and Precise Vocabulary Knowledge: Exploring the Relationships Among Mathematics Vocabulary, Problem Solving, and Confidence

In this action research study I focused on my eighth grade pre-algebra students’ abilities to attack problems with enthusiasm and self confidence whether they completely understand the concepts or not. I wanted to teach them specific strategies and introduce and use precise vocabulary as a part of the problem solving process in hopes that I would see students’ confidence improve as they worked with mathematics. I used non-routine problems and concept-related open-ended problems to teach and model problem solving strategies. I introduced and practiced communication with specific and precise vocabulary with the goal of increasing student confidence and lowering student anxiety when they were faced with mathematics problem solving. I discovered that although students were working more willingly on problem solving and more inclined to attempt word problems using the strategies introduced in class, they were still reluctant to use specific vocabulary as they communicated to solve problems. As a result of this research, my style of teaching problem solving will evolve so that I focus more specifically on strategies and use precise vocabulary. I will spend more time introducing strategies and necessary vocabulary at the beginning of the year and continue to focus on strategies and process in order to lower my students’ anxiety and thus increase their self confidence when it comes to doing mathematics, especially problem solving.

Nurturing Young Students' Writing Knowledge, Self-Regulation, Attitudes, and Self-Efficacy: The Effects of Self-Regulated Strategy Development (SRSD)

The purpose of this study was to investigate the effectiveness of implementing the Self-Regulated Strategy Development (SRSD) model of instruction (Graham & Harris, 2005; Harris & Graham, 1996) on the writing skills and writing self-regulation, attitudes, self-efficacy, and knowledge of 6 first grade students. A multiple-baseline design across participants with multiple probes (Kazdin, 2010) was used to test the effectiveness of the SRSD instructional intervention. Each participant was taught an SRSD story writing strategy as well as self-regulation strategies. All students wrote stories in response to picture prompts during the baseline, instruction, independent performance, and maintenance phases. Stories were assessed for essential story components, length, and overall quality. All participants also completed a writing attitude scale, a writing self-efficacy scale, and participated in brief interviews during the baseline and independent performance phases. Results indicated that SRSD can be beneficial for average first grade writers. Participants wrote stories that contained more essential components, were longer, and of better quality after SRSD instruction. Participants also showed some improvement in writing self-efficacy from pre- to post-instruction. All of the students maintained positive writing attitudes throughout the study.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.