Effects of special educator peer coaching on general educator effectiveness in inclusive classroom settings

This dissertation investigated the effects of a peer coaching relationship between a special education teacher and two general education teachers. More specifically, a two-tier multiple baseline design across subjects was used to evaluate the effects of peer coaching on the general education teachers' use of effective instructional practices (EIPs) and subsequent effects on the engagement rate and academic performance of students with and without disabilities. The peer coaching process included modeling, direct support, and feedback on the use of effective instructional practices including getting student attention, giving specific directions, asking specific questions with wait time, contingent positive reinforcement, positive error correction, precorrection, prompting, and proximity control. A 30-second partial interval recording procedure was used to observe the general education teachers' use of effective instructional practices and student engagement rates. Student participants' academic performance was measured using weekly quizzes. ^ Peer coaching resulted in an overall increase in the teachers' use of EIPs. One general education teacher had a 30% increase in average EIP use from 46% during the baseline phase to 76% during intervention. Student engagement for her two student participants with and without disabilities indicated an increase from 54% to 69% and from 47% to 65% respectively. Results for the second general education teacher indicated a 34% increase in average EIP use from 55% during the baseline to 89% during intervention. Student engagement for the two student participants with and without disabilities in her class increased from 48% to 83% and from 29% to 71% respectively. Student academic performance showed a small increase. In follow-up observations, the effects of peer coaching on teacher use of EIPs and student engagement and academic performance were maintained. ^ The results of this study suggest that using peer coaching to support general education teachers can be an effective method to improve the educational outcomes of students with and without disabilities in general education. Further research is needed to investigate the effects of peer coaching with other special and general educator partnerships and other student participants. ^

Application of intervention analysis to evaluate the impacts of special events on freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

Application of Intervention Analysis to Evaluate the Impacts of Special Events on Freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.