Thesis (Ed. D.)--Illinois State University, 1982. / Title from title page screen, viewed April 4, 2005. Dissertation Committee: Robert K. Rittenhouse (chair), Lanny E. Morreau, Ronald Halinski, Carol Mardell Czudnowski, Janet Hartman. Includes bibliographical references (leaves 107-110) and abstract. Also available in print.

No description available.

This study was to explore the process how a specified elementary school pushed school-based curriculum, there were three purposes of the study: 1.Through the practice of school-based curriculum, to understand existing curriculum development and judge the inner value and effectiveness. 2.Through the case research of school-based curriculum, to find the interaction of related individual, affair and object during planning and executing of school-based curriculum development. 3.Through the process of exploring school-based curriculum, to find the incompleteness for reference of pushing school-based curriculum. Than to build developing and executing mechanism of school-based curriculum. ...

This study examined the effect of intervention involving a humanoid robot on challenging or tantrum behaviors of four children with low-functioning autism spectrum disorders (ASD). The current work was part of a larger study involving the effect of the robot on functional communication skills on a variety of different interactions with different communication partners. All participants took part in a single-subject, multiple-baseline design with various session types including baseline, traditional play-based treatment, treatment including the robot, and follow-up sessions. For the purpose of this study, only the sessions including treatment with the robot where the robot interaction occurred at the beginning or the end of a 50-minute session were analyzed. Six different categories of tantrum behaviors were analyzed during the sessions including: crying/screaming; self-distracting behaviors; biting, hair pulling, squeezing or pinching; throwing/shoving; and hitting/kicking. Results indicate that for 3 out of the 4 children, tantrum behaviors decreased when the robot interaction came at the beginning of the session. The fourth child showed minimal change in tantrum behaviors. To improve understanding of the influence of a robot on children with ASD, future research should be conducted to determine what aspects of the robot interaction would be most effective on reducing these behaviors.

The purpose of this study is to discover the relationship between the specifications of medical institutes, FERCAP (Forum for Ethical Review Committees in Asia and the Western Pacific), TJCHA IRB Accreditation (Taiwan Joint Commission on Hospital Accreditation, TJCHA) and the practice of IRBs. By using questionnaires, and comparing the differences between all these medical institutes, we would have the information Research Ethics and the differentials in all the medical institutes. In this study, 268 completed questionnaires to the most southern region (64.7%), Medical Center (66.4%), physicians (36.9%), research assistants (21.3%), nurses (14.6%) and so on. About 60¢H can answer correctly of the knowledge of Human Research Ethics. We found that different medical institutions (Medical Centers and non-medical centers) and distinction (north, south and other regions) score differences in terms of cognition, in "human trials testing program information must be saved after three years", "IRB memberlist should be submitted to DOH", "study of individual or group characteristics or behavior (such as feeling, cognition, motivation, identity, language, communication, cultural beliefs or habits and social behavior, etc.) is expetided review " and "IRB membership and minutes should be open" have significantly difference (p <0.05). Also, we need to pay attention that only 30¢H of IRB members and staff have correct answer of "IRB memberlist should be submitted to DOH". Medical Centers and non-medical centers score differences in terms of attitude, in ¡uunit IRB that the information provided sufficient for you to understand the operation of the IRB¡v,¡uIRB promote education in human trials of great help to the project execution¡v,¡uIRB review process can focus on the implementation of the risk-benefit plans to provide specific advice¡v and ¡uyou are familiar with the regulations of the Department of Health ¡isuch as GCP, Medical Law and Research collected by the human body provides¡j¡vhave significantly difference (p <0.05). And expect the future to have further information for health policy evaluation and questionnaire data will be cross-comparison analysis of human trials to confirm the operation of the Board to provide further quality assurance and the IRB timely help.

Multilevel modeling represents a potentially viable method for meta-analyzing single-subject research, but questions remain concerning its methodological properties with regard to characteristics of single-subject data. For this dissertation, Monte Carlo methods were used to investigate the properties of a 3 level model (i.e., with a quadratic equation at level 1), and three different level 1 error specifications (i.e., different variance components and covariances of 0, lag-1 autoregressive covariance structures, and separate error terms for each phase, with different variance components and covariances of 0). Data for simulated subjects were generated to have characteristics typical of published single-subject data (e.g., typical variances and magnitudes of effect). Samples were simulated for conditions which varied in number of data points per phase, number of subjects per study, number of studies meta-analyzed, level of autocorrelation in residuals, and continuity of variance across phases. Outcome variables examined included rates of convergence of analyses, power for statistical tests of fixed effects, and relative parameter bias of estimates of fixed effects, random effects’ variance components, and autocorrelation estimates. Convergence rates were found to be 100% for all level 1 error specifications and data conditions. Power for statistical tests of fixed effects was observed to be adequate when 10 or more data points were generated per phase and 60 or more total subjects were included in meta-analyses. The relative biases of estimates of fixed effects were found to have limited associations with numbers of data points per phase, levels of autocorrelation, and the continuity/discontinuity of variance across phases. Random effects’ variance components were observed to be frequently biased. Associations between relative bias and data conditions were found to vary by random effect. Finally, autocorrelation estimates were found to be biased in all conditions for which autocorrelation was generated. Results are discussed with regard to study strengths and limitations, and their implications for the meta-analysis of single subject data and primary single subject research. / text

While enrolling in a college for a degree is still considered to be more of the expectation than the rule in households across the United States it is facing public criticism regarding its overall cost versus long-term benefits. This has prompted researchers to reevaluate practices in higher education to determine ways in which post-secondary institutions can improve their overall outcomes. In part, research indicates that this should include revisions to assessment, evaluation, and research (AER) practices. Currently, higher education faces many challenges associated with rigorous AER practices, which include an institutional focus on accountability measures, organizational challenges, and difficulties in operationally defining and measuring constantly changing definition for students, faculty, and higher education. These challenges have forced higher education to move away from rigorous quantitative designs that show causality. Additionally, higher education’s focus on large N research struggles to capture the unique identities and experiences of today’s college campus, which also poses challenges for the use of AER by practitioners across academic and student affairs. At present, new approaches to AER must be considered. The purpose of the current study was to propose and investigate one potential way to supplement large N AER with the use of single-subject research design (SSRD). Using visual analysis and the calculation of effect sizes with nonoverlap of all pairs (NAP), archival data from a unique behavioral program in a post-secondary transition program located at a land-grant institution in the southeastern United States was evaluated to determine if its implementation reduced student referrals at the program (N =25) and cohort level between Fall 2019 to Spring 2020. Results indicated that the behavioral program was most effective at the program level but had variable results at the cohort level. These results indicate that SSRD can be an effective approach to AER practices in higher education and would adequately supplement and potentially inform further large N research with its ability address to assess smaller populations.

This study contributes to the existing literature on treatment integrity (TI) by presenting TI findings across interventions aimed at the development of social emotional skills in learners with emotional and behavioural disorders. Social and emotional skills were selected as the target for our investigation given the significance of these skills in relation to the academic and behavioural success of learners and the challenges most often faced in these skill areas by students with emotional and behaviour disorders (E/BD). The study analysed single-subject experimental studies from 2000 to 2009 in two leading journals in the field of emotional and behaviour disorders: Behavior Disorders and The Journal of Emotional Behavioral Disorders. The degree to which studies operationally defined independent variables and evaluated and reported measures of treatment integrity and associated risk factors is reported. Thirty-three studies met the inclusion criteria for the present study and TI was evaluated across six variables (1) year published, (2) dependent variable(s), (3) independent variables(s), (4) participant characteristics, (5) treatment agent and (6) assessment of TI. Results indicated that approximately 49% of the studies monitored and reported TI, meaning that they provided a description of the TI procedure and resultant data. Findings from the study point to the need for attention to TI both in the description of methods used and in the reporting of TI data.

Athletes who merit the title ‘elite’ are rare and differ both quantitatively and qualitatively from athletes of lower qualifications. Serving and studying elite athletes may demand non-traditional approaches. Research involving elite athletes suffers because of the typical nomothetic requirements for large sample sizes and other statistical assumptions that do not apply to this population. Ideographic research uses single-athlete study designs, trend analyses, and statistical process control. Single-athlete designs seek to measure differences in repeated measurements under prescribed conditions, and trend analyses may permit systematic monitoring and prediction of future outcomes. Statistical process control uses control charting and other methods from management systems to assess and modify training processes in near real-time. These methods bring assessment and process control into the real world of elite athletics.

This study presents a set of data analysis approaches for single subject designs (SSDs). The primary purpose is to establish a series of statistical models to supplement visual analysis in single subject research using Bayesian estimation. Linear modeling approach has been used to study level and trend changes. I propose an alternate approach that treats the phase change-point between the baseline and intervention conditions as an unknown parameter. Similar to some existing approaches, the models take into account changes in slopes and intercepts in the presence of serial dependency. The Bayesian procedure used to estimate the parameters and analyze the data is described. Researchers use a variety of statistical analysis methods to analyze different single subject research designs. This dissertation presents a series of statistical models to model data from various conditions: the baseline phase, A-B design, A-B-A-B design, multiple baseline design, alternating treatments design, and changing criterion design. The change-point evaluation method can provide additional confirmation of causal effect of the treatment on target behavior. Software codes are provided as supplemental materials in the appendices. The applicability for the analyses is demonstrated using five examples from the SSD literature.