The Mississippi Student Progress Monitoring System (MSPMS) was developed for the Mississippi Department of Education to be used to monitor student progress on the state framework which constitutes the curriculum for each course taught in Mississippi schools. This study was designed to investigate teachers’ perceptions of the implementation and use of the MSPMS. Research question 1 was to determine if the various independent variables of age, level of education, years of experience as an educator, level of school where teaching, perceived level of computer and/or technology comfort, perceived level of computer and/or technology experience, subject area taught, number of MSPMS tests created, number of MSPMS tests given, amount of support provided, whether program works, and importance of information gained from MSPMS made any difference in teachers’ perceptions of the implementation and use of the MSPMS; and research question 2 was to determine whether the teachers’ perceptions and the various independent variables had any significant relationships. Research question 3 looked at teachers’ attitudes toward MSPMS. There were no statistically significant differences among the dependent and independent variables. Findings for research question 2 showed that there were no statistically significant correlations among the dependent and independent variables. However, correlations among the independent variables revealed statistically significant relationships between age and years of experience, subjects taught and school level taught, technology experience and level of education, and subjects taught and number of tests given. Examination of the response frequencies for situations in the vignettes for research question 3 revealed that teachers reported feeling more frustrated than anything else when confronted with adversities with the technologies or the MSPMS. All of the findings in this study are limited to a rural Mississippi school district using MSPMS.

The purpose of the present research was to examine the predictive validity of curriculum-embedded mastery-check measures (CEMs) for kindergarten students in Tier 2 intervention. Two studies examined the predictive validity, parsimony, and changing role of CEMs using a structural equation modeling (SEM) framework. Study 1 examined the ability of CEMs gathered throughout the kindergarten year to predict end-of-kindergarten latent reading outcomes. Study 2 examined the ability of kindergarten CEMs to predict end-of-first and end-of-second grade latent reading outcomes. Study 1 used SEM with two latent outcomes (i.e., phonemic and decoding) composed of diverse measures of early reading skills gathered at the end of kindergarten. Findings indicated moderate to large effects, as measured by variance explained, for CEMs on predicting phonemic and decoding outcomes. For CEMs gathered at four time points throughout the kindergarten year, a parsimonious set of subtests emerged. In addition, the role of CEMs changed throughout the year as predictors reaching statistical significance were increasingly difficult. Findings indicated that an increased amount of variance could be explained on the outcomes measures as the year progressed. Study 2 used one latent reading outcome factor gathered at the end of first and second grades. Findings for the end of first grade indicated that parsimonious sets of predictors from CEMs administered at three times during the kindergarten year predicted end-of-first grade outcomes. Additionally, the role of indicators changed during the year and the amount of variance explained increased from the first to third CEM. Results for the end of second grade indicated the variance explained on the outcome measure increased from the first CEM to the third CEM. When considering near-significant results, a pattern emerged demonstrating parsimonious subsets of indicators that changed during the kindergarten year. Findings from both studies provided support for the predictive validity of CEMs gathered during kindergarten for students in Tier 2 intervention. Results from both studies demonstrated statistically significant subsets of predictors that emerged and changed during the kindergarten year congruent with reading development, which can be useful for informing educational decisions.

The purpose of this study was to determine if there were differences in MCT2 scores between students who attended a school district that used MSPMS and students who attended a school district that did not use MSPMS. The data for this study were archived and consisted of math and language arts MCT2 scores for two groups of students. The independent variable was the use of MSPMS for progress monitoring and the dependent variable was student scores on the MCT2. All data were analyzed using the Analysis of Covariance (ANCOVA) statistical procedure. In this study the 2008-2009 math and language arts MCT2 scores were the covariate. Hypothesis one stated that there was no statistically significant difference in the MCT2 language scores of students in Grades 4-8 in a school district using MSPMS and MCT2 language scores of students in Grades 4-8 in a district not using MSPMS while controlling for pre-test differences. The results of the first hypothesis indicated that there was a statistically significant difference between the 2009-2010 language arts MCT2 scores of a school district that used MSPMS and a district that did not use MSPMS. The district that did not use the MSPMS had higher MCT2 Language Arts overall and higher scores in fourth and sixth grades. Hypothesis two stated that there was no statistically significant difference in the MCT2 math scores of students in grades 4-8 in a school district that used the MSPMS and MCT2 math scores of students in grades 4-8 in a district that did not use the MSPMS while controlling for pre-test differences. The results of the second hypothesis indicated that there was not a significant difference in the 2009-2010 math MCT2 scores of the school district that used the MSPMS and the school district that did not use the MSPMS. The district that did not use the MSPMS had higher MCT2 Math scores overall and higher scores in sixth grade. The district that did use the MSPMS had higher MCT2 math scores in eighth grade. Further study should explore larger populations, assessment instruments of different lengths and fidelity of teacher implementation.

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Construction progress monitoring allows schedule and/or cost deviations to be identified early enough to effectively implement corrective actions. At least 77% of transportation projects experience cost overruns, and as much as 75% of these overruns have been attributed to “real” construction management factors like progress monitoring. Progress is measured on road construction sites in terms of completion percentages at various activity and work package levels. This percentage is then used to identify schedule deviations and support the earned value analysis often used as the baseline for contractor progress payments. Unfortunately, the current methods for producing these completion percentages are not as correct or time efficient as they should be to enable effective project control. The objective of this research is to develop, test, and validate a novel solution for automatically producing completion percentages and progress status determinations that are more correct and time efficient than those generated in current practice. The proposed solution seeks to automatically detect incremental progress on road design layers in 3D as-built point cloud data generated using unmanned aerial photogrammetry and a novel data simulation approach. A parallel as-planned progress estimate is also automatically prepared using 4D information, and the progress status determinations are made by comparing the two results. This solution was tested on 15 datasets (13 simulated and 2 real-world) representing a variety of road designs and progress conditions. The method achieved an average 95% F1 score in layer detection on the real-world data, and mostly outperformed current practice in correctness. The automated processing of as-built and as-planned data to produce the progress estimate took 12 seconds for the real world data, which was indeed faster than the current practice equivalent. Although the research objectives were met, there remains room for further improvement, particularly in regards to the solution’s robustness to occlusions on the monitored surfaces.

This thesis presents a real-time automated building progress monitoring solution for indoor environments using a mobile device. Such a system could prompt accurate and timely assessment of work progress that would allow managers to make adjustments and minimise both time and cost overrun when deviations from the schedule occur. Although many researchers have proposed approaches for progress monitoring in outdoor scenes, these cannot perform in real-time and shift into the complex interior environment. Research efforts for indoor environments are not fully automated and lead to errors in more complex scenes. Systems based on mobile devices could potentially enhance the inspection process and reduce the required time by allowing the inspector to acquire progress data by simply walking around the site. The main challenge of these systems is the tracking of the pose of the camera to achieve accurate alignment between the 3D design model and the real-world scene. Methods for estimating the user’s pose rely on a) tags on each target of interest, which require additional time and cost for installation and maintenance; b) pre-selected user locations, which restricts the user to those locations only; or c) GPS on the augmented reality headset, which only applies to outdoor inspections. Additionally, current mobile-based inspection systems do not perform any comparison between the captured as-built and the as-planned data. In this research, different marker-less Augmented Reality (AR) potential methods were implemented and tested for finding the most robust tracking solution. The Microsoft HoloLens was found to be the top performer for tracking the user’s pose and for overall user-experience. Next, a semi-automated method was developed for initially registering the 3D model to the real environment by exploiting information from detected floor and wall surfaces. Results showed that this method reduces the time of the initial registration by 58%. Having the 3D model aligned to the real environment and knowing the pose of the camera at every moment, an automated method was developed that exploits the captured as-built surface mesh data from the mobile device, compares it against the 3D design model and identifies in real-time whether an object has been built according to plan. Different parameters were tested for finding the optimum combination based on the current quality of mesh data. If quality of mesh data changes, then new parameters should be explored. Finally, the proposed solution was tested in real site conditions resulting in 76.6% precision, 100.0% recall, and 83.5% accuracy.

The Behavior Education Program was implemented with four students at a large sub-urban elementary school in central Texas. The elementary school has a diverse population of 750 students and was implementing Tier 1 interventions with 81% fidelity as measured by the School-wide Evaluation Tool. The BEP was implemented in a multiple-baseline design. All students’ behavioral improvement was measured through daily behavior rating scales, office discipline referrals and time sampling data. Academic engagement was measured through direct observation, DIBELS progress-monitoring and nine-week grades. Progress on BEP goals was then compared to direct observation data of on-task behavior and DIBELS data. All three students’ improvement on BEP goals correlated with an improvement in academic engagement and increased scoring on DIBELS progress monitoring indicating that progress in the area of behavior is linked to academic achievement.

Progress monitoring in construction involves a set of inspection tasks with repetitive in-person observations on the site. The current manual inspection process is time-consuming, inefficient, inconsistent, and has many safety risks to project inspectors. Cyber-Physical Systems (CPS) are networks of integrated physical and cyber components, such as robots, sensors, actuators, cloud computing, artificial intelligence, and the building itself. Introducing CPS for construction progress monitoring can reduce risks involved in the process, improve efficiency, and enable remote progress monitoring. A robotic CPS uses a robot as the core component of the CPS. But human interaction with technology plays an important role in the successful implementation of any technology. This research studied the human-centered design of a CPS from a human-computer interaction perspective for facilitating construction progress monitoring that puts the needs and abilities of humans at the center of the development process. User experience and interactions play an important role in human-centered design. This study first develops a CPS framework to autonomously collect visual data and facilitate remote construction progress monitoring. The two types of interactions occur between the human and the CPS – the human provides input for the CPS to collect data referred to as mission planning, and CPS provides visual data to enable the human to perform progress analysis. The interaction may occur through different modalities, such as visual, tactile, auditory, and immersive. The goal of this research is to understand the role of human interactions with CPS for construction progress monitoring. The study answers five research questions – a) What robotic CPS framework can be applied in construction progress monitoring? b) To what extent is the proposed CPS framework acceptable as an alternative to traditional construction progress monitoring? c) How can natural interaction modalities like hand gestures and voice commands be used as human-CPS interaction modalities for the proposed CPS? d) How does the human interaction modality between the proposed CPS and its user affect the usability of the proposed CPS? e) How does the human interaction modality between CPS and its user affect the performance of the proposed CPS?. To answer the research questions, a mixed-method-based methodology is used in this study. First, a systematic literature review is performed on the use of robots in inspection and monitoring of the built environment. Second, a CPS framework for remote progress monitoring is developed and evaluated in lab conditions. Third, a set of industry experts experienced with construction progress monitoring are interviewed to measure their acceptance of the developed CPS and to collect feedback for the evaluation of the CPS. Fourth, two methodologies are developed to use hand gesture and voice command recognition for human-CPS interaction in progress monitoring. Fifth, the usability and performance of the CPS are measured for identified interaction modalities through a human subject study. The human subjects are also interviewed post-experiment to identify the challenges they faced in their interactions with the CPS. The study makes the following contributions to the body of knowledge – a) key research areas and gaps were identified for robots in inspection and monitoring of the built environment, b) a fundamental framework for a robotic CPS was developed to automate reality capture and visualization using quadruped robots to facilitate remote construction progress monitoring, c) factors affecting the acceptance of the proposed robotic CPS for construction progress monitoring were identified by interviewing construction experts, d) two methodologies for using hand gestures and voice commands were developed for human-CPS interaction in construction progress monitoring, e) the effect of human interaction modalities on the usability and performance of the proposed CPS was assessed in construction progress monitoring through user studies, f) factors affecting the usability and performance of the proposed CPS with different interaction modalities were identified by conducting semi-structured interviews with users. / Doctor of Philosophy / Progress monitoring in construction involves inspecting and observing the construction site in person. The current manual inspection process is slow, inefficient, inconsistent, and risky for inspectors. Cyber-Physical Systems (CPS) are networks that integrate physical and digital components like robots, sensors, cloud computing, and artificial intelligence. Implementing CPS in construction progress monitoring can reduce risks, improve efficiency, and enable remote monitoring. A robotic CPS uses a robot as its core component. However, acceptance of the technology by people in the industry is crucial for successful implementation. Past literature has suggested human-centered design of technology for better acceptance of the technology. This research focuses on the human-centered design of a robotic CPS for construction progress monitoring, by focusing on the role of human-CPS interactions. User experience and interactions are important in human-centered design. The study develops a CPS framework that autonomously collects visual data and facilitates remote progress monitoring. The interactions between humans and CPS involve the human providing input for data collection (called mission planning) and the CPS providing visual data for progress analysis. The research aims to understand the role of human interactions with CPS in construction progress monitoring and answers five research questions. To answer these questions, a mixed-methods methodology is used. The CPS framework is developed and evaluated in lab conditions, industry experts are interviewed for their acceptance and feedback, methodologies are developed to recognize hand gestures and voice commands for human-CPS interaction, and usability and performance of the CPS are measured through human subject studies. Key contributions are made in this research in terms of identification of the application domains of CPS in inspection and monitoring of buildings and infrastructure, a CPS framework for remote progress monitoring, identification of the factors affecting acceptance of CPS in construction progress monitoring, development of methodologies to use hand gestures and voice commands for interactions with CPS, assessment of the effect of interaction modalities on the user experience with the CPS.

Reciprocal teaching comprehension-monitoring is a reading comprehension instructional procedure that combines four instructional strategies: predicting, summarizing, questioning, and clarifying to enhance students' comprehension of text. The procedure is a dialogue between the teacher and the students. During reciprocal teaching instruction, the teacher and students take turns leading the dialogue in order to enhance the students' comprehension-monitoring skills. The research on reciprocal teaching has included meta-analyses, group designs, qualitative designs, and single-subject research designs. These studies have identified gaps in the literature to include the measurement of treatment fidelity and treatment acceptability, as well as the psychometric properties of the instruments used to measure daily reading comprehension growth. These gaps were investigated in this study. The purpose of this study was to investigate the effects of reciprocal teaching comprehension-monitoring with a group of fifteen 3rd grade students reading at grade level. Specifically, this study investigated the use of curriculum-based measurement maze probes (CBM-maze probes) to formatively assess the reading comprehension growth of the students. Additionally, this study implemented treatment integrity procedures and investigated the acceptability of reciprocal teaching and the CBM-maze probes through a treatment acceptability rating scale. A multiple baseline across groups with three phases (baseline, intervention, follow-up) was employed. Overall, visual analysis of the data suggested reciprocal teaching was an effective intervention in increasing reading comprehension abilities in students as measured by the CBM-maze probes. All three groups exhibited continual growth on the daily comprehension measures across all three phases. Implications for practice, cautions in interpreting the results, and future directions are discussed.

The purpose of this quantitative study was to investigate the perceptions regular education teachers have of the Response to Intervention framework and the Progress Monitoring Process. Participants of the study included 246 K-3 regular education teachers from 4 Northeast Tennessee school systems. The survey achieved a 42% return rate for a total of 104 participants. Specifically, this research assessed K-3 regular education teachers’ perceptions of the RTI framework as a whole, their perceptions of the progress monitoring process, their perceptions of their readiness to implement an RTI framework, their perceptions of the effectiveness of the professional development opportunities they had been provided by their school systems regarding RTI, and their perceptions of the effectiveness of RTI on the academic growth of their at-risk students. The data sources analyzed consisted of a survey design using a 5-point Likert scale. Each research question had a corresponding null hypothesis. Each research question was analyzed with a series of one-tailed single sample t-tests with mid-point of the scale (3.0) as the test value representing neutrality. All data were analyzed at the .05 level of significance. Findings indicated that participants’ overall perceptions of the RTI framework were significantly positive.