Feedback contextualized to curriculum content and misconceptions is a crucial piece in any learning experience. However, looking through student code and giving feedback requires more time and resources than an instructor typically has available, delaying feedback delivery. Intelligent Tutors for teaching Programming (ITPs) are designed to immediately deliver contextualized feedback of high quality to several students. However, they take significant effort and expertise to develop courses and practice problems, making them difficult to adapt to new situations. Because of this, the most frequently used feedback techniques for immediate feedback systems focus on highlighting incorrect output or pointing out errors in student code. These systems allow for quick development of practice problems and are easily adaptable to new contexts, however, the feedback isn't contextualized to curriculum content and misconceptions. This dissertation explores the implications of the Misconception-Driven Student Model (MDSM) as a model for developing alternatives to the aforementioned methods. I explore the implications and impact of MDSM with relation to feedback through the following thesis: Authoring feedback using a cognitive student model supports student learning of programming. In this dissertation I review relevant cognitive theory and feedback systems and two quasi-experimental studies examining the efficacy of MDSM. / Doctor of Philosophy / Feedback contextualized to curriculum content and misconceptions is a crucial piece in any learning experience. However, looking through student code and giving feedback requires more time and resources than an instructor typically has available, delaying feedback delivery. Intelligent Tutors for teaching Programming (ITPs) are designed to immediately deliver contextualized feedback of high quality to several students. However, they take significant effort and expertise to develop courses and practice problems, making them difficult to adapt to new situations. Because of this, the most frequently used feedback techniques for immediate feedback systems focus on highlighting incorrect output or pointing out errors in student code. These systems allow for quick development of practice problems and are easily adaptable to new contexts, however, the feedback isn't contextualized to curriculum content and misconceptions. This dissertation explores the implications of the Misconception-Driven Student Model (MDSM) as a model for developing alternatives to the aforementioned methods. I explore the implications and impact of MDSM with relation to feedback through the following thesis: Authoring feedback using a cognitive student model supports student learning of programming. In this dissertation I review relevant cognitive theory and feedback systems and two quasi-experimental studies examining the efficacy of MDSM.

As a teaching approach, digital game-based learning (DGBL) has grown in popularity and can positively influence students' motivational perceptions in difficult subjects, such as mathematics. DGBL has the capability to provide immediate feedback to students that can impact their results and experiences during gameplay; specifically, research studies have supported the conclusion that immediate feedback featured in DGBL can positively influence elementary students' self-efficacy and motivation related to DGBL gameplay. However, few studies have investigated the specific types of immediate feedback featured in DGBL within elementary mathematics. The purpose of this qualitative study was to investigate how different types of immediate feedback (i.e., destination, corrective, and explanatory) featured during DGBL use in mathematics influence elementary students' self-efficacy and motivation for gameplay. This study involved fifth grade students interacting with a digital game and being interviewed individually to elaborate on their perceptions regarding how feedback featured in DGBL influenced their self-efficacy and motivation. Findings from this study suggest the importance of DGBL immediate feedback as results indicated a positive change in both self-efficacy and motivation among students. / Doctor of Philosophy / Digital game-based learning (DGBL) is a teaching method used to enhance learning that is facilitated by the use of a digital game. DGBL provides students with opportunities to interact with virtual worlds that incorporate educational content with the goal of engaging learners in all subjects. A challenge for educators is to select digital games that motivate students to engage in difficult subjects, such as mathematics. The articles here seek to better understand how DGBL can potentially influence elementary students' motivation, engagement, and assist elementary educators' future instructional decisions implementing DGBL in an elementary mathematics setting. The study investigated how different types of immediate feedback (i.e., destination, corrective, and explanatory) featured during DGBL use in mathematics influence elementary students' self-efficacy and motivation for gameplay. Research featured in both articles indicated the importance in understanding how different motivational factors can affect students' motivation during DGBL use, and how an increased motivation can lead to increased engagement, which can lead to increased learning.

Although there is general agreement that feedback plays an important role in student performance, the majority of the studies found in the research literature explore the impact of different types of feedback in a traditional and university-level setting. In order to explore the impact of different feedback types in a non-traditional distance learning setting, 352 high school students enrolled in courses offered through BYU's Independent Study (IS) department received either delayed feedback or immediate feedback generated by Speedback™, BYU's automated grading and feedback program, depending on whether they had opted to submit end of unit assignments by mail or computer. Results of a comparison of final exam scores indicated that those students receiving immediate feedback performed significantly better on course final exams, but surprisingly those who received delayed feedback completed course in significantly less time.

An After Action Review (AAR) is the Army training system's performance feedback mechanism. The purpose of the AAR is to improve team (unit) and individual performance in order to increase organizational readiness. While a large body of knowledge exists that discusses instructional strategies, feedback and training systems, neither the AAR process nor the AAR systems have been examined in terms of learning effectiveness and efficiency for embedded trainers as part of a holistic training system. In this thesis, different feedback methods for embedded training are evaluated based on the timing and type of feedback used during and after training exercises. Those feedback methodologies include: providing Immediate Directive Feedback (IDF) only, the IDF Only feedback condition group; using Immediate Direct Feedback and delayed feedback with open ended prompts to elicit self-elaboration during the AAR, the IDF with AAR feedback condition group; and delaying feedback using opened ended prompts without any IDF, the AAR Only feedback condition group. The results of the experiment support the hypothesis that feedback timing and type do effect skill acquisition, retention and transfer in different ways. Immediate directive feedback has a significant effect in reducing the number of errors committed while acquiring new procedural skills during training. Delayed feedback, in the form of an AAR, has a significant effect on the acquisition, retention and transfer of higher order conceptual knowledge as well as procedural knowledge about a task. The combination of Immediate Directive Feedback with an After Action Review demonstrated the greatest degree of transfer on a transfer task.

Novice teachers in today's classroom are in need of support during the initial years of teaching. Providing beginning teachers in special education classroom settings with coaching and immediate feedback through Bug-In-Ear, Bluetooth technology has been identified as a effective strategy for supporting beginning teachers while simultaneously improving generalization and maintenance of instructional strategies in diverse classrooms (Anagnostopoulous, Smith & Basmadjian, 2007; Darling-Hammond and Baratz-Snowden, 2007; Brownell, Ross, Colon & McCallum, 2005). The present study was designed to examine the effects of using BIE, Bluetooth technology with novice teachers in inclusionary settings at a PK-5 charter school. As it has been demonstrated, Bug-In-Ear Bluetooth technology has allowed supervisors and mentors to increase desired teacher behaviors by providing immediate feedback, coaching and prompting during instructional delivery (Scheeler, McAfee, Ruhl and Lee (2006), Scheeler, Ruhl & McAfee, 2004; & Rock, et al., (2009). Specifically, this study looked to increase the average rate per minute of specific feedback statements made to students during reading instruction. Additionally, maintenance of increased rates of specific feedback once BIE coaching and prompting were withdrawn was also of interest. A multiple-baseline design across participants was used. Data were collected during baseline, intervention, and withdrawal phases. The independent variable was identified as prompts delivered by the coach through BIE Bluetooth technology. The dependent variable for this study was the average rate per minute of specific feedback statements made during reading instruction. Overall, the average rate per minute of specific feedback provided to students during reading instruction increased substantially with the use of Bug-In-Ear Bluetooth technology. Further, participants sustained higher than baseline averages of specific feedback provided to students. This study extended Scheeler (2004, 2006), and Rock's (2009) research on the use of immediate feedback through BIE technology, and demonstrated the effectiveness of this observation method with various participants, groups of students, and classroom diversity.

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The purpose of this study was to use a single subject research design to examine the effects of immediate feedback and delayed feedback within the Math to Mastery Intervention Package. The participants were 6 elementary school students who were performing approximately 1 year below grade level in math. A combined simple phase change design was used for the study. 3 of the students experienced the design in the A/B/A/C order, while the other 3 students experienced the design in a reversed order for B and C. During this study, ‘A’ represented the baseline phase and the return to baseline phase, ‘B’ represented the immediate feedback intervention phase, and ‘C’ represented the delayed feedback intervention phase. Each feedback phase was implemented separately for up to 4 weeks for each student. The final phase of intervention for each student included use of the most effective intervention condition after the student was exposed to both intervention feedback conditions. 2 weeks after the best intervention, follow-ups were conducted to determine if the students were able to maintain the skills that they were taught during the intervention. Results revealed that both intervention conditions were successful for addressing deficits in math academic performance. Improvement was seen for all 6 students with increases in digits correct per minute on single skill math worksheets, single skill math progress worksheets, and multiple skill math progress worksheets. Implications for school leadership within school settings are provided.

In manufacturing systems subject to machine and operator resource constraints the effects of rework can be profound. High levels of rework burden the resources unnecessarily and as the utilization of these resources increases the expected queuing time of work in process increases exponentially. Queuing models can help managers to understand and control the effects of rework, but often this tool is overlooked in part because of concerns over accuracy in complex environments and/or the need for limiting assumptions. One aim of this work is to increase understanding of system variables on the accuracy of simple queuing models. A queuing model is proposed that combines G/G/1 modeling techniques for rework with effective processing time techniques for machine availability and the accuracy of this model is tested under varying levels of rework, external arrival variability, and machine availability. Results show that the model performs best under exponential arrival patterns and can perform well even under high rework conditions. Generalizations are made with regards to the use of this tool for allocation of jobs to specific workers and/or machines based on known rework rates with the ultimate aim of queue time minimization.

Many professionals have successfully implemented discrete trial teaching in the past. However, there have not been extensive studies examining the accuracy of discrete trial teaching implementation. This study investigated the use of Bug in Ear feedback on the accuracy of discrete trial teaching implementation among two pre-service teachers majoring in elementary education and one pre-service teacher majoring in exceptional education. An adult confederate was used to receive discrete trial teaching. Implementing a multiple baseline across participants design, this study examined whether there was a functional relationship between receiving Bug in Ear feedback and the accuracy of discrete trial teaching implementation. The discrete trial teaching evaluation form was utilized to measure the accuracy of discrete trial teaching implementation. The findings demonstrated an increase in the discrete trial teaching implementation accuracy after Bug in Ear feedback was introduced. Participants agreed that using a self-instruction manual combined with receiving Bug in Ear feedback was beneficial in learning to implement discrete trial teaching