Lower tolerance limits (LTLs) methods was used to estimate design values of furniture joints. To have higher reliability in joint, LTLs were chosen for higher confidence/proportional level. The logic behind phenomena is that if stress on joint exceeds the given LTLs, failure on joints is most likely observed. Therefore, joint sizes were determined to maintain internal stresses on joint below LTLs value corresponding to external load.

<div>Although design is part of everyday experience, increased proficiency in managing and reflecting while designing signify greater proficiency as a designer. This capacity for regulation in design is crucial for learning, including from failure experiences, while designing. Failure and iteration are integral parts of design, with potential cognitive and psychological ramifications. On the one hand, failure can be framed as a learning experience that interrupts thinking and evokes reflection. On the other hand, it can be detrimental for confidence and motivation or derail the design process. Based on similarities between design and self-regulation, I articulate a framework whereby responses to failure might be regulated by beginning designers. Then, this case study applies the framework to describe the experiences and perspectives of beginning designers as they work and fail, illuminating issues of failure in design and the extent of their self-regulation.</div><div><br></div><div>The in situ design processes of four teams was examined to describe self-regulation strategies among student designers. Analysis was conducted with two methods: linkography and typological thematic analysis. Linkography, based on think-aloud data, provided a visual representation of the design process and tools to identify reflection, planning, and critical moments in the design process. Typological analysis, based on think-aloud data, follow-up interviews, and design journals, was used to investigate specific strategies of self-regulation. The complementary methods contribute to understanding beginning designers’ self-regulation from multiple perspectives.</div><div><br></div><div>Results portray varied trajectories in design, ranging from repeated failure and determination to fleeting success and satisfaction. Class structures emerge in designers’ patterns of planning and reflection. These highlight the contextualized and evolutionary nature of design and self-regulation. Furthermore, linkographic evidence showed a beginning sense-making process, followed by oscillating phases of forward and backward thinking, to various degrees. Moments of testing, both successes and failure, were critically connected in the design process.</div><div><br></div><div>Thematic analysis identified 10 themes, aligning with the self-regulatory phases of forethought, performance, and reflection. The themes highlight how regulation in forethought is used to shape performance based on past iterations; meanwhile, the identification and attribution of failures relays information on how, and whether to iterate. Collectively, thematic findings reinforce the cyclical nature of design and self-regulation.</div><div><br></div><div>Design and self-regulation are compatible ways of thinking; for designers, the juxtaposition of these concepts may be useful to inform patterns of navigating the problem-solving process. For educators, the imposition of classroom structures in design and self-regulatory thinking draws attention to instructional design and assessment for supporting student thinking. And for researchers of design or self-regulation, these methods can give confidence for further exploration.</div>

Engineering designers commonly make sequential information acquisition decisions such as selecting designs for performance evaluation, selecting information sources, deciding whom to communicate with in design teams, and deciding when to stop design exploration. There is significant literature on normative decision making for engineering design, however, there is a lack of descriptive modeling of how designers actually make information acquisition decisions. Such descriptive modeling is important for accurately modeling design decisions, identifying sources of inefficiencies, and improving the design process. To that end, the research objective of the dissertation is to understand how designers make sequential information acquisition decisions and identify models that provide the best description of a designer’s decisions strategies. For gaining this understanding, the research approach consists of a synthesis of descriptive theories from psychological and cognitive sciences, along with empirical evidence from behavioral experiments under different design situations. Statistical Bayesian inference is used to determine how well alternate descriptive decision models describe the experimental data. This approach quantifies a designer's decision strategies through posterior parameter estimation and Bayesian model comparison. <br><br>Two research studies, presented in this dissertation, focus on assessing the effects of monetary incentives, fixed budget, type of design space exploration, and the availability of system-wide information on information acquisition decisions. The first study presented in this dissertation investigates information acquisition by an individual designer when multiple information sources are available and the total budget is limited. The results suggest that the student subjects' decisions are better represented by the heuristic-based models than the expected utility(EU)-based models. <br>While the EU-based models result in better net payoff, the heuristic models used by the subjects generate better design performance. The results also indicate the potential for nudging designers' decisions towards maximizing the net payoff by setting the fixed budget at low values and providing monetary incentives proportional to the saved budget.<br><br>The second study investigates information acquisition through communication. The focus is on designers’ decisions about whom to communicate with, and how much to communicate when there is interdependence between subsystems being designed. This study analyzes team communication of NASA engineers at a mission design laboratory (MDL) as well as of engineering students designing a simplified automotive engine in an undergraduate classroom environment. The results indicate that the rate of interactions increases in response to the reduce in system-level design performance in both settings. Additionally, the following factors seem to positively influence communication decisions: the pairwise design interdependence, node-wise popularity (significant with NASA MDL engineers due to large team size), and pairwise reciprocity.<br><br>The dissertation work increases the knowledge about engineering design decision making in following aspects. First, individuals make information acquisition decisions using simple heuristics based on in-situ information such as available budget amount and present system performance.<br>The proposed multi-discipline approach proves helpful for describing heuristics analytically and inferring context-specific decision strategies using statistical Bayesian inference. This work has potential application in developing decision support tools for engineering design. Second, the comparison of communication patterns between student design teams and NASA MDL teams reveals that the engine experiment preserves some but not all of the communication patterns of interest. We find that the representativeness depends not on matching subjects, tasks, and context separately, but rather on the behavior that results from the interactions of these three dimensions. This work provides lessons for designing representative experiments in the future.

<p>Engineering engagement programs use service learning and community engagement pedagogies that require a real-world situated problem in which the community partners who experience those problems are integral to those spaces. Despite community partners being integral to engineering engagement programs, research on community partner perspectives is vastly unrepresented in literature Therefore, the goal of this work is to investigate engineering engagement programs from the perspective of the community partners by answering the research question: what meaning do community partners make of their experience in engineering engagement programs? This study describes a qualitative research inquiry in which interviews with three community partners from three different engineering engagement programs were conducted and analyzed for community partner meaning. Using a framework developed by Zittoun and Brinkmann for meaning making, this study presented several themes associated with pragmatic, semantic, and existential meanings made by community partners within this study (2012).</p><p>Findings from this study suggest implications for expansions of existing frameworks of constituents and components of engineering engagement programs, as well as potential opportunities to more deeply engaging community partners the assessment of student contributions and trajectories as a function of participation in EEPs. Additionally, findings from this study suggest an opportunity to investigate communication and thinking between students and community partners to better support the experience of the community partner (and potentially, the learning of the students). Lastly, findings from this study suggest that participation in EEPs presents the opportunity for community partners to learn by doing which can be more deeply investigated to begin addressing the gap in the literature associated with community partners in research on engineering engagement spaces.</p>