Students As Sequential Decision-Makers: Quantifying the Impact of Problem Knowledge and Process Deviation on the Achievement of Their Design Problem Objective

Shergadwala, Murtuza; Bilionis, Ilias; Panchal, Jitesh H.

doi:10.1115/detc2018-85537

Cited by 6 publications

(1 citation statement)

References 19 publications

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“…We note that domain knowledge and problem-specific aspects of the engineering design process influence design outcomes [35,37]. Such aspects are difficult to teach as a part of the engineering education curricula [36]. The understanding of the design of AI agents with a theory of mind that would assist esports players in discovering strategies could also be leveraged by engineering design teams.…”

Section: Broader Implications: Engineering Design and Design Educationmentioning

confidence: 99%

Esports Agents with a Theory of Mind: Towards Better Engagement, Education, and Engineering

Shergadwala¹,

El-Nasr²

2021

Preprint

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The role of AI in esports is shifting from leveraging games as a testbed for improving AI algorithms to addressing the needs of the esports players such as enhancing their gaming experience, esports skills, and providing coaching. For AI to be able to effectively address such needs in esports, AI agents require a theory of mind, that is, the ability to infer players' tactics and intents. To that end, in this position paper, we argue for human-in-the-loop approaches for the discovery and computational embedding of the theory of mind within behavioral models of esports players. We discuss that such approaches can be enabled by player-centric investigations on situated cognition that will expand our understanding of the cognitive and other unobservable factors that influence esports players' behaviors. We conclude by discussing the implications of such a research direction in esports as well as broader implications in engineering design and design education. CCS CONCEPTS• Human-centered computing → User models; HCI theory, concepts and models.

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Section: Broader Implications: Engineering Design and Design Educationmentioning

confidence: 99%

Esports Agents with a Theory of Mind: Towards Better Engagement, Education, and Engineering

Shergadwala¹,

El-Nasr²

2021

Preprint

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How Does Past Performance of Competitors Influence Designers’ Cognition, Behaviors, and Outcomes?

Shergadwala¹,

Panchal

Bilionis

2022

Journal of Mechanical Design

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Existing literature on information sharing in contests has established that sharing contest-specific information influences contestant behaviors, and thereby, the outcomes of a contest. However, in the context of engineering design contests, there is a gap in knowledge about how contest-specific information such as competitors' historical performance influences designers' actions and the resulting design outcomes. To address this gap, the objective of this study is to quantify the influence of information about competitors' past performance on designers' belief about the outcomes of a contest, which influences their design decisions, and the resulting design outcomes. We focus on a single-stage design competition where an objective figure of merit is available to the contestants for assessing the performance of their design. Our approach includes (i) developing a behavioral model of sequential decision-making that accounts for information about competitors' historical performance, and (ii) using the model in conjunction with a human-subject experiment where participants make design decisions given controlled strong or weak performance records of past competitors. Our results indicate that participants spend greater efforts when they know that the contest history reflects that past competitors had a strong performance record than when it reflects a weak performance record. Moreover, we quantify cognitive underpinnings of such informational influence via our model parameters. Based on the parametric inferences about participants' cognition, we suggest that contest designers are better off not providing historical performance records if past contest outcomes do not match their expectations set up for a given design contest.

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Students’ Decision-Making in a Product Design Process: An Observational Study

Shergadwala

Panchal

Ramani

2019

Volume 3: 21st International Conference on Advanced Vehicle Technologies; 16th International Conference on Design Education

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The objective of this study is to investigate students’ decision-making during the information gathering activities of a design process. Existing literature in engineering education has shown that students face difficulties while gathering information in various activities of a design process such as brainstorming and CAD modeling. Decision-making is an important aspect of these activities. While gathering information, students make several decisions such as what information to acquire and how to acquire that information. There lies a research gap in understanding how students make decisions while gathering information in a product design process. To address this gap, we conduct semi-structured interviews and surveys in a product design course. We analyze the students’ decision-making activities from the lens of a sequential information acquisition and decision-making (SIADM) framework. We find that the students recognize the need to acquire information about the physics and dynamics of their design artifact during the CAD modeling activity of the product design process. However, they do not acquire such information from their CAD models primarily due to the lack of the project requirements, their ability, and the time to do so. Instead, they acquire such information from the prototyping activity as their physical prototype does not satisfy their design objectives. However, the students do not get the opportunity to iterate their prototype with the given cost and time constraints. Consequently, they rely on improvising during prototyping. Based on our observations, we discuss the need for designing course project activities such that it facilitates students’ product design decisions.

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Students As Sequential Decision-Makers: Quantifying the Impact of Problem Knowledge and Process Deviation on the Achievement of Their Design Problem Objective

Cited by 6 publications

References 19 publications

Esports Agents with a Theory of Mind: Towards Better Engagement, Education, and Engineering

Esports Agents with a Theory of Mind: Towards Better Engagement, Education, and Engineering

How Does Past Performance of Competitors Influence Designers’ Cognition, Behaviors, and Outcomes?

Students’ Decision-Making in a Product Design Process: An Observational Study

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