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  • Purdue University
    West Lafayette, IN
    47907
Systems thinking is an essential skill for the future workforce. This study focuses on understanding students’ systems-thinking process via an agent-based model simulation. This study aimed to help students to improve their... more
Systems thinking is an essential skill for the future workforce. This study focuses on understanding students’ systems-thinking process via an agent-based model simulation. This study aimed to help students to improve their systems-thinking skills. We used a systems-thinking skills development framework to investigate and characterize students’ agent-based simulation assignment in the undergraduate level systems-methods course at a university in the American Midwest. We identified and characterized patterns of students’ systems-thinking processes based on four criteria: thinking, decision making, action, and interpretation. We classified students into three categories based on their systems-thinking abilities and qualitatively identified the least and most prominent patterns the students exhibited.
Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool... more
Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool available on the market for their cases to make sure they do not overlook any evidence resides in suspect device within a reasonable time frame. This is however hard decision to make, since learning and testing all available tools make their job only harder. In this paper, we define the digital forensics tool selection for a specific investigative task as a multi-armed bandit problem assuming that multiple tools are available for an investigator’s use. In addition, we also created set of disk images in order to create a real dataset for experiments. This dataset can be used by digital forensics researchers and tool developers for testing and validation purposes. In this paper, we also simulated multi-armed bandit algorithms to test whether using these al...
ABSTRACT
ABSTRACT
ABSTRACT This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the... more
ABSTRACT This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the same learning design and adapted it to three different populations, settings, and classroom contexts: at the middle-school, high-school, and pre-service teaching levels. Although the classroom orchestration of the particular learning design was customised for specific audiences and contexts, findings from this study suggest that the core components of the learning design, such as content, assessment, and pedagogy, and their alignment among them, resulted in students’ learning. Specifically, results from a pre-post science assessment suggest that the three student groups arrived at similar understanding post-intervention levels, along with a significant aggregate growth in their scientific understanding. Regarding design performance, students in different groups demonstrated different levels of success in meeting design constraints. The findings also suggest that students’ success rate in meeting the design constraints directly influenced their final design performance, where middle-school students had better performance than students in the other groups. That is, across the board, students increased their conceptual understanding of heat transfer, Earth, and solar science and were able to produce feasible designs. Implications of the study include how learning experiences with engineering and science simulations should be designed so that teachers can adopt and adapt materials for their specific audiences, contexts, and settings.
In this dissertation, we build several game-theoretic models to explore animal contest behavior. Classical game theory predicts that respect for ownership or ”Bourgeois” behavior can arise as an arbitrary convention to avoid costly... more
In this dissertation, we build several game-theoretic models to explore animal contest behavior. Classical game theory predicts that respect for ownership or ”Bourgeois” behavior can arise as an arbitrary convention to avoid costly fights. The same theory also predicts that disrespect for ownership or ”anti-Bourgeois” behavior can evolve under the same conditions. However, Bourgeois is very common in nature, while anti-Bourgeois is very rare. In order to explain the rarity of antiBourgeois behavior, we create a single-round Hawk-Dove model with four pure strategies: Hawk or H, Bourgeois or B, anti-Bourgeois or X and Dove or D. We show that if intruders sometimes believe themselves to be owners, then the resulting confusion can broaden the conditions under which Bourgeois behavior is evolutionarily stable in the single-round Hawk-Dove game. We also develop a multi-period Hawk-Dove model that includes the effect of confusion over ownership. We determine the effect of ownership uncerta...
Information technology professionals are required to possess both technical and professional skills while functioning in teams. Higher education institutions are promoting teamwork by engaging students in cooperative and project-based... more
Information technology professionals are required to possess both technical and professional skills while functioning in teams. Higher education institutions are promoting teamwork by engaging students in cooperative and project-based learning environments. We characterized teams based on their collective orientations and evaluated their team performance in a cooperative project-based learning environment situated in a sophomore-level systems analysis and design course. We explored the orientation patterns in terms of goals, roles, processes, and interpersonal relations (GRPI). Specifically, we analyzed team retrospectives of 23 teams using a mixed-method approach. Findings characterized teams into balanced and unbalanced orientations. Teams with balanced orientations demonstrated a higher level of team performance in terms of academic achievement than the unbalanced category.
Scrum methodology is widely used in the information technology (IT) industry for the purposes of team-based iterative software development. However, limited studies have been conducted to explore the nature of interactions between a Scrum... more
Scrum methodology is widely used in the information technology (IT) industry for the purposes of team-based iterative software development. However, limited studies have been conducted to explore the nature of interactions between a Scrum Master and other team members and the effect of these interactions on team effectiveness. The aim of this study is to understand the interactions between the Scrum Master and other team members in an educational setting and propose and demonstrate an application of cooperative game theory for the same. Cooperative game theory can model scenarios where other team members can benefit from cooperating. Through the lens of the cooperative game-theoretic model, we investigated the strategies employed by the Scrum Master and other team members when involved in a semi-capstone IT project. Specifically, the study explored the team interaction between a Scrum Master and other team members at three different levels of team effectiveness: least effective, par...
Digital forensic investigations are getting harder and more time consuming everyday because of various problems including rapid advances in technology, wide variety of available devices in investigations, and large amount of data to be... more
Digital forensic investigations are getting harder and more time consuming everyday because of various problems including rapid advances in technology, wide variety of available devices in investigations, and large amount of data to be analyzed. In order to tackle with these issues, digital forensic tools are developed by open-source communities and software companies. These software products are released as a complete toolkit or standalone tools targeting specific tasks. In either case, digital forensic investigators use these tools based on their familiarity because of previous training experiences, available funding from their agencies/businesses, tool’s ease of use, etc. Moreover, using additional tools to verify the findings is a common practice in digital forensic investigations. This is particularly common when the previously selected tools do not generate an expected output. In this paper, we propose a game theoretic approach to the tool selection problem in order to help in...
Digital forensic investigations are getting harder and more time consuming everyday because of various problems including rapid advances in technology, wide variety of available devices in investigations, and large amount of data to be... more
Digital forensic investigations are getting harder and more time consuming everyday because of various problems including rapid advances in technology, wide variety of available devices in investigations, and large amount of data to be analyzed. In order to tackle with these issues, digital forensic tools are developed by open-source communities and software companies. These software products are released as a complete toolkit or standalone tools targeting specific tasks. In either case, digital forensic investigators use these tools based on their familiarity because of previous training experiences, available funding from their agencies/businesses, tool’s ease of use, etc. Moreover, using additional tools to verify the findings is a common practice in digital forensic investigations. This is particularly common when the previously selected tools do not generate an expected output. In this paper, we propose a game theoretic approach to the tool selection problem in order to help in...
Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool... more
Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool available on the market for their cases to make sure they do not overlook any evidence resides in suspect device within a reasonable time frame. This is however hard decision to make, since learning and testing all available tools make their job only harder. In this paper, we define the digital forensics tool selection for a specific investigative task as a multi-armed bandit problem assuming that multiple tools are available for an investigator's use. In addition, we also created set of disk images in order to create a real dataset for experiments. This dataset can be used by digital forensics researchers and tool developers for testing and validation purposes. In this paper, we also simulated multi-armed bandit algorithms to test whether using these algorithms would be more successful than using simple randomization (non-MAB method) during the tool selection process. Our results show that, bandit based strategies successfully analyzed up to 57% more disk images over 1000 simulations. Finally, we also show that our findings satisfy a high level of statistical confidence. This work will help investigators to spend more time on the analysis of evidence than learning and testing different tools to see which one performs better.
This study employs an Agent-Based Model with Evolutionary Game Theory. First, we utilize a stock market simulation with four heterogeneous trader types: Momentum, contrarian, long term and speculative. They have deterministic decision... more
This study employs an Agent-Based Model with Evolutionary Game Theory.  First, we utilize a stock market simulation with four heterogeneous trader types:  Momentum, contrarian, long term and speculative. They have deterministic decision rules, and they are given realistic trading conditions such as wealth constraints and learning behaviors. Their interactions are applied to a simulated stock market where we were able to replicate the quasi-random dynamic behavior of an actual stock market. Each trader also has the ability to change its trader type based on its past trading performance and its competitors past performance. In the long run equilibrium, long term traders dominate the stock market; the number of momentum and contrarian traders remain relatively low.  In terms of relative total wealth, however, speculators hold almost half of the entire wealth that is invested in the stock market simulation. The results are very realistic compared to the long-term sustainable equilibrium in a continuous price-discovery process, such as the stock market. Secondly, we focus on understanding the behavior of the stock market traders by utilizing an evolutionary game theory model. This study is the first in literature to employ such theoretical analysis with four types of traders. We allow each trader type to have its own strategy to make trading decisions in the stock market to maximize wealth.  Each trader tries to maximize its payoff by changing the trading strategies with the consideration of learning and wealth constraints. However, each trading strategy will incur two types of costs: time value of money and transaction costs. We predict a variety of realistic trading strategies that have been documented in real-life stock market equilibrium.
Research Interests:
Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool... more
Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool available on the market for their cases to make sure they do not overlook any evidence resides in suspect device within a reasonable time frame. This is however hard decision to make, since learning and testing all available tools make their job only harder. In this paper, we define the digital forensics tool selection for a specific investigative task as a multi-armed bandit problem assuming that multiple tools are available for an investigator's use. In addition, we also created set of disk images in order to create a real dataset for experiments. This dataset can be  used by digital forensics researchers and tool developers for testing and validation purposes. In this paper, we also simulated multi-armed bandit algorithms to test whether using these algorithms would be more successful than using simple randomization (non-MAB method) during the tool selection process. Our results show that, bandit based strategies successfully analyzed up to 57% more disk images over 1000 simulations. Finally, we also show that our findings satisfy a high level of statistical confidence. This work will help investigators to spend more time on the analysis of evidence than learning and testing different tools to see which one performs better.
Research Interests:
An early prediction of game theory was that respect for ownership—“Bourgeois” or B behaviour—can arise as an arbitrary convention to avoid costly disputes. However, its mirror-image—the dispute-avoiding “anti- Bourgeois” or X behavior... more
An early prediction of game theory was that respect for ownership—“Bourgeois” or B behaviour—can
arise as an arbitrary convention to avoid costly disputes. However, its mirror-image—the dispute-avoiding “anti-
Bourgeois” or X behavior through which owners concede their property to intruders—also corresponds to an
evolutionarily stable strategy (ESS) under the same conditions. It has since been found repeatedly that first finders
of valuable resources are frequently left unchallenged in nature, while evidence for ceding property to intruders
without a contest is rare at best. An early verbal rationale for the observed rarity of X was that two individuals
employing such behaviour over repeated rounds would be interchanging roles repeatedly, a potentially inefficient
outcome known as “infinite regress.” This argument was formalized only recently, through a Hawk-Dove model
with ownership asymmetry and a fixed probability w that two individuals meet again. The analysis showed that
if w and the cost of fighting exceed thresholds determined by the costs of assuming and relinquishing ownership,
then B becomes the only stable convention. However, contrary to expectation, and despite the inefficiency of the X
equilibrium, the analysis also showed that “infinite regress” does not invariably render X unviable. Nevertheless,
this model dealt only with ESSs at which respect for ownership is either absolute or entirely absent. Here we
extend the model to allow for polymorphic evolutionarily stable states, and we use it to explore the conditions that
favor partial respect for ownership. In this way we produce an analytic model that predicts a range of degrees of
partial respect for ownership, dependent on model parameters. In particular, we identify a pathway through which
any degree of respect for ownership can evolve from absolute disrespect under increasing w with increasing costs
of fighting.
Research Interests:
Abstract Classical evolutionary game theory shows that respect for ownership (“Bourgeois” behavior) can arise as an arbitrary convention to avoid costly disputes, but the same theory also predicts that a paradoxical disrespect for... more
Abstract
Classical evolutionary game theory shows that respect for ownership (“Bourgeois” behavior) can arise as an arbitrary convention to avoid costly disputes, but the same theory also predicts that a paradoxical disrespect for ownership (“anti-Bourgeois” behavior) can evolve under the same conditions. Given the rarity of the latter strategy in the natural world, it is clear that the classical model is lacking in some important biological details. For instance, the classical model assumes that roles of owner and intruder can be recognized unambiguously. However, in the natural world there is often confusion over ownership, mediated for example by the temporary absence of the owner. We show that if intruders sometimes believe themselves to be owners, then the resulting confusion over ownership can broaden the conditions under which Bourgeois behavior is evolutionarily stable in the one-shot Hawk–Dove game. Likewise, introducing mistakes over ownership into a more realistic game with repeated interactions facilitates the evolution of Bourgeois behavior where previously such a result could arise only if owners are intrinsically more likely to win fights than intruders. Collectively, therefore, we find that mistakes over ownership facilitate the evolution of Bourgeois behavior. Nevertheless, relaxing the assumption that ownership is unambiguously recognized does not appear to completely explain the extreme rarity of anti-Bourgeois behavior in nature.
Research Interests: