2002 — 2006 |
Baylor, Amy |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Itr: Systematic Experimentation of the Role of Pedagogical Agent Features in Promoting Learning and Motivation @ Florida State University
This project systematically investigates the value of pedagogical agent features (*image: character, realism, gender, ethnicity; *animation: task-related, expressive; and *pre-defined agent roles: expert, motivational advisor, co-collaborator) in supporting learning-related outcomes. Using Multiple Intelligent Mentors Instructing Collaboratively (MIMIC) as the research environment, the standard experimental research design includes multiple factors and will be analyzed primarily via MANOVA. Additional micro-genetic data from logged agent-learner interactions and supplemental case studies triangulate the findings. All participants are individually randomly assigned to treatment conditions with large sample sizes (125-200 students), including educational technology undergraduate students from both a state university and a historically black university. The instructional content focuses upon the ill-structured domain of instructional planning with diverse learning outcomes, including metacognition, cognitive strategies, attitude/motivation, as well as traditional performance. Through extensive dissemination of results to the relevant multi-disciplinary communities, this project proposes to: a) illuminate principles of learning with pedagogical agents, b) facilitate computer scientists in prioritizing areas of future development for pedagogical agents; c) inform teachers of the most desirable characteristics of agent-based applications for their students; d) refine key features for pedagogical agents within distance learning course nvironments; and, e) advise instructional systems designers in developing training systems for industry and government.
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0.915 |
2004 — 2009 |
Plant, Elizabeth Ashby [⬀] Baylor, Amy |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Gse/Res: Pedagogical Agents as Social Models: Challenging Gender-Related Stereotypes of Engineering @ Florida State University
Florida State University will study the effectiveness of pedagogical agents as social models to influence girls' beliefs and stereotypes about engineering, the potential for using pedagogical agents to change beliefs.
Many females have negative and unconstructive beliefs regarding engineering. As stated by Muller (2002), these misperceptions are prompted by a social fabric that pervades our society and results in stereotypic perceptions of engineering and scientific fields as "geeky" and particularly inappropriate for girls and women. Consequently, young women need more exposure to productive beliefs about engineering, ideally through some form of a social model (e.g., Bandura, 1986). While human models can help to bridge the gap, the logistics of arranging such opportunities are difficult to coordinate, and available mentors may not necessarily best match a particular young women's needs. By implementing computer-based social models, factors can be controlled that cannot be in human mentors, with a greater potential for outreach through avenues such as the Internet. Pedagogical agents, which are three-dimensional, animated computer-based characters, are particularly advantageous for serving as such models given that there is strong evidence that students, particularly females, easily develop social relationships with them. However, there is limited evidence to guide the design of such agents for the purpose of influencing beliefs about engineering.
The goals of this interdisciplinary project are as follows: 1) to systematically investigate the effectiveness of pedagogical agents as social models to influence girls' beliefs and stereotypes about engineering; and, in parallel, 2) to use pedagogical agents as a vehicle to systematically examine the nature of the belief-changing process. Two populations, representing two age groups (middle school girls, and freshman female undergraduates from both a traditional and a historically-Black institution), will be sampled for the research. Three types of research designs (Choice, Construction, and System-Controlled Studies (experimental and adaptive)) will be implemented to provide a more integrative understanding. Specifically, the first year will focus on investigating agent appearance; the second year on agent message/delivery; and, the third year on agent persona (combined factors). Dependent variables include student beliefs about and motivation toward engineering, intentions to pursue engineering, and perceptions of the agent. Dependent variables will be assessed by a combination of self-report (e.g., Likert-scale items), performance, and behaviorally-indicated measures.
Intellectual Merit. Given that little is known as to the affordances and learner preferences for pedagogical agents as social models, this project is critical for advancing several interdisciplinary fields (e.g., instructional systems, social psychology, human-computer interaction, education/training, ecommerce and marketing, and game designers). By integrating multiple research approaches, the project is creative and original and draws on the two PIs' experience conducting pedagogical agent and social psychology research. Importantly, it will provide insight for influencing females' beliefs and stereotypes regarding engineering. Results will also complement ongoing development of pedagogical agents and other technology-mediated learning, such as intelligent tutoring systems. Along this line, the research will also help better illuminate the social impact of agents as an information technology, which is important given that society is becoming increasingly more information-driven.
Broader Impact. It is expected that the project will build a strong empirical research base in this area with guidelines for designing agents to support engineering (or other types of) belief adoption. These findings will have the potential to broadly influence computer interface design, agent implementations in learning environments, and have marketing-related implications for other projects that involve "selling" engineering to females. Based on the findings, the next step would be to develop and implement a highly competent (e.g., artificially intelligent) and persuasive agent that would positively impact young women's beliefs about engineering.
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0.915 |
2006 — 2011 |
Seel, Norbert Johnson, Tristan [⬀] Baylor, Amy |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Dru Collaborative Research: Understanding Mental Models of Expertise in Construction Management Using Interactive Adaptive Simulations @ Florida State University
This research uses recent advances in simulations and data analysis techniques to investigate the cognitive and engineering aspects of decision making in complex dynamic construction management scenarios. Expertise plays a crucial role in managing crisis scenarios that call for critical decision making under constraints of time, resource, and rapidly unfolding events. An example of such a crisis scenario is managing complex heavy construction projects. In such scenarios, effective decision making requires knowledge of complex inter-relationships between several simultaneous events and preparing for the uncertainty and risks arising from feedbacks in time and space. Such knowledge is inductively constructed by assimilating and organizing experiential knowledge into patterns of information that are difficult to formalize or analytically perceive. The researchers propose to investigate the dynamics and variation of such cognitive knowledge organization patterns, or mental models, of decision making, specifically among construction managers.
This goal of this research effort will be to use an interdisciplinary approach to understand how expert and novice construction managers differ in their knowledge organization, information processing, risk assessment, and decision making in construction management crisis scenarios. Interactive, adaptive simulations of critical construction scenarios will be developed in collaboration with construction management firms, and expert and novice construction managers will be tested in them to capture human-subject interaction data that will be analyzed to develop mental models of expertise. In addition, an instructional interface will be integrated into the simulation using pedagogical agents, and it will be deployed in the construction management curriculum to test its effectiveness as a training environment for novice decision makers. This will also allow the researchers to investigate how novices construct knowledge in simulated training environments.
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0.915 |