Amy L. Baylor

What Factors Facilitate Teacher Skill, Teacher Morale, and Perceived Student Learning in Technology-Using Classrooms?

Abstract Based on a comprehensive study of 94 classrooms from four states in different geographic regions of the country, this quantitative study investigated the impact of seven factors related to school technology (planning, leadership, curriculum alignment, professional development, technology use, teacher openness to change, and teacher non-school computer use) on five dependent measures in the areas of teacher skill (technology competency and technology integration), teacher morale, and perceived student learning (impact on student content acquisition and higher order thinking skills acquisition). Stepwise regression resulted in models to explain each of the five dependent measures. Teacher technology competency was predicted by teacher openness to change. Technology integration was predicted by teacher openness to change and the percentage of technology use with others. Teacher morale was predicted by professional development and constructivist use of technology. Technology impact on content acquisition was predicted by the strength of leadership, teacher openness to change, and negatively influenced by teacher non-school computer use. Technology impact on higher-order thinking skills was predicted by teacher openness to change, the constructivist use of technology, and negatively influenced by percentage of technology use where students work alone. Implications for the adoption and use of school technologies are discussed.

Pedagogical agent design: The impact of agent realism, gender, ethnicity, and instructional role

In the first of two experimental studies, 312 students were randomly assigned to one of 8 conditions, where agents differed by ethnicity (Black, White), gender (male, female), and image (realistic, cartoon), yet had identical messages and computer-generated voice. In the second study, 229 students were randomly assigned to one of 12 conditions where agents represented different instructional roles (expert, motivator, and mentor), also differing by ethnicity (Black, White), and gender (male, female). Overall, it was found that students had greater transfer of learning when the agents had more realistic images and when agents in the expert role were represented non-traditionally (as Black versus White). Results also generally confirmed prior research where agents perceived as less intelligent lead to significantly improved self-efficacy. The presence of motivational messages, as employed through the motivator and mentor agent roles, led to enhanced learner self-regulation and self-efficacy. Results are discussed with respect to social cognitive theory.

Pedagogical agents as learning companions: the impact of agent emotion and gender

The potential of emotional interaction between human and computer has recently interested researchers in human–computer interaction. The instructional impact of this interaction in learning environments has not been established, however. This study examined the impact of emotion and gender of a pedagogical agent as a learning companion (PAL) on social judgements, interest, self-efficacy, and learning. Two experiments investigated separately the effects of a PAL’s emotional expression and empathetic response. Experiment 1 focused on emotional expression (positive vs. negative vs. neutral) and gender (male vs. female) with a sample of 142 male and female college students in a computer literacy course. Experiment 2 investigated the impact of empathetic response (responsive vs. non-responsive) and gender with 56 pre-service teachers. Overall, the results yielded main and interaction effects of PAL emotion and gender on the dependent variables. In particular, the PAL’s empathetic response had a positive impact on learner interest and self-efficacy; PAL gender had a positive impact on recall. The findings imply that the emotion and the gender of the digital learning companion could be utilized to optimize college students’ motivation and learning.

Promoting motivation with virtual agents and avatars: role of visual presence and appearance

Anthropomorphic virtual agents can serve as powerful technological mediators to impact motivational outcomes such as self-efficacy and attitude change. Such anthropomorphic agents can be designed as simulated social models in the Bandurian sense, providing social influence as virtual ‘role models’. Of particular value is the capacity for designing such agents as optimized social models for a target audience and context. Importantly, the visual presence and appearance of such agents can have a major impact on motivation and affect regardless of the underlying technical sophistication. Empirical results of different instantiations of agent presence and appearance are reviewed for both autonomous virtual agents and avatars that represent a user.

Designing nonverbal communication for pedagogical agents: When less is more

This experimental study employed a 2x2x2 factorial design to investigate the effects of type of instruction (procedural module, attitudinal module), deictic gesture (presence, absence), and facial expression (presence, absence) on student perception of pedagogical agent persona, attitude toward the content, and learning. The interaction effect between type of instruction and agent nonverbal behavior (deictic gestures and facial expression) was also investigated. A total of 236 college students learned from an animated pedagogical agent that varied by two factors: deictic gestures and facial expression within one of two instructional environments: one training them to perform tasks within a software program (procedural learning outcome); the other focusing on changing their beliefs regarding intellectual property (attitudinal learning outcome). Results indicated that the main effects of agent facial expression and gesture as well as the interaction were significant for agent perception and learning. With regard to learning, for attitudinal instruction, participants learned more when the agents facial expression was present but deictic gesture was absent; however, for procedural instruction, students learned more when the agents gestures were present. These results are discussed in light of a preliminary pedagogical agent design principle that suggests that it is most desirable to employ the one nonverbal communicative behavior that is most appropriate to the learning outcome.

A U-shaped model for the development of intuition by level of expertise

Abstract Based on a review of the literature, this paper proposes a non-linear U-shaped model of intuition development influenced by an individuals level of expertise within a given subject area. Two qualitatively different types of intuition are described: immature intuition and mature intuition, each differentiated by the level of expertise of the individual in a specific subject area. Immature intuition is most available when an individual is a novice in a given knowledge domain, where his/her analytical knowledge of the subject does not interfere with the ability to make novel insights. Mature intuition is more rare and is most available when an individual is more of an expert in the subject area with well-developed relevant knowledge structures. Issues regarding the viability of this preliminary model are discussed.

Beyond Butlers: Intelligent Agents as Mentors

This article discusses pedagogical issues for intelligent agents to successfully serve as mentors for educational purposes. Broader issues about the nature or persona necessary for an intelligent agent as mentor are discussed, incorporating usability and human-computer interaction issues such as the anthropomorphic qualities of the agent and the social relationship between learner and agent. Overall, to be effective for learning, it is argued that there are three main requirements for agents as mentors: 1) regulated intelligence; 2) the existence of a persona; and 3) pedagogical control.

Agent-Based Learning Environments as a Research Tool for Investigating Teaching and Learning

By using intelligent agents to simulate instruction, agent-based learning environments can serve as a powerful research tool to investigate teaching and learning. The agent metaphor provides a way to operationalize and simulate the “human” aspect of instruction in a more ecologically valid way than other controlled computer-based methods. Additionally, from an architectural perspective, since agents are independent objects in the learning environment, it allows for more flexibility in research design. In particular, agent-based learning environments with multiple agents, such as MIMIC (Multiple Intelligent Mentors Instructing Collaboratively), allow for investigating the effect of multiple mentors or multiple perspectives on a learning topic. Preliminary results from MIMIC research indicate that multiple agents can serve to effectively operationalize instructional theory. In terms of overall impact, creating agent-based learning environments to investigate instructional issues is at the leading edge of revitalized research integrating artificial intelligence with education, and in exploring new paradigms for researching teaching and learning.

The impact of three pedagogical agent roles

This exploratory experimental study validated the effectiveness of pedagogical agent roles for promoting motivational and learning outcomes within the MIMIC agent-based learning environment. In a between-subjects design, 73 learners worked with an agent representing one of the following three agent roles while learning about instructional planning: Motivator, Expert, or Mentor (designed to incorporate both motivation and expertise). The roles were evaluated according to three contrast comparisons, comparing the value of the agents with and without motivation, the value of the agents with and without expertise, and the overall value of the Mentor agent (which combined motivation and expertise). Results indicated that the motivational agents (Motivator & Mentor) were significantly more engaging, human-like and facilitative of learning than the Expert agent, yet were also less credible. The agents with expertise (Expert & Mentor) were significantly more credible, and led to better performance on the transfer measure than the Motivator agent, yet were also less supportive and less human-like. Overall, the Mentor was perceived as significantly more engaging and facilitative of learning than the other two agents, and also led to significantly better transfer performance.

The Effects of Agent Nonverbal Communication on Procedural and Attitudinal Learning Outcomes

This experimental study investigated the differential effects of pedagogical agent nonverbal communication on attitudinal and procedural learning. A 2x2x2 factorial design was employed with 237 participants to investigate the effect of type of instruction (procedural, attitudinal), deictic gesture (presence, absence), and facial expression (presence, absence) on learner attitudes, agent perception (agent persona, gesture, facial expression), and learning. Results indicated that facial expressions were particularly valuable for attitudinal learning, and were actually detrimental for procedural learning. Similarly, gestures were perceived as more valuable for students in the procedural module, even though they did not directly enhance recall.