Jeremiah Sullins

Affect and learning: an exploratory look into the role of affect in learning with AutoTutor

The role that affective states play in learning was investigated from the perspective of a constructivist learning framework. We observed six different affect states (frustration, boredom, flow, confusion, eureka and neutral) that potentially occur during the process of learning introductory computer literacy with AutoTutor, an intelligent tutoring system with tutorial dialogue in natural language. Observational analyses revealed significant relationships between learning and the affective states of boredom, flow and confusion. The positive correlation between confusion and learning is consistent with a model that assumes that cognitive disequilibrium is one precursor to deep learning. The findings that learning correlates negatively with boredom and positively with flow are consistent with predictions from Csikszentmihalyis analysis of flow experiences.

The Deep-Level-Reasoning-Question Effect: The Role of Dialogue and Deep-Level-Reasoning Questions During Vicarious Learning

We investigated the impact of dialogue and deep-level-reasoning questions on vicarious learning in 2 studies with undergraduates. In Experiment 1, participants learned material by interacting with AutoTutor or by viewing 1 of 4 vicarious learning conditions: a noninteractive recorded version of the AutoTutor dialogues, a dialogue with a deep-level-reasoning question preceding each sentence, a dialogue with a deep-level-reasoning question preceding half of the sentences, or a monologue. Learners in the condition where a deep-level-reasoning question preceded each sentence significantly outperformed those in the other 4 conditions. Experiment 2 included the same interactive and noninteractive recorded condition, along with 2 vicarious learning conditions involving deep-level-reasoning questions. Both deep-level-reasoning-question conditions significantly outperformed the other conditions. These findings provide evidence that deep-level-reasoning questions improve vicarious learning.

The influence of modality on deep-reasoning questions

This study investigated the influence that modality (print versus spoken text) had on learning with deep reasoning questions. Half the participants were randomly assigned to receive deep-reasoning questions during the learning session. The other half received the same information in the absence of deep-reasoning questions. The participants who received deep reasoning questions were randomly assigned to one of two different groups. One group received deep reasoning questions as on-screen printed text while the other group received deep reasoning questions in a spoken modality via a text to speech engine. Participants who received deep reasoning questions had higher post-test scores than those who did not, a finding that replicated previous research. Additionally, learning was better for the learners who received printed text than spoken messages, a finding that is not compatible with a number of theoretical and empirical claims in the literature.

The relationship between cognitive disequilibrium, emotions and individual differences on student question generation

The purpose of this study was to explore the effects of cognitive disequilibrium and individual differences on student question generation. Students were placed in a state of cognitive disequilibrium while they learned topics of computer literacy. During the course of the study a confederate was present to answer any questions that the participant may have had. Additional analyses examined any potential influence the confederates had on student question asking. Furthermore, the study explored the relationship between emotions and cognitive disequilibrium. Lastly, we examined any relationship between individual differences (e.g., personality and motivation) on question generation. Results revealed that participants who were not placed in a state of cognitive disequilibrium generated a significantly higher proportion of questions. Results did reveal significant main effects as a function of time for certain facial action units. Lastly, it was discovered that certain measures of individual differences were related to student question generation.

Tough Love: The Influence of an Agent's Negative Affect on Students' Learning

In this paper we explored the relationship between learning gains and affective displays of an animated pedagogical agent. Students read information on the topic of computer literacy while receiving either positive or negative affective responses from an on-screen animated agent. Analyses revealed that only students with low prior knowledge were influenced by the emotion displayed by the animated agent. We discuss the generalizability of our findings to other domains and the implications of these results on intelligent tutoring systems that are emotionally intelligent.

The Impact of a Mathematical Intelligent Tutoring System on Students’ Performance on Standardized High-Stake Tests

Recent research has suggested that standardized high-stakes tests, such as the SAT, have become increasingly important to policy makers, school districts, and society in general. Scoring well on these tests may determine the access to educational opportunities beyond high school. Unfortunately, recent reports have shown that Americans are falling behind their peers in other nations on comparable assessments (Gollub et al., 2002). Additionally, schools in the U.S. must adhere to the demands of the No Child Left Behind Act (NCLB). The policy states that federal district funding is dependent on student overall performance on standardized tests in mathematics, reading and other content areas. To alleviate the problem of U.S. students underachieving on standardized tests, educators must explore areas of pedagogy that have been empirically shown to be effective.

Exploring shame in engineering education

Individual experiences of inclusion or exclusion are increasingly recognized for their relevance in relation to attracting and retaining diverse students in engineering programs. Referring to this emerging body of work, this article explores the emotion of shame as a psychological and sociological construct that might underpin student experiences of inclusion, exclusion, or belonging in engineering majors. To begin unpacking this underexplored concept in the engineering context, we draw on literature from psychology that conceptualizes shame as a construct of emotion with dynamics that greatly affect an individuals perceived experience. We also examine sociological perspectives on shame that attend to how this emotion exists in an intersubjective reality between an individual and his or her social context. Finally, we review the sparse literature in engineering education that explicitly mentions shame and examine a larger body of literature that suggests how engineering student experiences that can be understood as phenomena related shame. This survey of the literature points to the importance of considering shame in engineering education and, in its synthesis, provides the theoretical basis for future empirical studies.