Question Generation from Concept Maps

In this paper we present a question generation approach suitable for tutorial dialogues. The approach is based on previous psychological theories that hypothesize questions are generated from a knowledge representation modeled as a concept map. Our model automatically extracts concept maps from a textbook and uses them to generate questions. The purpose of the study is to generate and evaluate pedagogically-appropriate questions at varying levels of specificity across one or more sentences. The evaluation metrics include scales from the Question Generation Shared Task and Evaluation Challenge and a new scale specific to the pedagogical nature of questions in tutoring

The language of instruction: Compensating for challenge in lectures.

Recent studies have used Coh-Metrix, an automated text analyzer, to assess differences in language characteristics across different genres and academic disciplines (Graesser, McNamara, & Kulikowich, 2011; McNamara, Graesser, McCarthy, & Cai, 2014). Coh-Metrix analyzes text on many constructs at different levels, including Word Concreteness (vs. abstractness), Narrativity (vs. informational), Deep Cohesion, Referential Cohesion, and Syntactic Simplicity. In previous research, texts in the natural sciences had lower Narrativity and Word Concreteness than texts in the language arts, but were higher in Syntactic Simplicity and Referential Cohesion. This pattern suggests a form of compensation in which difficulty on one dimension (e.g., Word Concreteness) is compensated for by increasing text ease on another dimension (e.g., Syntactic Simplicity). In the present study, we provide a further test of this compensation idea by analyzing oral language use across humanities and natural science lectures. We demonstrate that decreases in Word Concreteness across lectures are associated with increases in Narrativity, Deep Cohesion, and Syntactic Simplicity. In addition, within lectures, decreases in Word Concreteness are associated with increases in Syntactic Simplicity. Compensatory mechanisms are discussed in this article at different levels of language and discourse

Assessing Student-Generated Design Justifications in Engineering Virtual Internships

ABSTRACT Engineering virtual internships are simulations where students role play as interns at fictional companies, working to create engineering designs. To improve the scalability of these virtual internships, a reliable automated assessment system for tasks submitted by students is necessary. Therefore, we propose a machine learning approach to automatically assess student generated textual design justifications in two engineering virtual internships, Nephrotex and RescuShell. To this end, we compared two major categories of models: domain expert-driven vs. general text analysis models. The models were coupled with machine learning algorithms and evaluated using 10-fold cross validation. We found no quantitative differences among the two major categories of models, domain expert-driven vs. general text analysis, although there are major qualitative differences as discussed in the paper

Pedagogical Agents for Fostering Question-Asking Skills in Children

Question asking is an important tool for constructing academic knowledge, and a self-reinforcing driver of curiosity. However, research has found that question asking is infrequent in the classroom and children's questions are often superficial, lacking deep reasoning. In this work, we developed a pedagogical agent that encourages children to ask divergent-thinking questions, a more complex form of questions that is associated with curiosity. We conducted a study with 95 fifth grade students, who interacted with an agent that encourages either convergent-thinking or divergent-thinking questions. Results showed that both interventions increased the number of divergent-thinking questions and the fluency of question asking, while they did not significantly alter children's perception of curiosity despite their high intrinsic motivation scores. In addition, children's curiosity trait has a mediating effect on question asking under the divergent-thinking agent, suggesting that question-asking interventions must be personalized to each student based on their tendency to be curious.Comment: Accepted at CHI 202

The real foundation of fictional worlds

I argue that judgements of what is ‘true in a fiction’ presuppose the Reality Assumption: the assumption that everything that is (really) true is fictionally the case, unless excluded by the work. By contrast with the more familiar Reality Principle, the Reality Assumption is not a rule for inferring implied content from what is explicit. Instead it provides an array of real-world truths that can be used in such inferences. I claim that the Reality Assumption is essential to our ability to understand stories, drawing on a range of empirical evidence that demonstrates our reliance on it in narrative comprehension. However, the Reality Assumption has several unintuitive consequences, not least that what is fictionally the case includes countless facts that neither authors nor readers could (or should) ever consider. I argue that such consequences provide no reason to reject the Reality Assumption. I conclude that we should take fictions, like non-fictions, to be about the real world

Experiencing neutropenia: Quality of life interviews with adult cancer patients

BACKGROUND: Neutropenia is a common toxicity in chemotherapy but detailed information about how neutropenia is associated with changes in patients' quality of life is not readily available. This prospective study interviewed patients with grade 4 neutropenia to provide qualitative information on patients' experience of developing and coping with grade 4 neutropenia during a cycle of chemotherapy. METHODS: A sample of 34 patients who developed grade 4 neutropenia during the first cycle of chemotherapy completed a total of 100 structured clinical interviews. Interviews were transcribed, and 2 raters inductively developed 5 broad categories comprising 80 specific complaint domains nominated by patients. Thirty-five patient-nominated problems were mentioned in 5% or more of the interviews. RESULTS: Fatigue was the most common physical symptom. Interference in daily routine, negative self-evaluation, negative emotion, and social isolation were other common complaints associated with neutropenia. CONCLUSION: Neutropenia is associated with a number of negative experiences among cancer patients undergoing chemotherapy, and these negative experiences have an adverse effect on the patient's quality of life. Oncology nurses can play a key role in helping patients manage adverse effects to maintain their quality of life

Learning, thinking, and emoting with discourse technologies

This is an unusual moment in the history of psychology because of landmark advances in digital information technologies, computational linguistics, and other fields that use the computer to analyze language, discourse, and behavior. The technologies developed from this interdisciplinary fusion are helping students learn and think in ways that are sensitive to their cognitive and emotional states. Recent projects have developed computer technologies that help us understand the nature of conversational discourse and text comprehension in addition to improving learning. AutoTutor and other systems with conversational agents (i.e., talking heads) help students learn by holding conversations in natural language. One version of AutoTutor is sensitive to the emotions of students in addition to their cognitive states. Coh-Metrix analyzes texts on multiple levels of language and discourse, such as text genre, cohesion, syntax, and word characteristics. Coh-Metrix can assist students, teachers, principals, and policymakers when they make decisions on the right text to assign to the right student at the right time. Computers are not perfect conversation partners and comprehenders of text, but the current systems are undeniably useful. (PsycINFO Database Record (c) 2011 APA, all rights reserved)