Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

BackgroundUsing knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms?ResultsOur existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important.ConclusionsWith some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels

An investigation of the effectiveness if the Case Method as compared with the Lecture-Textbook Method to stimulate critical thinking in the fifth grade social studies

Thesis (Ed.M.)--Boston Universit

An Online Tutor for Astronomy: The GEAS Self-Review Library

We introduce an interactive online resource for use by students and college instructors in introductory astronomy courses. The General Education Astronomy Source (GEAS) online tutor guides students developing mastery of core astronomical concepts and mathematical applications of general astronomy material. It contains over 12,000 questions, with linked hints and solutions. Students who master the material quickly can advance through the topics, while under-prepared or hesitant students can focus on questions on a certain topic for as long as needed, with minimal repetition. Students receive individual accounts for study and course instructors are provided with overview tracking information, by time and by topic, for entire cohorts of students. Diagnostic tools support self-evaluation and close collaboration between instructor and student, even for distance learners. An initial usage study shows clear trends in performance which increase with study time, and indicates that distance learners using these materials perform as well as or better than a comparison cohort of on-campus astronomy students. We are actively seeking new collaborators to use this resource in astronomy courses and other educational venues.Comment: 15 pages, 9 figures; Vogt, N. P., and A. S. Muise. 2015. An online tutor for general astronomy: The GEAS self-review library. Cogent Education, 2 (1

Student questioning : a componential analysis

This article reviews the literature on student questioning, organized through a modified version of Dillon's (1988a, 1990) componential model of questioning. Special attention is given to the properties of assumptions, questions, and answers. Each of these main elements are the result of certain actions of the questioner, which are described. Within this framework a variety of aspects of questioning are highlighted. One focus of the article is individual differences in question asking. The complex interactions between students' personal characteristics, social factors, and questioning are examined. In addition, a number of important but neglected topics for research are identified. Together, the views that are presented should deepen our understanding of student questioning

Using Natural Language as Knowledge Representation in an Intelligent Tutoring System

Knowledge used in an intelligent tutoring system to teach students is usually acquired from authors who are experts in the domain. A problem is that they cannot directly add and update knowledge if they don’t learn formal language used in the system. Using natural language to represent knowledge can allow authors to update knowledge easily. This thesis presents a new approach to use unconstrained natural language as knowledge representation for a physics tutoring system so that non-programmers can add knowledge without learning a new knowledge representation. This approach allows domain experts to add not only problem statements, but also background knowledge such as commonsense and domain knowledge including principles in natural language. Rather than translating into a formal language, natural language representation is directly used in inference so that domain experts can understand the internal process, detect knowledge bugs, and revise the knowledgebase easily. In authoring task studies with the new system based on this approach, it was shown that the size of added knowledge was small enough for a domain expert to add, and converged to near zero as more problems were added in one mental model test. After entering the no-new-knowledge state in the test, 5 out of 13 problems (38 percent) were automatically solved by the system without adding new knowledge

Designing Women: Essentializing Femininity in AI Linguistics

Since the eighties, feminists have considered technology a force capable of subverting sexism because of technology’s ability to produce unbiased logic. Most famously, Donna Haraway’s “A Cyborg Manifesto” posits that the cyborg has the inherent capability to transcend gender because of its removal from social construct and lack of loyalty to the natural world. But while humanoids and artificial intelligence have been imagined as inherently subversive to gender, current artificial intelligence perpetuates gender divides in labor and language as their programmers imbue them with traits considered “feminine.” A majority of 21st century AI and humanoids are programmed to fit female stereotypes as they fulfill emotional labor and perform pink-collar tasks, whether through roles as therapists, query-fillers, or companions. This paper examines four specific chat-based AI --ELIZA, XiaoIce, Sophia, and Erica-- and examines how their feminine linguistic patterns are used to maintain the illusion of emotional understanding in regards to the tasks that they perform. Overall, chat-based AI fails to subvert gender roles, as feminine AI are relegated to the realm of emotional intelligence and labor

Physician and Nurses\u27 Knowledge and Use of Natural Family Planning

Perinatal health professionals are in key positions to either promote or dissuade the use of Natural Family Planning (NFP). The purpose of this article is to describe a survey conducted with perinatal physicians and nurses on their knowledge and professional use of NFP. Four hundred and fifty physicians and nurses (150 MDs and 300 RNs) were sent a questionnaire on the use of and knowledge of NFP. One hundred sixty-six (or 37%) returned the completed questionnaires. Fifty-two percent of the nurses who returned the questionnaires and 48% of the physicians indicated they were taught about NFP in basic (generic) medical or nursing school. The average lecture time spent on the subject in either nursing or medical school was less than one hour. The majority learned about NFP through self-education or on-the-job training. Only four (1 RN and 3 MDs) are certified to teach NFP. Fifty-three percent of the nurses and 44% of physicians would not advise the use of NFP to avoid pregnancy. The most frequent reasons given for not promoting the use of NFP to either avoid or achieve pregnancy were that it is not effective, not natural, too difficult to learn, better methods are available, and it only works for highly motivated educated women

Preferences of fourth grade children for certain social studies activities.

Thesis (Ed.M.)--Boston Universit