Michael Maxwell - US grants

This project is designing and implementing a model to assist in integrating people with orthopedical disabilities into careers in technology. Twenty-four orthopedically disabled individuals have been chosen to be provided with an education opportunity in the Construction Technology Department of Indiana-Purdue University at Indianapolis through a special Certificate Program. Handicapped accessible computer stations are being established and equipped with software for students with disabilities. Computer- aided and other innovative types of instructional methodologies are being developed and employed in the courses in this program. Education of the disabled in technology programs are being researched through this model undertaking. Disabled students are thus able to access mainstream construction technology education and resultant careers. Graduates of the model project will be placed in the industry and their progress monitored.

With National Science Foundation support, Dr. Mark Liberman and Dr. Steven Bird will lead a team conducting three years of research on data models and query languages for linguistic databases. The project will develop relational and XML data models for linguistic databases combining annotated recordings, comparative wordlists, data tabulations, interlinear texts, syntactic trees, ontologies of descriptive terms, and links between all these types. High-level user interfaces will support query-by-example and online analytical processing, permitting linguists to select appropriate language data, integrate data from multiple sources, transform the structure of the data, add new annotations in collaboration with others, and convert it all to suitable formats for archiving and for use in research and teaching.

Describing and analyzing human languages depends on being able to manage large databases of annotated text and recorded speech. The size and complexity of these databases promises to bring unprecedented depth and breadth to empirical linguistic research. However, this promise will not be fulfilled until language scientists can readily access and manipulate the data. This project will apply recent research in databases to linguistics, develop a linguistic query language, and deploy it in a variety of open-source tools for creating, managing, analyzing, and displaying annotated linguistic databases. By making rich data re-usable, the research will open the way to a deeper and broader understanding of the world's languages.

A dictionary documents the building blocks of a language -- its words and idiomatic phrases, with descriptions of their pronunciations, grammatical properties, meanings and uses -- and is an essential component of language documentation, together with a reference grammar and transcribed texts and recordings. Until recently, dictionaries were compiled and organized by hand, entered into some kind of typesetting system, and finally rendered in print form for use by scholars and language learners. Contemporary dictionaries are now compiled and organized electronically so that the information they contain can be used not only to produce stand-alone print artifacts, but also be integrated with the other components to ensure greater accuracy of the documentation as a whole, enable updates to be produced at regular intervals, and support the development of natural-language processing tools for the languages that are documented in this way. The goal of this exploratory project is to develop methods for machines to understand the implicit structure of the hundreds of extant print dictionaries of endangered and other low-resource languages as a critical first step in enabling their documentation to be of maximal usefulness to future generations.


Print dictionaries use ordering, typeface and other formatting conventions to indicate the intended structure of dictionary entries. The first task of this project is to use optical character reading (OCR) software to convert those entries to machine-interpretable form so as to preserve the original formatting. The second is to develop software to convert the corrected OCR output into structured, machine-interpretable archive-standard formats. Because print formats vary widely across dictionaries, human intervention is required to inform the software about how to translate the implicit representations for a particular dictionary's entries into explicit ones. But such manual annotation is only required for a small part of the dictionary, as the formatting conventions are consistent across all of its entries, and once learned can be used to identify and correct errors and inconsistencies, and enable automated editing tasks like updating orthographies. The tool will be developed, tested and evaluated using print dictionaries of two indigenous languages of Latin America that were produced in the latter part of the twentieth century. This project is jointly supported by the Documenting Endangered Languages Program in the Behavioral and Cognitive Sciences Division and by the Robust Intelligence Program in the Information and Intelligent Systems Division.

This project establishes an interdisciplinary network of biologists and artists to develop and implement teaching practices that integrate artistic expression with biology education. This approach builds on the demonstrated cognitive and academic benefits of art-enhanced instruction in biology courses to increase creativity, course engagement, and concept comprehension by diverse students: traditional and non-traditional, and biology majors and non-majors. This project’s rationale is rooted in two national trends. First, undergraduate students are becoming increasingly “non-traditional”, and these students show lower degree completion rates and more difficulty integrating into university life than their traditional counterparts. Second, this proposal is a response to recent calls from national advisory bodies for the integration of education in biology and the sciences with the arts and humanities, as well as emphasis on the college graduate as a scientifically literate member of society. To engage diverse students with diverse learning preferences, this project emphasizes concrete, immediate expression of concepts in biology, and encourages thinking about concepts from diverse perspectives. By providing opportunities for students to interpret and express course material in personal, creative ways, this project addresses the achievement gap faced by non-traditional students and enriches the course experience of biology majors and non-majors.

This project has two main objectives: establish a collaborative network of biologists and artists to develop and implement methods and techniques of art-enhanced instruction in undergraduate biology courses and increase course engagement and concept comprehension among biology-majors and non-majors through art-enhanced instruction. To achieve the first objective, the network will hold a series of meetings to develop feasible art-enhanced course material, as well as appropriate assessment approaches and metrics for project evaluation. Ten art-enhanced biology instruction and ten non-art-enhanced biology courses will be implemented at four institutions (two HSIs, a teaching-focused university, and an international institution that includes programs offered through a Native American education center); three courses for non-majors and seven for majors. Major courses will include lower level (General Biology) and upper level (Invertebrate Zoology, Ecology, Cell Biology, and Microbiology) biology. Formative evaluation will assess the processes through which the network develops and implements the integration of artwork in biology courses and summative evaluation will examine the outcomes of implementation through assessment data on student course engagement and concept comprehension.

This project is being funded by the Directorate for Biological Sciences, Division of Biological Infrastructure, as part of efforts to address the challenges posed in Vision and Change in Undergraduate Biology Education: A Call to Action (http://visionandchange/finalreport/).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.