4 resultados para modeling trends and data
em Digital Commons @ DU | University of Denver Research
Resumo:
This study examines worldwide usage of over 600,000 e-books from Ebook Library (EBL) and ebrary. Using multiple modes of analysis, the study shows that there are variations in usage by geographic region as well as by subject. The study examines usage in relation to availability of titles, different types of usage per session, usage of the top ten percent of titles, and intensive and extensive use. These patterns can be used for benchmarking and as a model for local e-book studies.
Resumo:
Fragmentation of wildlife habitat is a primary driver of global species decline. A major contributor to habitat fragmentation in the United States is rural residential development. Rural development in Colorado is occurring at rates far greater than the national average. Additionally, the lack of state-level planning control coupled with a lack of comprehensive, effective planning tools at the local level creates conditions that contribute to habitat fragmentation in many rural counties. Greater oversight and involvement in land use planning is needed by the state level to assist county governments. This study provides five recommendations to strengthen Colorado state land use policy in order to reduce habitat fragmentation.
Resumo:
The purposes of this study were (1) to validate of the item-attribute matrix using two levels of attributes (Level 1 attributes and Level 2 sub-attributes), and (2) through retrofitting the diagnostic models to the mathematics test of the Trends in International Mathematics and Science Study (TIMSS), to evaluate the construct validity of TIMSS mathematics assessment by comparing the results of two assessment booklets. Item data were extracted from Booklets 2 and 3 for the 8th grade in TIMSS 2007, which included a total of 49 mathematics items and every student's response to every item. The study developed three categories of attributes at two levels: content, cognitive process (TIMSS or new), and comprehensive cognitive process (or IT) based on the TIMSS assessment framework, cognitive procedures, and item type. At level one, there were 4 content attributes (number, algebra, geometry, and data and chance), 3 TIMSS process attributes (knowing, applying, and reasoning), and 4 new process attributes (identifying, computing, judging, and reasoning). At level two, the level 1 attributes were further divided into 32 sub-attributes. There was only one level of IT attributes (multiple steps/responses, complexity, and constructed-response). Twelve Q-matrices (4 originally specified, 4 random, and 4 revised) were investigated with eleven Q-matrix models (QM1 ~ QM11) using multiple regression and the least squares distance method (LSDM). Comprehensive analyses indicated that the proposed Q-matrices explained most of the variance in item difficulty (i.e., 64% to 81%). The cognitive process attributes contributed to the item difficulties more than the content attributes, and the IT attributes contributed much more than both the content and process attributes. The new retrofitted process attributes explained the items better than the TIMSS process attributes. Results generated from the level 1 attributes and the level 2 attributes were consistent. Most attributes could be used to recover students' performance, but some attributes' probabilities showed unreasonable patterns. The analysis approaches could not demonstrate if the same construct validity was supported across booklets. The proposed attributes and Q-matrices explained the items of Booklet 2 better than the items of Booklet 3. The specified Q-matrices explained the items better than the random Q-matrices.
Resumo:
United States Air Force (USAF) energy policy is a measured but aggressive response to federal energy policy guidance. Previous USAF efforts, like those of the federal government, focused primarily on energy intensity reduction, cost, and BTU savings, and in certain cases have resulted in facility greenhouse gas (GHG) emission reductions. The USAF now faces the challenge of integrating GHG reduction goals and inventory requirements set forth in Executive Order 13514. Using USAF reported energy consumption data, facility GHG emission estimates have been synthesized to identify trends and elucidate existing energy best practices to be applied as part of overarching USAF GHG mitigation efforts and to highlight areas of possible concern for the integration of EO 13514 into operational USAF policy.