Beyond the Veil: A Case Study of Context, Culture, Curriculum, and Constructivism at Dubai Women's College

This case study of curriculum at Dubai Women's College (DWC) examines perceptions of international educators who designed and implemented curriculum for female Emirati higher-educational students in the UAE, and sheds light on the complex social, cultural, and religious factors affecting educational practice. Participants were faculty and supervisors, mainly foreign nationals, while students at DWC are exclusively Emirati. Theories prominent in this study are: constructivist learning theory, trans formative curriculum theory, and sociological theory. Change and empowerment theory figure prominently in this study. Findings reveal this unique group of educators understand curriculum theory as a "contextualized" construct and argue that theory and practice must be viewed through an international lens of religious, cultural, and social contexts. As well, the study explores how mandated "standards" in education-in the form of the International English Language Testing System (IEL TS) and integrated, constructivist curriculum, as taught in the Higher Diploma Year 1 program-function as dual curricular emphases in this context. The study found that tensions among these dual emphases existed and were mediated through specific strategies, including the use of authentic texts to mirror the IEL TS examination during in-class activities, and the relevance of curricular tasks.

Old and new views of Niagara Falls : with short description /

On cover: Niagara.

Second Welland Canal - Book 3, Survey Map 5 - Old Canal and New Canal along Chippewa Creek in Port Robinson, Thorold Township

Survey map of the Second Welland Canal created by the Welland Canal Company showing the canal along Chippewa Creek in Thorold Township. Identified structures and features associated with the Canal include the towing path, float bridge, and the waterway itself. The surveyors' measurements and notes can be seen in red and black ink and pencil. Local area landmarks are also identified and include a road allowance between Lot 213 and 214, Chippewa Creek, an unnamed creek, and the Old Canal. Wetlands adjacent to Chippewa Creek are illustrated. Properties and property owners of note are: Lots 213 and 214, Samuel Hill, and Duncan Coleman. The boundary of the land deeded to Coleman is outlined in blue.

Receipt from Parsons and Harvey, English Hams and Bacon, Guelph for bacon and ham

Receipt from Parsons and Harvey, English Hams and Bacon, Guelph for bacon and ham, Jan. 20, 1888.

Letter to H.H. Collier of Austin, Texas to the care of Cruger and Moore of Houston, Texas and New Orleans

Letter to H.H. Collier of Austin, Texas to the care of Cruger and Moore of Houston, Texas and New Orleans. The letter is from his sister, E. Richards. She writes about family life, her job as a teacher and politics (3 ¼ pages, handwritten), Jan. 23, 1841.

A Scalability Study and New Algorithms for Large-Scale Many-Objective Optimization

Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or three objectives. Unfortunately, when tasked with solving MOPs with four or more objectives, referred to as many-objective problems (MaOPs), a large majority of optimizers experience significant performance degradation. The downfall of these optimizers is that simultaneously maintaining a well-spread set of solutions along with appropriate selection pressure to converge becomes difficult as the number of objectives increase. This difficulty is further compounded for large-scale MaOPs, i.e., MaOPs possessing large amounts of decision variables. In this thesis, we explore the challenges of many-objective optimization and propose three new promising algorithms designed to efficiently solve MaOPs. Experimental results demonstrate the proposed optimizers to perform very well, often outperforming state-of-the-art many-objective algorithms.