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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
231

Educational Design and Implementation of a Blended Active Learning Instructional Model for Undergraduate Gross Anatomy Education: A Multi-Modal Action Research Study

Foster, Allison A. January 2019 (has links)
No description available.
232

Using Scientific Teaching Principles to Teach Genetic Modification

Brock, Orion D. 25 February 2020 (has links)
No description available.
233

The Observed Use of Technology Enabled Active Learning Classrooms and Interactive Learning Strategies in Higher Education: A Case Study

Alreiahi, Nadeyah January 2020 (has links)
No description available.
234

The Relationship Between Undergraduate, Baccalaureate Nursing Student Engagement and Use of Active Learning Strategies in the Classroom

Popkess, Ann M. 03 March 2010 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Nursing schools are facing demands to admit and graduate increasing numbers of students to meet the needs of the future healthcare system. Nursing schools must therefore admit, retain and graduate qualified applicants, able to provide care in complex healthcare environments. Educators are challenged to identify the best educational practices to retain and engage learners in the learning process. Research has indicated that student engagement contributes to student success in college. Learning environments may influence student engagement through the use of active learning strategies in the classroom. The purpose of this descriptive study was to explore the extent of engagement reported by nursing students in classrooms and determine relationships among student engagement, demographic and academic variables and learning environments. Astin’s (1985) Input-Environments-Output model provided the framework for this study, linking student characteristics, and student engagement in learning with outcomes of learning. A sample of 347 undergraduate baccalaureate nursing students from 5 mid-western schools of nursing completed the Adapted Engaged Learning Index (AELI) and the Active Learning Environments Scale (ALES), measuring their level of engagement and perceived degree of active learning in the classroom, respectively. Subjects also provided demographic data including age, academic level, type and number of hours worked off campus, and prior learning experience. T-test and ANOVA analyses were conducted to compare group differences on demographic, learning environments (active, passive and mixed) and levels of engagement. Results indicated a significant (p≤.001) difference in the level of student engagement related to the perceived active learning occurring in the classroom. Students in active and mixed learning environments reported higher engagement levels than those in passive learning environments. Students over 25 years (p=.003), students with higher GPA’s (p≤ .05) and junior students (p≤ .001) reported significantly higher engagement scores than their counterparts. Findings from this study indicate that student engagement in the learning process may be positively influenced by an active learning environment in the classroom.
235

Story Writing in the Accounting Classroom

Freeman, Michelle, Friedman, Mark 01 December 2020 (has links)
A story is an established method of communicating fact, fiction, parable, and myth from cultural generation to generation. Is it possible to actively engage accounting students with content when the student becomes the storywriter? Can story writing by the student be an effective teaching tool, and should accounting professors consider its use in their classrooms? This archival research seeks to review the literature regarding the value of story writing as a pedagogical tool across academic disciplines in higher education, synthesize the findings of existing research and describe the uses, benefits and difficulties with using story writing in various accountancy classes across the curriculum.
236

A Case Study of Learning Community Curriculum Models Implemented in Business Programs in Three Public Community Colleges in Ohio

Wood, Vicky L. January 2012 (has links)
No description available.
237

Utilizing Human-Computer Interactions to Improve Text Annotation

Carmen, Marc A. 08 July 2010 (has links) (PDF)
The need for annotated corpora in a variety of different types of research grows constantly. Unfortunately creating annotated corpora is frequently cost-prohibitive due the number of person-hours required to create the corpus. This project investigates one solution that helps to reduce the cost of creating annotated corpora through the use of a new user interface which includes a specially built framework and component for annotating part-of-speech information and the implementation of a dictionary. This project reports on a user study performed to determine the effect of dictionaries with different levels of coverage on a part-of-speech annotation task. Based on a pilot study with thirty-three participants the analysis shows that a part-of-speech tag dictionary with greater than or equal to 60% coverage helps to improve the time required to complete the part-of-speech annotation task while maintaining high levels of accuracy.
238

Evaluating Teaching Grammar In Specific Constraints Of Context: A Pilot Study In The Developmental Writing Program At Seminole State College

Roney, Joshua 01 January 2012 (has links)
This pilot study investigated the efficacy of a supplemental Active Learning intervention that was administered with grammar workbook software in remedial-level composition classrooms at Seminole State College. The study analyzed student response data in a pre-test and post-test instrument in four classrooms; two followed standard methods while two incorporated the additional experimental intervention. The groups are identified in this study as either “Standard” or “Experimental,” according to the method administered in the classroom. The intervention was designed based on five grammar topic areas which correspond with content assessed in the pre-test and post-test. The Active Learning method required students to prepare a short, guided presentation on selected grammar topics. Findings showed that there was no significant change in improvement between the pre-test and post-test among the Standard or the Experimental groups, due in part to a relatively small sample size. A positive change approaching significant level occurred in the Experimental group in topic areas related to critical thinking. No significant or near-significant change was observed in the topic areas related to memorization in either group. Recommendations were made for further sampling, modification, and future applications of the intervention used in the study and for continued testing of grammar software used for instruction in Developmental Writing classes at Seminole State College.
239

Metamorphosis: intensive telerehabilitation to maximize upper limb function and integration in adults with chronic stroke

Nuckols, Kristin Noelle 26 September 2020 (has links)
Metamorphosis is a theory-driven occupational therapy program using telerehabilitation based on the concept of self-management of stroke (Warner et al., 2015), which emphasizes the crucial role of client adherence and engagement between formal therapy sessions to drive neuroplastic change. This program utilizes self-determination theory (Ryan & Deci, 2000) to cultivate the intrinsic motivation of individuals with chronic stroke to participate in evidence-based therapy from the home setting (Chemtob et al., 2019; Moore et al., 2016). Repetitious but interesting and engaging gamified therapy (Cramer et al., 2019; Proffitt & Lange, 2015; Thielbar et al., 2019) can lead to motor changes which are then translated into improvements in UL engagement during ADL guided by the Active Learning Program for Stroke (ALPS) (Fasoli & Adans-Dester, 2019), solidifying the motor changes by reducing learned non-use of the stroke-affected limb. Emotional support is provided through a moderated forum for stroke survivors (Owen et al., 2010) which can aid in continued translation of skills and motivation to participate in the program during a challenging time. / 2022-09-25T00:00:00Z
240

Accelerating Structural Design and Optimization using Machine Learning

Singh, Karanpreet 13 January 2020 (has links)
Machine learning techniques promise to greatly accelerate structural design and optimization. In this thesis, deep learning and active learning techniques are applied to different non-convex structural optimization problems. Finite Element Analysis (FEA) based standard optimization methods for aircraft panels with bio-inspired curvilinear stiffeners are computationally expensive. The main reason for employing many of these standard optimization methods is the ease of their integration with FEA. However, each optimization requires multiple computationally expensive FEA evaluations, making their use impractical at times. To accelerate optimization, the use of Deep Neural Networks (DNNs) is proposed to approximate the FEA buckling response. The results show that DNNs obtained an accuracy of 95% for evaluating the buckling load. The DNN accelerated the optimization by a factor of nearly 200. The presented work demonstrates the potential of DNN-based machine learning algorithms for accelerating the optimization of bio-inspired curvilinearly stiffened panels. But, the approach could have disadvantages for being only specific to similar structural design problems, and requiring large datasets for DNNs training. An adaptive machine learning technique called active learning is used in this thesis to accelerate the evolutionary optimization of complex structures. The active learner helps the Genetic Algorithms (GA) by predicting if the possible design is going to satisfy the required constraints or not. The approach does not need a trained surrogate model prior to the optimization. The active learner adaptively improve its own accuracy during the optimization for saving the required number of FEA evaluations. The results show that the approach has the potential to reduce the total required FEA evaluations by more than 50%. Lastly, the machine learning is used to make recommendations for modeling choices while analyzing a structure using FEA. The decisions about the selection of appropriate modeling techniques are usually based on an analyst's judgement based upon their knowledge and intuition from past experience. The machine learning-based approach provides recommendations within seconds, thus, saving significant computational resources for making accurate design choices. / Doctor of Philosophy / This thesis presents an innovative application of artificial intelligence (AI) techniques for designing aircraft structures. An important objective for the aerospace industry is to design robust and fuel-efficient aerospace structures. The state of the art research in the literature shows that the structure of aircraft in future could mimic organic cellular structure. However, the design of these new panels with arbitrary structures is computationally expensive. For instance, applying standard optimization methods currently being applied to aerospace structures to design an aircraft, can take anywhere from a few days to months. The presented research demonstrates the potential of AI for accelerating the optimization of an aircraft structures. This will provide an efficient way for aircraft designers to design futuristic fuel-efficient aircraft which will have positive impact on the environment and the world.

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