Academic literature on the topic 'Searching, Bibliographical – Computer programs'

In today's FTIR market, many instrument manufacturers provide software to perform searches of computer library spectra. With the increased speed of computers running FTIR instruments, you can have the result of a computer library search in literally seconds. However, as we rely more and more on computers in the laboratory we need to keep in mind the limitations and possible areas for error in these applications.Computer library search programs calculate the difference between the sample spectrum and reference spectrum typically based on peak position and intensity. Different searching algorithms can stress one or the other. The result of a computer search is a Hit List with each hit having a hit quotient index (HQI) to indicate how close that particular spectrum matches the sample spectrum. In some programs the quotient which indicates an exact match would be 1 or 100, in others it is 0.

This article describes a quest for the GRAIL (Giant Radial Array for Immersive Listening), a large-scale loudspeaker system with related hardware and software control equipment. The GRAIL was developed at the Center for Computer Research in Music and Acoustics (CCRMA) at Stanford University, evolving from the need for optimal sound quality in our multichannel concerts. It is also used for teaching and research. The current GRAIL is one step in an ongoing evolutionary process, characterized by the use of off-the-shelf hardware components and custom software–based on free software languages and libraries. While developing our software, we have, as much as possible, aimed to take advantage of existing programs and utilities.

AbstractTwo new VAX/VMS computer programs are presented for accessing and searching the Powder Diffraction File (PDF) (1989) of the JCPDS-International Centre for Diffraction Data (ICDD). The programs use binary mapped index files which affords rapid searches of the database. Program LOGIC permits entries in the database to be selected by chemistry, peak position or name constraints. The selected entries may be displayed, printed or graphed. The program can display or print entries from the full PDF-2 (1989) database, if on-line. Program SEARCH searches for patterns in the database which match an unknown set of peaks; the program may be optimized for a wide variety of applications including identification of component phases in mixtures. Commands may be entered to the programs in two modes. In the “novice-friendly” mode, users must answer questions to select options. However, experienced users may opt to use a concise one-line command syntax. The modes may be mixed.

AbstractLearning probabilistic logic programming languages is receiving an increasing attention, and systems are available for learning the parameters (PRISM, LeProbLog, LFI-ProbLog and EMBLEM) or both structure and parameters (SEM-CP-logic and SLIPCASE) of these languages. In this paper we present the algorithm SLIPCOVER for “Structure LearnIng of Probabilistic logic programs by searChing OVER the clause space.” It performs a beam search in the space of probabilistic clauses and a greedy search in the space of theories using the log likelihood of the data as the guiding heuristics. To estimate the log likelihood, SLIPCOVER performs Expectation Maximization with EMBLEM. The algorithm has been tested on five real world datasets and compared with SLIPCASE, SEM-CP-logic, Aleph and two algorithms for learning Markov Logic Networks (Learning using Structural Motifs (LSM) and ALEPH++ExactL1). SLIPCOVER achieves higher areas under the precision-recall and receiver operating characteristic curves in most cases.

Speculative parallelism refers to searching in parallel for a solution, such as finding a pattern in a data base, where finding the first solution terminates the whole parallel process. Different performance prediction methods are required as compared to traditional parallelism. In this paper we introduce an analytical approach to predict the execution time distribution of data-dependent parallel programs that feature N-ary and binary speculative parallel compositions. The method is based on the use of statistical moments which allows program execution time distribution to be approximated at O(1) solution complexity. Measurement results for synthetic distributions indicate an accuracy that lies in the percent range while for empirical distributions on internet search engines the prediction accuracy is acceptable, provided sufficient workload unimodality.

Abstract:Advances in electronic image recording and computer technologyhave resulted in a remarkable increase in the power and flexibility of interactive computer-video teaching systems. The University of Washington Health Science Videodisc Development Group first demonstrated a laser videodisc controlled by a remote central computer in 1980. Even this rudimentary unit highlighted basic medical informatics principles including: rapid accessibility; a “generic” or multi-purposed format; ease of computer control; and large collections of valid, rigorously reviewed images. Advances in medical informatics have led to the development of the following previously undescribed series of teaching units:1. The hypertext programs Hypercard, Linkway, and Guide have been used with videodiscs to develop easy-to-use instructional and reference materials. These materials demonstrate the ease with which a computer-naive instructor may develop new programs and the advantage that the intuitive nature of these programs brings to student users.2. Patient simulations using single and double screens plus pre-defined knowledge structures;3. Interactive single topic tutorials using preset knowledge structures;4. A key-word-based disc searching system;5. Electronic video microscopy;6. A series of programs developed independently by health science faculty who have purchased multi-purpose videodiscs that demonstrate the flexibility of the multi-purpose or “generic”: collection concept.

It is common to see documents with explicit structure marked up in languages such as XML. Queries, on the other hand, typically have no structure. There is a clear mismatch, although documents contain structure it is typically not used in information retrieval. An efficient index structure for document-centric searching is proposed and its efficiency is discussed. It is shown to be at worst linear with respect to the number of occurrences of a given search term. The algorithm is then extended to accommodate element-centric information retrieval. Ranking algorithms for structured documents are examined. Genetic Algorithms are used to learn different weights for each structure present in a document. Applying these weights as part of a function is shown to yield significant precision improvements in some functions. Genetic Programming is then used to learn an entire ranking function. This function is shown to be portable between document collections. A query language for structured information retrieval is proposed. Use of this language in the 2004 INEX workshop resulted in a large decrease in query errors. Structured information retrieval is now a viable alternative to its unstructured counterpart. A successful query language, efficient indexing structures, and improved ranking functions are all presented.

The professional profile of researchers is established through communication of scientific work practices, leading to the establishment of a scholarly identity. Understanding scholarly identities is currently addressed through a conceptualisation of research narrative mechanisms. Citation and citing practices are a central component of scientific communication work practices. Therefore understanding these formal communication practices of researchers through their citing behaviours may contribute to the building of scholarly identity. This study is undertaken to understand whether scholarly identity could be informed through the use of citation identities. Studies on the citation identities of individuals were conducted, using authors working in the area of Consciousness, which provided a diverse field of participants for the testing of citation analysis techniques. This is accomplished through methodological development and further examined using a combination of field-level and individual-level analyses. A new methodology was developed for the generation of citing identities, based on the calculation of the Gini coefficient and the citee-citation ratio of authors' citing profiles. The resu!ting relationship was found to have high levels of consistency across a heterogenous set of researchers. An exploration of identification of author characteristics was subsequently undertaken using the new methodology and existing citation analysis techniques. The techniques were successful in identifying departures from conventional citation practice, highlighting idiosyncrasies well, but otherwise understanding of scholarly identity through citation analysis was only marginally successful. Aportion of the difficulty of achieving clarity was the complexity of the Consciousness author set, which was useful for establishing broad applicability of a new methodology, but poor for judging its successful application. In summary, definition of citing identity type offers possibilities for improving the understanding of scholarly identity, but will require further methodology development to reach its full potential.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1993.
Vita. Abstract. Vol. 2 is appendices. Includes bibliographical references (leaves 327-337). Also available via the Internet.

The nature of Internet and Intranet Web applications has changed from a static content-distribution medium into an interactive, dynamic medium, often used to serve multimedia from back-end object-relational databases to Web-enabled clients. Consequently, developers need to make an informed technological choice for developing software that supports a Web-based application for distributing multimedia over networks. This decision is based on several factors. Among the factors are ease of programming, richness of features, scalability, and performance. The research focuses on these key factors when distributing images from an Oracle9i database using Java Servlets, JSP, ASP, and ASP.NET as the server-side development technologies. Prototype applications are developed and tested within each technology: one for single image serving and the other for multiple image serving. A matrix of recommendations is provided to distinguish which technology, or combination of technologies, provides the best performance and development platform for image serving within the studied envirorunent.
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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 1990.
eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 120-125).

MASTS is an extensible, feature rich, software architecture based on tabu search (TS), a metaheuristic that relies on memory structures to intelligently organize and navigate the search space. MASTS introduces a new methodology of rule based objectives (RBOs), in which the search objective is replaced with a binary comparison operator more capable of expressing a variety of preferences. In addition, MASTS supports a new metastrategy, dynamic neighborhood selection (DNS), which “learns” about the search landscape to implement an adaptive intensification-diversification strategy. DNS can improve search performance by directing the search to promising regions and reducing the number of required evaluations. To demonstrate the flexibility and range of capabilities, MASTS is applied to two complex decision problems in conservation planning and groundwater management. As an extension of MASTS, ConsNet addresses the spatial conservation area network design problem (SCANP) in conservation biology. Given a set of possible geographic reserve sites, the goal is to select which sites to place under conservation to preserve unique elements of biodiversity. Structurally, this problem resembles the NP-hard set cover problem, but also considers additional spatial criteria including compactness, connectivity, and replication. Modeling the conservation network as a graph, ConsNet uses novel techniques to quickly compute these spatial criteria, exceeding the capabilities of classical optimization methods and prior planning software. In the arena of groundwater planning, MASTS demonstrates extraordinary flexibility as both an advanced search engine and a decision aid. In House Bill 1763, the Texas state legislature mandates that individual Groundwater Conservation Districts (GCDs) must work together to set specific management goals for the future condition of regional groundwater resources. This complex multi-agent multi-criteria decision problem involves finding the best way to meet these goals considering a host of decision variables such as pumping locations, groundwater extraction rates, and drought management policies. In two separate projects, MASTS has shaped planning decisions in the Barton Springs/Edwards Aquifer Conservation District and Groundwater Management Area 9 (GMA9). The software has been an invaluable decision support tool for planners, stakeholders, and scientists alike, allowing users to explore the problem from a multicriteria perspective.
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This chapter gives a relatively non-technical introduction to computer programs for marking of essays, generally known as Automated Essay Scoring (AES) systems. It identifies four stages in the process, which may be distinguished as training, summarising mechanical and structural aspects, describing content, and scoring, and describes how these are carried out in a number of commercially available programs. It considers how the validity of the process may be assessed, and reviews some of the evidence on how successful they are. It also discusses some of the ways in which they may fall down and describes some research investigating this. The chapter concludes with a discussion of possible future developments, and offers a number of searching questions for administrators considering the possibility of introducing AES in their own schools.

The World Wide Web is known as the “universe of network-accessible information, the embodiment of human knowledge” (W3C, 1999). Internet-based knowledge management aims to use the Internet as the world wide environment for knowledge publishing, searching, sharing, reusing, and integration, and to support collaboration and decision making. However, knowledge on the Internet is buried in documents. Most of the documents are written in languages for human readers. The knowledge contained therein cannot be easily accessed by computer programs such as knowledge management systems. In order to make the Internet “machine readable,” information extraction from Web pages becomes a crucial research problem.

Chronic diseases are the leading causes of death and disability worldwide. By 2020, it is expected to increase to 73% of all deaths and 60% of global burden of disease associated with chronic diseases. For all these reasons, early diagnosis and treatment of chronic diseases is very important. Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning is the development of computer programs that can access data and use it to learn for themselves. The learning process starts by searching for patterns in the examples, experiences, or observations. It will make faster and better decisions in the future based on all these. The primary purpose in machine learning is to allow computers to learn automatically without human help and affect. Considering all the reasons above, this chapter finds the most appropriate artificial intelligence technique for the early detection of chronic diseases.

The subtitle of John Holland's pioneering 1975 book Adaptation in Natural and Artificial Systems correctly anticipated that the genetic algorithm described in that book would have "applications to.. .artificial intelligence." When the entities in the evolving population are computer programs, Holland's genetic algorithm can be used to perform the task of searching the space of computer programs for a program that solves, or approximately solves, a problem. This variation of the genetic algorithm (called genetic programming) enables the genetic algorithm to address the long-standing challenge of getting a computer to solve a problem without explicitly programming it. Specifically, this challenge calls for an automatic system whose input is a high-level statement of a problem's requirements and whose output is a satisfactory solution to the given problem. Paraphrasing Arthur Samuel [33], this challenge concerns "How can computers be made to do what needs to be done, without being told exactly how to do it?" This challenge is the common goal of such fields of research as artificial intelligence and machine learning. Arthur Samuel [32] offered one measure for success in this pursuit, namely "The aim [is].. .to get machines to exhibit behavior, which if done by humans, would be assumed to involve the use of intelligence." Since a problem can generally be recast as a search for a computer program, genetic programming can potentially solve a wide range of problems, including problems of control, classification, system identification, and design. Section 2 describes genetic programming. Section 3 states what we mean when we say that an automatically created solution to a problem is competitive with the product of human creativity. Section 4 discusses the illustrative problem of automatically synthesizing both the topology and sizing for an analog electrical circuit. Section 5 discusses the problem of automatically determining the placement and routing (while simultaneously synthesizing the topology and sizing) of an electrical circuit. Section 6 discusses the problem of automatically synthesizing both the topology and tuning for a controller. Section 7 discusses the importance of illogic in achieving creativity and inventiveness.

Data mining, which is defined as the process of extracting previously unknown knowledge and detecting interesting patterns from a massive set of data, has been an active research area. As a result, several commercial products and research prototypes are available nowadays. However, most of these studies have focused on corporate data — typically in an alpha-numeric database, and relatively less work has been pursued for the mining of multimedia data (Zaïane, Han, & Zhu, 2000). Digital multimedia differs from previous forms of combined media in that the bits representing texts, images, audios, and videos can be treated as data by computer programs (Simoff, Djeraba, & Zaïane, 2002). One facet of these diverse data in terms of underlying models and formats is that they are synchronized and integrated hence, can be treated as integrated data records. The collection of such integral data records constitutes a multimedia data set. The challenge of extracting meaningful patterns from such data sets has lead to research and development in the area of multimedia data mining. This is a challenging field due to the non-structured nature of multimedia data. Such ubiquitous data is required in many applications such as financial, medical, advertising and Command, Control, Communications and Intelligence (C3I) (Thuraisingham, Clifton, Maurer, & Ceruti, 2001). Multimedia databases are widespread and multimedia data sets are extremely large. There are tools for managing and searching within such collections, but the need for tools to extract hidden and useful knowledge embedded within multimedia data is becoming critical for many decision-making applications.

Gas turbines need to operate efficiently due to the high specific fuel consumption. In order to reach the best possible efficiency the main gas turbine components, such as compressor and turbine, need to be optimized. This work reports the use of two specially developed computer programs: AFCC [1, 2] and GTAnalysis [3, 4] for such purpose. An axial flow compressor has been designed, using the AFCC computer program based on the stage-stacking technique. Major compressor design parameters are optimized at design point, searching for best efficiency and surge margin. Operation points are calculated and its characteristics maps are generated. The calculated compressor maps are incorporated to the GTAnalysis computer program for the engine performance calculation. Restrictions, like engine complexity, manufacture difficulties and control problems, are not taken into account.

Now FPSO (Floating Production Storage and Offloading) has been widely used in exploitative engineering of offshore petroleum/gas reservoir and becoming one of the most important production facilities. FPSO which is a floating structure has the virtue of sea keeping, permanent mooring, large oil storage, offshore unloading and recursive and so on. FPSO can be used in lots of kinds of oil fields. The Paper mainly introduces software FPSO Mooring Management System which is designed for CNOOC Oil Base Group. There are 17 FPSO serving in China Sea area, so that it is becoming more and more serious on FPSO mooring system. The main failures of mooring system are as follows: broken of main bearing, fracture of YOKE transverse beam, crack of anchor chain, leak of swivel head, local damage under typhoon etc. FPSO Mooring Management System is designed to track and control FPSO mooring situation and to keep detailed information on FPSO mooring management, operation, maintenance etc. This system puts chief data of 136 FPSO together which are serving, under construction, maintaining in the world. This system also provides technical support for company decision. FPSO Mooring Management System is made with JSP, using ORACLE as database, so it can run at any operating system. This system offers access to upload folders and EXCEL files to database to save time and decrease errors in managing lots of data. There are a lot of kinds of files which should be classified by subject. In order to satisfy the need to get different united information not only by certain classification, this system is designed with open structure, it allows users to store files by any classification and own the power to change it. The system offers different searching ways, by which user can get what they want exactly, then the transfers corresponding programs in the computer to play these files. This system meets the requirement of users to get what they want efficiently.

Aim/Purpose: This paper provides the results of the preliminary analysis of the findings of an ongoing study that seeks to examine the social media use, cultural and political awareness, civic engagement, issue prioritization, and social activism of Gen Z students enrolled at four different institutional types located in the Mid-Atlantic region of the United States. The aim of this study is to look at the group as a whole as well as compare findings across populations. The institutional types under consideration include a mid-sized majority serving or otherwise referred to as a traditionally white institution (TWI) located in a small coastal city on the Atlantic Ocean, a small Historically Black University (HBCU) located in a rural area, a large community college located in a county that is a mixture of rural and suburban and which sits on the border of Maryland and Pennsylvania, and graduating high school students enrolled in career and technical education (CTE) programs in a large urban area. This exploration is purposed to examine the behaviors and expectations of Gen Z students within a representative American region during a time of tremendous turmoil and civil unrest in the United States. Background: Over 74 million strong, Gen Z makes up almost one-quarter of the U.S. population. They already outnumber any current living generation and are the first true digital natives. Born after 1996 and through 2012, they are known for their short attention spans and heightened ability to multi-task. Raised in the age of the smart phone, they have been tethered to digital devices from a young age with most having the preponderance of their childhood milestones commemorated online. Often called Zoomers, they are more racially and ethnically diverse than any previous generation and are on track to be the most well-educated generation in history. Gen Zers in the United States have been found in the research to be progressive and pro-government and viewing increasing racial and ethnic diversity as positive change. Finally, they are less likely to hold xenophobic beliefs such as the notion of American exceptionalism and superiority that have been popular with by prior generations. The United States has been in a period of social and civil unrest in recent years with concerns over systematic racism, rampant inequalities, political polarization, xenophobia, police violence, sexual assault and harassment, and the growing epidemic of gun violence. Anxieties stirred by the COVID-19 pandemic further compounded these issues resulting in a powder keg explosion occurring throughout the summer of 2020 and leading well into 2021. As a result, the United States has deteriorated significantly in the Civil Unrest Index falling from 91st to 34th. The vitriol, polarization, protests, murders, and shootings have all occurred during Gen Z’s formative years, and the limited research available indicates that it has shaped their values and political views. Methodology: The Mid-Atlantic region is a portion of the United States that exists as the overlap between the northeastern and southeastern portions of the country. It includes the nation’s capital, as well as large urban centers, small cities, suburbs, and rural enclaves. It is one of the most socially, economically, racially, and culturally diverse parts of the United States and is often referred to as the “typically American region.” An electronic survey was administered to students from 2019 through 2021 attending a high school dual enrollment program, a minority serving institution, a majority serving institution, and a community college all located within the larger mid-Atlantic region. The survey included a combination of multiple response, Likert scaled, dichotomous, open ended, and ordinal questions. It was developed in the Survey Monkey system and reviewed by several content and methodological experts in order to examine bias, vagueness, or potential semantic problems. Finally, the survey was pilot tested prior to implementation in order to explore the efficacy of the research methodology. It was then modified accordingly prior to widespread distribution to potential participants. The surveys were administered to students enrolled in classes taught by the authors all of whom are educators. Participation was voluntary, optional, and anonymous. Over 800 individuals completed the survey with just over 700 usable results, after partial completes and the responses of individuals outside of the 18-24 age range were removed. Findings: Participants in this study overwhelmingly were users of social media. In descending order, YouTube, Instagram, Snapchat, Twitter, Facebook, Pinterest, WhatsApp, LinkedIn and Tik Tok were the most popular social media services reported as being used. When volume of use was considered, Instagram, Snapchat, YouTube and Twitter were the most cited with most participants reporting using Instagram and Snapchat multiple times a day. When asked to select which social media service they would use if forced to choose just one, the number one choice was YouTube followed by Instagram and Snapchat. Additionally, more than half of participants responded that they have uploaded a video to a video sharing site such as YouTube or Tik Tok. When asked about their familiarity with different technologies, participants overwhelmingly responded that they are “very familiar” with smart phones, searching the Web, social media, and email. About half the respondents said that they were “very familiar” with common computer applications such as the Microsoft Office Suite or Google Suite with another third saying that they were “somewhat familiar.” When asked about Learning Management Systems (LMS) like Blackboard, Course Compass, Canvas, Edmodo, Moodle, Course Sites, Google Classroom, Mindtap, Schoology, Absorb, D2L, itslearning, Otus, PowerSchool, or WizIQ, only 43% said they were “very familiar” with 31% responding that they were “somewhat familiar.” Finally, about half the students were either “very” or “somewhat” familiar with operating systems such as Windows. A few preferences with respect to technology in the teaching and learning process were explored in the survey. Most students (85%) responded that they want course announcements and reminders sent to their phones, 76% expect their courses to incorporate the use of technology, 71% want their courses to have course websites, and 71% said that they would rather watch a video than read a book chapter. When asked to consider the future, over 81% or respondents reported that technology will play a major role in their future career. Most participants considered themselves “informed” or “well informed” about current events although few considered themselves “very informed” or “well informed” about politics. When asked how they get their news, the most common forum reported for getting news and information about current events and politics was social media with 81% of respondents reporting. Gen Z is known to be an engaged generation and the participants in this study were not an exception. As such, it came as no surprise to discover that, in the past year more than 78% of respondents had educated friends or family about an important social or political issue, about half (48%) had donated to a cause of importance to them, more than a quarter (26%) had participated in a march or rally, and a quarter (26%) had actively boycotted a product or company. Further, about 37% consider themselves to be a social activist with another 41% responding that aren’t sure if they would consider themselves an activist and only 22% saying that they would not consider themselves an activist. When asked what issues were important to them, the most frequently cited were Black Lives Matter (75%), human trafficking (68%), sexual assault/harassment/Me Too (66.49%), gun violence (65.82%), women’s rights (65.15%), climate change (55.4%), immigration reform/deferred action for childhood arrivals (DACA) (48.8%), and LGBTQ+ rights (47.39%). When the schools were compared, there were only minor differences in social media use with the high school students indicating slightly more use of Tik Tok than the other participants. All groups were virtually equal when it came to how informed they perceived themselves about current events and politics. Consensus among groups existed with respect to how they get their news, and the community college and high school students were slightly more likely to have participated in a march, protest, or rally in the last 12 months than the university students. The community college and high school students were also slightly more likely to consider themselves social activists than the participants from either of the universities. When the importance of the issues was considered, significant differences based on institutional type were noted. Black Lives Matter (BLM) was identified as important by the largest portion of students attending the HBCU followed by the community college students and high school students. Less than half of the students attending the TWI considered BLM an important issue. Human trafficking was cited as important by a higher percentage of students attending the HBCU and urban high school than at the suburban and rural community college or the TWI. Sexual assault was considered important by the majority of students at all the schools with the percentage a bit smaller from the majority serving institution. About two thirds of the students at the high school, community college, and HBCU considered gun violence important versus about half the students at the majority serving institution. Women’s rights were reported as being important by more of the high school and HBCU participants than the community college or TWI. Climate change was considered important by about half the students at all schools with a slightly smaller portion reporting out the HBCU. Immigration reform/DACA was reported as important by half the high school, community college, and HBCU participants with only a third of the students from the majority serving institution citing it as an important issue. With respect to LGBTQ rights approximately half of the high school and community college participants cited it as important, 44.53% of the HBCU students, and only about a quarter of the students attending the majority serving institution. Contribution and Conclusion: This paper provides a timely investigation into the mindset of generation Z students living in the United States during a period of heightened civic unrest. This insight is useful to educators who should be informed about the generation of students that is currently populating higher education. The findings of this study are consistent with public opinion polls by Pew Research Center. According to the findings, the Gen Z students participating in this study are heavy users of multiple social media, expect technology to be integrated into teaching and learning, anticipate a future career where technology will play an important role, informed about current and political events, use social media as their main source for getting news and information, and fairly engaged in social activism. When institutional type was compared the students from the university with the more affluent and less diverse population were less likely to find social justice issues important than the other groups. Recommendations for Practitioners: During disruptive and contentious times, it is negligent to think that the abounding issues plaguing society are not important to our students. Gauging the issues of importance and levels of civic engagement provides us crucial information towards understanding the attitudes of students. Further, knowing how our students gain information, their social media usage, as well as how informed they are about current events and political issues can be used to more effectively communicate and educate. Recommendations for Researchers: As social media continues to proliferate daily life and become a vital means of news and information gathering, additional studies such as the one presented here are needed. Additionally, in other countries facing similarly turbulent times, measuring student interest, awareness, and engagement is highly informative. Impact on Society: During a highly contentious period replete with a large volume of civil unrest and compounded by a global pandemic, understanding the behaviors and attitudes of students can help us as higher education faculty be more attuned when it comes to the design and delivery of curriculum. Future Research This presentation presents preliminary findings. Data is still being collected and much more extensive statistical analyses will be performed.