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Survey Analysis of Computer Science, Food Science, and Cybersecurity Skills and Coursework of Undergraduate and Graduate Students Interested in Food Safety

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Title: Survey Analysis of Computer Science, Food Science, and Cybersecurity Skills and Coursework of Undergraduate and Graduate Students Interested in Food Safety
Language: English
Authors: Feye, K. M. (ORCID 0000-0002-5346-8390), Lekkala, H., Lee-Bartlett, J. A., Thompson, D. R., Ricke, S. C.
Source: Journal of Food Science Education. Oct 2020 19(4):240-249.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 10
Publication Date: 2020
Sponsoring Agency: National Institute of Food and Agriculture (USDA)
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: College Students, Food, Safety, Computer Literacy, Computer Security, Extracurricular Activities, Knowledge Level, Familiarity
DOI: 10.1111/1541-4329.12200
ISSN: 1541-4329
Abstract: Automation is coming and will enable not only the ability to increase poultry processing line speeds, but also the collection of considerable "big data." These data can be collected "en masse," stored, analyzed, and used to improve food safety, quality, enhance traceability, and also be used for risk assessment. However, as this technology is implemented in the poultry industry, computer hackers will emerge to pose a clear and present danger to the poultry industry and the upcoming generation of professionals must be equipped with the knowledge to protect sensitive data. The objective of this study was to quantitate the current computer science (CS) competency, food science exposure and extracurricular activities, and familiarity with cybersecurity topics of students in food science and related fields. Students ranked their CS abilities, 1 through 5, with 1 being the lowest level of competence and 5 representing the highest level of confidence. To assess their knowledge of food safety-related sciences, participants were asked about their familiarity with the respective fields. The average student was familiar with common avenues of food safety exposure, such as television and the Internet. Students were less familiar with more advanced, and arguably important topics, such as botnet. Finally, the students ranked their familiarity with cybersecurity topics, 1 through 5, with 1 representing being not familiar at all and 5 representing extremely familiar. Therefore, to meet the future technological demands, specific course-work is required to improve prospective student CS and cybersecurity competency.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1270549
Database: ERIC
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  Value: <anid>AN0146395023;[2yg1]01oct.20;2020Oct14.05:17;v2.2.500</anid> <title id="AN0146395023-1">Survey analysis of computer science, food science, and cybersecurity skills and coursework of undergraduate and graduate students interested in food safety </title> <p>Automation is coming and will enable not only the ability to increase poultry processing line speeds, but also the collection of considerable "big data." These data can be collected en masse, stored, analyzed, and used to improve food safety, quality, enhance traceability, and also be used for risk assessment. However, as this technology is implemented in the poultry industry, computer hackers will emerge to pose a clear and present danger to the poultry industry and the upcoming generation of professionals must be equipped with the knowledge to protect sensitive data. The objective of this study was to quantitate the current computer science (CS) competency, food science exposure and extracurricular activities, and familiarity with cybersecurity topics of students in food science and related fields. Students ranked their CS abilities, 1 through 5, with 1 being the lowest level of competence and 5 representing the highest level of confidence. To assess their knowledge of food safety‐related sciences, participants were asked about their familiarity with the respective fields. The average student was familiar with common avenues of food safety exposure, such as television and the Internet. Students were less familiar with more advanced, and arguably important topics, such as botnet. Finally, the students ranked their familiarity with cybersecurity topics, 1 through 5, with 1 representing being not familiar at all and 5 representing extremely familiar. Therefore, to meet the future technological demands, specific course‐work is required to improve prospective student CS and cybersecurity competency.</p> <p>Keywords: computer skills; cybersecurity; food safety; undergraduate students</p> <hd id="AN0146395023-2">INTRODUCTION</hd> <p>The advent of big data and smart technologies continues to lead to significant innovation across numerous industries, with very few sectors remaining untouched by its effects (Rose & Chilvers, 2018). Despite being a scientific argot, data classified as "big data" lend itself to impressive heterogenicity within and between fields; therefore, the definition continues to evolve as various sectors learn how to create, interpret, and apply expansive datasets. The breadth and speed of its use results in an ever‐evolving definition, which currently is: "<emph>the Information assets characterized by High Volume, Velocity, and Variety to require specific Technology and Analytical Methods for its transformation into Value</emph>" (De Mauro, Greco, & Grimaldi, 2015). Big data is by its nature highly quantitative and requires the use of advanced analytical technology to maximize its use and value to the data consumer (De Mauro et al., 2015).</p> <p>The emergence of big data necessitates significant advances in cybersecurity to ensure that potentially sensitive information is sequestered from the public domain (Denning & Denning, 2016; Tariq et al., 2019). Hackers are nefarious contributors to the coevolution of cybersecurity and data science, where vulnerabilities are actively exploited with potentially devastating effects (Hemberg, Zipkin, Skowyra, Wagoner, & O'Reilly, 2018; Hutson, 2018). While on the surface, the xennial and millennial generations are naturally more computer literate than previous generations, there are profound differences in how they use and adapt to technology (Taylor, 2018). An adaptation to technology does not necessarily mean that topics such as cybersecurity and the vertical integration of large datasets are an assumed skill. The increase in IoT (Internet of Things) competent devices does not correlate to a standard understanding of computer and cybersecurity literacy, especially in divergent computer‐literate populations (Hutson, 2018; Taylor, 2018).</p> <p>The food industry is no different from any other sector when it comes to the acquisition of high‐tech, computer science (CS)‐based skillsets. Big data has the potential to revolutionize food safety and traceability as well as to improve product on‐demand quality and shelf‐life (Taboada et al., 2017; Thompson, Rainwater, Di, & Ricke, 2017). Previous generations of professionals focused on the importance of reducing and monitoring for physical cross‐contamination events that led to foodborne outbreaks of disease (Thompson et al., 2017). However, the implementation of automated and high‐throughput and quality checks centering around food safety monitoring will necessitate change (Thompson et al., 2017). The further vertical integration of food systems continues to create a niche of big data management becoming a keystone in food safety monitoring, as well as product quality and consumer demand (Thompson et al., 2017).</p> <p>The use of big data has already assisted in improving epidemiological tracing of foodborne outbreaks of disease and microbial communities throughout processing plants (Kim, Park, Lee, Owens, & Ricke, 2017; Mayo et al., 2014; Schurch, Arredondo‐Alonso, Willems, & Goering, 2018). The unrestrained power of analysis and traceability allows for the potential of real‐time management decisions that can both reduce the cost to producers and safeguard the public food supply (Taboada et al., 2017; Thompson et al., 2017). As with other sectors, the heterogenicity of the data coming off of the food production lines in real‐time is extensive. Not only is there a potential for real‐time pathogen monitoring and whole genome sequencing for epidemiological tracking of foodborne disease, but it also includes colorimetric mass spectroscopy for meat quality, vibrational and fluorescence spectroscopy, and chemometrics (Danezis, Tsagkaris, Camin, Brusic, & Georgiou, 2016; Deurenberg et al., 2017; Granato et al., 2018; Mayo et al., 2014; Thompson et al., 2017). Data gathered can be processed with integrated systems that utilize artificial intelligence and integrated networks will both improve the economics of food production and reduce food spoilage and waste (Ji, Hu, & Tan, 2017; Thompson et al., 2017). The improved integration of economies and product tracking through systems, such as blockchain, will only add selective pressure to continue this evolution (Kamanth, 2018; Lin, Shen, Zhang, & Chai, 2018; Mayo et al., 2014; Tariq et al., 2019). Artificial intelligence compounds the utility and complexity of these data, which both adds robustness to the structures in place as well as increases the potential for data breaches (Hutson, 2018).</p> <p>Effectively, the up and coming generations of professionals will be required to engage and integrate large‐scale scientific and statistical computer‐based systems. While it is assumed that the xennial and millennial generations are equipped to handle this emerging problem, it is necessary to evaluate the baseline knowledge of computers, food science, and cybersecurity in undergraduate and graduate students. In both analyzing coursework and relationships to food safety and cybersecurity, knowledge‐gaps can be identified. Furthermore, by evaluating the extreme ends of the university‐based educational spectra, undeclared freshman and graduate students in food science, it can be determined if research in food science impacts the survey outcomes and the educational deficiencies (Singh, Gammie, & Lorsch, 2016). As a result, the creation of new coursework to fill those gaps becomes a natural and necessary next step as exposure to threats and the subsequent education are powerful ways to shape up and coming professionals (Kern, Fabian, & Ermakova, 2018; Thompson et al., 2017). This study provides information that enables educators to identify strengths and weaknesses and develop tools for future xennial and millennial food science professionals.</p> <hd id="AN0146395023-3">METHODOLOGY</hd> <p></p> <hd id="AN0146395023-4">Identification of students to assess and target audience</hd> <p>The University of Arkansas (UA) Department of Food Science is a department contained within the Dale Bumpers College of Agriculture, and is also a part of the UA Division of Agriculture. The food science undergraduate degree requires 120 credit hours and does not include any CS or cybersecurity coursework in any of the concentrations of study offered. Two different types of courses were identified to study CS competency, food science exposure, and cybersecurity familiarity, one undergraduate and one graduate level. The undergraduate Exploring Topics in Food Science one‐hour credit course is an introduction to food science targeting freshman‐level students, undeclared majors, with an approximate enrollment of 65 students. The course emphasizes the importance of science in processing and preservation of food as well as practical information on food processing, composition, additives, labeling, environmental issues, regulations, safety, sensory analysis, and health benefits. This undergraduate course was identified as a good course for assessing entry level and potential food science students. Graduate student CS competency, food science exposure, and cybersecurity familiarity were also of interest, especially CS competency and cybersecurity familiarity, as they will be gathering and analyzing large datasets that contain sensitive information. Therefore, graduate students in a graduate‐level one‐hour seminar were surveyed in three separate semesters. The graduate seminar for students in food science and related fields discusses graduate student research, faculty research, and also brings in outside speakers from industry and other academic departments. To summarize, one survey was administered in an undergraduate course that introduces food science to undeclared majors and three separate surveys were administered in a graduate seminar course for students in food science and related fields. Information gained throughout this study will enable educators to design new coursework for both undergraduate and graduate students in food science and related fields aimed at addressing the vulnerabilities of the evolving world of CS, food science, and cybersecurity.</p> <hd id="AN0146395023-5">Survey design and use</hd> <p>A survey was designed to quantitate the current CS competency, food science exposure and extracurricular activities, and familiarity with cybersecurity topics of students in food science and related fields. The first part of the survey focused on CS competency, CS coursework, and familiarity with cybersecurity topics. The students were asked to indicate their perception of their level of ability in 13 CS skill areas that ranged from basic skills, such as word processing, spreadsheets, and presentation software up to advanced skills, such as web design, software development, and hacking. Students were asked to indicate their perception of their level of ability in each area from 1 through 5, with 1 being no level of competence, 2 being low level of competence, 3 being average level of competence, 4 being moderately high level of competence, and 5 being high level of competence. In addition, the students were asked if they had taken any CS courses in high school, including AP Computer Science A, AP Computer Science Principles, Mobile App Development, or any other CS or programming course. The students were subsequently asked to indicate their familiarity with 8 cybersecurity topics, such as phishing attacks, ransomware, identity theft, hacking, and botnets. Students were asked to indicate their familiarity with each topic from 1 through 5, with 1 being not at all familiar, 2 being slightly familiar, 3 being somewhat familiar, 4 being moderately familiar, and 5 being extremely familiar.</p> <p>The second part of the survey focused on food science‐related questions grouped into exposure to food science topics and participation in food science courses and extracurricular activities. Students were asked to indicate how often they were exposed to food science topics on TV, cooking shows, newspapers, farmers markets, farm, food bank, Internet, home garden, radio, grocery shopping, and magazines. Students were asked to indicate their exposure from 1 to 5, with 1 being never, 2 being almost never, 3 being occasionally/sometimes, 4 being almost every time, and 5 being frequently. In addition, students were asked if they had taken courses, participated in extracurricular activities, or worked at a job related to food science in high school.</p> <hd id="AN0146395023-6">Data analysis</hd> <p>Given the two very different sample populations of undergraduate and graduate students, the data were analyzed separately but plotted on the same graphs to compare. The average CS competency was plotted as a histogram for each of the 13 CS skill areas for both undergraduate and graduate students. In addition, the percentage of students taking CS coursework in high school was plotted as a histogram for both undergraduate and graduate students. For exposure to food science topics, the average amount of exposure from each area was plotted as a histogram for both undergraduate and graduate students. Finally, the percentage of students who had taken courses, participated in extracurricular activities, or worked at a job related to food science in high school was plotted as a histogram for both undergraduate and graduate students.</p> <hd id="AN0146395023-7">RESULTS</hd> <p></p> <hd id="AN0146395023-8">Cohort demographics</hd> <p>Throughout the survey period, demographic data were collected, including academic standing, full‐time/part‐time student status, sex, degrees, and race for both the undergraduate and graduate students. One survey was conducted targeting undergraduates (<emph>N</emph> = 61) and three surveys were conducted targeting graduate students (<emph>N</emph> = 43), resulting in a total of 104 students surveyed. For the undergraduate students, the distribution of academic standing is shown in Figure 1, the distributions of full‐time/part‐time status and sex are shown in Figure 2, the distribution of degrees the students are pursuing is shown in Figure 3, and the race is shown in Figure 4. For the graduate students, the distributions full‐time/part‐time status and degrees are shown in Figure 5 and the distributions of sex and race are shown in Figure 6.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0001.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0001.jpg" title="1 Undergraduate course: academic standing" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0002.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0002.jpg" title="2 Undergraduate course: status and sex" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0003.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0003.jpg" title="3 Undergraduate course: final degree student is pursuing" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0004.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0004.jpg" title="4 Undergraduate course: race" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0005.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0005.jpg" title="5 Graduate seminar courses: status and final degree student is pursuing" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0006.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0006.jpg" title="6 Graduate seminar courses: sex and race" /> </p> <p></p> <p>The undergraduate student academic standing was mostly freshman, sophomores, and juniors as seen in Figure 1. As seen in Figure 2, most of the students were full‐time students and there were slightly more female students than male students. Most students were pursuing a BS degree (<reflink idref="bib37" id="ref1">37</reflink>) but nine were pursuing a BA and nine declared that they wanted to pursue a Ph.D. in the area even though they were undergraduate students as seen in Figure 3. As seen in Figure 4, the undergraduate population was more homogenous than the graduate students discussed below, with 43 students identifying as white, 10 students identified as Black, 4 were identified as Asian or Pacific Islander, and 1 student was American Indian.</p> <p>Of the graduate students, 20 were pursuing a Ph.D., with the remainder of the students pursuing Master's degrees in their respective fields as seen in Figure 5. As seen in Figure 6, the racial make‐up of the graduate cohort was mildly diverse with 23 graduate students being white, 4 students Hispanic, 11 Asian or Pacific Islander, 3 students Black or of African descent, 1 student Native American, and the remaining students were either declared as other or not disclosing their status. A total of 50 students belonged to the College of Agriculture, with the remaining students representing the Colleges of Arts and Science, College of Engineering, College of Business, Undecided, and Other with two students not identifying their status.</p> <hd id="AN0146395023-15">Survey results</hd> <p>Trends for the undergraduate and graduate students were relatively consistent throughout the survey. Figure 7 describes the CS skill areas of each of the student populations, with a ranking from 1 (no level of competence) to 5 (high level of competence). As expected, undergraduate and graduate students had the most experience in email, web searches, and social networking. Graduate students had more experience in word processing, spreadsheets, and presentation software. More advanced understanding of CS, such as hacking, Linux, programming, and web design, was less common. This was not surprising as both the graduate and undergraduate population exhibited a very low frequency of exposure to CS coursework in high school as seen in Figure 8. In fact, no graduate students had experience with mobile app development despite the large social media experience shared by both the graduate and undergraduate students.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0007.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0007.jpg" title="7 Computer science competency" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0008.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0008.jpg" title="8 Computer science coursework in high school" /> </p> <p></p> <p>Deficiencies continued to emerge when evaluating the familiarity with important cybersecurity topics by both the undergraduate and graduate students. As shown in Figure 9, identity theft was the most commonly reported topic of familiarity followed by hacking. However, botnets, the Internet protocol, denial of service attacks, and ransomware were all only slightly to somewhat familiar to the student population. Graduate students numerically had more familiarity with phishing attacks but virtually the same familiarity as undergraduate students in all other cybersecurity topics.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0009.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0009.jpg" title="9 Familiarity with cybersecurity topics" /> </p> <p></p> <p>How often students were exposed to food science in different avenues is shown in Figure 10. When the students were surveyed, the Internet and grocery shopping were the most common experiences for students. Graduate students numerically had more exposure to food science through the shopping and Internet. Newspapers, farmers market, farm, food bank, home garden, and radio food science exposure were less often for students, which may represent generational differences that are already emerging. However, the information was more accessible than CS‐based questions. As seen in Figure 11, most students had a greater frequency of exposure to hands‐on food science experiences, like home economics and nutrition courses. Graduate students also exclusively had experience working in food processing plants, 4‐H, and preparing food preservatives for the state fair.</p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0010.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0010.jpg" title="10 Food science frequency of exposure in different avenues" /> </p> <p></p> <p> <img src="https://imageserver.ebscohost.com/img/embimages/rdk/2YG1/01oct20/jfs312200-fig-0011.jpg?ephost1=dGJyMNXb4kSepq84yOvqOLCmsE6epq5Srqa4SK6WxWXS" alt="jfs312200-fig-0011.jpg" title="11 Food science courses, extracurricular activities, and jobs" /> </p> <p></p> <hd id="AN0146395023-21">DISCUSSION AND CONCLUSION</hd> <p>This work provides an analysis of the CS competency, food science exposure and extracurricular activities, and familiarity with cybersecurity topics of the up and coming food science skilled labor workforce. As with all fields, times are rapidly changing and the educational needs of the corresponding workforce will need to follow suit. In order to determine the deficiencies of undergraduate and graduate food students, this study was conducted. Not surprising, social media and commonly accessed technologies, such as the word processing, spreadsheets, and presentation software, were very familiar to the students. However, significant deficiencies appeared when students were asked about different types of CS topics, such as programming and web design, and cybersecurity topics, such as encryption, Linux, and denial of service attacks. This is extremely concerning given the importance of data security required to safeguard the public food supply and how other platforms, like Linux, will become increasingly important for food science students to master (Dutta & Mathur, 2012). Linux and computer programming languages, such as R, Python, C++, and Java, will be important tools for students to master if they are expected to meet the demands of their jobs. This is very concerning as K through 12 education, nor undergraduate and graduate food science education, emphasize these important skillsets (Dutta & Mathur, 2012).</p> <p>Solving the CS‐based deficiencies of our up and coming generation of undergraduate and graduate students will require an interdisciplinary approach. Interestingly, graduate students had more experience in a few select knowledge sets, including phishing attacks. While the differences reported in this study are based on a small sample size, it does potentially indicate that the longer students are in education systems, the more familiar with cybersecurity topics they become. Approaching these educational needs with unique, interdisciplinary coursework may be the best approach. Even within generation, the way technology is accessed and used is extremely different. Educational coursework will need to address the unique relationship each generation has with technology, broadening students from the more familiar social media applications to programming languages and applying that information to their field. For instance, if microbiome mapping is to become a tool, having a cybersecurity expert teach the course in conjunction with a microbiologist may provide unique educational experiences all around. This will enable communications across multiple disciplines with different needs and disparate understandings of each other's field and potentially serve as a bridge for students to broaden their perspectives. As regulatory agencies embrace these technologies, this type of training will become even more critical (Parrish et al., 2018).</p> <p>Breaches in cybersecurity along the food safety chain will be devastating and some of these challenges can already be seen in the medical field (Hagestand & Straumann, 2017). The risk for cyber‐terrorism or potentially leaking sensitive information to the public unnecessarily will pose a significant risk for food producers. By acknowledging deficiencies in undergraduate and graduate education and identifying needs, colleges and universities can properly prepare the next generation of food scientists to meet the demands of the future.</p> <hd id="AN0146395023-22">ACKNOWLEDGMENTS</hd> <p>A portion of this work was supported by <emph>Student Cross‐Training Opportunities for Combining Food and Cybersecurity into an Academic Food Systems Education Program</emph>, USDA National Institute of Food and Agriculture (NIFA), Higher Ed Challenge, Challenge Grants Program, under Grant Number 2018‐70003‐27663.</p> <hd id="AN0146395023-23">CONFLICT OF INTEREST</hd> <p>The authors do not declare a conflict of interest.</p> <hd id="AN0146395023-24">AUTHOR CONTRIBUTIONS</hd> <p>KMF prepared and analyzed the data and wrote the manuscript. JAB provided significant intellectual support and guidance on the analysis. SCR and DRT conceived the study. DRT prepared the final graphs and created the surveys. HL and DRT gathered student information. KMF, DRT, and SCR edited and prepared the manuscript for submission, as well as handled edits.</p> <ref id="AN0146395023-25"> <title> Footnotes </title> <blist> <bibl id="bib1" type="bt">1</bibl> <bibtext> The University of Arkansas Institutional Review Board (IRB) Committee granted an exemption under protocol # 1709074137 for the Computer Science and Food Science Survey.</bibtext> </blist> </ref> <ref id="AN0146395023-26"> <title> REFERENCES </title> <blist> <bibtext> Danezis, G. P., Tsagkaris, A. S., Camin, F., Brusic, V., & Georgiou, C. A. (2016). Food authentication; Techniques, trends, and emerging approaches. Trends in Analytical Chemistry, 85, 123 – 132.</bibtext> </blist> <blist> <bibl id="bib2" type="bt">2</bibl> <bibtext> Denning, P. J., & Denning, D. E. (2016). Cybersecurity is harder than building bridges. American Scientist: Computing Science, 104, 154 – 157.</bibtext> </blist> <blist> <bibl id="bib3" type="bt">3</bibl> <bibtext> Deurenberg, R. H., Bathroon, E., Chlebowicz, M. A., Couto, N., Ferdous, M., bos, Garcia‐C., ... Roosen, J. W. A. (2017). Application of next generation sequencing in clinical microbiology and infection prevention. Journal of Biotechnology, 243, 16 – 24.</bibtext> </blist> <blist> <bibl id="bib4" type="bt">4</bibl> <bibtext> De Mauro, A., Greco, M., & Grimaldi, M. (2015). What is big data? A consensual definition and a review of key research topics. AIP Conference Proceedings, 1644, 97 – 104. https://doi.org/10.1063/1.490783</bibtext> </blist> <blist> <bibl id="bib5" type="bt">5</bibl> <bibtext> Dutta, S., & Mathur, R. (2012). Cybersecurity. An integral part of STEM. IEEE. 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Elsevier.</bibtext> </blist> </ref> <aug> <p>By K. M. Feye; H. Lekkala; J. A. Lee‐Bartlett; D. R. Thompson and S. C. Ricke</p> <p>Reported by Author; Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib37" firstref="ref1"></nolink>
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  Data: Survey Analysis of Computer Science, Food Science, and Cybersecurity Skills and Coursework of Undergraduate and Graduate Students Interested in Food Safety
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Feye%2C+K%2E+M%2E%22">Feye, K. M.</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-5346-8390">0000-0002-5346-8390</externalLink>)<br /><searchLink fieldCode="AR" term="%22Lekkala%2C+H%2E%22">Lekkala, H.</searchLink><br /><searchLink fieldCode="AR" term="%22Lee-Bartlett%2C+J%2E+A%2E%22">Lee-Bartlett, J. A.</searchLink><br /><searchLink fieldCode="AR" term="%22Thompson%2C+D%2E+R%2E%22">Thompson, D. R.</searchLink><br /><searchLink fieldCode="AR" term="%22Ricke%2C+S%2E+C%2E%22">Ricke, S. C.</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Food+Science+Education%22"><i>Journal of Food Science Education</i></searchLink>. Oct 2020 19(4):240-249.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: Y
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  Data: 10
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  Data: 2020
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  Data: National Institute of Food and Agriculture (USDA)
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  Data: Journal Articles<br />Reports - Research
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  Label: Education Level
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Food%22">Food</searchLink><br /><searchLink fieldCode="DE" term="%22Safety%22">Safety</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Literacy%22">Computer Literacy</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Security%22">Computer Security</searchLink><br /><searchLink fieldCode="DE" term="%22Extracurricular+Activities%22">Extracurricular Activities</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+Level%22">Knowledge Level</searchLink><br /><searchLink fieldCode="DE" term="%22Familiarity%22">Familiarity</searchLink>
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  Data: 10.1111/1541-4329.12200
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  Data: 1541-4329
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  Label: Abstract
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  Data: Automation is coming and will enable not only the ability to increase poultry processing line speeds, but also the collection of considerable "big data." These data can be collected "en masse," stored, analyzed, and used to improve food safety, quality, enhance traceability, and also be used for risk assessment. However, as this technology is implemented in the poultry industry, computer hackers will emerge to pose a clear and present danger to the poultry industry and the upcoming generation of professionals must be equipped with the knowledge to protect sensitive data. The objective of this study was to quantitate the current computer science (CS) competency, food science exposure and extracurricular activities, and familiarity with cybersecurity topics of students in food science and related fields. Students ranked their CS abilities, 1 through 5, with 1 being the lowest level of competence and 5 representing the highest level of confidence. To assess their knowledge of food safety-related sciences, participants were asked about their familiarity with the respective fields. The average student was familiar with common avenues of food safety exposure, such as television and the Internet. Students were less familiar with more advanced, and arguably important topics, such as botnet. Finally, the students ranked their familiarity with cybersecurity topics, 1 through 5, with 1 representing being not familiar at all and 5 representing extremely familiar. Therefore, to meet the future technological demands, specific course-work is required to improve prospective student CS and cybersecurity competency.
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  Data: 2020
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  Label: Accession Number
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  Data: EJ1270549
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        PageCount: 10
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      – SubjectFull: Safety
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