8 research outputs found

    Defining data ethics in library and information science

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    In the library and information sciences (LIS), data ethics is an area of increasing focus. The purpose of this study is to answer these questions and comprehensively define data ethics in the LIS fields based on the diverse body of literature on the topic. Through an integrative literature review, we found four overarching themes in LIS literature on data ethics: privacy, research ethics, ethical ecosystems, and control. Additionally, these four themes gave us an opportunity to create a comprehensive definition of data ethics in the library and information science fields

    Improving research techniques for categorical predictors for multiple regression in information science publication

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    This poster discusses strategies for incorporating categorical predictors into regression analyses. It will conduct a systematic literature review, on Information Science (IS) articles published in the last five years, to assess how researchers in the field handled categorical predictors in their multiple regression analyses. Researchers often use categorical variables, such as gender, ethnicity, religion, regions, etc., as probable predictors of various outcomes. For example, a researcher may be interested in examining whether ethnicity (categorical) influences individuals’ online information seeking behavior. While the analysis of variance (ANOVA) can be used to compare the means between groups in such a case, researchers can opt to use multiple regression analysis. The ability of multiple regression analysis to subsume other univariate analyses, such as ANOVA, has increased its popularity over the last couple of decades (Davis, 2010; Thompson, 2015). Multiple regression, however, requires all variables entered in the model be continuous, unlike other analysis techniques. Therefore, whenever categorical variables are employed in a study, they need to be coded before incorporating the variables in the regression model. This research will be the first attempt to analyze how information science (IS) academic researchers utilize categorical predictors for regression analyses, and 2) it will guide researchers in converting categorical data to quantitative data and best interpret the regression coefficients

    Paralegal Students’ and Paralegal Instructors’ Perceptions of Synchronous and Asynchronous Online Paralegal Course Effectiveness: A Comparative Study

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    To improve online learning pedagogy within the field of paralegal education, this study investigated how paralegal students and paralegal instructors perceived the effectiveness of synchronous and asynchronous online paralegal courses.  This study intended to inform paralegal instructors and course developers how to better design, deliver, and evaluate effective online course instruction in the field of paralegal studies.Survey results were analyzed using independent samples t-test and correlational analysis, and indicated that overall, paralegal students and paralegal instructors positively perceived synchronous and asynchronous online paralegal courses.  Paralegal instructors reported statistically significant higher perceptions than paralegal students: (1) of instructional design and course content in synchronous online paralegal courses; and (2) of technical assistance, communication, and course content in asynchronous online paralegal courses.  Instructors also reported higher perceptions of the effectiveness of universal design, online instructional design, and course content in synchronous online paralegal courses than in asynchronous online paralegal courses.  Paralegal students reported higher perceptions of asynchronous online paralegal course effectiveness regarding universal design than paralegal instructors.  No statistically significant differences existed between paralegal students’ perceptions of the effectiveness of synchronous and asynchronous online paralegal courses. A strong, negative relationship existed between paralegal students’ age and their perceptions of effective synchronous paralegal courses, which were statistically and practically significant.  Lastly, this study provided practical applicability and opportunities for future research. Akyol, Z., & Garrison, D. R. (2008). The development of a community of inquiry over time in an online course: Understanding the progression and integration of social, cognitive and teaching presence. Journal of Asynchronous Learning Networks, 12, 3-22.  Retrieved from https://files.eric.ed.gov/fulltext/EJ837483.pdf Akyol, Z., Garrison, D. R., & Ozden, M. Y. (2009). Online and blended communities of inquiry: Exploring the developmental and perceptional differences. The International Review of Research in Open and Distributed Learning, 10(6), 65-83.  Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/765/1436 Allen, I. E., & Seaman, J. (2014). Grade change: Tracking online education in the United States. Babson Park, MA:  Babson Survey Research Group and Quahog Research Group, LLC.  Retrieved from https://www.utc.edu/learn/pdfs/online/sloanc-report-2014.pdf Alreck, P. L., & Settle, R. B. (2004). The Survey Research Handbook (3rd ed.) New York, NY: McGraw-Hill Irwin. American Association for Paralegal Education (2013, Oct.).  AAfPE core competencies for paralegal programs.  Retrieved from https://cdn.ymaws.com/www.aafpe.org/resource/resmgr/Docs/AAfPECoreCompetencies.pdf American Bar Association, Standing Committee on Paralegals.  (2017). https://www.americanbar.org/groups/paralegals.html American Bar Association, Standing Committee on Paralegals (2013, September).  Guidelines for the approval of paralegal education programs.  Retrieved from https://www.americanbar.org/content/dam/aba/administrative/paralegals/ls_prlgs_2013_paralegal_guidelines.authcheckdam.pdf Astani, M., Ready, K. J., & Duplaga, E. A. (2010). Online course experience matters: Investigating students’ perceptions of online learning. Issues in Information Systems, 11(2), 14-21.  Retrieved from http://iacis.org/iis/2010/14-21_LV2010_1526.pdf Bailey, C. J., & Card, K. A. (2009). Effective pedagogical practices for online teaching: Perception of experienced instructors. The Internet and Higher Education, 12, 152-155. doi: 10.1016/j.iheduc.2009.08.002 Bernard, R., Abrami, P., Borokhovski, E., Wade, C., Tamim , R., Surkes, M., & Bethel, E. (2009).  A meta-analysis of three types of interaction treatments in distance education.  Review of Educational Research, 79, 1243-1289.  doi: 10.3102/0034654309333844 Cherry, S. J., & Flora, B. H. (2017). Radiography faculty engaged in online education: Perceptions of effectiveness, satisfaction, and technological self-efficacy. Radiologic Technology, 88(3), 249-262.  http://www.radiologictechnology.org/ Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York: Taylor & Francis Group. Colorado, J. T., & Eberle, J. (2010). Student demographics and success in online learning environments.  Emporia State Research Studies, 46(1), 4-10.  Retrieved from https://esirc.emporia.edu/bitstream/handle/123456789/380/205.2.pdf?sequence=1 Dutcher, C. W., Epps, K. K., & Cleaveland, M. C. (2015). Comparing business law in online and face to face formats: A difference in student learning perception. Academy of Educational Leadership Journal, 19, 123-134.  http://www.abacademies.org/journals/academy-of-educational-leadership-journal-home.html Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191.  Retrieved from http://www.gpower.hhu.de/fileadmin/redaktion/Fakultaeten/Mathematisch-Naturwissenschaftliche_Fakultaet/Psychologie/AAP/gpower/GPower3-BRM-Paper.pdf Field, A. (2009).  Discovery statistics using SPSS. (3rd ed.).  Thousand Oaks, CA:  Sage Publications, Inc. Gall M., Borg, W., & Gall, J. (1996). Educational research: An introduction (6th ed.). White Plains, NY: Longman Press. Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. American Journal of distance education, 15(1), 7-23.  Retrieved from http://cde.athabascau.ca/coi_site/documents/Garrison_Anderson_Archer_CogPres_Final.pdf Green, S. B., & Salkind, N. J. (2005). Using SPSS for Windows and Macintosh: Internal consistency estimates of reliability. Upper Saddle River, NJ: Pearson Prentice Hall. Harrell, I. L. (2008). Increasing the Success of Online Students. Inquiry, 13(1), 36-44.  Retrieved from http://files.eric.ed.gov/fulltext/EJ833911.pdf Horspool, A., & Lange, C. (2012). Applying the scholarship of teaching and learning: student perceptions, behaviours and success online and face-to-face. Assessment & Evaluation in Higher Education, 37, 73-88.  doi: 10.1080/02602938.2010.496532 Inman, E., Kerwin, M., & Mayes, L. (1999). Instructor and student attitudes toward distance learning. Community College Journal of Research & Practice, 23, 581-591.  doi:10.1080/106689299264594 Institute of Legal Executives (ILEX).  https://www.cilexcareers.org.uk/ Johnson, J. & Taggart, G. (1996).  Computer assisted instruction in paralegal education: Does it help? Journal of Paralegal Education and Practice, 12, 1-21. Johnstone, Q. & Flood, J. (1982).  Paralegals in English and American law offices.  Windsor YB Access to Justice 2, 152. Jones, S. J. (2012). Reading between the lines of online course evaluations: Identifiable actions that improve student perceptions of teaching effectiveness and course value. Journal of Asynchronous Learning Networks, 16(1), 49-58.  doi:http://dx.doi.org/10.24059/olj.v16i1.227 Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30, 607-610.  http://journals.sagepub.com/home/epm Liu, S., Gomez, J., Khan, B., & Yen, C. J. (2007). Toward a learner-oriented community college online course dropout framework. International Journal on ELearning, 6(4), 519-542.  https://www.learntechlib.org/j/IJEL/ Lloyd, S. A., Byrne, M. M., & McCoy, T. S. (2012). Faculty-perceived barriers of online education. Journal of online learning and teaching, 8(1), 1-12.  Retrieved from http://jolt.merlot.org/vol8no1/lloyd_0312.pdf Lockee, B., Burton, J., & Potter, K. (2010, March). Organizational perspectives on quality in distance learning. In D. Gibson & B. Dodge (Eds.), Proceedings of SITE 2010—Society for Information Technology & Teacher Education International Conference (pp. 659-664). San Diego, CA:  Association for the Advancement of Computing in Education (AACE).  https://www.learntechlib.org/p/33419/ Lowerison, G., Sclater, J., Schmid, R. F., & Abrami, P. C. (2006). Student perceived effectiveness of computer technology use in post-secondary classrooms. Computers & Education, 47(4), 465-489.  doi:10.1016/j.compedu.2004.10.014  Retrieved from https://pdfs.semanticscholar.org/fc9c/13f0187d3967217aa82cc96c188427e29ec9.pdf Martins, L. L., & Kellermanns, F. W. (2004). A model of business school students' acceptance of a web-based course management system. Academy of Management Learning & Education, 3(1), 7-26.  doi: 10.5465/AMLE.2004.12436815 Mayes, J. T. (2001). Quality in an e-University. Assessment & Evaluation in Higher Education, 26, 465-473.  doi:10.1080/02602930120082032 McCabe, S. (2007).  A brief history of the paralegal profession.  Michigan Bar Journal, 86(7), 18-21.  Retrieved from https://www.michbar.org/file/barjournal/article/documents/pdf4article1177.pdf McMillan, J. H. (2008). Educational Research: Fundamentals for the customer.  Boston, MA:  Pearson Education, Inc. Myers, C. B., Bennett, D., Brown, G., & Henderson, T. (2004). Emerging online learning environments and student learning: An analysis of faculty perceptions. Educational Technology & Society, 7(1), 78-86.  Retrieved from http://www.ifets.info/journals/7_1/9.pdf Myers, K. (2002). Distance education: A primer.  Journal of Paralegal Education & Practice, 18, 57-64. Nunnaly, J. (1978). Psychometric theory. New York: McGraw-Hill. Otter, R. R., Seipel, S., Graeff, T., Alexander, B., Boraiko, C., Gray, J., Petersen, K., & Sadler, K. (2013). Comparing student and faculty perceptions of online and traditional courses. The Internet and Higher Education, 19, 27-35.  doi:10.1016/j.iheduc.2013.08.001 Popham, W. J. (2000). Modern educational measurement: Practical guidelines for educational leaders. Boston, MA:  Allyn & Bacon. Rich, A. J., & Dereshiwsky, M. I. (2011). Assessing the comparative effectiveness of teaching undergraduate intermediate accounting in the online classroom format. Journal of College Teaching and Learning, 8(9), 19.  https://www.cluteinstitute.com/ojs/index.php/TLC/ Robinson, C., & Hullinger, H. (2008).  New benchmarks in higher education:  Student engagement in online learning.  The Journal of Education for Business, 84(2), 101-109.  Retrieved from http://anitacrawley.net/Resources/Articles/New%20Benchmarks%20in%20Higher%20Education.pdf Salkind, N. J. (2008). Statistics for people who think they hate statistics. Los Angeles, CA: Sage Publications. Santos, J. (1999, April). Cronbach's Alpha: A tool for assessing the reliability of scales.  Journal of Extension, 37, 2. Retrieved from https://www.joe.org/joe/1999april/tt3.php Seok, S., DaCosta, B., Kinsell, C., & Tung, C. K. (2010). Comparison of instructors' and students' perceptions of the effectiveness of online courses. Quarterly Review of Distance Education, 11(1), 25.  Retrieved from http://online.nuc.edu/ctl_en/wp-content/uploads/2015/08/Online-education-effectiviness.pdf Sheridan, K., & Kelly, M. A. (2010). The indicators of instructor presence that are important to students in online courses. Journal of Online Learning and Teaching, 6(4), 767-779.  Retrieved from http://jolt.merlot.org/vol6no4/sheridan_1210.pdf Shook, B. L., Greer, M. J., & Campbell, S. (2013). Student perceptions of online instruction. International Journal of Arts & Sciences, 6(4), 337.  Retrieved from https://s3.amazonaws.com/academia.edu.documents/34496977/Ophoff.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=1508119686&Signature=J1lJ8VO0xardd%2FwH35pGj14UeBg%3D&response-content-disposition=inline%3B%20filename%3DStudent_Perceptions_of_Online_Learning.pdf Song, L., Singleton, E. S., Hill, J. R., & Koh, M. H. (2004). Improving online learning: Student perceptions of useful and challenging characteristics. The Internet and Higher Education, 7, 59-70.  doi:10.1016/j.iheduc.2003.11.003 Steiner, S. D., & Hyman, M. R. (2010). Improving the student experience: Allowing students enrolled in a required course to select online or face-to-face instruction. Marketing Education Review, 20, 29-34.  doi:10.2753/MER1052-8008200105 Stoel, L., & Hye Lee, K. (2003). Modeling the effect of experience on student acceptance of web-based courseware. Internet Research, 13(5), 364-374.  http://www.emeraldinsight.com/loi/intr Taggart, G., & Bodle, J. H. (2003). Example of assessment of student outcomes data from on-line paralegal courses: Lessons learned. Journal of Paralegal Education & Practice, 19, 29-36. Tanner, J. R., Noser, T. C., & Totaro, M. W. (2009). Business faculty and undergraduate students' perceptions of online learning: A comparative study. Journal of Information Systems Education, 20, 29-40.  http://jise.org/ Tung, C.K. (2007).  Perceptions of students and instructors of online and web-enhanced course effectiveness in community colleges (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses database (Publication No. AAT 3284232). Vodanovich, S. J.  & Piotrowski, C., & (2000). Are the reported barriers to Internet-based instruction warranted? A synthesis of recent research. Education, 121(1), 48-53.  http://www.projectinnovation.com/education.html Ward, M. E., Peters, G., & Shelley, K. (2010). Student and faculty perceptions of the quality of online learning experiences. The International Review of Research in Open and Distributed Learning, 11, 57-77.  Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/867/1610? Wilkes, R. B., Simon, J. C., & Brooks, L. D. (2006). A comparison of faculty and undergraduate students' perceptions of online courses and degree programs. Journal of Information Systems Education, 17, 131-140. http://jise.org/

    The role of cognitive authority in social media

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    This poster discusses the role that cognitive authority may play in the context of social media. A term coined by TD Wilson, “cognitive authority” refers to the authority that someone or some sources may have over the thoughts of an individual. When a person gives another person cognitive authority, they give them the opportunity to influence their thoughts without hesitation. This poster aims to see how cognitive authority can be used in the realm of social media. In an environment where people “follow” or “friend” other people or news sources that they trust enough to have a connection with, is cognitive authority an influential factor? If cognitive authority is an influential factor, how does it affect the information seeking process and what potential influence can it have on information literacy? Information literacy requires critically thinking about information and determining its validity; when cognitive authority is at play, how much thought and effort is put into validating the information encountered

    Virtual knowledge spaces: A call for research

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    Davis (1989) authored the widely acclaimed book titled “Future Perfect” prescribing that, in a “future perfect, anyone in an anytime – anyplace mode would be able to communicate to anyone else in the world.” The year 2020 provided clear affirmation that the knowledge workforce of the future is poised to not only communicate anytime – anyplace, but to create workplace environments that thrive across time zones and unlimited virtual locations. Knowledge management (KM) is “a systematic and integrative process of coordinating organization-wide activities of acquiring, creating, storing, sharing, diffusing, and deploying knowledge by individuals and groups, in pursuit of major organizational goals” (Rastogi, 2000, p. 40). Information scientists and knowledge management scholars must reexamine models of organizational learning, competency development and organizational culture to harness the collective capability of not only a virtual workforce, but a virtual organization. The researchers’ “work in progress” poster presents a preliminary systematic literature review and offers guiding questions to scholars and scholar practitioners exploring this rich area of KM research in a virtual organization. The three primary research areas are organizational learning, knowledge archiving, and knowledge system modeling. The final systematic literature review will define the topic and will utilize scholarly research methodologies (e.g., Torocco, 2016) to critically analyze and synthesize existing knowledge management literature and present virtual workforce implications that give direction for future research. In this growing research area, this poster poses the questions: (1) What are the obstacles of storing and deploying knowledge in a virtual organization? (2) How does the virtual organization impact the social nature of knowledge (namely sharing and creation)? (3) How must knowledge systems evolve to accommodate a virtual workforce? Davis, S. (1989). Future Perfect. Reading, Massachusetts: Addison-Wesley. Rastogi, P. (2000) Knowledge management and intellectual capital — the new virtuous reality of competitiveness. Human Systems Management 19(1), 39 – 49. Torocco, R. (2016). Writing Integrative Reviews of Literature: Methods and Purposes. International Journal of Adult Vocational Education and Technology, 7(1), 62 – 70. doi: 10.4018/IJAVET.201607010

    The Association Between FokI Vitamin D Receptor Polymorphisms With Metabolic Syndrome Among Pregnant Arab Women

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    Metabolic syndrome (MetS) is a serious health condition that is becoming extremely threatening in Saudi Arabia. The link between vitamin D receptor (VDR) gene polymorphisms and maternal MetS has been observed in several ethnic groups, but is yet to be clarified in the Arabian population. This study aims to investigate the relationship between the FokI VDR genotype and the risk of MetS and its components in pregnant Saudi women. A cross-sectional study was conducted using 368 pregnant Saudi women on first trimester screened for MetS (44 with MetS and 324 without MetS). Measurements included anthropometrics, glycemic and lipid profile and 25(OH)D. TaqMan genotyping assay was used to determine Fokl VDR genotype of participants. Vitamin D deficiency (25(OH)D <50nmol/l) was seen in 85% of the participants. An estimated 12% of participants had MetS. In the MetS group, the FokI VDR genotyping frequencies for FF, Ff, and ff genotypes were 50%, 36.4% and 13.6%, respectively. In controls, the frequencies were 62.7%, 31.4% and 5.9%, respectively. No significant association between the individual MetS components and FokI VDR genotypes were observed. Nevertheless, carriers of the ff allele had a significant risk for full maternal MetS [Odds Ratio 4.2 (95% Confidence Interval 1.4-12.2; adjusted p=0.009). The study suggests that the ff FokI VDR genotype is a genetic marker of maternal MetS in pregnant Arabian women. Prospective studies that include neonatal outcomes may confirm present findings

    Burden of tracheal, bronchus, and lung cancer in North Africa and Middle East countries, 1990 to 2019: Results from the GBD study 2019

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    ObjectiveTo provide estimates on the regional and national burden of tracheal, bronchus, and lung (TBL) cancer and its attributable risk factors from 1990 to 2019 in the North Africa and Middle East (NAME) region.Methods and materialsThe Global Burden of Disease (GBD) 2019 data were used. Disability-adjusted life years (DALYs), death, incidence, and prevalence rates were categorized by sex and age groups in the NAME region, in 21 countries, from 1990 to 2019. Decomposition analysis was performed to calculate the proportion of responsible factors in the emergence of new cases. Data are presented as point estimates with their 95% uncertainty intervals (UIs).ResultsIn the NAME region, TBL cancer caused 15,396 and 57,114 deaths in women and men, respectively, in 2019. The age-standardized incidence rate (ASIR) increased by 0.7% (95% UI -20.6 to 24.1) and reached 16.8 per 100,000 (14.9 to 19.0) in 2019. All the age-standardized indices had a decreasing trend in men and an increasing trend in women from 1990 to 2019. Turkey (34.9 per 100,000 [27.6 to 43.5]) and Sudan (8.0 per 100,000 [5.2 to 12.5]) had the highest and lowest age-standardized prevalence rates (ASPRs) in 2019, respectively. The highest and lowest absolute slopes of change in ASPR, from 1990 to 2019, were seen in Bahrain (-50.0% (-63.6 to -31.7)) and the United Arab Emirates (-1.2% (-34.1 to 53.8)), respectively. The number of deaths attributable to risk factors was 58,816 (51,709 to 67,323) in 2019 and increased by 136.5%. Decomposition analysis showed that population growth and age structure change positively contributed to new incident cases. More than 80% of DALYs could be decreased by controlling risk factors, particularly tobacco use.ConclusionThe incidence, prevalence, and DALY rates of TBL cancer increased, and the death rate remained unchanged from 1990 to 2019. All the indices and contribution of risk factors decreased in men but increased in women. Tobacco is still the leading risk factor. Early diagnosis and tobacco cessation policies should be improved
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