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Gurmeet singh Sunstein, C. R. (2017). #Republic: divided democracy in the age of social media. Princeton University Press. As the Internet grows more sophisticated, it is creating new threats to democracy. Social media companies such as Facebook can sort us ever more efficiently into groups of the like-minded, creating echo chambers that amplify our views. Sobaci, M. Z., & Hatipoğlu İbrahim (Eds.). (2018). Sub-national democracy and politics through social media (Ser. Public administration and information technology, volume 29). Springer. https://doi.org/10.1007/978-3-319-73386-9 This book analyzes the impact of social media on democracy and politics at the sub-national level in developed and developing countries. Over the last decade or so Arthur, C. (2021). Social Warming: The Dangerous and Polarising Effects of Social Media. Simon and Schuster. An impassioned exploration of the ways in which social media has manipulated us all. Facebook didn't mean to facilitate a genocide. Twitter didn't want to be used to harass women. Scott, D. M. (2010). The Political Candidate Social Media Divide. EContent, 33(4), 40. In this article the author talks about the use of social media in campaigns and cites the Obama for America program which yielded millions of connections on the Facebook and MyBO accounts of U.S. President Barack Obama. Lukes CA. (2010). Social media. AAOHN Journal, 58(10), 415–417. https://doi-org.trexler.idm.oclc.org/10.3928/08910162-20100928-02 Various social media sites, including Facebook, have become part of everyday life. They are used by individuals of all ages and are even favored by companies and organizations as a promotional mechanism. Professional organizations, including the American Association of Occupational Health Nurses, Inc., would be remiss to overlook the potential of social media. Student Paper CS 475 – Ethics and Technology Research Paper – Educational Technology and Reducing Achievement Gaps Throughout the United States, large achievement gaps exist between students of higher- socioeconomic status and those of lower socioeconomic status, often with several grade levels of achievement separating students from these different groups (Groeger, Waldman, & Eads, 2018). American schools have increasingly turned to digital technology, such as the use of SmartBoards and iPads as well as general computer usage, to supplement the learning experience. However, students of higher socio-economic status are more likely to have access to digital technology at home than are those who come from lower socio-economic backgrounds, which can give them an advantage over students without access to such resources. Students in impoverished schools also tend to have less access to educational technology opportunities, both in-school and without. This phenomenon is known as the “digital divide”, and it has received attention from several policy-makers and ethicists. The digital divide has many implications for the effort of ensuring that all students receive equal and adequate educational opportunities that will allow them to reach their full potentials and, as St. Francis de Sales said, “be who [they] are and be that well”. Many school districts across the United States have implemented various educational technology policies, such as one-to-one laptop initiatives, in an effort to close the digital divide between students from various socioeconomic backgrounds. The hope is that by providing resources and opportunities through such programs, not only will the digital divide close but achievement gaps will as well. However, a consideration of such initiatives implemented until the present day shows that while they have generally increased overall academic achievement, they often affect members of various demographic groups differently such that achievement gaps may actually increase. 2 One example of an educational technology program aimed at reducing the digital divide is the Tech Goes Home initiative, described by DeGennaro (2010) in her article “Opening Digital Doors”. The Tech Goes Home initiative is a program in lower-income communities of Boston in which students and teachers help parents learn technology skills after regular school classes are finished for the day. These technology skills are specifically oriented towards helping parents be involved in their children’s educations and towards helping both students and parents succeed in the workforce. DeGennaro provided several examples: [W]e have parents practice using Microsoft Word and Excel by keeping a record of their child’s progress in school and of their own progress in learning computer skills. Kids teach parents web searching strategies by helping them pursue information about their career goals. (para. 15) Once a family has completed twenty-five hours of this training, they may purchase a computer for fifty dollars and then keep this computer at home to use for schoolwork and other purposes. Since the implementation of this program, testing scores in both language arts and mathematics have risen. DeGennaro reported, Between June 2008 and July 2009, for instance, the number of 6th graders failing math at Frederick [a Boston middle school implementing the program] decreased by almost 50 percent and the number of 7th graders failing English language arts decreased by 20 percent. (para. 27) This seems to show that the program has had significant positive results in improving achievement in at least one mainly low-income school in which most students come from minority racial / ethnic backgrounds. Some aspects of this program that may have been particularly instrumental in achieving this result ought again to be emphasized: the partnership 3 between students, parents, and educators and the way that the program is oriented towards identifying and fulfilling the needs and desires of the participants. The need for educational initiatives to consider the individual needs of the persons they are intended to serve has been shown in various other ways as well and is in keeping with a personalistic approach to equalizing educational opportunities. For example, Eglash, Gilbert, Taylor, and Geier (2013) elaborated on this need in their article “Culturally Responsive Computing in Urban, After-School Contexts: Two Approaches”. The article weighed the effects of two different types of educational technology tools on the achievement of minority populations. Specifically, both types of educational technology referenced the cultures of minority demographic groups, including African-Americans, Hispanic-Americans, and Native Americans, to try to more fully engage such students and have them perceive the concepts taught as more relevant and applicable to them. The article showed the importance of cultural sensitivity when designing educational technologies meant to help bridge the digital divide and increase the achievement of racial / ethnic minority populations in the United States. The first type of program, African American Distributed Multiple Learning Styles Systems (AADMLSS) involved a narrative program steeped in urban vernacular culture as a way of teaching mathematics. Culturally Situated Design Tools (CSDTs), the other program introduced, worked to teach mathematical concepts such as fractal geometry through references to geometric patterns and structures found in traditional African, Hispanic, and Native American art and architecture. The authors of the report identified the difference between the two approaches: “In reverse from AADMLSS history, which began with an educational system attempting to develop math/culture connections, CSDTs began with a culture/math connection – and the question was then how to apply these rich relationships to education” (p. 639). Both 4 were found to be associated with “statistically significant improvement in math and computing performance and attitudes toward computing careers in some controlled studies” (p. 641), again showing the need for programs to consider well the needs and situations of their participants. Other studies have shown that not all programs introduced have been equally successful in improving student outcomes, however. For example, Falck, Mang, and Woessman (2018) conducted an empirical study of data collected from countries worldwide on the impact of classroom computers on academic achievement. Their article “Virtually No Effect? Different Uses of Classroom Computers and Their Effect on Student Achievement” found that the use of computers to look up information positively affected students’ overall achievement, but the use of computers to practice skills, at least while learning mathematics and science, actually decreases students’ achievement. The authors reported, The effect sizes suggest that in 4th grade, a one-standard-deviation increase in the intensity of computer use to look up ideas and information increases student achievement by 1.9-2.3% of a standard deviation (depending on the included controls) in maths (and an insignificant 0.8-1.0% in science). By contrast, a one-standard deviation increase in the intensity of computer use to practice skills and procedures decreases achievement by 1.2-1.9% of a standard deviation in maths and by 2.3-2.8% in science. (p. 22) It is interesting to note the especially negative effect of computer use on science achievement. This may seem counterintuitive, as one might think that science concepts would be much easier to practice and learn online in comparison with mathematical concepts (due to the difficulty involved in displaying and inputting mathematical symbols in digital environments). However, perhaps it is the loss of the hands-on aspect of science education that can account for the overall negative impact. The results found in this study imply that educators and policy-makers must 5 carefully consider whether digital educational technology truly will improve students’ academic achievement more than traditional learning and teaching methods will. Educators and policy-makers must also consider the effects of proposed policies on achievement gaps, keeping in mind the common good of society. Closer analysis of the effects of many programs intended to close the digital divide between students from various socio- economic backgrounds reveals that they may affect these different groups of students to different extents. For example, the paper referenced above found that the use of computers in education has stronger effects (both positive and negative) on the academic performance of high- socioeconomic status students than low-socioeconomic status students (p. 25), with the number of books available in a student’s home used as a measure of socioeconomic status. Thus, it seems that students of high socioeconomic status are more sensitive to technology than are those of low socioeconomic status. Tawfik, Reeves, and Stich’s (2016) article “Intended and Unintended Consequences of Educational Technology on Social Inequality” noted that this is due to various concerns such as “proficiency in the language of the software, ability to interpret output, or understanding of how to apply the technology to increase learning” (p. 602). The authors thus cautioned that prior knowledge regarding technology, which is stratified across the members of different socioeconomic groups, plays a significant role in the effectiveness of digital education initiatives. For this reason, educational technology initiatives intended to bridge the digital divide and provide equal opportunity to all may in fact increase achievement gaps rather than narrow them. Smith (2012) researched this phenomenon in his dissertation “Leveling the Playing Field: Using a One-to-One Laptop Initiative to Close the Achievement Gap”, an empirical study of the effects of a one-to-one laptop initiative (a program in which each student has access to a laptop 6 in school for educational purposes) in the Mooresville Graded School District of Mooresville, North Carolina. He found that a conversion to digital technology narrowed the achievement gap between female and male students but actually increased the achievement gap between black and white students and between students who were proficient in English and those who were not. For example, regarding the mathematical achievement gap between black and white students before and after the initiative, the author reported, The average scale score for black students before the one-to-one laptop initiative was 147.6286. The average scale score after the implementation year was 147.77075. There was an average scale score increase of 0.14215 for black students. The average scale score for white students before the one-to-one laptop initiative was 152.70445, compared with an average scale score of 154.00725 after the implementation year. The average scale score for white students increased by 1.3028 from before to after the one-to-one laptop initiative. (p. 72) Thus, the one-to-one laptop initiative had an almost ten times greater effect on the mathematical achievement of white students than on the mathematical achievement of black students. The preceding discussion shows that educational technology initiatives intended to close achievement gaps must be considered and evaluated very carefully. We have noted two factors that should be taken into consideration: different effects of technological initiatives on students from various backgrounds, due to differing prior knowledge of the technology involved in such initiatives; and the importance of cultural sensitivity when designing such programs. Especially important is a consideration of whether educational technology initiatives will truly bring about a fairer and more equal society. This points to the larger question of whether equalizing educational opportunity or equalizing educational outcome should be prioritized. On