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Alexa, Make Me Smart — AI and Social Networking Technology in Education:

Alexa, what is the sine of fifty? Saying this in a dorm room at the University of Saint Louis in Missouri would prompt an answer from one of the 2,300 Echo Dot smart speakers that have been enabled since 2018 (Stoneman). This is an example of AI and cognitive technology impacting education. AI and cognitive technology can be defined as “the theory and development of computer systems able to perform tasks that normally require human intelligence,” and “products of the field of artificial intelligence…able to perform tasks that only humans used to be able to do” (Demystifying Artificial Intelligence). Social networking technology has also impacted education and can be defined as “conversational, web-based sites that allow users to develop profiles of self, upload personal resources and connect with multiple networks via the Internet” (Rambe 379). Given the potential for positive educational impact, there should be more research on the efficacy of social networking, artificial intelligence (AI), and cognitive technology to increase student outcomes, especially among ethnic minorities.

Social networking technologies have the potential to accumulate support for students from peers and instructors. In a study investigating the impact of personal motivation and social environment on the success of ethnic minority first-generation college students, it was found that lack of peer support was a negative predictor of college adjustment the following spring (Dennis et al. 223). Additionally, a separate study found that college students reported relying on other students in their classes in order to form study groups and share assignments (Richarson & Skinner). Given the significant impact of peer support on student success and the familiarity of social networking technology among students, the development and efficacy of a specialized social networking technology platform to enable peer support could improve student outcomes.

As for instructor-student relations, social networking technologies can strengthen connections while combining the instant gratification techniques of popular platforms. In a study investigating how to support college developmental readers using Facebook, a system of virtual gifts was introduced as a reward system acknowledging the efforts of students on the course with the aim of improving the ‘connectedness’ between student and instructor. The experiment led the author to argue that Facebook “may be helpful in improving low self-efficacy and self-regulated learning by increasing connection with the instructor, increasing social contact with classmates, and providing an opportunity to guide students” (Bowens-Campbell). While Facebook is not designed specifically for education, identifying those the social theory behind its features are worth emulating and researching on specialized platforms to verify their impact. If a reliable and valid research study were to verify the benefits and strengths, educational technology companies or research institutions could develop better platforms for universities to adopt. However, without research, it is impossible to test the efficacy of these features, creating untouched potential in technology. As for AI and cognitive technology, their strengths lie in versatility.

AI and cognitive technology allow for personalization and accessibility in various areas. Advancements in the field and availability of technology have inspired researchers to investigate its use in mentorship. Researchers at Morehouse University are investigating whether or not a Twitter Conversational Agent (TCA) and an Embodied Conversational Agent for HBCU can effectively serve as a virtual mentor for black undergraduate students with an interest in graduate studies in computing (Hampton and Gosha). Given that “mentoring has been shown to be a crucial element in preparing African Americans for graduate school” (Hampton and Gosha 1) and personal/career motivation and a lack of needed support from peers are predictors of college GPA, adjustment, and commitment to college among first-generation ethnic minorities in college (Dennis et al. 235), projects similar to the Twitter Conversational Agent have substantial potential for positively impacting student outcomes.

Some people may dismiss the idea of integrating these technologies in education by arguing the challenges cannot be resolved, resulting in wasted research resources. For example, on social networks, “Learners face some difficulty through social networking in expressing their views and ideas in writing, as many learners prefer to express their ideas orally…” (Zaidieh 20). However, challenges these challenges another reason why research is so vital. Without research, there are no ways to investigate resolutions to overcome challenges so that the benefits of the technology can be fully leveraged.

In conclusion, there is tremendous potential within educational technology using social networks, AI, and cognitive technology. This paper has discussed benefits to student outcomes including student and peer motivation, mentorship and the need to overcome challenges but further research should only bring forth further value. Thus, there should be more research on the efficacy of social networking, artificial intelligence (AI), and cognitive technology to increase student outcomes, especially among ethnic minorities.

Works Cited

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Readers.” Journal of College Reading and Learning, vol. 39, no. 1, Sept. 2008, pp. 74–87. EBSCOhost, search.ebscohost.com/login.aspx?direct=true&db=eoah&AN=33290822&site=ehost-live.

“Demystifying Artificial Intelligence.” Deloitte Insights,

www2.deloitte.com/us/en/insights/focus/cognitive-technologies/what-is-cognitive-technology.html.

Dennis, Jessica M., et al. “The Role of Motivation, Parental Support, and Peer Support in the

Academic Success of Ethnic Minority First-Generation College Students.” Journal of College Student Development, vol. 46, no. 3, Jan. 2005, pp. 223–236. EBSCOhost, search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ743884&site=ehost-live.

Hampton, Lelia and Kinnis Gosha. “Development of a Twitter graduate school virtual mentor for

HBCU computer science students.” ACM Southeast Regional Conference (2018).

Rambe, Patient. “Appraisal theory: Opportunities for social networking sites’ complementation

of writing centres.” Handbook of research on educational technology integration and active learning. IGI Global, 2015. 358–379.

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high school education: Motivation, pressure, and learning performance.” Computers & Education 50.1 (2008): 1–22.

Richardson, Richard C., Jr., and Elizabeth Fisk Skinner. “Helping First-Generation Minority

Students Achieve Degrees.” New Directions for Community Colleges, no. 80, Jan. 1992, pp. 29–43. EBSCOhost, search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ460060&site=ehost-live.

Stoneman, Amanda. “ASU and Amazon Inspire New Student Ventures with Alexa.” ASU Now:

Access, Excellence, Impact, ASU News, 29 Aug. 2018, asunow.asu.edu/20180823-asu-amazon-inspire-new-student-ventures-alexa.

Zaidieh, Ashraf Jalal Yousef. “The use of social networking in education: Challenges and

opportunities.” World of Computer Science and Information Technology Journal (WCSIT) 2.1 (2012): 18–21.