In the early 2020s, a series of pivotal events, for better or worse, have significantly reshaped the educational technology landscape. These included the global COVID-19 pandemic and subsequent lockdowns, which fundamentally impacted how education is delivered and experienced, the upheaval in the social media landscape, and the release of generative artificial intelligence (GenAI) tools like Chat Generative Pre-trained Transformer (ChatGPT). There are many critical questions to ask and conversations to be had about uses of the Internet, everything on the spectrum from the concerns and problems of mental, physical, and digital health/safety which have been increasingly in the spotlight, to the implications of empowerment and engagement for teaching and learning. In higher education, it is too soon to fully understand the full impact of the pandemic; however, things seem to have settled a bit in a simultaneously concerning yet hopeful aftermath. It is a concerning time due to disruptions, failures and dehumanization in education due to the pandemic ^[1][2][1,2], as well as increased uncertainty and instability evidenced in existing and new technologies [3]; yet, it is hopeful because we are humans, and as we can, we will strive to take the next best steps for our students and for each other.

2. Intentional Uses of Social Media

Social media was not originally designed for educational purposes, but certain features such as Web 2.0 applications and social networking have made it a useful tool in education ^[4][10]. Twitter as a microblogging tool that includes the engaging and organizational feature of hashtags, supported professional ^[5][11] and self-directed learning ^[6][12], and has an impact on the community, communication, and casual (informal) learning for students ^[7][13]. Social media creates connections for niche communities and is often described in the context of the development of personal and/or professional learning networks (PLN) ^[8][9][14,15], creating broader individual and collective learning opportunities. Professional educational communities have found numerous types of interaction, engagement, and empowerment ^[10][16], and consider the criticality of Black Twitter ^[11][17], wherein exists “one of the largest gatherings of Black online users ever” and “serves as a potent example of Black digital expertise” (para 3); and some are asking, “What’s going to happen to Black Twitter?” (para 2). The literature on social media and education highlighted that the use of social media platforms such as wikis ^[12][18], Twitter ^[13][14][19,20], and/or Facebook ^[15][21] resulted in higher participation and improved learning in secondary and higher education ^[16][22]. In aour own recent research, the researchers we looked at social media and Twitter use in theour online courses. In one study, the researchers we identified “(1) evidence of cognitive, social, and teaching presence for students completing course activities using Twitter, that is, for their formal learning; and that (2) students developed course competencies during formal course activities using Twitter that supported cognitive and social presence beyond the course requirements, that is, for their informal learning” ^[17][8] (p. 327). In a follow-up study, thwe researchers identified the importance of engaging students with “(1) sharing of learning artifacts, (2) engaging in creative pedagogical practice, (3) the concept of fun, and (4) collaboration and teamwork”, which confirmed for us “(1) the importance of student-centered design, (2) the continued use and adoption of relevant technology tools and skills, and (3) building community with the frameworks of Community of Inquiry and the modes of interaction model” ^[18][23] (p. 251). This successful use of Twitter encouraged us to continue revising theour courses, focusing on student engagement as a priority during and immediately after the pandemic, when the challenges for online learning were amplified. 

3. The Challenges and Concerning Status of Social Media

Until recently, the perceived benefits of integrating social media into education outweighed its disadvantages ^[19][20][24,25] prompting many educators, like us, to adopt it as a tool for facilitating engaged learning ^[21][26]. Of course, using social media in education has had its issues. Challenges have included classroom distractions ^[22][27], a perceived loss of control over students in the classroom ^[23][28], and reduced student focus and multitasking negatively impacting learning, performance, and retention ^[24][29]. Additionally, concerns have arisen among students who are not comfortable using social media due to concerns of social media addiction and cyberbullying ^{[25][26][27][28]}[30,31,32,33], issues related to security and privacy such as the public accessibility of information ^[29][34], and an inundation of misinformation and disinformation ^[30][35]. Sundaram and Radha ^[31][36] investigated the security involved in social media use among youth internet users. They found that social networks store end users’ information remotely to personalize services and sell information to advertisers. These practices raise concerns about privacy and the commodification of personal information and contribute to the accumulation of “Big Data” ^[31][36]. Big data has been identified both as a priority and concern since 2014–2016 by the policy of the Obama White House Office of Science and Technology ^[32][37]. Moreover, this use of automated and algorithmic processes in social media has led to concerns about unintended bias and discrimination ^[33][34][38,39], which can be perpetuated through academic texts ^[35][36][40,41] and news outlets ^[37][42]. Bias in machine learning has been discussed by researchers ^[38][39][43,44], and experts argue that these technologies are not neutral; rather, they are value laden ^[40][41][42][45,46,47] and their design has the potential for “racialized, gendered and colonized hierarchies” ^[32][37] (pp. 2123–2124). These issues have become increasingly present in recent years, particularly with significant events such as the COVID-19 pandemic, the sale of Twitter, and the rise of GenAI tools. Author B encountered increased concerns about the use of social media from students in an undergraduate course in 2022 and author A was experiencing increasing challenges using Twitter in her classes; both authors have felt the need to step back and hold critical conversations with each other and their students. As humans and educators, it is incumbent upon us to take responsibility and be accountable for the outcomes we are all experiencing. With increasing challenges and concerns in the social media landscape, educators and educational researchers are taking a step back, and with the advent of generative AI tools that carry many of the same issues alongside new challenges, Mishra et al. note both “hand-wringing-and some celebration-about the impact these tools will have on education” [3] (p. 235).

4. The Implications of Artificial Intelligence

Artificial intelligence in education has been the subject of research for over two decades ^[43][48]. However, it was not until the past couple of years (2022–2023) that AI tools, specifically generative AI tools like ChatGPT, DALL-E, MidJourney, Bard, Bing Chat, Lensa AI, and Canva Magic Write ^[3][44][45][3,49,50], became widely accessible and started to influence online teaching practices. ChatGPT was released by OpenAI to the world in the late fall of 2022, and at the time, it was estimated to have reached “100 million monthly active users in January 2023” ^[46][51] and was noted to be “the fastest-growing consumer application in history” (p. 1). Watters and Lemanski ^[47][52] conducted a review of the early literature on ChatGPT, with findings revealing a “predominance of negative sentiment across disciplines” and “raising concerns about employment opportunities and ethical considerations” similar to concerns of use of social media and the internet in general of “privacy, bias, transparency, and accountability”, yet holding “promise for improved communication” and needing further research “to address its capabilities and limitations” (Abstract and Discussion para 2). Dai, Liu, and Lim ^[48][53] identify ChatGPT as “a student-driven innovation” (p. 1) and a “potent enabler for enhancing education quality and transforming higher education” specifically, as it and tools like it “can be leveraged to enhance learning analytic techniques, generate customized scaffoldings, facilitate idea formation, and eventually expand educational access and resources for social justice” (p. 2). Sok and Heng ^[49][54] highlighted some time-saving educational uses of ChatGPT, including helping teachers develop learning assessments, provide virtual tutoring, draft outlines, and brainstorming. They identified concerns related to such uses of ChatGPT, especially in regards to academic integrity including biased learning assessments, inaccurate or fake information, and an overreliance on AI tools. For example, using AI for brainstorming an idea or to create an outline could interfere with students developing these skills as well as losing the practical experience of becoming successful after struggle ^[50][55]. Part of the art of teaching and learning is scaffolding student learning and balancing it with the right amount of struggle, i.e., through the zone of proximal development ^[51][56]. If artfully used, these burgeoning GenAI tools might support scaffolding and assistance to the struggling learner, creating the opportunity for learning at the early stages where a student might give up, thereby facilitating and deepening learning experiences, e.g., “get away from the high school paper and go further, to write something larger, like a thesis” ^[50][55] (para 33). The impact of GenAI on educational practices is in its early stages, and it is ChatGPT that is generating most of the discussion. The discussions cross the spectrum from the language of opportunity, time-saving strategies and efficiencies, hopeful transformations, and the potential to revolutionize education ^[52][53][54][57,58,59] to the language of challenges and fears; again, mostly regarding how assessments will be impacted and long-held concerns related to cheating and plagiarism ^[53][58], but also vulnerabilities related to bias, dis- and misinformation, and cybersecurity and privacy ^[47][55][56][52,60,61]. Fullan, Azorín, and Harris ^[53][58] note that “an assessment of the real impact that this technology will have on teaching and learning for good or bad, has yet to be made,” that “there is a lack of research, guidelines, and regulations specific to ethical issues raised by the application of GenAI to education,” (p. 2) and that there is a tangible fear regarding “whether AI in education has been designed to supplant teachers/leaders or reduce them to a functional role, rather than to assist them to teach/lead more effectively” (p. 5). Of note, two key publications have been especially instrumental as we engaged in dialogue and critical conversations. The first, “TPACK in the age of ChatGPT and Generative AI” [3] was a product of interinstitutional coauthoring by one of our colleagues within our department who shared it with us. In this article, Mishra et al. [3] highlighted the need to further develop “TPACK in the age of Gen AI,” (p. 247) arguing for a “more expansive description of contextual knowledge (XK)” (p. 236) that accounts for the broader implications of GenAI on individuals and society. This work provided key essential descriptions and terminology, including a description of GenAI as “applications which are designed to create new content (text, images, video, music, artwork, synthetic data, etc.)” (p. 236). Additionally, they offered a set of probing questions that enriched our critical conversations. They note that these questions should have been “asked of social media over a decade ago” (p. 237) and we agree, as we step back from our own uses of social media. The first questions in their list are “What does it mean to teach in an era where GenAI becomes part of our everyday life? In a time when it will be increasingly difficult to distinguish between AI-generated and human-generated content?” (p. 237). The second publication, “How do we respond to generative AI in education?” by Mills, Bali, and Eaton ^[57][62], proposes that open educational practices “can help educators cope and perhaps thrive in an era of rapidly evolving AI” (p. 16). It was shared with one of us on LinkedIn and begins to address the aforementioned questions by advocating for open educational practices, two of which stood out for their immediate relevance to this study: engaging with interdisciplinary and interinstitutional online communities for ideas exchange and reflection and collaborating with students. These practices are not just theoretical, as they are the very means by which these articles reached us, exemplifying the power of open educational resources. Furthermore, the practice of collaborating with students has been crucial for us in answering the question “where do we go from here?”