Sharan B. Merriam - Learning in Adulthood

Individuals can also learn about themselves via technology. Scholars investigated how “social media, particularly social networking sites, serve as informal learning environments for lesbian, gay, bisexual, transgender, questioning, and otherwise-identified (LGBTQ) individuals” (Fox & Ralston, 2016, p. 635). In traditional learning, participants sought out information about “identity labels and meaning” (p. 638) to understand their LGBTQ identity. They could learn this information in an anonymous setting for those who were not yet ready to come out offline. Second, they engaged in social learning through technology such as YouTube as they could follow LGBTQ celebrities and see role models coming out, which helped them in their coming out process. Study participants reported seeing how LGBTQ individuals faced discrimination in their daily lives through social media posts. In addition, they engaged in experiential learning before coming out to “test the waters” by posting LGBTQ-related information on their social media outlets to see what reaction they'd receive. Participants also used online dating sites to check out what it was like to seek others of the same sex, for example. Last, when individuals became more comfortable with their LGBTQ identity, some of them educated others. For example, a woman who identified as asexual educated others about her identity.

Nonformal learning can occur in a variety of organizational settings such as workplaces, museums, and institutions and can also include “instructor-led experiences… outside the formal schooling context” (Ross-Gordon, Rose, & Kasworm, 2017, p. 34). For example, virtual team training for members of the police force was compared to standard in-person training (Bertram, Moskaliuk, & Cress, 2015). Those in the standard group had higher knowledge scores and were more satisfied with their training than those in the virtual reality group. However, “in the more complex scenario of the reality task, the virtual training group outperformed the [standard and control] groups” (p. 291). The transfer of learning was effective for both the standard and virtual groups. In another study concerning virtual training for coal miners, participants found the training very useful and its positive effects were felt several months after the training occurred (Grabowski & Jankowski, 2015). Virtual reality technology has also helped veterans with posttraumatic stress disorder perform better during the job-interview process (Smith et al., 2015).

Another technology that is used for workplace learning are mobile phones. Scholars have investigated “how mobile Web 2.0 technologies support SDL and how learner's self-directedness is fostered in [the workplace] context” (Gu, 2016, p. 308). Researchers interviewed five workers including a “technical sales representative, computer engineer, accountant, human resource specialist and magazine editor” in China (p. 308). Participants used a work app called MobLearn@Work for work-related SDL. The four functions of the app included “microblogging, RSS, podcasting, and mobile web-searching” (p. 309). Participants used these functions to “obtain industry information, problem solving, obtain general information, keep up with the industry trend, discover new ideas” and “language learning” (p. 314). They stated that the app “enhanced their responsibility and initiative toward learning” (p. 315).

Not only have researchers examined the use of mobile phones to promote learning in the workplace, but researchers have looked at how mobile phones are used to promote lifelong learning among rural women in Southern India (Balasubramanian, Thamizoli, Abdurrahman, & Kanwar, 2010). A federation of self-help groups, called VIDIVELLI, selected 320 women and gave them the opportunity to learn how to raise goats. Women received training on the mobile phones consisting of three to five voicemails or audio messages on topics such as “buying goats, feed management, disease and health management, and marketing management” (p. 194). Women found that delivering information via the mobile phone was more convenient than face-to-face classes. They used the mobile phone to “discuss and ascertain the validity of the lessons and information passed through the audio and voicemail messages” (p. 204) and they attended monthly self-help group meetings to clarify and discuss information they receive via the mobile phone. Some women reported feeling empowered as a result of the program. They are seen as having “cognitive social capital” because they know how to use mobile phones to learn more about their business from the lessons and from each other (p. 207).

In summary, technology is intertwined with our daily informal learning. Learning occurs via YouTube, Internet search, our mobile phones, and social media. Mobile phones and virtual reality are used to train workers. We use technology to learn how to do something, to find community, and to learn more about ourselves.

As is shown by the assistive technologies available to older adults, technology continues to evolve. Nanotechnology “is technology that functions at the atomic level. ‘Nano’ refers to… the width of five carbon atoms” (Picciano, 2019, p. 162). Companies are working on nanochip technology so “the whole concept of a digital computer may give way at some point to a quantum computer that operates entirely on the scale the size of atoms and smaller” (p. 162). These advances will require changes in the delivery of education (Picciano, 2019). Others argue that quantum computing may be too expensive to be practical for educational settings.

Cloud computing will be used more by universities. If course development moves from “private developers and onto computer facilities in the cloud, the ease with which faculty and students can access course material will increase tremendously and be most attractive” (Picciano, 2019, p. 164). Students may have access to cloud materials and be able to develop their own courses of study. By the 2030s, “supercloud computer service will evolve that will… be more personalized and more integrated into people's daily lives” (p. 172). It will be able to do daily activities such as starting our car and providing medical diagnoses or legal advice.

Artificial intelligence (AI) will increasingly be used in education. Faculty will be able to use artificial intelligence to know students' strengths and weaknesses. This information will help teachers improve their instruction. Georgia Tech and Penn State already use AI for teaching and advising. AI tutors can analyze students' written work and give feedback that is helpful in large courses (Adams Becker, Cummins, Davis, Freeman, Hall Giesinger, & Ananthanarayanan, 2017). At the University of Michigan, AI is being used to assist learners with disabilities. They are working on technology that helps computers know the needs of individuals who are visually impaired or lack fine motor control (Artificial Intelligence Laboratory, 2019). Picciano (2019) predicts that “general purpose AI will have much broader capabilities and will be applied in a variety of activities” (p. 165).

As mentioned earlier in the chapter, mobile devices have enhanced learning. More than half of web browsing is performed on a mobile or tablet (Adams Becker et al., 2017). Mobile apps can increase engagement within and outside class meetings. Purdue University developed an application called Hotseat where students can ask questions in real time and respond to polls or quizzes (Becker et al., 2017). “By creating ubiquitous access to educational materials, mobiles also have potential to foster learning independence and build habits for lifelong learning” (p. 40). Joint Information Systems Committee (JISC), a web-based resource for educators, helps teachers understand mobile learning and provides teachers resources that discuss mobile learning pedagogy (JISC, 2015).