Access to Information

The World Wide Web (WWW) begat online learning as we know it, so it is appropriate that we begin here. The growth of the Internet has made enormous amounts of information on just about everything available to anyone with a computer and a broadband connection. In November 2018, for example, it was estimated that there were over a billion publically available websites and 5.28 billion publicly indexed webpages (see www worldwidewebsize.com/). Obviously, such numbers are constantly and quite rapidly expanding. They make the notion that the purpose of higher education is the acquisition of scarce or privileged knowledge somewhat absurd, especially in the context of the Open Educational Resources (OER) movement and the growth of Massive Open Online Courses (MOOCs). In 2016, there were over 7000 MOOCs being offered worldwide (ICEF Monitor, 2016), and in 2018, Creative Commons alone listed 1.4 billion content resources. These numbers do, however, highlight the problem of information overload, and the need to be able to separate the wheat therein from the chaff. The growth of the Internet, then, provides educators with the opportunity, perhaps the imperative, to change their pedagogical focus from the transmission of knowledge to one enabling students to both critically make sense of an overabundance of information and to use it to generate knowledge themselves.

Multimedia Integration

Concurrent with the growth of the Internet has been the growth of digital multimedia and the ready availability of relatively inexpensive multimedia tools. Digital multimedia makes it possible to access, evaluate, manipulate, create, and share ideas in a variety of media formats. According to MerchDope (2018), for example, 1.3 billion people use YouTube; they upload over 300 videos to YouTube every minute and watch five billion YouTube videos every day. Virtually every news organization in the world today provides news and information not just in textual form, but in a wide variety of video, graphical, and interactive formats. The critical use and/or production of multimedia calls for intellectual skills and ways of knowing that are quite different from the manipulation of text and numbers privileged by higher education (Stephens, 1998).The growth of digital multimedia thus challenges such privilege, as well as our conventional notions of what it means to be literate (Snyder, 1998; Tyner, 1998). Indeed, the growth of digital multimedia challenges educators not only to expand their pedagogical repertoires to include multimedia, but, in particular, to facilitate their critical understanding and generation.

Social Media

Technological innovation has also produced a suite of digital applications collectively labeled “social media.” The pedagogical affordances of social media are many but they center on supporting communication and collaboration over time and distance. The success of crowd sourced projects like Wikipedia, as well as the dominance of social media like Facebook and Twitter, has led some scholars (Jenkins, 2006; Surowiecki, 2005;Tapscott & Williams, 2006) to argue that large-scale collaboration, and not the individual labors of an elite few, will drive knowledge creation in the twenty-first century. Although there are obvious problems with such arguments (Keen, 2007), social media clearly and explicitly support the social construction of knowledge, and so favor collaborative pedagogical approaches over individualistic and/or authoritative ones. Serious problems involving the validity of information shared through social media (Allcott & Gentzkow, 2017) as well as the seemingly counterintuitive social isolation associated with its use (Hobson, 2017) continue to plague the popular social media platforms. Moreover, experiments with the educational use of social media have had mixed results (Lau, 2017).

Learning Analytics

The growth of computing power has led to tools for collecting, organizing, and analyzing vast amounts of data. The use of predictive analytics that has become common in business ventures is being quickly adapted to educational settings, especially online settings in which enormous amounts of data are generated where they are known as “learning analytics” and defined as tools that measure, collect, analyze, and report data about students and their learning behaviors and context “for the purpose of understanding and optimizing learning” (Maseleno, Sabani, Huda, Ahmad,Jasmi, & Baisron, 2018, p. 1124). Learning analytics today are most commonly used to support student success, whether they are faculty and staff or student facing, but analytics also support competency-based and adaptive learning systems which are being shown to support learning in a variety of domains (Dziuban, Moskal, Cassisi, & Fawcett, 2016; Levy, 2013; Woodward, 2015), and artificial intelligence which has tremendous potential for the future (McFarland, 2016).The pedagogical affordances of analytics in all its various current and future forms center on the personalization of learning made possible through the ongoing collection of large amounts of information about individual students.The obvious downside to such efforts is a loss of privacy. The not so obvious downside is that the use of analytics tends to skew the educational enterprise toward that which can be quantitatively measured.

At the beginning of this section, I argued that the unique characteristics of online technologies significantly change what is pedagogically possible. I identified four such unique characteristics and the kinds of pedagogical change they enable. Much greater access to information enables a change in pedagogy from knowledge transmission to knowledge generation. Multimedia integration makes possible a more media inclusive understanding of what it means to be literate. Support for large-scale collaboration facilitates a change from authoritative and individualistic to collaborative and more democratic teaching and learning strategies. Analytics make the personalization of learning and supports for learning possible and the machine learning they enable is making artificial intelligence a reality.

Please note my use of the word “possible.” You may have noted that higher education really hasn’t yet abandoned its centuries’ old authoritative, lecture and text based model of knowledge transmission; indeed, most MOOCs recreate this model online. However, please also note that this model itself was made possible by the development of print technologies (Eisenstein, 1980). The point is that the traditional model of higher education takes advantage of the unique characteristics of print technologies, and has, moreover, until now been constrained by them.The emergence of digital technologies removes many of those constraints at a period in time when social constructivist pedagogies are gaining favor among the education community. This latter trend and its implications for online learning are explored in the following section of this chapter.