Author Archives: foxmusician

About foxmusician

I am a musician and cultural psychologist.

Online instruction- class size

Research on optimal class size for online education

Stephen Fox, PhD

University of Hawaii Maui College

“Participation is an important factor in achieving a desirable outcome in higher-level learning.” (Kim, 2013, p. 123)

Online education is increasing at a phenomenal rate, with increases in both online offerings from traditional schools and from entirely online institutions where degrees are completed at distance. Hybrid classes with a mix of online and physical conditions are also popular, including the “flipped classroom” in which material is delivered online with in-person classes serving as time for activities and elaboration. The latter have been shown to be especially effective, possibly because of the interactive and supportive nature of the reinforcing activities (Lewis & Harrison, 2012). Simultaneously, an initiative has been proposed by President Obama in which schools would be rated on retention and completion rates, highlighting an area of particular risk in online education. Students fail to pass or complete online courses more often than in-person classes, a trend that may only be countered by specific intervention and mentoring (Gaskell, 2006; Waters, 2013).

Three interrelated issues predominate concerns in research on class size: retention, interaction, and quality. Students want and need quality delivery to have a successful matriculation and subsequent outcomes. In terms of retention, without other factors intervening, previous student success predicts retention (Cochran, Campbell, & Baker, 2013). Hixenbaugh, Dewart, & Towell, (2012) found that student physical health, well-being, and social support were primary factors in retention. If completion is to be the measure of success and funding, the simple solution is to raise entry standards, which will disenfranchise a massive portion of potential students. The alternative is to find methods to improve student success even amongst those with previous low performance and insufficient social support. Given the confluence of increasing demand for online classes and placement of accountability for completion at the institutional level, serious analysis is warranted. Triangulating with retention, quality of instruction and interaction are obvious areas of focus.

As Kim (2013) states, participation is a key element in outcomes, but participation may vary from simply completing assignments to synchronous interaction between students and instructors. In Boettcher’s (2013) Best Practices compendium, practice number 5 suggests use of both synchronous and asynchronous activities, which would typically include a combination of posted asynchronous discussions along with some form of synchronous participation in a textual chat or other voice or video situation. Size of class affects both of these, with systems such as Blackboard Collaborate breaking down at over 20 participants, which is about the same range where textual chat becomes unwieldy. Personalized instructor interaction is particularly time consuming, but satisfying to students. Item 5 in Hanover Research Groups (2009) Checklist for Online Interactive Learning (COIL) states that institutions should “Mandate smaller class sizes for online courses to give faculty appropriate time to deliver quality instruction” (p. 6). A surprisingly small number of journal articles address the issue of class size, despite the rapid increase of online learning in recent years and the huge increase in class sizes as Massive Open Online Courses (MOOC’s) are increasingly seen as an economically viable option for lower cost education.

Optimal Class Size (OCS)

Current actual class sizes range from very small (2 to 5) to MOOC’s of hundreds of thousands. Retention, grade, and completion begin to decrease markedly at relatively low numbers. Oestmann and Oestmann (2007) reported an optimal online class size of 20 to 25. In classes of less than 10 or greater than 25, the amount and quality of interaction decreased, and the resulting grade outcomes were reduced. Students were more likely to disengage when enrollment passed 25 (Meredith, pp. 9-10). In her review of available studies, Artz (2011) cites a number of factors that influence outcomes beyond size. For new instructors, a class of 12 appears optimal. In general, sizes of 16 to 19 students appear to have best outcomes. Overall, class size gauged for success appears to be remaining constant or going down across time.

Orleana, Instructors’ Perceptions of Optimal Class Sizes

Measure Min Max. M SD
Optimal class size 7 80 18.9 9.1
OCS if interaction goals achievable 5 50 15.9 6.6
Actual class size 4 81 22.8 13.7

Class size by publication year

Authors Year Optimal size Comments
Vrasidas and McIssac 1999 Not too small Interaction decreases
Jones, Ravid, & Rafaeli 2004 Not too big Too many discussion posts overwhelm
Arbaugh & Benbunnan-Finch 2005 25-30
Tomei 2006 12 Smaller size generates more detailed messages
Rovai 2007 min 8–10, max 20–30 Good interactions
Qiu, Hewitt, & Brett 2012 13-15 Smaller groups benefit class discussions

Asynchronous discussion

A primary method of interaction is asynchronous discussion, which brings benefit of engagement and elaboration to increase learning outcomes. Berry’s (2008) review of research suggests that discussions work best in very small groups less than ten, or in classes of 15 divided into smaller groups, though some studies recommend larger class sizes. He cites Fisher, Thompson and Silverberg (2005), who recommended 25 students as the optimal class size for such a discussion. Their two year study found that this group size, which they deem large, produced an optimal number of acceptable messages in discussions. Also cited is Reonieri (2006), whose surveys of faculty and students concluded that 10 – 15 students per class is optimal. Smaller class sizes lacked diversity of views and larger classes became effective only when “divided into the optimally sized groups so that all voices could be heard.” (Berry, 2008, p.1)

Generally, larger class sizes may generate more messages, but not improved or uniformly distributed interactions. Arguello et al. (2006) found that while lager classes generated a high volume of messages, these tended to be posted by a relatively small proportion of the students who dominated discussions (Caspi, Gorsky, & Chajut, 2003; Abuseileek, 2012). Kim (2013) designed a study empirically to test effect of group size on discussion participation and interactivity. In a class totaling 138, students either discussed as a whole class or were divided into groups of 25-30 across the semester. In the smaller groups, both postings and interactivity were consistently much higher, with a particularly greater level of interactive posts in the small group discussions. Kim concludes that his study confirms earlier research “that small grouping itself encourages more interactive participation since the activity of reading in a small group does not remain to be passive and does encompass engagement, thoughts and reflection (Hrastinski, 2009)” (Kim 2013, p. 127).

Social support

Social support as a factor in student success online seems to receive only passing mention, despite a general feeling of benefit. Interestingly, anonymity of posting without personal interaction has been observed to be beneficial to certain students (Higgs, 2012). Social support online can come from student or instructor, but can become toxic if not monitored on a fairly constant basis, based on my own experience.


As previously mentioned, both frequency and quality of interaction are highly relevant in student outcomes. An avenue of future research would be to investigate what kinds of interaction, and with whom, lead to better outcomes. My prediction would be that frequent interaction, in a class of around 20 students, that can be monitored on a regular basis by the instructor, will result in sufficient social support delivered along with quality content, leading to optimal retention and completion. Not mentioned is the reduced cost of material infrastructure, given the elimination of physical space needed, which should be counterbalanced against need for more (but probably less expensive) expenditure on technological infrastructure and support. Online instruction involves an inevitable amount of tech support provided by the instructor, which should be included in calculation of instructional time spent, and which could be provided more effectively by IT support personnel, allowing the instructor to specialize in relevant delivery of information and social support.


Abuseileek, A. F. (2012). The effect of computer-assisted cooperative learning methods and group size on the EFL learners’ achievement in communication skills. Computers & Education, 58, 231–239.

Arguello, J., Butler, B. S., Joyce, E., Kraut, R., Ling, K. S., Rose, C., et al. (2006). Talk to me: foundations for successful individual-group interactions in online communities. In Proceedings of the SIGCHI conference on human factors in computing systems, New York, MY.

Artz, J. (2011). Online Courses and Optimal Class Size: A Complex Formula.

Berry, G. (2008). Asynchronous Discussions: Best Practices. 24th Annual Conference on Distance Teaching & Learning.

Boettcher, J. V. (2013). Ten Best Practices for Teaching Online Quick Guide for New Online faculty. Designing for Learning 2006 – 2013.

Caspi,A., Gorsky, P.,&Chajut, E. (2003). The influence of group size on mandatory asynchronous instructional discussion groups. The Internet and Higher Education, 6, 227–240.

Cochran, J. D., Campbell, S. M., Baker, H. M., & Leeds, E. M. (2013). The role of student characteristics in predicting retention in online courses. Research in Higher Education. Advance online publication. doi:10.1007/s11162-013-9305-8

Gaskell , A. (2006). Rethinking access, success and student retention in Open and Distance Learning. Open Learning, 21(2), 95-98. doi: 10.1080/02680510600712997

Glenn, L. M. and Berry, G. R. (2006). Online Best Practice: Interaction Matters. Journal of Business Inquiry.

Hanover Research Group (2009). Best Practices in Online Teaching Strategies.

Higgs, A. (2012). E-learning, ethics and ‘non-traditional’ students: Space to think aloud. Ethics and Social Welfare, 6(4), 386-402. doi:10.1080/17496535.2012.654496

Hixenbaugh, P., Dewart, H., & Towell, T. (2012). What enables students to succeed? An investigation of socio-demographic, health and student experience variables. Psychodynamic Practice: Individuals, Groups and Organisations, 18(3), 285-301. doi:10.1080/14753634.2012.695887

Hrastinski, S. (2009). A theory of online learning as online participation. Computers & Education, 52, 78–82.

Kim, J. (2013). Influence of group size on students’ participation in online discussion forums. Computers & Education, 62, 123-129. doi:10.1016/j.compedu.2012.10.025

Lee, K. C., Chung, N., & Lee, S. (2011). Exploring the influence of personal schema on trust transfer and switching costs in brick-and-click bookstores. Information & Management, 48(8), 364-370. doi:10.1016/

Lewis, J. S., & Harrison, M. A. (2012). Online delivery as a course adjunct promotes active learning and student success. Teaching of Psychology, 39(1), 72-76. doi:10.1177/0098628311430641

McCarthy, J. W., Smith, J. L., & DeLuca, D. (2010). Using online discussion boards with large and small groups to enhance learning of assistive technology. Journal of Computing in Higher Education, 22(2), 95-113. doi:10.1007/s12528-010-9031-6

Meredith, B. P. (?). Online Course Class Sizes: A Review of Current Research on the Optimal Size of the Online Classroom.

Orellana, A. (2006). Instructors’ Perceptions of Optimal Class Sizes.

Qiu, M., Hewitt, J., & Brett, C. (2012). Online class size, note reading, note writing and collaborative discourse. International Journal of Computer-Supported Collaborative Learning, 7(3), 423-442. doi:10.1007/s11412-012-9151-2

Waters, J. K. (09/03/13). SJSU MOOC Study Reveals Achievement Gains but Low Retention Rates. Campus Technology.


ETEC642 project stage 2

The following reflects my experiences and results investigating possibilities for a Personal Learning Network as a student in ETEC 642.

This post summarizes my second stage on the road to my final project for ETEC 642. Online teaching is my primary livelihood, and rather than seeking ways to make online learning more similar to traditional classroom teaching, I feel the wiser course is to embrace development of new methodologies that arise organically from the medium. Social media form obvious assets in this regard, but the difficulty lies in organizing tools, determining what is accessible and practical for students, and conforming to federal and institutional regulations in their usage. The difficulty is compounded by a historical context in which these tools are themselves being developed every day as technologies emerge and are gradually supported, adopted, and rejected by a growing public of users. We cannot say with certainty what will be popular in a few months or years, but trends suggest we must be flexible enough to accommodate systems we cannot currently imagine.

In this assignment, we were asked to identify tools and creating a personal learning network (PLN). This happened in several stages, which are combined below.

Quest for a PLN

The adventure begins

    • Do you know what a PLN is?

PLN’s and me

What I knew about PLN’s?

Not much

But the concept made sense

I would now say a PLN is a network of contacts who are knowledgeable about a topic or energetic in finding answers

    • do you have one?

My own PLN? Do I have one?

Actually, I have created and curated my own over many years

This was a natural result of my education and collaboration process. My activities cross several disciplines, so no single PLN comes close to meeting my needs. I do, however, have connections with superb professionals in all of my fields, and I have created methods of connecting with them on a constant basis.

    • what do you define as your PLN?

I describe it as the sum total of my SM connections across my interests and disciplines

    • how important do you think this is for educators?

I think they are a superb resource and are critical to adaptation to a changing cultural and educational climate

    • how do you think this will improve your PD?

Examining the process of PLN creation, looking at PLN’s, and refining my own will help me to keep up to date, to learn about new technologies, and generally to do a better job for my students. PLN’s provide a constant avenue of professional development.

    • What do you see as the value in PLNs in education?

I think PLN’s have multiple levels of value. They will help us to be better educators and to know our subjects better. They also provide an avenue to guide our students into ongoing and lifelong learning, whatever their areas of interest. If we allow students limited and gradual access to our own PLN’s


  • There seem to be no Cultural Psych PLN’s
  • Classroom 2.0 never responded to my application
  • But I examined: The Educator’s PLN and Classroom 2.0 without actively becoming involved

The Educator’s PLN

The personal learning network for educators


  • 15,477 members
  • Informative Blogs
  • Groups and forums
  • Resources


  • Geared for gradeschools
  • No resources specific to my discipline
  • Groups did not appeal to me

Rating 4

  • Comment: not relevant enough to what I do

Classroom 2.0


  • 76,403 members
  • Extensive forums & discussions
  • Conferences, if you can pay
  • 1,086 groups
  • Forums
  • Other resources


  • Once again, the site seems geared to grade school
  • I did not see content-specific areas
  • The site feels very commercial

Rating 3

  • Comment: Once again, it is not directly relevant to what I do
  • I am also turned off by the commercial vibe- I feel like I am being steered to spend money


  • PLN’s are a great concept
  • They form a good framework for personal develoopment
  • My interests are too specialized for me to find one waiting
  • I think the time of the PLN has arrived, but it will be several years before they proliferate enough to flourish

For these reasons, I embarked on defining and refining my own PLN

Creating my custom PLN

I took the results of my earlier stage and furthered my examination of social media to use in constructing my PLN. In that project, I chose to specify Facebook as a primary choice for rating social media sites because it is by far the most popular and all of my participants are friends of mine there. I did not choose additional sites, but rather let them specify, which resulted in one user of Google +. Qualitative results revealed serious usage of Twitter for professional news reporting. This reflects a recent poll of colleges and universities found that the most common systems used are Facebook (96 percent) and Twitter (82 percent) (Gardner, 20130).

Ratings and usage data were similar in reporting by Tech Media Networks (2013), which publishes top-10 ratings of various technical matters and systems (Table 1). Each also includes a review of the system and the functions offered. While the reviews are somewhat cursory, the site actually provides technical details such as age, ease of use, and site appearance (Fig. 1). For breadth of information, I give this site a 5.

Table 1: SM sites and ratings



Fig. 1: Details provided in reviews

As far as reasons for using social media, research has developed gradually over a number of years. Pew Research (Brenner, 2013) provides a detailed picture of users (N=1895) in terms of demographics, and places their motivations into categories of  social impact, creators and curators, power users, and politics. These motivations do not reflect those of my sample, but this may be explained in two ways: first, the Pew sample is large enough to include averaging effects that make participants like mine outliers who are not significant, leading to the second effect of bias in my sample toward some highly specialized and intensive participants in creation and curation of content. I would categorize them as power users, but the Pew researchers limited “power” behaviors to friending, liking, and tagging. I rate this article at 5 for demographics and 3 for limited insights.

Whiting & Williams (2013) provide a different view, but once again, it differed from my small sample in a number of ways. The researchers interviewed 25 participants in depth, but the study may have been flawed from the outset by a focus on gratification as underlying theoretical stance. Their results described the following motivations:

  • social interaction (88 percent),
  • information seeking (80 percent),
  • pass time (76 percent),
  • entertainment (64 percent),
  • relaxation (60 percent),
  • communicatory utility (56 percent),
  • expression of opinions (56 percent),
  • convenience utility (52 percent),
  • information sharing (40 percent),
  • surveillance and watching of others (20 percent).

At face value, my participants would seem to fit into information seeking and sharing categories, but clarification in results and discussion take a different direction. I rate the article at 3 for having missed an important segment of social media users.

Though my own results are not really supported by these or any other studies I found, the nature of the inquiry precludes its success. Well over a billion people use Facebook alone. Including social sites in China and other countries, easily one quarter of humanity actively uses social media. To describe their motivations and activities without missing entire segments is impossible: an online community of 100,000 is much less than 1% of the total SM public. What I chose instead was primarily to survey people within my PLN whose usage I find compelling in some way. These are people from whom I learn and with whom I spar ideologically at times, which gives my PLN the power of both strong and weak ties. For my purposes, this is an effect sampling of my PLN and represents my own online experiences and needs.

I am using these elements along with listserves to construct my own PLN.


Brenner, J. (2013). Commentary: Social Networking. Pew Internet: Social Networking (full detail).

Gardner, L. (20130). Social-Media Use Grows at Colleges, Despite Little Dedicated Staff. The Chronicle of Higher Education. April 19, 2013.

Smith, C. (2013). How many people use the top social media, apps, and services.

Tech Media Networks (2013). 2013 Best Social Networking Site Reviews and Comparisons.

Whiting, A. & Williams, D. (2013). Why People Use Social Media: A Uses and Gratifications Approach. Qualitative Market Research: An International Journal 16(4).

Qualitative data in the raw:


Why do you think social media is important for your learning (or not)?

  • It is immediate and has a broad reach but can be customized to my own interests and connections.
  • For me, as a journalist it’s vitally important as it affords a platform of open and frank dialogue and robust debate. I’ve learnt a lot about how and what people really think. Topics such as Middle Eastern issues, political issues and other topics such as national security and foreign policy are intensive topics that are censored in the main stream media. Social media has allowed me to learn from others views in a way that they may otherwise not have shared. I have an international audience on my facebook with people from Israel, Palestine and across the Arab world, in addition to many people from across the West, Asia and the Sub Continent so for me, facebook particularly has allowed me to learn from others views on these tough topics which have helped me both academically and also in my broadcasting job. I have also used FB to find guests to interview, I’ve also used it to post my radio broadcasts. Twitter was also very important to my broadcasting role when I was living in the Middle East. I joined Twitter Feb 2009 and at the time, in Dubai the media (and still is) was very censored. A country like the UAE doesn’t afford free speech to its citizens and expatriates who make up 90 pc of the population in Dubai, about 80 pc UAE wide. Twitter allowed me to communicate honestly and frankly with my listeners when I was broadcasting live talk back radio out of Dubai from a State owned network in a way that I couldn’t do through the traditional radio broadcast. The authorities in the UAE were completely unaware of what Twitter was or how it worked so they were not monitoring it, as such it allowed me to learn from the audience what they really thought about any given topic I was talking about on air. It also afforded me the ability to share my views on Twitter with my listeners in a frank and transparent way that I couldn’t do on air. This really brought the community together, it removed the barrier that existed in a censored environment and allowed for a real sense of freedom of expression.
  • It connects people in different spaces and give a cultural conxt
  • Lateral information networks allow for more authentic sharing of ideas and information.
  • Helps keep me up to date with what is going on in the world.
  • The use of social media has the potential to expand student interest by exposure to a broad group of people interested in the same subject. Online education has removed the traditional classroom face-to-face discussions.
  • social learning, how to live and play with each other and understanding society and the role or impact that i do have on society and the planet is very important.
  • I have a friends list of people who are very intelligent, diverse and hunger for information and knowledge. When the post on their status something fascinating, I am likely to follow up via Google.
  • I get it from people u trust and value
  • Connects me with many, many professionals.
  • introduces me to new ideas and hot topics, which I might follow up with a google or Wikipedia search.
  • Used as a tool social media can be focused to expose the user to his or her specific areas of interest and find like minded people. Those like minded people can share their specific interests which I find often gives new perspectives and ideas and even whole new topics of interest.
  • I’ve never associated FB with learning, just a way to see what others are doing.
  • With music, I can listen to an interview, or a lesson with the artist who wrote the music, for more insight to interpretation.
  • Although I try to follow EdTech groups and keep up on current events via social media, I feel I learn the most from keeping around a diverse list of people with occasionally different perspectives. I get my Hawaii news, my cultural and news items of interest from Black friends, reflection from my token Libertarians, pop culture and civil rights info from my queer friends, Turkish uprising information, and even (from one college buddy) a window into the Singapore theater scene. Social media isn’t just for keeping up with people far away, or passing around meme images, or being horrified by family members’ racism or politics. I learn when I keep up with my current interests, but I am able to learn more when I keep my mind open by keeping my eyes on the larger currents.

Any other comments about the idea of learning in social media?

  • Make it fun and it (learning) will grow and expand boundaries.
  • it is a kind of community consciousness that we learn from.
  • More insight to fan interest. What types of songs elicit more response….
  • Social media gets dismissed as shallow and shoddy thinking, passed around without reflection. It’s not all like that, though. In my experience, you just have to be willing to not be too invested in convincing other people they are wrong and more in listening and considering how people got to that other point of view. I see it as a place not for deepening learning, but as a source of touchstones you must pursue on your own.
  • It also helps me 1) see what is current and 2) find my market.
  • I would want groups monitored, especially for younger students. Many groups now have trouble with “trolls” entering with intentions that differ from the group’s.
  • Love to see it!
  • Along with FB, Twitter is also vital in its role of affording true freedom of speech. The online community is given the authority to correct itself and others rather than being governed by laws around speech. It’s a testing ground at the moment for challenging authority. It’s shaping a new way of thinking both good and bad for the sustainability of humanity both online and off line. On the other hand, social media seems to have created a thinking vacuum (if such a thing exists) as a result of information overload combined with the concept of the 24 hour news cycle. Questions can be raised about whether the avalanche of information provided through social media actually encourages people to develop their cognitive processes by really thinking deeper and learning more. Does having access to endless social media prompt people to create value in information or is the overload of information devaluing information and our potential to really learn? People forget to think and social media seems to have a sinister way of somehow giving us heaps of information, lulling us into the idea that we know more but making us ignorant and lazy at the same time. It conjures up the image of seagulls just gorging on anything that seems to fall their way. Desensitising and devaluing society through too much information and not enough thinking I think is actually leading to an increase in mental health issues including depression and a load of other things. Our ability to analyse and give value and importance to what really matters is becoming vitally important as we face an ongoing and increasing bombardment of information available to us through social media.

The emerging cultural psychology of an emergent culture

We humans are unquestionably cultural creatures. We are born after some process of mating, raised and trained to understand certain rules, and sustained by livelihood earned via fulfillment of particular roles and tasks. The web and growing social media are new, but they extend from a trajectory of cultural development that is many millennia old. The pace of cultural development is increasing, but we are still physiologically mostly the same hairless monkeys we were when we the great African droughts in the caves of Bolombos 70,000 years ago.

Wellman proposes that the most important shift arising from the web is “the shift from group centered to network centered life.” (Reinhold, p. 220). If this is true, we may extend our practical social networks beyond Robin Dunbar’s number of 150, or we may not. Analysts of social networks have long acknowledged that we have both strong and weak links to others, and that strong ties require more investment of ourselves and our time than weak ones. Rheingold summarizes the strong ties require:

  • More time
  • Shared experiences
  • Deeper trust
  • More frank self disclosure (p. 225)

We may never expand beyond the 150 of our optimal tribal group in terms of strong ties, and we may never need to do so. Weak ties provide more divergent information than the information we already share with our network of strong ties, and the web drastically increases our ability to connect and interact with more distant individuals and to reactivate latent ties that would normally fade when we leave our high school or home town.

Wellman and others describe our new condition as networked individualism. Individualism as a concept in social sciences dates back to well before Mead’s investigations of “primitive” cultures, and is normally contrasted with the “collectivism” of non-Western cultures. Rheingold summarizes characteristics of this networked individualism as:

  • Boundaries are more permeable
  • Interactions are with diverse others
  • Linkages switch between multiple networks
  • Hierarchies are flatter and more recursive
  • People and organizations communicate with others in ways that ramify across group boundaries (Wellman, Quan-Haase, Boase, Chen, Hampton, de Diaz, & Miyata, 2003).

This list maps well onto the domains of cultural variation outlined in cultural psychology (e.g. Hofstede, 1980).

Collectivist cultures enjoy very deep connections within the group, and those boundaries are often very solid because accepting a new intimate implies addition of lasting obligations and responsibilities. Responsibilities in the digital domain will probably never have the depth or richness of relationships that span centuries and generations, and our lives will be the lesser for loss of ancient mechanisms of cohesion and connection. We cannot foresee what may replace them on the digital commons.

The web offers new realms of social capital, which is garnered through trust, cooperation, reciprocity, and consistency. We may act as individuals on the net, but social capital is conferred by collective interaction with others, much like the Asian concept of “face” (Ho, 1976). One gains face by displaying competence in one’s role as a member of the community faithfully and consistently, enhanced by showing wisdom and benevolence in social relations. Online social capital is not so different.

What can be different is the structure of society, which can often be quite hierarchic in collectivist cultures, disadvantaging those of lower status, whether by gender of heredity. Putnam and colleagues observed that Northern Italy, with its more horizontal system of guilds and civic organizations, built greater wealth than the vertical social structures of the feudal south, the people becoming citizens versus subjects. The net has been designed to remain horizontal, and hopefully will remain such.

The developing norms of online culture are generally egalitarian. Norms are necessary for social interaction and are learned through modeling, such as the social inattention by which we let minimally embarrassing situations and behavior pass unremarked if not unnoticed. Norms of reciprocity can be specific or diffuse, and the possibility of highly diffuse avenues for return on invested energy make the net a field ripe for exceptional levels of collaboration.



Granovetter, M. S. (1973). The Strength of Weak Ties. American Journal of Sociology, 78(6), 1360-1380.

Ho, David Yau-Fai (1976), “On the Concept of Face,” American Journal of Sociology, 81 (4), 867–84.

Hofstede, G. (1980). Culture‘s consequences: International differences in work related values. Beverly Hills, CA: Sage.

Wellman, B., Quan-Haase, A., Boase, J., Chen, W., Hampton, K., de Diaz, I. I., & Miyata, K. (2003). The Social Affordances of the Internet for Networked Individualism. Journal of Computer-Mediated Communication, 8(3).

© Stephen Fox, 2013, contact

pondering the emerging cultural dynamics of life on the Web

ETEC 642 Week 4

I seem to have accidentally anticipated Rheingold’s fourth chapter, with its opening emphasis on the human propensity for cooperation. I am convinced about the value of the social brain hypothesis and expect that we will see a continued limit of around 150 direct contacts regardless of how many “friends” one might have on FB. Within the hundreds or thousands on a friend list, I suspect the closer interactions will remain limited to that group size because it is just how we are hard-wired. Cultural evolution has to some degree outstripped our neurolgic capacity.

Humans are notoriously bad at thinking on very big scales, as is illustrated in the “tragedy of the commons” (Kramer & Brewer, 1984) and in denial of effects of carbon fuels as we race to burn up global reserves. Ostrom’s superb enumeration of factors needed for successful “institutions of collective action” become too abstract to achieve buy-in when the average person must imagine cooperation with people on the other side of the globe, even if that average person is running a country. We inexorably think in terms of in-group and out-group, even when the group is made up by researchers in a lab using the most meaningless criteria they can dream up, as Marilyn Brewer has demonstrated for decades (Brewer, 1979, etc.). We align best with villages and clans, though we are capable of identification with super-ordinate groups such as national, ethnic, or religious groups (Kramer & Brewer, 2006). Unfortunately, this is most effectively done in contrast to an opposing group and not in unifying the human race for cooperative efforts.

The section on crowdsourcing gives a certain amount of hope, though Rheingold’s summary of Sharma’s elements of successful crowdsourcing begin with buy-in and include identification with the superordinate project group to stimulate a sense of self-interest .

Sharma’s elements

  • Vision & strategy
  • Human capital
  • Infrastructure
  • Linkages & trust
  • External environment
  • Motive alignment of the crowd

In the long run, commons based production will be a challenge for prevailing social psychological thought. That thought, however, is based on a predominance of Western researchers located in the US, using American college students as participants, most of whom are raised in a highly individualistic culture. The Web democratizes intercultural contact beyond any single region or culture, perhaps providing a counter to the alarming focus on individual gain characteristic of American culture and business.


Brewer, M. B. (1979). In-group bias in the minimal intergroup situation: A cognitive-motivational analysis. Psychological Bulletin, 86(2), 307-324. doi:10.1037/0033-2909.86.2.307

Brewer, M. B. (1996). When contact is not enough: Social identity and intergroup cooperation. International Journal of Intercultural Relations, 20(3-4), 291-303. doi:10.1016/0147-1767(96)00020-X

Kramer, R. M., & Brewer, M. B. (1984). Effects of group identity on resource use in a simulated commons dilemma. Journal of Personality and Social Psychology, 46(5), 1044-1057. doi:10.1037/0022-3514.46.5.1044

© Stephen Fox, 2013, contact

Connectivism and the evolution of culture

For ETEC 642 Week 3

In the week 3 materials, I am most mindful of two streams of content: growing power of online communities and revised metaphors of learning as networking. Interestingly, they share some common structures. Both emphasize connections as the primary mechanism for growth and success, and that growth is described as organic and intertwined rather than linear and self-contained.

Our online communities are powerful, to be sure. We can engage in collective action, including learning, on unprecedented scales. We can share knowledge about issues and events instantaneously in communities of interest that span across oceans and continents. This power, however, is new and completely immature. Communities of interest are implicitly susceptible to group processes such as confirmation bias, in which we overly weight information congruent with our opinions and discount disconfirming information (Oswald & Grosjean, 2004), and “groupthink” errors in which homogenous groups typically fail to examine evidence outside their limited range of experience (Baumeister & Bushman, 2011).  Social media also offer vast opportunities to interact with diverse views that contradict our own, but until the medium matures, those with highly accurate but differing views may be seen as “trolls” by communities of interest.

These observations are congruent with Rheingold’s (2012) observation that instructors fear social media might be using our students rather than visa versa. He looks to crowd-sourcing and other group interactions to battle the spread of counter-factual information, but social psychology has demonstrated that a diversity of views must be honored for this to happen (Sanderson, 2010). Currently, the group polarization of contemporary politics is reflected by entrenchment of ideas in surprisingly isolated communities. Overall, this phase may be outgrown as the process of extended and shared learning develops.

Humans evolved and spread in no small way because of our ability to transmit knowledge to others, allowing us to outlive other hominid lines with greater strength, speed, or climbing ability. The Social Brain Hypothesis (Dunbar, 2003; Jerison, 1973) suggests that we evolved our brains specifically for social interaction and that our success arises from our ability to cooperate. Lenski and Lenski (1987) posited that our cultures are growing more complex as part of a natural evolutionary process. Similarly, Shirov and Gordon (2013) applied Moore’s Law (that computers double in complexity every two years) to the complexity of life, and to the expanding complexity of our cultural knowledge and abilities. We have now reached a point where our ability to share and transmit information has allowed for massive, global transmission in a medium that enhances our neural and direct interpersonal networks with this vast digital nervous system.

Connectivism, as described by Kop and Hill (2008), has become an inexorable part of human life. Our current traditional aged college students are the first to be born into a world where computers in most homes is a normal part of their natural world (at least in developed countries). Those who were born into a world of robust and widespread social media usage are still in elementary school. I suspect that as these young people grow, learning the skills of global networking from the start, we will see continuing increases in the quality and quantity of informational technology such that our current systems will look as primitive as Gutenberg’s press very shortly. On a metacognitive level, this is a natural progression for creatures who appear to have flourished specifically by evolving mechanisms to communicate and transmit knowledge. Hopefully, we value and spread wisdom more quickly than we develop tools to divide, dominate, and destroy.

Baumeister, R. F., & Bushman, B. J. (2011). Social Psychology and Human Nature (2nd Edition). San Francisco, CA: Cengage.

Dunbar, R. I. M. (2003). The social brain: Mind, language, and society in evolutionary perspective. Annual Review of Anthropology, 32, 163-181. doi:10.1146/annurev.anthro.32.061002.093158

Jerison, H. J. (1973). Evolution of the Brain and Intelligence. New York, Academic Press.

Jerison, H. J. (1955). Brain to Body Ratios and the Evolution of Intelligence. Science
New Series, 121
(3144) 447-449.

Kop, R. & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past?. The International Review of Research in Open and Distance Learning, 9(3). Available at:

Lenski, G., & Lenski, J. (1987). Human Societies: An Introduction to Macrosociology (5th edition). New York: McGraw-Hill Book Company.

Oswald, Margit E.; Grosjean, Stefan (2004), “Confirmation Bias”, in Pohl, Rüdiger F., Cognitive Illusions: A Handbook on Fallacies and Biases in Thinking, Judgement and Memory, Hove, UK: Psychology Press, pp. 79–96, ISBN 978-1-84169-351-4, OCLC 55124398

Rhinegold, H. (2012). Netsmart: How to thrive online. Canbridge MA: MIT Press.

Sanderson, C. A. (2010). Social Psychology. Danvers, MA: John Wiley & Sons, Inc.

© Stephen Fox, 2013, contact

PLN diagram

This is my PLN, expressed in terms of tight and loose connections. Presently, I see FB as crossing all levels. G+ is a somewhat loose set of connections: though I know some of my contacts well, we do not share closely in that domain.