The research todate has not converged on an archetypal profile of the online learner. Althoughsome situational, affective, and demographic characteristics may cut acrossthis learner population, what seems to be more prevalent is the changing oremerging nature of the online learner and the multiplicity of learning stylesand generational differences represented. This situation carries considerablepedagogical implications for the design of online learning environments andnecessitates a review of the research to determine the characteristics andskills of the emerging online learner. Determining the characteristics andeducational needs of the online learner may not necessarily guarantee successin a distance education course or program (Galusha, 1997). It could, however,significantly help administrators, teachers, and instructional designersunderstand (a) who is likely to participate in online learning, (b) whatfactors or motivators contribute to a successful online learning experience,and (c) the potential barriers detering some students from participating in orsuccessfully completing an online course. In order to better understand thecharacteristics and perceived skills of the online learner and the underlying motivationsand barriers that impact successful online learning experiences, a review ofthe characteristics of the traditional or classic distance education learner isessential.
The Classic Distance Education Learner
Earlier profiles of theonline learner can be traced to classic distance education settings (e.g.,correspondence or home study) where most learners were adults withoccupational, social, and family commitments (Hanson et al., 1997). TheNational Home Study Council (NHSC) founded in 1926 collected information aboutits students and created the following demographic profile for home studystudents (Lambert, 2000): “Average age is 34 years; 66% are male; 25% have acollege degree; over 50% have had some college education; and over 75% aremarried” (p. 11). Home study students were also described as self-motivated,goal-oriented, and disciplined self-starters.
A student’s academicself-concept was also shown to be a key predictor for success in a distanceeducation setting. Dille and Mezack(1991) studied the profile of students who enrolled in telecourses (coursesdelivered through television) focusing on locus of control (internal/externalattribution of success and failure) and learning style (e.g., verbal, visual,or kinesthetic) as predictors of success among college distance educationstudents. They found that locus of control is a significant predictor ofsuccess and persistence in distance education courses. Specifically, studentswith an internal locus of control (those who attribute success and failure ontasks to personal behaviors and efforts) were more likely to succeed (receive agrade of C or better) and persevere (complete a telecourse) in a telecoursethan did students with an external locus of control (those who attributesuccess and failure on tasks to external or uncontrollable factors such as luckor task difficulty).
Several other studies examinedstudent attitudes, personality characteristics, study practices, coursecompletion rates, and other academic, psychological, and social integrationvariables to identify barriers to persistence in distance education anddetermine predictors for successful course achievement (e.g., Bernt &Bugbee, Biner, Bink, Huffman & Dean, 1995; Fjortoff, 1995; Garland, 1993;Laube, 1992; Pugliese, 1994; Stone, 1992; 1993;). Overall results of suchstudies indicated that intrinsically motivated learners possessing a highinternal locus of control, coupled with a positive attitude toward theinstructor and a high expectation for grades and degree completion were morelikely to succeed in a distance education course.
Interestingly, individual learning style did not proveto be a significant predictor of success, the rationale being that distanceeducation is inherently accommodating for a variety of learning styles (Dille& Mezack, 1991). This finding is consistent with the pedagogicalcharacteristics of technology supported learning environments and, inparticular, Web-based or online learning environments that emphasizeinteraction and collaboration. Such environments are multimodal (support audio,video, and text), provide individual and group interaction spaces insynchronous and asynchronous formats, support linear and nonlinearrepresentation of content, and provide a variety of learning tools to cater toa variety of individual learning styles. As Brown (2000) stated, “The Webaffords the match we need between a medium and how a particular person learns”(p. 12).
The Changing Nature of the Distance Education Learner
Thisresearch demonstrates that although distance education learners share broaddemographic and situational characteristics, no concrete evidence indicatesthat this group is homogeneous or unchanging (Thompson, 1998). In fact, thecurrent profile of the online distance learner can be characterized as emerging,responsive to rapid technological innovations and new learning paradigms, andprogressively including a younger age bracket. In a recent Sloan Consortiumreport on the state of online learning in the United States, Allen and Seaman(2006) reported that undergraduates represented 82.4% of the total populationof higher education students taking at least one course online.
Researchalso suggests that today’s youth, who are increasingly growing up with Internetand Web-based technologies such as search engines, instant messaging, massivemultiplayer online role-playing games (<ahref=”http://en.wikipedia.org/wiki/MMORPG” target=”_blank”>MMORPG), <ahref=”http://en.wikipedia.org/wiki/Podcasting” target=”_blank”>podcasting, <ahref=”http://en.wikipedia.org/wiki/Videocasting” target=”_blank”>vodcasting, <ahref=”http://del.icio.us/” target=”_blank”>social bookmarking and <ahref=”http://en.wikipedia.org/wiki/Folksonomy” target=”_blank”>folksonomies, are wellprepared to engage in online learning activities that support interaction andcollaboration (Dabbagh & Bannan-Ritland, 2005). In addition, distributed onlinelearning delivery models such, as knowledge networks, learning communities, asynchronouslearning networks, and knowledge portals, are designed to effectively meet the characteristicsof this emerging learner population. These models support interacting withpeers in virtual spaces on team projects, engaging in online discourse,researching term papers using Web-based resources, and developing Web sites anddigital products to demonstrate learning. Although Generation Xers (born1960-1980) continue to represent the majority of online distance educationlearners, generation Nexters (born 1980-2000) will soon represent a sizableportion of this population, bringing with them new communication andtechnological skill sets.
Thedistance education population as a whole is also becoming more heterogeneous ordiverse, encompassing students from a variety of cultural and educationalbackgrounds (Dabbagh & Bannan-Ritland, 2005). Globalization of distanceeducation has enabled students from across the globe to participate in onlinelearning activities, such as joining moderated listservs, participating inonline seminars, and sharing information through knowledge portals.Additionally, distance education learners are becoming less location bound.Thompson (1998) elaborated on this point as follows: “Increasingly, students inclose proximity to traditional educational institutions are choosing distancestudy not because it is the only alternative, but rather because it is thepreferred alternative” (p. 13). Attraction to innovative technology-mediated learningenvironments and flexible course delivery schedules are two of the reasonslisted for the desire to be outside the educational mainstream.
The Emerging Online Learner
The concept of the independent, place-bound, adult,self-motivated, disciplined self-starter, and goal-oriented learner, which largely characterized the classic distance education learner, isnow being challenged with socially mediated online learning activities thatde-emphasize independent learning and emphasize social interaction andcollaboration. As stated by Anderson and Garrison (1998), “The independence andisolation characteristic of the industrial era of distance education is beingchallenged by the collaborative approaches to learning made possible bylearning networks” (p. 100). Therefore, online learners must be ready to sharetheir work, interact within small and large groups in virtual settings, andcollaborate on projects online or otherwise risk isolation in a community growing increasingly dependent on connectivity and interaction. Given thisnew context, what are the perceived characteristics and skills of the emergingonline learner?
Researchindicates that interpersonal and communication skills and fluency in the use ofcollaborative online learning technologies are critical competencies for theonline learner (Dabbagh & Bannan-Ritland, 2005). Williams (2003) found thatinterpersonal- and communication-related skills (which include writing skills)dominated the top 10 general competencies across all roles in distanceeducation programs supported by the Internet. Powell (2000) described theonline learner as someone who is “very comfortable with written communications,somewhat savvy with Web technologies, and proficient with computers.”Additionally, Cheurprakobkit, Hale, and Olson (2002) reported that lack ofknowledge and skill in the use of online learning technologies, particularlycommunication and collaborative technologies, could present barriers tolearning for students in online learning settings.
Anotherimportant characteristic of the online learner that carries forward from theprofile of the classic distance learner is self-directed learning.Self-directed learning can be described as the skill of “learning how to learn,”or being metacognitively aware of one’s own learning (Olgren, 1998, p. 82).Cheurprakobkit et al. (2002) reported that students in online learningenvironments must possess “self” behaviors such as self-discipline,self-monitoring, self-initiative, and self-management, which are characteristicsof self-regulated or self-directed learning. Given the physical absence of aninstructor in online learning, the ability of learners to monitor and regulatetheir own learning is critical.
Furthermore, online learners must understand and value thelearning opportunities afforded by collaborative and communication technologiesin order to engage actively and constructively in learning. Some learners areinherently drawn to peer interaction or collaboration, while others need tounderstand the educational value of these pedagogical constructs. Beinginherently drawn to interaction can be characterized as an individualdifference referred to in the literature as the need for affiliation. In onlinelearning environments the need for affiliation can be interpreted as the needto be connected or to belong to supportive groups (MacKeracher, 1996).
Acommunity of practice (COP) is an example of how the need for affiliation canmanifest itself in online learning environments. Members of a COP understandthat a social mind is at work and that knowledge is a shared intellectualcapital. COP is a pedagogical model grounded in a theory of learning as a social processand implemented in an online context through knowledge networks, asynchronouslearning networks, and other Internet and Web-based collaborative andcommunication technologies (Wenger & Snyder, 2000). Although online learnersstill need to (a) act competently on their own; (b) have confidence in their knowledge,skills, and performance; and (c) learn how to create and manage a personalpresence; sensing or exhibiting a need for affiliation is key to a successfuland meaningful online learning experience (Dabbagh & Bannan-Ritland, 2005).
Characteristics of theOnline Learner
In summary, the following characteristicsand skills are perceived as critical to the success of the online learner:
- Having a strong academic self-concept.
- Exhibiting fluency in the use of online learning technologies.
- Possessing interpersonal and communication skills.
- Understanding and valuing interaction and collaborative learning.
- Possessing an internal locus of control.
- Exhibiting self-directed learning skills.
- Exhibiting a need for affiliation.
Competency in the use of online learning technologies,particularly communication and collaborative technologies, does not guaranteemeaningful interaction, collaboration, and knowledge building in onlinelearning environments (Lindblom-Ylanne & Pihlajamaki, 2003). Therefore, inaddition to the previously listed characteristics and skills, online learnersshould possess or develop collaborative learning skills independent of thesetechnologies. These skills include social learning skills, discursive ordialogical skills, self and group evaluation skills, and reflection skills(Comeaux, Huber, Kasprzak, & Nixon, 1998; Spector, 1999). Each of theseskill sets are briefly described in the following section.
Social Learning Skills
Social learning skills supportdecision-making, communication, trust building, and conflict management, all ofwhich are important components for effective collaboration. Social learningskills are needed to assume leadership roles as well as other roles typicallyassigned in teamwork.
Discursive or Dialogical Skills
Discursive or dialogical skillsinclude the ability to discuss issues (being discursive), share and debateideas, negotiate meaning, demonstrate openness to multiple perspectives, andpossess good articulation and listening skills.
Self and Group EvaluationSkills
Self and group evaluation skillsinclude learning how to be individually accountable for (a) being active andengaged in group activity (b) doing a fair share of the work and (c) helpingother group members to demonstrate competence and learning achievement (i.e.,promotive interaction).
Reflection skills include theability to apply frequent and substantive consideration and assessment of one’sown learning process and products and the group’s learning process andproducts. Learners must be skilled in time management and orienting strategiesthat help them prepare to learn, and in cognitive learning strategies thathelp them interact meaningfully with the learning content. In addition, time-managementskills and orienting strategies have a direct impact on collaborative learningin terms of effectively and efficiently carrying out the responsibilities of beingan active and accountable member of a group. Cognitive learning strategies, onthe other hand, are perceived to be most relevant to an individual’s ability toreflect upon, monitor, and assess one’s own learning when carrying out alearning task.
Tosummarize, a successful online learner should
- Be skilled in the use of online learning technologies, particularly communication and collaborative technologies.
- Have a strong academic self-concept and good interpersonal and communication skills.
- Have a basic understanding and appreciation of collaborative learning and develop competencies in related skills.
- Acquire self-directed learning skills through the deployment of time management and cognitive learning strategies.
Toeffectively accommodate, support, and promote the characteristics and skills ofthe successful online learner as discussed in this paper, online learningdevelopers, instructors, and teachers should consider two pedagogical modelswhen designing their online courses and learning interactions: exploratory and dialogical.
Exploratory Pedagogical Models
Exploratory learningmodels are based on the theoretical construct of discovery or inquiry-basedlearning, in which learners are provided with a scientific-like inquiry orauthentic problem in a given content area and asked to generate a hypothesis, gatherrelevant information using a variety ofresources, and provide solutions, action plans, recommendations, andinterpretations of the situations (Dabbagh & Bannan-Ritland, 2005).Examples of such models include Microworlds, simulations, WebQuests,cognitive apprenticeships, situated learning, and problem-based learning. Thesemodels support collaborative learning, interpersonal and communication skills,social learning skills, self and group evaluation skills, reflection skills,and self-directed learning skills, all of which are characteristics of thesuccessful online learner.
The exploratory orexperiential mode of learning is provided within online learning through theuse of several online learning technologies, including hypermedia, multimedia,search engines, digital audio and video, graphics, and self-containedinstructional modules developed using a variety of authoring tools. Examples ofhow exploratory models can be implemented in online learning include thefollowing:
- Using Web-based authoring tools and scripting languages to develop self-contained instructional modules such as <ahref=”http://www.microworlds.com/” target=”_blank”>Microworlds and simulations that engage students in exploratory-type activities.
- Providing Web-based resources using hypermedia and multimedia links to support students’ exploratory activities.
- Providing a link to a search engine in the course site enabling students to search for Web-based resources to promote exploration.
- Providing links to online databases and knowledge repositories that provide real time data such as up-to-date weather information and other scientific data and statistics.
- Providing students with a Web posting area and appropriate tools to publish their work (e.g., draft papers, problem solutions, etc.). Students can then engage in an exercise of peer evaluation of each other’s work, prompting reflective thinking.
When designing online learning basedon exploratory pedagogical models, the decision as to which learningtechnologies or combination of learning technologies to use will rest ultimatelyon the expertise of the online learning developer, the available resources andtechnologies, the characteristics of the audience, and the instructionalcharacteristics of the pedagogical model implemented (Dabbagh &Bannan-Ritland, 2005). A popular online learning activity with K-12 teachers thatsupports many of the instructional characteristics of exploratory learningmodels is a WebQuest. A WebQuest
is an inquiry-oriented activity in which most or all of the information used by learners is drawn from the Web. <ahref=”http://webquest.sdsu.edu/webquest.html” target=”_blank”>WebQuests are designed to use learners’ time to help them focus on using information rather than looking for it, and to support learners’ thinking at the levels of analysis, synthesis and evaluation. (Dodge, n.d.)
Dialogical learning models emphasize social interactionthrough dialogue and conversation. The idea is to assist learners inconstructing new knowledge primarily through dialogue as a form of interaction.Internet and Web-based technologies provide various mechanisms for supportingdialogue related to both informal and formal learning situations. For example,a Web-based group forum (discussion board) can support a formal conversationalexchange that occurs in support of specific instructional objectives or aninformal conversational exchange based on content interest (Dabbagh &Bannan-Ritland, 2005). Both of these conversational exchanges foster a sense ofcommunity and belonging. Examples of dialogical pedagogical models includelearning communities, knowledge building communities, and communities ofpractice. These models emphasize discursive or dialogical skills such asarticulation, reflection, collaboration, and social negotiation, as well asself and group evaluation skills, which support the characteristics ofsuccessful online learners.
Online learning technologies supporting the implementationof dialogical pedagogical models include asynchronous and synchronous tools,such as email, bulletin boards or discussion forums, listservs, computerconferencing, groupware, document sharing, virtual chat, and videoconferencing. Examples of ways dialogicalpedagogical models can be implemented in online learning include the following:
- Setting up online group discussion areas focused around a topic or specific activity, goal, or project, such as a case study, using asynchronous discussion forums to promote collaboration and social negotiation. Some group discussion areas can be open ended and unmoderated, allowing students to solicit information from each other, while others can take the form of a structured online discussion.
- Designing activities that allow group members to share documents related to a group project. Sharing documents online is a collaborative activity and can range from simply displaying the document in a designated Web posting area to having group members work simultaneously on a document using groupware (an application sharing tool). When the document is displayed, group members can discuss its contents via email, videoconferencing, or chat. When <ahref=”http://www.writely.com/” target=”_blank”>groupware is used, group members can co-edit the document online and annotate the document if the groupware has built-in annotation systems.
- Engaging students in synchronous communication activities using virtual chat and videoconferencing. Real-time collaborative activities allow groups to brainstorm ideas, debate problems, and develop action plans in a finite and short period of time.
Additionalexamples of online learning applications that support dialogical pedagogicalmodels are MUDsand MOOs (Dabbagh & Bannan-Ritland, 2005). MUDs and MOOs are knowledgenetworks that emphasize social interaction and negotiation throughrole-playing. A MUD (Multiple User Dungeon or Multiple User Dimension) is a”complete virtual world in which you become the body of a character youadopt to navigate that world” (Hall, 2001, p. 55). Users explore thevirtual world in real time and typically at the same time as other users whoare also controlling characters. Users can talk to each other and form teams.Theme, content, and style vary from one MUD to the next. MUDs originated in agame called Dungeons and Dragons developed for multi-users on the Internet. Ineducational settings, MUDs are being used as a collaborative tool for students.“In Web-based learning, simulated role portrayal can be facilitated throughMulti-User Dialogue (MUD) environments, in which instructors create amulti-user space with a central theme, characters and artifacts” (Khan, 2001,p.81).
A MOO(Multi-User Object Oriented environment) is a type of MUD that gives users theopportunity to experience virtual worlds as players of a game or explorers of atheme or course. An essential difference between MOOs and MUDs is that MOOsmake use of multimedia, whereas MUDs are primarily text based. Additionally,MOOs developed into social spaces, lending themselves more readily for use as avirtual classroom or as spaces for conferences and meetings (Center forTeaching Enhancement Workshop on Synchronous Communication, 1997). For example, Tapped In is a COP that supports theimplementation of MOOs in classroom contexts. To see an example of how MUDs and MOOs are used in the classroom, go to http://ti2data.sri.com/info/teachers/mare.html.
Theprofile of the online learner population is changing from one that is older,mostly employed, place bound, goal oriented, and intrinsically motivated, toone that is diverse, dynamic, tentative, younger, and responsive to rapidtechnological changes. This change in profile poses considerable pedagogical challenges that canbe addressed through a better understanding of the emerging online learner. Theemerging online learner can be described as someone who has a strong academicself-concept; is competent in the use of online learning technologies,particularly communication and collaborative technologies; understands, values,and engages in social interaction and collaborative learning; possesses strong interpersonaland communication skills; and is self-directed.
In order to supportand promote these characteristics and skills more effectively, the online course developer,instructor, or teacher should focus on designing online learning environmentsthat support exploratory and dialogical learning. Exploratory and dialogicallearning environments engage learners in online learning activities thatrequire collaboration, communication, social interaction, reflection,evaluation, and self-directed learning. As the characteristics and skills of theonline learner population continue to emerge across generations and futuretechnologies, more immersive pedagogical models will develop, transforming thedesign of online learning environments.
Allen, I.E., & Seaman, J. (2006, November). Making thegrade: Online education in the United States. Sloan Consortium and BabsonSurvey Research Group. Retrieved http://www.sloan-c.org/publications/survey/index.asp
Anderson, T.D., & Garrison, D.R. (1998). Learning in anetworked world: New roles and responsibilities. In C.C. Gibson (Ed.), Distancelearners in higher education (pp. 97-112). Madison, WI: AtwoodPublishing.
Bernt, F.L., & Bugbee, A.C. (1993). Study practices andattitudes related to academic success in a distance learning programme. DistanceEducation, 14(1), 97-112.
Biner, P.M., Bink, M.L., Huffman, M.L., & Dean, R.S.(1995). Personality characteristics differentiating and predicting theachievement of televised-course students and traditional-course students. TheAmerican Journal of Distance Education, 9(2), 46-60.
Brown, J.S. (2000). Growing up digital: How the Web changeswork, education, and the ways people learn. Retrieved July 27, 2007, from http://www.usdla.org/html/journal/FEB02_Issue/article01.html
Cheurprakobkit, S., Hale, D.F., & Olson, J.N. (2002).Technicians’ perceptions about Web-based courses: The University of Texassystem experience. The American Journal of Distance Education, 16(4),245-258.
Comeaux, P., Huber, R., Kasprzak, J., & Nixon, M.A.(1998). Collaborative learning in Web-based instruction. Paper presented at the3rd WebNet 98 World Conference on the WWW, Internet, and Intranet, Orlando, FL.
Dabbagh, N., & Bannan-Ritland, B. (2005). Onlinelearning: Concepts, strategies, and application. Upper Saddle River, NJ:Prentice Hall.
Dille, B., & Mezack, M. (1991). Identifying predictorsof high risk among community college telecourse students. The AmericanJournal of Distance Education, 2(1), 25-37.
Dodge, B. (n.d.). What is a WebQuest? Retrieved July 27, 2007, from the WebQuest home page: http://webquest.org
Fjortoff, N.F. (1995, October). Predicting persistence in distancelearning programs. Paper presented at the Mid-Western Educational Research Meeting, Chicago. (ERIC Document Reproduction Service No. ED 387 620).
Galusha, J. M. (1997). Barriers to learning in distanceeducation. Interpersonal Computing and Technology, 5(3-4), 6-14.
Garland, M. R. (1993). Student perceptions of thesituational, institutional, dispositional, and epistemological barriers topersistence. Distance Education, 14(2), 181-198.
Hall,B. (1997). Web-based training cookbook. New York: John Wiley & Sons,Inc.
Hanson, D., Maushak, N. J., Schlosser, C. A., Anderson, M.L., Sorensen, C., & Simonson, M. (1997). Distance Education: Review ofthe Literature (2nd ed.). Bloomington, Indiana: Association for Educational Communications and Technology.
Khan, B.H. (2001). A framework for Web-based training. InB.H. Khan (Ed.), Web-based training ( pp. 75-97). Englewood Cliffs, NJ:Educational Technology Publications.
Lambert, M.P. (2000). The home study inheritance. In M.G.Moore & N. Shin (Eds.), Speaking personally about distance educationfoundations of contemporary practice (pp. 7-11). University Park, PA: TheAmerican Center for the Study of Distance Education at The Pennsylvania StateUniversity.
Laube, M.R. (1992). Academic and social integrationvariables and secondary student persistence in distance education. Researchin Distance Education, 4(1), 2-5.
Lindblom-Ylanne, S., & Pihlajamaki, H. (2003). Can acollaborative network environment enhance essay-writing processes? BritishJournal of Educational Technology, 34(1), 17-30.
MacKeracher, D. (1996). Making sense of adult learning.Toronto: Culture Concepts.
Olgren,C.H. (1998). Improving learning outcomes: The effects of learning strategiesand motivation. In C.C. Gibson (Ed.), Distance learners in higher education (pp. 77-96). Madison, WI: Atwood Publishing.
Powell,G.C. (2000). Are you ready for WBT? (Paper No. 39). Retrieved July 27, 2007, from the Instructional Technology Forum Web site: http://it.coe.uga.edu/itforum/paper39/paper39.html
Pugliese, R.R. (1994). Telecourse persistence andpsychological variables. The American Journal of Distance Education, 8(3), 22-39.
Spector, J. M. (1999, February-March). Teachers as designers ofcollaborative distance learning. Paper presented at the 10th annual meeting of the Society for Information Technology & Teacher Education International Conference, San Antonio, TX. (ERIC Document Reproduction Service No. ED432 259)
Stone, T. E. (1992). A new look at the role of locus ofcontrol in completion rates in distance education. Research in DistanceEducation, 4(2), 6-9.
Thompson, M.M. (1998). Distance learners in highereducation. In C.C. Gibson (Ed.), Distance learners in higher education (pp.9-24). Madison, WI: Atwood Publishing.
Wenger, E.C., & Snyder, W.M. (2000,January-February). Communities ofpractice: The organizational frontier. Harvard Business Review, 139-145.
Williams,P.E. (2003). Roles and competencies of distance education programs in highereducation institutions. The American Journal of Distance Education, 17(1), 45-57.
College of Education and Human Development
George Mason University
3,547 total views, 4 views today