Online genderpresentation
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This study examined differences in communication patterns between men and women in four online graduate courses. Posts were coded using Henri's and Gunawardena's classification systems. Results found that while there were no differences in overall participation or social communication, men posted more about exploring inconsistencies while women posted more corroborating examples. No differences were found in use of linguistic intensifiers or qualifiers. The implications are that instructional designers should mix genders in small groups and be aware that men may express more need to explore inconsistencies while women offer more support. More research is still needed to fully understand gender differences in online communication.
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Online genderpresentation
- 1. Communication By Gender in Online Courses Embracing Innovation, Encouraging Excellence Conference By Linda Loring, Ph.D
- 2. Summary This study examined language use (linguistic qualifiers and intensifiers), communication of beliefs (classification of postings), and patterns of communication (interaction) in four online graduate courses to determine whether differences in patterns of communication existed between men and women. These three elements are the major aspects of the “dimensions of discourse” (Mazur, 2004, p. 1074). These patterns of communication, or types of interactions, are related to the quality of learning as communication of beliefs is a major indication of cognition (Mazur, 2004).
- 3. Relation to Learning Computer-Mediated Communication (CMC) Online Learning and Collaborative Learning Theory Gender Differences Evidenced in CMC Use of Content Analysis when Studying Learning Online
- 4. Model of Communication for CMC (Simonson et al., 2003, p. 87)
- 5. Online Learning and Collaborative Learning Theory Interaction of peer group and individual Aspects Emotional support Shared outcomes via social discourse Collaborative Process
- 6. Gender Differences Evidenced in CMC Communication differs between genders and self-regulated differently Studies on gender differences in communication
- 7. Use of Content Analysis Many online studies use Content Analysis (CA) Used to help understand online learning Many classification systems available Most widely used are Henri and Gunawardena
- 8. Process for Content Analysis An individual originates a communication. Another individual then views it. A researcher questions some of its aspects and develops criteria for coding the parts of the communication. Researchers code the communication. They compile the codes, and then analyze the data collected
- 9. My Research Questions Are there difference between the types of communication patterns in the posts of men and women in the online course room? Is there a difference in terminology used in online courses between men and women?
- 10. Methodology Postings were coded using both Henri’s classification (Henri, 1992) and Gunawardena’s classification (Gunawardena et al., 1997) system The unit of meaning was coded for Henri, and for Gunawardena the entire message was coded. A text analysis identified linguistic intensifiers and qualifiers
- 11. Population/Statistics Mid-west University, graduate program More Females in the classes than males Mann-Whitney Tests
- 12. Coding Classification Henri’s Classification System Gunawardena’s Classification System Discussion Forums from graduate online courses were coded according to two classification systems that have had relatively extensive use:
- 13. Henri’s Classification System Participation: Compiling statistics on quantity of messages Social: Communication not related to course content Interaction: Clear connections to other messages Cognitive: Knowledge and learning skills Metacognitive: Personal regulation of learning
- 14. Henri: Social Definition: Communication not related to course content Explanation: “Statement or part of statement not related to formal content of subject matter” * Example: “Self-introduction; Verbal support; 'I'm feeling great.......!'”* “I teach at …”
- 15. Henri: Interaction Definition: Clear connections to other messages “Direct response; direct commentary; indirect response; indirect commentary”*** Explanation: “Continuing a thread; Quoting from others’ messages; Referring explicitly to others’ messages; Asking questions; complimenting, expressing appreciation, or agreement
- 16. Henri: Cognitive Definition: knowledge and learning skills Explanation: “Statements exhibiting knowledge and skills relating to learning processes”** Example: “Asking questions; Making inferences; Formulating hypotheses” **
- 17. Henri: Metacognitive Definition: Personal regulation of learning Explanation: “Statement or part of statement not related to formal content of subject matter” ** Example: “Commenting on own manner of accomplishing a task;” “Being aware of the emotional context of task completion.” **
- 18. Gunawardena’s Classification System Sharing/Comparing of information Discovery and exploration of dissonance or inconsistency among ideas, concepts or statements Negotiation of meaning /Co-construction of knowledge Testing and modification of proposed synthesis or co-construction Agreement statements; Applications of newly constructed meaning
- 19. Gunawardena’s Sharing/Comparing of information A statement of observation or opinion A statement of agreement from one or more other participants Corroborating examples provided by one or more participants Asking and answering questions to clarify details of statements Definition, description, or identification of a problem
- 20. Gunawardena’s Discovery and exploration of dissonance Identifying and stating areas of disagreement Asking and answering questions to clarify the source and extent of disagreement Restating the participant’s position, and possibly advancing arguments or considerations in its support by references to the participant’s experience, literature, formal data collected, or proposal of relevant metaphor or analogy to illustrate point of view
- 21. Gunawardena’s Negotiation of meaning Negotiation or clarification of the meaning of terms Negotiation of the relative weight to be assigned to types of argument Identification of areas of agreement or overlap among conflicting concepts Proposal and negotiation of new statements embodying compromise co-construction Proposal of integrating or accommodating metaphors or analogies
- 22. Gunawardena’s Testing Testing the proposed synthesis against “received fact” as shared by the participants and or their culture Testing against existing cognitive schema Testing against personal experience Testing against formal data collected Testing against contradictory testimony in the literature
- 23. Gunawardena’s Agreement statements Summarization of agreement(s) Application of new knowledge Metacognitive statements by the participants illustrating their understanding that their knowledge or ways of thinking (cognitive schema) have changed as a result of the conference interaction
- 24. Combination Henri’s and Gunawardena’s classification systems are the most-widely replicated and/or adapted when studying online courses. Gunawardena’s and Henri’s classification system compliment each other. The social aspects some scholars found lacking in Henri’s classification are addressed in Gunawardena’s system.
- 25. Terminology Is there a difference in the use of linguistic intensifiers, such as very, only, every, never, or always in online courses between men and women? Is there a difference in the use of linguistic qualifiers, such as but, if, may, I think, often, probably, or though in online courses between men and women.
- 26. Results from Henri’s Classification No difference quantity of messages posted by men and women No difference between the amount of social communication posted not related to the course content posted by men or women. No difference between the numbers of interactions posted by men or women. No significant difference between the quantity of metacognitive postings made by men and women.
- 27. Implications from Henri’s Data Generally an instructional designer does not need to make special accommodations when both men and women are involved in computer- mediated communication
- 28. Results from Gunawardena’s Classification Generally there was no difference between the quantity of posts indicating sharing and comparing of information made by males and females. However, there is one aspect of Gunawardena’s Phase I classification that is labeled corroboration. Data from this study indicated females wrote significantly more corroborating postings than did males Data from this study demonstrated that males posted a statistically significant higher number of postings related to the discovery and exploration of dissonance and inconsistencies between ideas, concepts, and statements Not enough postings were coded to the last three classification phases. Lack of postings at these levels is also consistent with other research studies
- 29. Implications from Gunawardena’s Data Men express more of a need to explore inconsistencies. Do they fit? “Do you see any inconsistencies between ‘a’ and ‘b’?” Women offer more corroborating examples Need listing brainstorming Support for proposals Mix males and females in Small Groups if at all possible
- 30. Results from Study of Terminology The data from this study demonstrated there was no difference in the use of linguistic intensifiers (very, only) or linguistic qualifiers (“I think,” “probably”) by men and women.
- 31. Implications of Textual Analysis on Terminology Findings from this study are in direct contradiction to studies by Fahy (2002a, b), Fahy and Ally (2001), Lawlor (2006), and Guiller and Durndell (Guiller & Durndell, 2007). However, the data from this study is consistent with the findings by Graddy (Graddy, 2006) and Palomares (2004). In this study, as also in Graddy’s study (2006), there was no male crowding out because the preponderance of the sample was females. Unfortunately, conflicting results from replication of this part of the study point out the necessity for studies to be larger, more comprehensive, and include multiple disciplines
- 32. Ramifications Relatively large number of postings. Significant findings were found in two patterns of communication. The fact that no significant difference were found in terminology is very controversial. Design certain populations Questioning Techniques
- 33. Conclusion “We look forward to further application of these and other such protocols to provide researchers and online instructors with improved analysis tools and data that ultimately will have a positive impact on our abilities to design and implement effective online learning experiences.” (Marra et al., 2004, p. 39).
- 34. How can IWU use this Information? Mixing Groups male and female Possibility of using content analysis to discover other facets of learning online
- 35. References for Presentation Fahy, P. J. (2002a). Epistolary and expository interaction patterns in a computer conference transcript. The Journal of Distance Education, 17(1). Fahy, P. J. (2002b). Use of linguistic qualifiers and intensifiers in a computer conference. The American Journal of Distance Education, 16(1), 5- 22. Retrieved October 30, 2004 from http://cde.athabascau.ca/showcase/ajde.doc Fahy, P. J., Crawford, G., & Ally, M. (2001). Patterns of interaction in a computer conference transcript. International Review of Research in Open and Distance Learning, 2(1). Retrieved October 15, 2004 from http://www.irrodl.org/content/v2.1/fahy.html) Graddy, D. B. (2006). Gender salience and the use of linguistic qualifiers and intensifiers in online course discussions [Electronic version]. American Journal of Distance Education, 20(4), 211-229.
- 36. References (cont) Gregory, M. Y. (1997). Gender differences: An examination of computer mediated communication. Paper presented at the Annual Meeting of the Southern States Communication Association, Savanah, GA (ERIC Document Reproduction Service No. ED 410 604). Guiller, J., & Durndell, A. (2007). Students’ linguistic behaviour in online discussion groups: Does gender matter? [electronic version]. Computers in Human Behavior, 23(5), 2240-2255. Gunawardena, C. N., Lowe, C. A., & Anderson, T. (1997). Analysis of a global online debate and the development of an interaction analysis model for examining social construction of knowledge in computer conferencing [Electronic version]. Journal of Educational Computing Research, 17(4), 397-431.
- 37. References (cont) Henri, F. (1992). Computer conferencing and content analysis. In A. R. Kaye (Ed.), Collaborative learning through computer conferencing (pp. 117-136.). London: Springer-Verlag. Herring, S. C. (2000). Gender differences in CMC: Findings and implications. CPSR Newsletter, 18(1). Retrieved July 25, 2006 from http://www.cpsr.org/issues/womenintech/herring/view?searchterm=Herring) Herring, S. C. (2003). Gender and power in online communication. In M. Meyerhoff (Ed.), The handbook of language and gender (pp. 202 228). Oxford: Blackwell. Lawlor, C. (2006). Gendered interactions in computer-mediated computer conferencing [electronic version]. The Journal of Distance Education, 21(2), 26-43.
- 38. References (cont) Marra, R. M., Moore, J., & Klimczak, A. (2004). Content analysis of online discussion forums: A comparative analysis of protocols [Electronic version]. Educational Technology Research & Development, 52(2), 23-40. Mazur, J. M. (2004). Conversation analysis for educational technologists: Theoretical and methodological issues for researching the structures, proecesses and meaning of on-line talk. In D. H. Johassen (Ed.), Handbook for research in educational communications and technology (2nd ed., pp. 1073-1098). Mahwah, NJ: Lawrence Erlbaum Associates. Palomares, N. A. (2004). Gender schematicity,gender identity salience, and gender linked language use [Electronic version]. Human Communication Research, 30(4), 556-588.
- 39. References (cont) Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2003). Teaching and earning at a distance: Foundations of distance education. Upper Saddle, NJ: Merrill Prentice Hall.
Editor's Notes
- Communication is the “quintessential way in which humans make meaningful connections with each other, whether as caring, sharing, loving, teaching, or learning” (G. Gay, 2000, p. 80). Patterns of communication, or types of interaction, are related to the quality of learning (Cavanaugh, 2001; Kawachi, 2006). Content analysis is a way of “gathering evidence of the learning process” (Anderson, 2004a, p. 7). Understanding differences in communication in an audience may help increase learning in the online class or help to sequence communication when designing the course. Communicating is an integral part of the learning process. Studying patterns of communication can increase the level of understanding of peer interaction (Garrison, 2000; LaPointe & Gunawardena, 2004).
- Communication. the “transfer of information (message) from a transmitter (source) to a receiver in the form of a signal, which is sometimes modified by disturbance (‘noise’) in the transmission system itself” (Riva & Galimberti, 2003, p. 28). Gudykunst (1991) says it is effective “to the extent that we are able to minimize misunderstanding” (p. 24). It is also defined as “the transactional, multifunctional and multimodal processes of social interaction by which meaning is negotiated between people” (Thurlow, Lengel, & Tomic, 2004, p. 246). Computer-mediated communications. Berge and Collins have defined computer-mediated communication as “the ways in which telecommunications technologies have merged with computers and computer networks to give us new tools to support teaching and learning" (Brush & Uden, 2000, CMC via Internet, para 1). Purdy presents a visual picture. CMC refers to “electronic communication by which senders write text messages on their computers that are relayed to receivers' computers and are viewable on a screen” (Purdy, 2000, p. 166). Romiszowski and Mason add the user-dimension to their definition (Romiszowski & Mason, 2004).
- A learning theory describes how learning occurs (Reigeluth, 1999). The development of Web-based training (WBT) frequently employs collaborative learning, which includes the importance of active engagement (Hedberg, 2003; S. D. Johnson & Aragon, 2003; Lai, 1997; McIsaac, Blocher, Mahes, & Vrasidas, 1999; M. G. Moore, 2002; Rafaeli & Sudweeks, 1997; Saunders, 2001). For WBT one must consider the importance of adult goals (Kerka, 2001) and the fact that self-directed learning is important to adults (Abdullah, 2001). Collaborative learning is based on Vygotsky’s definition of zone of proximal development (ZPD) Collaborative learning depends on interaction between the peer group and the individual. Important aspects of collaboration are provision of emotional support (O'Regan, 2003) and construction of shared outcomes via social discourse (Moallem, 2003). Discussion as a way of teaching has long been recognized as an appropriate pedagogical approach (Brookfield & Preskill, 1999) which enhances student learning and can easily be accommodated online (Bender, 2003). Scholars claim the success of online courses depends on interaction and active discussion (Swan, Shea, Fredericksen, Pickett, & Pelz, 2000). During the collaborative process, ideas are shared, generating even more ideas, resulting in a synergetic effect that individuals would not have been able to attain individually. The process raises the level of potential development of the individuals because of collaboration with peers and the facilitator, becoming another example of the zone of proximal development.
- Not only is communication of meaning influenced by multiple factors (Brush & Uden, 2000), communication differs between genders as well and even appears to be self-regulated differently (Bidjerano, 2005). Savicki and Kelley (2000) reviewed four major studies on group gender composition. Typically, women send more “I” messages and are more self-disclosing. Men tend to disregard the socio-emotional aspects of group functioning, take a more monologue approach, and even include mild flaming in their discourse online. Mixed groups did not exhibit the same extremes (Savicki & Kelley, 2000). Differences were found between genders in different studies, and there also appears to be a technological imbalance between the genders (Broos, 2005; Gunn, McSporran, MacLeod, & French, 2003; Herring, 1996, 2000; Joiner et al., 2005; Sherman et al., 2000), even a hidden agenda to attract males to technological games and educational experiences (Heemskerk, Brink, Volman, & ten Dam, 2005, pp. 2-3). Some studies have found gender differences have influenced online learning (Gunawardena et al., 2001), and one study found that females appreciated the online learning environment more than males (Sullivan, 2001). Gender differences have been found in communication styles online (Gougeon, 1998). Fahy determined that females use more qualifiers to sustain conversation such as “I,” “you,” “never,” “very,” “but,” “if,” “may,” and “might” (Fahy, 2002).
- Content Analysis. Krippendorf has updated his text of a quarter century earlier and now defines content analysis (CA) as a “research technique for making replicable and valid inferences from texts (or other meaningful matter) to the contexts of their use” (Krippendorff, 2004, p. 18). This definition “focuses attention on the process of content analysis and does not ignore the contributions that analysts make to what counts as content” (Krippendorff, 2004, p. 21). After analyzing definitions from scholars over a fifty-year period, Neuendorf adds some of the methodology necessary to conduct CA to her definition: Content analysis is a summarizing, quantitative analysis of messages that relies on the scientific method (including attention to objectivity, intersubjectivity, a priori design, reliability, validity, generizability, replicability, and hypothesis testing) and is not limited to the types of variables that may be measured or the context in which the messages are created or presented. (Neuendorf, 2002, p. 10)
- Coding. “involves critically analyzing the data and identifying themes and topics which represent categories into which numerous pieces of data can be classified” (L. R. Gay, 1996, p. 245). It is done either manually with pen and pencil or on the computer (Bauer, 2000). Miles and Huberman explain it this way: Codes are tags or labels for assigning units of meaning to the descriptive or inferential information compiled during a study. Codes usually are attached to ‘chunks’ of varying size—words, phrases, sentences, or whole paragraphs, connected or unconnected to a specific setting. They can take the form of a straightforward category label or a more complex one (e.g., a metaphor). (Miles & Huberman, 1994, p. 56)
- TestsThese are non-parametric t-tests, which compare medians rather than means to search for statistically significant differences. Calculating whether significant differences exist is only the first step, but tells researchers nothing about size of a potential significant difference. For this reason, the size effect (r) value will be calculated from the results either of the t-tests, or of the Mann Whitney test to report the size of any potential significant differences.
- In 1992 Francis Henri developed a five pronged classification system to identify the learning taking place during a computer conference defined as an educational session taking place over the computer (Henri, 1992). In a compilation of research studies using content analysis, Loring found that 11 used some of Henri’s model for at least one coding exercise (Clulow & Brace-Govan, 2001; Gunawardena, Lowe, & Anderson, 1997; Hara, Bonk, & Angeli, 1998; Lally, 2000; Lally & de Laat, 2002b; McDonald, 1998; McKenzie & Murphy, 2000; Monteith, 2002; D. R. Newman, Webb, & Cochrane, 1995; Pena-Shaff & Nicholls, 2004; Prammanee, 2003) In addition, Spatariu, Hartley, and Bendixen (2004) consider Henri to be the lead content analysis classification system for online learning. Garrison aptly summarizes Henri’s contribution to the field: Perhaps Henri’s real contribution is that it is a collaborative view of teaching and learning and provides a potential structure for coding CMC messages to study the nature and quality of the discourse. Henri’s framework is a psychosocial, transactional perspective focusing specifically on teaching and learning facilitated through mediated communication. (Garrison, 2000, p. 10) Stacey and Gerbic note that Henri’s framework has been modified by many researchers who have worked to refine it to fit the purpose of their research. Henri’s framework has been highly influential, possibly because it is so comprehensive, and covers many of the basic facets of CMC. It has been used in its entirety, adapted and through its critique, has provided a springboard for new kinds of content analysis approaches. (Stacey & Gerbic, 2003, p. 499)
- Cognitive Critical thinking Elementary clarification In depth clarification Inference Judgment Strategy Information processing Surface Repetition without adding new information; statement without justification; suggesting a solution without explanation.”*** In depth “Brings in new information, shows links, solutions proposed with analysis of possible consequences; evidence of justification; presents a wider view.”*** “Observing or studying a problem, identifying its elements and observing their linkages in order to come to a basic understanding Analyzing and understanding a problem to come to an understanding which sheds light on the values, beliefs, and assumptions which underlie the statement of the problem Induction and deduction, admitting or proposing an idea on the basis of its link with propositions already admitted as true. Making decisions, statements, appreciations, evaluations, and criticisms; Sizing up. Proposing co-ordinated actions for the application of a solution, or following through on a choice or decision.” (H, p. 129)
- Knowledge “Comparing self to others as a cognitive being, e.g., student perspective vs. teacher perspective.Showing an awareness of one's approach to a cognitive task, eg, preparing a lecture.Comment on strategies used to reach an objective and assess progress, eg, I find do X when trying to ....'”*** Skills “Question about value of one's ideas or way of going about a task, eg, 'I do not have a good understanding of ....' Evidence of organising steps needed and prediction of what is likely to happen. Evidence of implementing a strategy and assessing progress: e.g., 'I know I feel .....' / 'I found learning about ... interesting' “ *** Knowledge and skills Rourke, Anderson, Garrison, and Archer (2001, Table 1, Interactive, indicators), **Lally (2000, Table 1), and *** McKenzie and Murphy (2000, Tables 1 & 2)
- Gunwardena, Lowe, and Anderson’s (1997) classification system is an “interaction analysis model for examining social construction of knowledge in computer conferencing (p. 412). After Gunawardena and her colleagues developed their own classification system to analyze online learning, seven other studies used that classification system (Aviv, Erlich, Ravid, & Geva, 2003; de Laat, 2002; Kanuka & Anderson, 1998; Lally, 2000; McLoughlin & Luca, 1999, 2000a; Stansberry, Haulmark, & Sheeran, 2003). Because of the number of studies replicating both Henri and Gunawardena’s classifications, it is important to examine their systems
- (Flynn & Polin, 2003; Gunawardena et al., 1997; Ingram & Hathorn, 2004) Trevelean states (of Gunawardena): This model was designed to help answer two evaluation questions: namely, was knowledge constructed within the group by means of the exchanges among participants? And second, did individual participants change their understanding or create new personal constructions of knowledge as a result of interaction within the group? … Their model outlines five phases in the co-construction of new knowledge within which different types of cognitive activity (such as, questioning, clarifying, negotiating and synthesizing) takes place….their approach to investigating knowledge creation and sharing online may well be worth building on. (Treleaven, 2004, p. 170)
- A text analysis program that performs word counts can identify differences in terminology used in communication dependent upon learner gender (Fahy, 2002b; Fahy, Crawford, & Ally, 2001). Text analysis is a more specific subcategory of content analysis that focuses on “written or transcribed words” (Neuendorf, 2002, p. 25).
- Data from the study indicated that there is no statistically significant difference between the quantity of messages posted by men and women in these online courses. There is no significant difference between the amount of social communication posted not related to the course content posted by men or women. There is no significant difference between the numbers of interactions posted by men or women. There is no significant difference between the quantity of metacognitive postings made by men and women.
- This is helpful information for instructional designers and online educators. The data indicates that generally an instructional designer does not need to make special accommodations when both men and women are involved in computer-mediated communication. A decade ago when online learning became popular, studies showed that women did not enjoy using computers and disliked many aspects of conversation online (for example see Gregory, 1997; Herring, 2000, 2003). The data from this study indicates a reversal of this trend.
- (women) Examples of these types of postings include such things as, “In my classroom,” “At my school,” and “For example.” This suggests that women are supportive. They appreciated making connections, and they enjoyed collaboration. This significant finding is supported by the data from a study by Gougeon that concluded women needed connectedness (Gougeon, 1998). This significant finding from this study indicating women post more corroborating examples also supports the result from Guiller and Durndell (2006) that women approach the communication online from a more positive, supportive framework. Results from this study also offer confirmation of the conclusion from a meta-analysis of fifty research studies that observed, “females had a significantly higher frequency of collaborative instances using CMC than men (mean ES=-.09). That is, women’ communication tends to be more collaboratively oriented” (Li, n.d., para 1). The study by Guiller and Durndell (2006) concluded men were more likely than women to express disagreement. Results of the data from this study support Guiller and Durndell’s conclusion.. The need for men to explore dissonance and inconsistencies might be related to the conclusion by Gourgeon (1998) that indicated communication by men in an online situation needed status. One way to obtain status for men could be to find inconsistencies in various theories and proposals.
- The findings from this study are very encouraging. Men express more of a need to explore inconsistencies. They need to find out if things really fit together and what are the possibilities they do not fit together. This information is very important for instructional designers and facilitators of online courses, for if groups that are predominately or all male, providing methodologies to explore situations that might not be consistent would be an excellent approach to the learning content. An ideal query for facilitators to use when questioning males would be “Do you see any inconsistencies between ‘a’ and ‘b’?” It also appears, based on the data from this study, that either the instructional designer, or the facilitator of the course, place males and females as evenly as possible in the different collaborative work assignments within the online course.
- This study has contributed to the evaluation of online classification systems by taking two highly respected classification systems and classifying course content from a relatively large number of postings. Attempting to identify where patterns of communication differ in online communication aids both the instructional designer in designing course room content for specific populations and assists online facilitators by helping them develop questioning techniques that will help types of learners excel in the online community. Significant findings were found in two patterns of communication. The fact that no significant difference were found in terminology is very controversial.