Online genderpresentation

Communication By Gender in Online Courses

Embracing Innovation, Encouraging Excellence Conference

By Linda Loring, Ph.D

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).

Relation to LearningComputer-Mediated Communication

(CMC)Online Learning and Collaborative

Learning TheoryGender Differences Evidenced in

CMCUse of Content Analysis when

Studying Learning Online

Model of Communication for CMC (Simonson et al., 2003, p. 87)

Online Learning and Collaborative Learning TheoryInteraction of peer group and

individualAspects

Emotional supportShared outcomes via social

discourseCollaborative Process

Gender Differences Evidenced in CMC

Communication differs between genders and self-regulated differently

Studies on gender differences in communication

Use of Content AnalysisMany online studies use Content

Analysis (CA)Used to help understand online

learningMany classification systems

availableMost widely used are Henri and

Gunawardena

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

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?

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

Population/Statistics

Mid-west University, graduate program

More Females in the classes than males

Mann-Whitney Tests

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:

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

Henri: SocialDefinition: Communication not

related to course contentExplanation: “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 …”

Henri: InteractionDefinition: 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

Henri: CognitiveDefinition: knowledge and learning

skillsExplanation: “Statements exhibiting

knowledge and skills relating to learning processes”**

Example: “Asking questions; Making inferences; Formulating hypotheses” **

Henri: MetacognitiveDefinition: 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.” **

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

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

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

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

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

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

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.

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.

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.

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

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

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 examplesNeed listing brainstorming

Support for proposals

Mix males and females in Small Groups if at all possible

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.

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

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

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).

How can IWU use this Information?

Mixing Groups male and female Possibility of using content analysis

to discover other facets of learning online

References for Presentation

Fahy, P. J. (2002a). Epistolary and expository interaction patterns in acomputer 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 inOpen 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 andintensifiers in online course discussions [Electronic version].American Journal of Distance Education, 20(4), 211-229.

References (cont)

Gregory, M. Y. (1997). Gender differences: An examination of computermediated communication. Paper presented at the Annual Meeting ofthe Southern States Communication Association, Savanah, GA(ERIC Document Reproduction Service No. ED 410 604).

Guiller, J., & Durndell, A. (2007). Students’ linguistic behaviour in onlinediscussion 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 globalonline debate and the development of an interaction analysis modelfor examining social construction of knowledge in computerconferencing [Electronic version]. Journal of Educational ComputingResearch, 17(4), 397-431.

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. 202228). Oxford: Blackwell.

Lawlor, C. (2006). Gendered interactions in computer-mediated computerconferencing [electronic version]. The Journal of Distance Education,21(2), 26-43.

References (cont)

Marra, R. M., Moore, J., & Klimczak, A. (2004). Content analysis of onlinediscussion forums: A comparative analysis of protocols [Electronicversion]. Educational Technology Research & Development, 52(2),23-40.

Mazur, J. M. (2004). Conversation analysis for educational technologists: Theoretical and methodological issues for researching thestructures, proecesses and meaning of on-line talk. In D. H.Johassen (Ed.), Handbook for research in educationalcommunications and technology (2nd ed., pp. 1073-1098). Mahwah,NJ: Lawrence Erlbaum Associates.

Palomares, N. A. (2004). Gender schematicity,gender identity salience, andgender linked language use [Electronic version]. HumanCommunication Research, 30(4), 556-588.

References (cont)

Simonson, M., Smaldino, S., Albright, M., & Zvacek, S. (2003). Teaching and earning at a distance: Foundations of distance education. UpperSaddle, NJ: Merrill Prentice Hall.