Introduce Topic – Collaborative Online Learning for High School Shot video of myself introducing the topic Hello and welcome to the National Secondary Education Technology Conference. My name is David Harms and it is my pleasure to introduce today’s featured speaker, Dr. Keith Pratt.Today, Dr. Pratt is going to talk about Collaborative Online Learning in Secondary Education.
Introduce Dr. Pratt Key Points of his background on bulleted list with pictures

 

Pratt spent 22 years in the Air Force as a computer systems engineer. Now he is a highly sought after distance learning consultant (Crossroads Consulting Group, 2006b).

 

  Show pictures of his books while reading credentials

 

Dr. Pratt wrote Building Learning Communities in Cyberspace, The Virtual Student, Building Online Learning Communities, and Collaborating Online which discusses Piaget and constructivism (Crossroads Consulting Group, 2006a).
  Still picture of Dr. Pratt

 

Crossroads Consulting Group (2006b).
Pedagogy supporting collaboration Picture of Piaget http://webspace.ship.edu/cgboer/genpsypiaget.html
Definition of constructivism

 

Piaget (1969) as quoted in Palloff and Pratt (2005) defined constructivism as the theory that believes humans learn from their experiences which they use to construct meaning (p. 6).
Quote from Pratt on link between collaboration and constructivism – Ken Burns’ effect on book quote comes from Palloff and Pratt (2005) explained that collaboration is a method of instruction that helps students achieve constructivist learning (p. 6).

 

Secondary Online Education Description of increase in secondary online

Video of my classroom (empty) panning to computers in back

education and lack of research specifically studying secondary students -video of journal

Huett, Moller, Foshay, and Coleman (2008) reported enrollment in high school online courses has increased (p. 63). Although there are many online high school courses, most of the literature focuses on online posts secondary collaboration (p. 65).
Best Collaborative Practices Bulleted list from Pratt’s books Palloff and Pratt (2005) recommended the following collaborative activities, “role playing (p. 57)”, “simulations (p. 60)”, “case studies (p. 63)”, “questioning techniques for collaborative discussions (p. 69)”, “dyads (p. 73)”, “small-group projects (p. 77)”, “jigsaw activities (p. 79)”, “blogs (p. 81)”, “virtual teams (p. 83)”, “debates (p. 85)”, “fishbowls (p. 87)”, “learning cycles (89)”, and “webquests (p. 93)”.
Current Literature Discussion Male v female groups (Video of a boy and a girl)

In his presentation, Pratt will be addressing current research in collaborative online learning for secondary education.

Ding (2009) discovered that mixed sex groups completed online work best, but reported that female participation was overshadowed by the males (p. 517).

  New software aids – Shared Space (SS) (Study from Netherlands – map showing location)

Janssen, Erkins, and Kanselaar (2007) tested the effect a new visual tool called shared space had on collaborative learning (p. 1105) and found that shared space only increased group performance in the early stages of online collaboration (p. 1122).
  Impact of familiarity on online collaboration (Video of two people shaking hands to show familiarity)

Jahnke (2010) found that student relationships with each other and their instructor were identified as important in online learning (pp. 29-30), and transferred into stronger face to face relationships upon course completion (p. 34).
  Off task behavior and solutions (Video of someone on Facebook or playing video game)

Marttunen and Laurinen (2009) discovered that students were on task 96.3% in face to face debates, but only 68.9% in online debates (p. 966).
  Map http://www.malaysiatravel.infoguidance.net/malaysia1500001.jpg
  Calendar Picture http://meds.queensu.ca/assets/calendar.jpg
  Self regulated strategies (study from Malaysia – map showing where it is) Vighnarajah, Wong, and Bakar (2009), Malaysian researchers, investigated student perceptions of self regulation in online courses (p. 98) and concluded that self regulating strategies are essential to online learning success (p. 103).
Problems and Solutions Lack of instant feedback (video of someone looking at time on the phone impatiently) Barbour (2008) discovered that the lack of immediate feedback was a common problem for many online students (p. 359).
  Google Picture http://www.bing.com/images/search?q=moodle+picture&go=&form=QBIR&qs=n&sk=#focal=17da065809e3b98aa8d8b20c0c27d25e&furl=http%3A%2F%2Fwww.todmordenprimary.org.uk%2Fhomedir%2Fimages%2Fmoodle-desktop.jpg
Future of Online Collaboration List from Dr. Pratt’s PowerPoint

Video of iPad in use

Screen Capture of Second Life

Video of Skype in use

 

Pratt (2010) will also be discussing the future of online learning including new hardware such as iPads, smartphones, and new presentation technology.

Pratt (2010) hypothesized that educational use in applications such as Second life will increase in the future. He believed games and simulations will drive education away from standardized tests and quizzes.

Pratt (2010) believed that there will be a shift in education to a personalized approach that will be self paced and designed around student needs. He felt learning management systems such as MOODLE, Angel, and Blackboard will be replaced with tools such as GoogleApps.

Pratt (2010) also identified a shift in the focus of education from content to connection, conversations, and networking.

Downes (2009) as cited in Pratt (2010) identified the following four characteristics in online education; “students follow their own objectives”, “unstructured learning and discussions”, “no leader”, and “no boundaries”.

I hope you’ve enjoyed this overview of collaborative online learning for secondary students. Please join me in welcoming Dr. Pratt as he addresses the questions, “How can [online educators] prepare for the future?” and “How can we prepare our students for their future (Pratt, 2010)”.

 

 

Annotated Bibliography

Barbour, M. (2008, Winter). Secondary students’ perceptions of web-based learning. Quarterly Review of Distance Education, 9(4), 357-371. Retrieved June 4, 2009, from Education Research Complete database.

 

Barbour (2008) investigated secondary student’s perception of their online learning environments experiences (p. 357). He conducted a literature review and discovered that post-secondary online students enjoy both flexibility and collaborating with other students (p. 358). He identified that a major weakness of online education was the lack of immediate feedback from both the instructor and other students (p. 359). Barbour replicated a previous post-secondary quantitative study on 38, n=38,  secondary students enrolled in small rural Canadian high schools and discovered that students had a positive perception of their online learning experience (pp. 359-361).  Barbour concluded that the similar results between this secondary study, and the previous results in post-secondary studies needed to be further tested so that the results could be applied to future secondary online course design (p. 365).

Barbour’s (2008) sample size, n=38, was limited to 38 Canadian students who lived in English districts making generalizations to a larger population difficult. A larger sample size is recommended to increase transferability of this study to other student populations. The study was limited to small rural districts and results may not apply to other student populations. This study needs to be replicated with a proper random sample. Barbour’s study adds to the literature on online secondary education, which is often overshadowed by online post-secondary education.

Ding, N. (2009). Visualizing the sequential process of knowledge elaboration in computer-supported collaborative problem solving, Computers & Education 52(2). DOI: 10.1016/j.compedu.2008.10.009

Ding (2009) conducted a case study using six tenth grade students, three male and three female, in a five day online Dutch physics lesson (p. 513). The participants were assigned to three pairs; a mixed gender pair, a female only pair, and a male only pair. The participant pairs completed physics problems online collaboratively in 90 minutes (p. 513). Interactions between the participants were divided into three categories; productive, on task but not productive, and off task (p. 511). This categorization allowed the collaboration to be graphed for evaluation. Student pairs utilized a software platform called “Physhint (p. 511)” that was designed by the researchers. The purpose of the study was investigating how the partnerships’ collaborative online work differed by sex make up. The study found that the mixed sex group completed the greatest number of problems correctly, but the female participant’s participation was overshadowed by the males (p. 517). Another finding was that the female only partnership communicated by text as opposed to visual communication method of the male partnership (p. 518).

Ding (2009) did not disclose why the study was limited to six participants. As a case study, it is very hard to generalize findings to a larger population. Further research on this study’s findings of the differences in online collaboration between the sexes needs to be conducted before any generalizations can be used. Although diagrams and explanations describing the Physhint training software were included (pp. 511-513), information about how the software was tested to eliminate any gender bias to the study caused by Physhint should have been included. Further research building on Ding’s work will help Instructional Designers build collaborative online environments that are equable to both sexes.

Jahnke, J. (2010). Student perceptions of the impact of online discussion forum participation on learning outcomes. Journal of Learning Design, 3(2), 27-34. Retrieved from Education Research Complete database

Jahnke (2010) conducted a grounded theory study on thirty-three twelfth grade students involved in an online asynchronous class that lasted for two weeks (pp. 27-28). The online class assisted students in completing a required independent writing assignment of 4000 words included in the International Baccalaureate program at a school that provides a laptop for every student (p. 27). Jahnke identified four themes that emerged; “interactivity”, “group construction of knowledge”, “ability to `revisit recorded thinking”, and “awareness of online identity (p. 29).”

Jahnke (2010) reported students identified collaboration with both other students and instructors was one of the most beneficial aspects of the project (pp. 29-30). Students contributed ideas to each other and gained an understanding of what other students’ ideas and opinions were through online collaboration (p. 30). An essential part of creating the online community was the discussion forum which focused on achieving the common goal of successful completion of the essay (p. 31). Students reported that the online environment forced them to be cautious when posting comments because of the absence of informal communication cues (p. 32). Jahnke concluded that positive student experiences in the online class overshadowed the negative experiences they identified (p. 32). The researcher also revealed that students discovered relationships built online during the study transferred to stronger relationships in their face to face environment after the study concluded (p. 34).

Jahnke (2010) revealed that she was not only the researcher, but also the coordinator for the program. This may have inadvertently tainted the study to report positive results to protect the researcher’s position. The research relied solely on a single school that has both adopted the International Baccalaureate program and provides a laptop to each student making transferability for different populations difficult. Additionally, the qualitative design of the study does not lend to transferability to different populations. The researcher did not reveal information about the abilities of the subjects of the study. Revealing grade point averages and other relevant academic history of the subjects would help other researchers utilize the research. Jahnke dismissed the negative aspects associated with the study which should be explored so that they can be reduced in future online designs.

Janssen, J., Erkens, G., & Kanselaar, G. (2007). Visualization of agreement and discussion processes during computer-supported collaborative learning, Computers in Human Behavior, 23(3), 1105-1125. DOI: 10.1016/j.chb.2006.10.005

Janssen, Erkens, and Kanselaar (2007) conducted a quantitative study with 117 eleventh grade history students in the Netherlands (p. 1109) to test a new visual tool, Shared Space (SS), has on collaborative learning (pp. 1105). Participants were randomly assigned to groups of between two and four students in either the test group, who used chat with SS, or the control group. SS evaluates student collaboration and categorizes responses as agreement or debate (p. 1122). Results revealed SS only increased group performance in the early stage of the collaboration (p, 1122).

Janssen, Erkens, and Kanselaar (2007) relied on student groups who were familiar with each other in a face to face environment (p. 1123) and did not elaborate on the gender makeup of the groups. This study revealed that Shared Space (SS) did result in significant differences in the early stages of collaboration suggesting that further research in the proper utilization of SS is necessary.

Janssen, J., Erkens, G., Kirschner, P., & Kanselaar, G. (2009). Influence of group member familiarity on online collaborative learning, 25(1), 161-170. DOI: 10.1016/j.chb.2008.08.010

Janseen, Erkens, Kirschner, and Kanselaar (2009) conducted a quantitative study investigating the effect of familiarity on online collaboration with 105 eleventh grade students completing the same lesson used in Janssen, Erkens, and Kanselaar’s (2007) study (p. 163). Janseen, Erkens, Kirschner, and Kanselaar (2009) used students from the same face to face classes in their study to ensure familiarity (p. 163). The researchers discovered that familiarity did increase performance in online lessons however it also increased off task online communication as well (p. 167). Four hypothesis were tested relating to familiarity and online collaboration including; “group member familiarity will contribute to more critical and exploratory group norms (p. 162)”, “group member familiarity will lead to positive perceptions regarding the collaborative process (p. 162)”, “group member familiarity will influence online collaborative activities (p. 163)”, and “group member familiarity will lead to better group performance (p.163)”. Janseen, Erkens, Kirschner, and Kanselaar (2009) concluded that the first three hypothesis held but group performance in familiar groups did not improve. The researchers concluded that this was because the students engaged in social interactions online that had nothing to do with the tasks and suggested using software such as Shared Space (SS) could help keep familiar students on task.

Janseen, Erkens, Kirschner, and Kanselaar (2009) relied on data from two schools. The data did not reveal the ethnic makeup of the participants, the percentage on an Individualized Education Plan (IEP), the percentage of second language students, or their social economic status. These characteristics would allow researchers to evaluate the transferability of the results to other populations. Additionally the study was funded by the Computerized Representation of Coordination in Collaborative Learning (CRoCiCL) and the Netherland government who both have interests in positive results.

Marttunen, M. & Laurinen, L. (2009). Secondary school students’ collaboration during dyadic debates face-to-face and through computer chat. Computers in Human Behavior, 25(4), 961-969. DOI: 10.1016/j.chb.2009.04.005

Marttunen and Laurinen (2009) quantitatively investigated the collaborative interaction of 27 secondary students at a single school in Finland in both face to face and online discussions (p. 963). The researchers collected data for 24 debates. They tape recorded face to face debates and collected online debates on the computer (p. 964). Participant dialogue was separated into eight different categories based on the dialogue’s collaborative quality (p.964). The researchers found that the following three categories were more prevalent in the online environment; “the speech acts used to maintain collaborative discussion (p. 966)”, “the students responded to issues presented by their interlocutor (p. 966)”, and “students presented questions or provocative statements or asked for clarification (p. 967)”. The following three categories of interaction were more prevalent in the face to face debates; “short positive feedback (p. 967)”, “students extended their interlocutor’s thoughts (p. 967)”, and “students continued their own ideas (p. 967)”. Students in face to face debates were on task 96.3% of the time while the online debates were on task only 68.9% of the time (p. 966). The researchers believed the off task behavior during the online debates was caused by the lack of immediate feedback and difficulty of teacher monitoring inherent in the online environment. They recommended adding coaching to the online environment and increasing rewards for proper online behavior (p. 968). Marttunen and Laurinen (2009) concluded that both face to face and online debates are effective constructivist strategies however online debates require more time is required to keep students on task (p. 968).

Marttunen and Laurinen (2009) utilized data collected at a single school with a very small number of students. They revealed that only 24 students participated in both of the debates (p. 963). Student demographic data, besides sex, was not included in this study making generalizations to other populations difficult.

Vighnarajah, Wong, S., & Bakar, K. (2009). Qualitative findings of students’ perception on practice of self-regulated strategies in online community discussion, Computers & Education, 53(1), 94-103. DOI: 10.1016/j.compedu.2008.12.021

Vighnarajah, Wong, and Bakar (2009) conducted a mixed methods study of the perception of students enrolled in self paced online classes in four schools in Malaysia (p. 98). The researchers used a premade questionnaire to collect data from students who were completing a self paced science class and compared it to data collected from students enrolled in the same class taught traditionally (p.99). Additional data was acquired through random interviews performed by the researchers (p. 100). Quantitative methods were used to indicate an increase of self regulated learning strategies was found in the online student data (p. 100). The qualitative study discovered that 33 participants rated their self regulated experience positively while 17 participants rated their experience negatively (p.100). The researchers concluded that self regulating strategies are essential to online learning success and recommended that these skills be taught to struggling students (p. 103).

Vighnarajah, Wong, and Bakar (2009) had to be approved by many departments in the Malaysian government to get approval to work with the four schools (p. 98). The government has a vested interest to make elearning look good as they are using this as a platform to bring Malaysia into the developed world (pp. 94-95). The government selection of the schools may have skewed the results and may not be representative of the rest of the country, or other areas of the world.

 

 

References

Barbour, M. (2008, Winter). Secondary students’ perceptions of web-based learning. Quarterly Review of Distance Education, 9(4), 357-371. Retrieved June 4, 2009, from Education Research Complete database.

Crossroads Consulting Group (2006a). Our books. Retrieved from: http://xroadservices.com/home/books.html

Crossroads Consulting Group (2006b). About the partners. Retrieved from: http://xroadservices.com/home/partners.html

Ding, N. (2009). Visualizing the sequential process of knowledge elaboration in computer-supported collaborative problem solving, Computers & Education 52(2). DOI: 10.1016/j.compedu.2008.10.009

Huett, J., Moller, L., Foshay, W. & Coleman, C. (2008, September/October). The evolution of distance education: Implications for instructional design on the potential of the Web (Part 3: K12). TechTrends, 52(5), 63–67.

Jahnke, J. (2010). Student perceptions of the impact of online discussion forum participation on learning outcomes. Journal of Learning Design, 3(2), 27-34. Retrieved from Education Research Complete database

Janssen, J., Erkens, G., & Kanselaar, G. (2007). Visualization of agreement and discussion processes during computer-supported collaborative learning, Computers in Human Behavior, 23(3), 1105-1125. DOI: 10.1016/j.chb.2006.10.005

Janssen, J., Erkens, G., Kirschner, P., & Kanselaar, G. (2009). Influence of group member familiarity on online collaborative learning, 25(1), 161-170. DOI: 10.1016/j.chb.2008.08.010

Marttunen, M. & Laurinen, L. (2009). Secondary school students’ collaboration during dyadic debates face-to-face and through computer chat. Computers in Human Behavior, 25(4), 961-969. DOI: 10.1016/j.chb.2009.04.005

Palloff, R. M., & Pratt, K. (2007). Building online learning communities: Effective strategies for the virtual classroom. San Francisco: Jossey-Bass.

Palloff, R. M., & Pratt, K. (2005). Collaborating online. Learning together in community. San Francisco: Jossey-Bass.

Palloff, R. M., & Pratt, K. (2003). The virtual student. A profile and guide to working with online learners. San Francisco: Jossey-Bass.

Palloff, R. M., & Pratt, K. (1999). Building learning communities in cyberspace. San Francisco: Jossey-Bass.

 

Pratt, K. (2010). The future is now! The past, present, and future of online learning. Retrieved from: http://sylvan.live.ecollege.com/ec/crs/default.learn?CourseID=4432198&Survey=1&47=5590091&ClientNodeID=404183&coursenav=1&bhcp=1&BrswrOK=1&PrevRef=http://sylvan.live.ecollege.com/ec/crs/default.learn%3FCourseID%3D4432198%26Survey%3D1%2647%3D5590091%26ClientNodeID%3D404183%26coursenav%3D1&submit1=Continue

Vighnarajah, Wong, S., & Bakar, K. (2009). Qualitative findings of students’ perception on practice of self-regulated strategies in online community discussion, Computers & Education, 53(1), 94-103. DOI: 10.1016/j.compedu.2008.12.021

 

 

 

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