| May 2007 Index | Home Page |
Editor’s Note: In a world where team work and collaboration are increasing productivity in the workplace, successful group activities are an essential component of online learning. This research relates group processes to outcomes, identifies elements that were successful in this study, and raises additional questions for research.
The Perceived Benefits and Difficulties of Online Group Work in a Teacher Education Program
Heejung An, Sang Kyung Kim
Abstract
This study reports on the ways in which online group work was perceived by inservice K-12 teachers participating in a virtual school of education program. Data was drawn from an open-ended online survey distributed at the end of the course. Following Chi's verbal analysis coding method (1997), recurring themes were identified through a quantified qualitative data analysis. Results indicate that the three most prominent benefits which teachers perceived involved 1) their belief that collaborative practices could develop their metacognitive knowledge, 2) recognition of the value of a supportive learning community, and 3) new understanding of how to use online communication technology tools. Besides these benefits, the teachers also perceived difficulties in completing online group tasks, which involved 1) cognitive conflicts, 2) individual differences, 3) group grading challenges, 4) working across different time-zones, and 5) the challenges posed by online communication. Recommendations pertaining to these findings are also provided, with an emphasis on the ways in which online faculty and instructional designers can enhance students’ engagement in online group work.
Keywords: Online learning, collaborative learning, online group learning, online teacher education, metacognition
Introduction
At the current time, most online teacher education programs are adopting a constructivist pedagogical model emphasizing learner-centered collaboration, while at the same time deemphasizing didactic teaching approaches (Bush, 2003; Honebein, 1996; Duffy & Jonassen, 1992; Jonassen, 1994). Within the constructivist framework, knowledge cannot simply be transmitted from teacher to student or individual to individual. Instead, it is built up through the synthesis of social experiences transpiring online (Doolittle, 2001). The question is then whether the plethora of online degree programs in teacher education adequately addresses this collaborative approach in a manner that enables teachers to enhance their pedagogical practices in the classroom. This is an important issue since web-based distance learning is frequently considered as an effective means for meeting the educational needs of busy inservice teachers (Schulz, 2003).
By and large, collaborative learning has been addressed in a growing body of research asserting that such practices lead to improved student learning outcomes and improved social skills development (Johnson & Johnson, 1989; Smith, 1995). In studies on online collaborative activities in teacher education programs, critical thinking skills and multiple perspectives on tasks stand out for having a positive impact on the learning process (Jegede, 2002; Jetton, 2003). Moreover, it is suggested that teachers become more self-reflective through participation in online collaboration, leading to the development of metacognitive skills (Jetton, 2003; Ruhleder & Michael, 2000).
However, while the aforementioned research regarding online collaborative learning processes has been quite positive, this area of study is not without its critics. Some studies investigating students’ experiences with collaborative learning methods suggest that students often express little enthusiasm, particularly for group work in online environments. The primary reasons for this are due to “fears of loss of individual voice and identity, and fears of isolation, alienation, and estrangement from the group” (Dirkx & Smith, 2004, p. 134; Smith & Berg, 1997). Coupled with these negative responses, it has been argued that negative experiences with online technologies can intensify students’ hesitation toward participating in future collaborative efforts (Bernard, Beatriz, & St. Piere, 2000, as cited in Dirkx & Smith, 2004).
Keeping in mind these two opposing viewpoints about online group work, this study therefore aimed to explore the ways in which inservice teachers perceived their learning experiences while participating in online collaborative group tasks. A guiding assumption of this study was that teachers would not be likely to make a concerted effort in adopting certain instructional approaches unless they could experience such practices firsthand as learners. It was anticipated that this process would subsequently enhance their values and beliefs (Alexander, Schallert, & Hare, 1991; Bird, Anderson, Sullivan, & Swidler, 1992; Florio-Ruane & Lensmire, 1990; Kennedy, 1991). The questions addressed in this study were:
What are the teachers’ perceived benefits while participating in an online group project?
What are the teachers’ perceived difficulties while participating in an online group project?
Conceptual Framework
A growing body of research provides insights regarding the ways in which collaborative work can impact students’ learning in face-to-face environments; however, there has been much less exploration of the ways in which teachers perceive this method of learning in online environments. Overall, this literature review was conducted through a combination of both deductive and inductive approaches in order to understand emerging patterns of online collaborative learning in teacher education (Patton, 2002). We first examined the literature focusing on collaborative learning in teacher education. We then reviewed the literature about metacognition and learning communities, which emerged from the participants’ answers to the survey questions. This process led us to an understanding of the characteristics of online collaborative group work, thus providing a conceptual framework.
Collaborative Learning[1] in Teacher Education
The constructivist teaching model emphasizes the creation of learning environments that provide students with opportunities for critical thinking, discovery, and collaboration (Duffy & Jonassen, 1992; Lave & Wenger, 1991). A great deal of research indicates that learning through collaborative efforts often results in improved learning outcomes, such as higher levels of academic performance and social competency, as compared to competitive or individual learning (Johnson & Johnson, 1989; Johnson, Johnson, & Smith, 1991; Smith, 1995).
Within teacher education programs, an emphasis on collaboration is also deemed to be of paramount importance. Faculty is often encouraged to utilize collaborative learning with their preservice and inservice students, primarily because these students are also expected to utilize similar learning approaches during their classroom practice (Kemery, 2000; Kochan, 2000; Schultz, 2003). Schultz (2003) asserts that incorporating well-planned collaborative activities benefits teachers as well as their students, since this usage develops higher order thinking skills[2]. In a similar vein, Jegede (2002) asserts that collaborative online learning in teacher education programs has a positive impact on the learning process, by improving socialization skills as well as enhancing critical thinking. Other benefits of collaborative learning in online environments that have been cited include reflection, peer feedback (Ruhleder & Michael, 2000), and the reduction of anxieties (Gokhale, 1995).
Moreover, it has been asserted that online collaborative learning can facilitate metacognition. As Jonassen (1996) points out, those who participate in asynchronous online discussions often “read a posting and decide whether or not to respond, how to respond, and the likely consequences of such a response” (p. 251). Such thought processes not only allow students to engage in self-reflection (Jetton, 2003), but also make it likely to track how their peers’ thinking has changed over long periods of time (Ruhleder & Michael, 2000). Oura and Hatano (2001) also emphasized that the process of gaining expertise is assisted by other people, and expertise occurs in socioculturally significant contexts. For example, participation in group decision making can have important cognitive consequences for group members, leading them to adopt the problem-solving strategies that the group has used (Levine, Resnick, & Higgins, 1993). Computer Mediated Discussions (CMD), for example, can serve as a powerful vehicle for understanding the ways in which students share and better understand complex issues pertaining to their schools and surrounding communities (Jetton, 2003).
Collaborative learning activities that are well-suited for online environments include debates, group projects, case study discussions, simulations, role-playing exercises, the sharing of solutions for homework problems, and the collaborative composition of essays, stories, and research plans (Hiltz & Turoff, 2002). Yet, as noted by Schultz (2003), online collaborative work for such courses is usually relegated to discussion board conversations in which participants merely generate a dialogue with their peers about the weekly readings. While this type of activity can certainly be of value, the extent of actual collaboration is usually quite limited. Furthermore, due to the lack of instructional models when implementing online collaborative learning initiatives, there has been a considerable amount of criticism of this learning approach. For example, Dirkx and Smith (2004) assert that learners are usually dissatisfied with group work in online courses because they “struggle with the development of a sense of interdependence and intersubjectivity within their online groups, but end up holding fast to subjective, individualistic conceptions of learning.” (p.134). They further suggest that these aspects could also be exacerbated in online environments, due to the difficulty of providing the emotional dynamics deemed to be so critical in the learning process. Other frequent complaints related to online collaboration are found to include the lapse of response time, thus preventing participants from obtaining immediate feedback (Jetton, 2003).
In relation to the aforementioned findings, a substantial amount of research indicates that inservice teachers often feel more comfortable with didactic teaching approaches especially when participating in online environments, primarily because this is the approach they experienced during their own K-12 education (Ball & McDiarmid 1987; Calderhead & Robson, 1991; Duffy & Jonassen, 1992; Sparks & Hirsh, 2000).
Teachers’ Beliefs
Researchers who study the behavior of teachers and how they are trained, stress the importance of understanding what teachers think and what their beliefs actually are (Pajares, 1992). This understanding appears significant in that teachers’ beliefs play a key role in determining their attitudes and behaviors toward their instructional practices and ways of interacting with students. In turn, student behavior largely mirrors the discourse modeled by and the expectations communicated by teachers when they engage in cooperative learning (Webb, Nemer, & Ing, 2006). In an investigation of teachers’ beliefs, Pajares (1992) proposes to consider teachers’ beliefs about their confidence to affect students’ performance (“teacher efficacy”), about the nature of knowledge (“epistemological beliefs”), about causes of teachers’ or students’ performance (“attributions, locus of control, motivation, etc.”), and about perceptions of self (“self-concept and self-esteem”).[3]
Metacognition
Metacognition refers to knowledge about one’s own cognition and the ability to monitor the assumptions and implications of one’s activities (Cordero-Ponce, 2000; Flavell, 1979; Gagné, Briggs, & Wager, 1992). According to Flavell (1987), metacognitive knowledge is divided into three categories: knowledge of person variables, task variables, and strategy variables. Knowledge of person variables is geared for the ways in which people learn and process information, as well as their own awareness of these learning processes. Knowledge of task variables involves an understanding of the nature of the task as well as the type of processing demands it may place upon the individual. Lastly, knowledge of strategy variables encompasses knowledge about both cognitive and metacognitive strategies, as well as conditional knowledge about when and where it is appropriate to use such strategies.
Metacognition is also a means to accessing the knowledge of others, which guides learners toward new perspectives on specific aspects of their learning (Davis, 2000). When students compare their thinking with that of others, their understanding deepens due to their spontaneous reflections and exposure to multiple perspectives (Davis, 2000; Levine et al., 1993; Scardmalia & Bereiter, 1991; Vye, Schwartz, Bransford, Barron, & Zech, 1998). For example, Lin and her colleagues (1999) found that when students compared their thinking with peers, their understanding was deepened. Furthermore, Levine, Resnick, and Higgins (1993) argue that people’s self-perceptions and evaluations are influenced by comparing themselves to others. Additionally, they argue that “people actively select comparison targets and construct and distort comparison information to serve their goals” (p. 594) when they are engaged in a social comparison.
In teacher education, the notion of engaging teachers in activities calling for development of metacognition has also become a central focus of teacher education programs, as many researchers believe it plays an important role in students’ academic performance and cognitive development (Chi, Bassock, Lewis, Reimann, & Glaser, 1989; Jacobson, 1998; Schoenfeld, 1987; Sternberg, 1984). Studies have also found that those who reflect upon their performance and who use that awareness to guide their thoughts and actions are more likely to succeed academically (Alexander, Graham, & Harris, 1998; Lin, 2001). Because of this, Hatano and Inagaki (1992) emphasize that “exploration and reflection” should be incorporated in the learning process in classrooms.
However, metacognition is not an automatic process. Instead, it is the result of the long-term development of a cognitive system (Jacobson, 1998). Merely forcing learners to reflect on various tasks does not guarantee any expected learning outcomes. Learners must be supported by instruction that scaffolds their attention and makes them consciously aware of topics of inquiry, such as explicitly instructing them to compare examples (Brown & Kane, 1988).
Bransford, Brown, and Cocking (2000) posited that in order to develop metacognition, the teaching of metacognitive skills should be integrated into the curriculum in a variety of subject areas. While most metacognition intervention initiatives focus on strategy training in which novice learners learn expert strategies to solve complex problems, Lin (2001) and Pramling (1990) highlight the importance of developing a supportive social environment for nurturing metacognition. In such a supportive social learning context, students could work with and listen to others and develop ways of dealing with complex issues that require different kinds of expertise (Bielaczyc & Collins, 1999; Brown, Collins, & Duguid, 1989).
Learning Communities
Vygotsky (1978) notes that learning does not always occur in vacuum, but in a social setting. In other words, learning is influenced by the context in which it takes place: the process of gaining expertise is assisted by other people, and expertise occurs in socioculturally significant contexts (Oura & Hatano, 2001). Furthermore, learners need a supportive learning context in which they can experience multiple perspectives and group feedback on their performance. A community-centered approach that requires the development of classroom and school based norms, as well as connections to the nation and world that support these norms (Bransford, Brown, & Cocking, 2000) could provide this type of learning context. When provided with the chance to practice in an actual in situ environment, students begin to utilize the relevant jargon, imitate behaviors, and gradually start to act in accordance with this norm. (Brown et al., 1989).
Yet, Brown (1994) argues that schools are still inundated with behaviorist principles that are not conducive to bringing about meaningful learning opportunities. Many of her ideas were attempted in the Fostering Communities of Learners project, which was based on Vygotsky's multiple zones of proximal development (1978) and reciprocal teaching (Palincsar & Brown, 1984). This project involved the development of a classroom learning community, with the intent of understanding and interpreting texts. Brown (1997) claimed that through processes like these, reflective activities within the learning community could become internalized, thus fostering self-reflective practices and personal theories of learning. In this learning context, individuals experienced differences in their perceptions of learning (Hogan, 1999), which then became recognized, valued and fostered (Brown, 1994, 1997). According to Brown (1997), encouragement of diversity contributes richness to classroom activities by offering participants opportunities to develop expertise and interests as they work towards a broader, shared goal of understanding. "This interdependence promotes an atmosphere of joint responsibility, mutual respect and a sense of personal and group identity" (Brown, 1994, p. 10), as expertise is distributed in both social and material terms (Roth, 1998).
Thomas (2002) noted that a supportive learning context can be formed within web-based learning environments in which learners process information, increase their knowledge, and conduct reflective thinking about their own and others’ teaching practices. While pursuing their own group’s goal in an online environment, students have the opportunity to participate in asynchronous online discussions, which can serve as personally meaningful and spontaneous tasks. When engaged in online discussions, participants are sometimes urged to role-play with the audience, which enables them to “get inside the skin” of the audience and to experience the message as the audience would (Hays, 1996). By forming one’s own ideas to persuade their readers and replying to others’ messages through critical analysis, students can practice real-world interactions of the given topics (Brown et al., 1989; Horwitz, 2000).
Methods
Context and Participants
This study was conducted with two online classes (the same course with different sections) in an instructional technology program during the Spring 2005 semester, at an online graduate school of education located in the southwestern U.S. Two sections were held at the same time, and taught by the same instructor (the first author of this article) via the Blackboard Learning SystemTM. The course sequences, materials, and learning activities were exactly the same in both classes. This course was 8-weeks long, and was required for students who had just entered the program during their first year. This course was intended to orient students to the program, through exposure to basic instructional design approaches, national technology standards and the development of an electronic portfolio.
Data was drawn from twenty-six participants (Female: 17 and Male: 9) who were enrolled in these two classes. All of the participants were K-12 teachers, except for five (3: technology coordinators/specialists, 1: military officer; 1: science coach). Students were participating in this course from different areas of the U.S., in states such as Alaska, California, Florida, Georgia, Illinois, Massachusetts, New Jersey, North Carolina, Ohio, South Carolina, and Texas). Participant ages ranged were 25 – 56 years old and their teaching experience was also very diverse, ranging from 1 to more than 25 years of experience. Only 3 of the participants had ever taken an online course before.
Participants’ reasons for enrolling in this online program included furthering their own education, becoming a proficient / highly qualified teacher, and interest in enhancing their students’ knowledge and skills. Secondary reasons included upgrading their professional status, seeking a promotion, and obtaining a higher level of compensation. Participants also indicated that this online Masters Degree program enabled them to accomplish their aforementioned goals more easily. The program allowed for a more flexible schedule that enabled them to meet work and family commitments more easily than in face-to-face classes.
Description of the Group Project
The instructor randomly formed groups of 3-4 students and initiated the online collaborative group project by posting a message indicating the project specifications as well as some successful tips for communicating within the groups. Each group was provided with a group discussion board on the Blackboard Learning SystemTM. All participants were required to rely on each other, while also being held accountable for their own portion of the work. Participants communicated primarily via group discussion boards, because this was considered to be the most convenient and conducive method for collaboration. In addition, some participants indicated that they made numerous phone calls to clarify group objectives and some students used email to make comments geared for a specific individual within their group.
The instructor did not intervene in any group processes except to answer student questions in relation to the project. Group members were advised to choose their own role regarding portions of work they expected to complete. Note that student assessment was based on the group’s work, rather than the efforts of any particular individual. Students had three weeks to complete it. The actual assignment description is listed as follows:
With your learning community, write an 8-10 page APA formatted paper that compares and contrasts the five different design approaches described in your text. Explain how each supports problem-solving skills, literacy, building of learning environments, and a community of learners. Does one design lend itself to one particular goal more than the others? Is anything missing from these designs? Include within your discussion particular National Educational Technology Standards that might be met through this approach. You should refer to the Standards designed for your students, rather than those geared for teachers.”
Data Resources and Analysis
The data was collected through an online questionnaire that was distributed on the last day of the 8-week course. Student involvement was entirely voluntary. Participants were first asked to indicate their reasons for enrolling in the program and to provide information about their group’s communication methods. The participants were then asked to answer two open-ended questions regarding what they perceived to be the benefits and difficulties of working on the online group papers. These two written protocols were expected to capture students’ beliefs and perceptions on their experiences in online collaborative learning. In response to these two primary research questions, we used Chi's verbal analysis coding method (1997), which blends qualitative and quantitative analyses. A great deal of literature suggests that the combination of these two types of data analysis is necessary in order to remove each method’s shortcomings in the research field (Chi, 1997; Creswell, 1994; Rourke & Anderson, 2004). The qualitative aspect of this approach focused on the verbal data analysis of the written comments in order to provide a much richer, more detailed, and more accurate representation of the students’ knowledge and attitudes (Chi, 1997; Rourke & Anderson, 2004). To reduce the subjectiveness of qualitative coding and to obtain validation, quantitative measures along with the qualitative measures were blended together.
Coding Schemes. The data coding was accomplished through a recursive process of identifying themes in the text-based data for the open-ended questions (Jetton, 2003). During the preliminary coding process, emerging themes and categories were recorded independently by the two authors of this study. This data became the basis for the coding structure. We compared similarities and differences in the recurring themes and established specific categories for the perceived benefits as well as the difficulties, which guided us to more detailed coding. Through this iterative process, identifying themes in students’ written production and from existing literature, two coding schemes (The Coding Scheme of the Perceived Benefits and The Coding Scheme of the Perceived Difficulties) were developed (See Tables 1 and 2).
For the perceived benefits, three categories emerged from the coding of the entire data set. These included: 1) the development of metacognitive knowledge (subcategories: task knowledge, person knowledge, and strategy knowledge); 2) the recognition of the value of a supportive learning community; and 3) a new understanding of how to use online communication technology tools. For the perceived difficulties, five categories emerged from the preliminary coding of the entire data set were: 1) cognitive conflicts; 2) individual differences; 3) group grading challenges; 4) time-zone scheduling problems; and 5) the challenges posed by online communication
Table 1
Coding Scheme of the Perceived Benefits
Category | Sub-category | Definition | Example |
Development of metacognitive knowledge | Task knowledge | Knowledge about the nature of the task as well as the type of processing demands that it places on the individual (Flavell, 1987). For this study, specific knowledge focused on a collaborative task. | "I learned how to put everyone's work together into one document." |
| Person knowledge | General knowledge about one's own learning processes (Flavell, 1987). | “I realized that I am a good logical researcher that does not go off in too many directions.” |
| Strategy knowledge | Knowledge about both cognitive and metacognitive strategies, as well as conditional knowledge about when and where it is appropriate to use such strategies (Flavell, 1987). | "I learned that I need to be more assertive with issues that I want to see implemented." |
Recognition of the value of a supportive learning community |
| A sense of community established through collaborative online group work, and students’ recognition of the positive influence of their group on their own learning and the context in which learning takes place (Bransford et al, 2000). | “The group papers made me feel like a part of the class and not just someone aimlessly wandering out in cyberspace.”
“Group work allowed me to know more about others.” "I was able to see other students’ work, the team leader putting everything together and the group members trying to really discuss issues." “The best part was being able to see other class members’ work.” |
New understanding of how to use online communication technology tools. |
| Learning about online communication technology tools and also constructively using them for the group work process in an online environment. | “I liked learning from other people in my group about technology and how to use it.” |
Table 2
Coding Scheme of the Perceived Difficulties
Category | Definition | Example |
Cognitive conflicts | Awareness of differences in perspectives and opinions on the group’s task and solutions (Cho & Schunn, 2003). | “There are different interpretations of the assignment.” “It is hard to get everyone to have the same vision as you.” “There was too much verbiage generated when two or more viewpoints were discussed.” |
Individual differences | Irreconcilable individual differences among group members, such as different work styles and pace. | “Many people have different work patterns. I am an early starter and like to get things organized quickly and, if possible, complete assignments before the deadline.” “I like to complete my assignments early and sometimes many people like to complete assignments at the last minute. I am not really a great writer; therefore I must spend more time writing papers in order to receive my desired score.” “Everyone works at a different pace.” |
Group grading challenges
| Non-differentiated grading system for group members | “I did not like being at the mercy of a group for my grade. Not everyone carries the same workload, so it is not fair to receive the same grade.” “It is unfair to motivate students to have to do the work for others in order to attain the grade they want.” |
Working across different time-zones | Difficulty scheduling, communicating and collaborating across different time zones within the U.S. | “It was also difficult working with so many time zones.” “Even under the best of circumstances in which every group member is motivated, it is very difficult to coordinate schedules.” |
Obstacles that developed during the online conversations, due to the unique challenges caused by virtual absenteeism, a lack of spontaneous response, facial expressions, and audio tones. | “If someone doesn’t respond quickly, it is very frustrating. It is hard to know if it is for an important or frivolous reason” “Not having facial interactions.” |
Scoring Procedure of Written Protocols. Analysis of students’ written protocols occurred at different phases. First, two coders segmented all the features in the students’ answers using the coding schemes (“Segmenting stage”). This served as a preliminary data set. Following the preliminary segmentation, intercoder agreement on the preliminary segmented units was determined. Discrepancies were resolved through discussion. The two coders (the two authors of this paper) then individually coded the segmented units based on the coding schemes (“Coding stage”). Lastly, intercoder reliability was again checked for all answers and discrepancies were again resolved by discussion. Cautious action was taken to rule out the possibility that some students were simply more articulate or fluent in their written protocols. For instance, if a student described the same idea using different expressions, such as “collaboration” and “working as a group,” only one point was assigned to the answer.
Intercoder reliability for the analysis of the written protocols was computed by percentage agreement. The two coders were blind to students’ names. The intercoder reliability between the two raters ranged from 91% to 94% of agreement. Although there was some disagreement between the two coders, discrepancies were resolved by a second examination and discussions between the researchers.
Results and Discussion
Table 3 presents the results of the perceived benefits, by category, from highest percentage to lowest percentage. From the responses for perceived benefits, we found a total of 94 idea units. Out of 94 idea units, 57 idea units (60%) were related to the development of metacognitive knowledge (task knowledge 33%; person knowledge 13%; and strategy knowledge 15%). Thirty three idea units (35%) were found for the recognition of the value of a supportive learning community category. Four idea units (4%) were associated with learning about online communication technology tools. Figure 1 provides a graphic illustration of these results.
Table 3
The Perceived Benefits in Online Group Learning, from Highest to Lowest
Category | Sub-category | Number of Units | % of the total |
Development of metacognitive knowledge | - Task knowledge | (31) | (33%) |
- Person knowledge | (12) | (13%) | |
- Strategy knowledge | (14) | (15%) | |
sub-total |
| 57 | 61% |
Recognition of the value of a supportive learning community |
| 33 | 35% |
New understanding of how to use online communication technology tools |
| 4 | 4% |
Total |
| 94 units | 100% |
Figure 1. The perceived benefits of online group learning
from highest to lowest
Table 4 presents results for perceived difficulties, by category, from the highest to lowest percentage. From the responses for perceived difficulties, we found a total of 62 idea units. Out of 62 idea units, twenty three idea units (37.1%) were associated with individual differences, fifteen idea units were related to online communications, and ten idea units involved cognitive conflicts. The remaining categories took up very small percentages: eight idea units (12.9%) were found for group grading challenges, and six idea units (9.7%) were for working across different time-zones. Figure 2 also illustrates these results.
Three students out of 26 reported that they did not encounter any difficulties in the completion of this online collaborative project. Their comments are as follows:
“None, I cannot think of any particular item that I disliked about working on the group paper.”
“None, the online environment is a ‘natural’ platform for group work.”
”I was originally afraid that working together online wouldn't work, but after talking to each other in our groups that fear subsided and we jelled together to produce a group paper.”
Table 4
Perceived Difficulties in Online Collaborative Group Learning: Highest to Lowest
Category | Number of Units | % of the total |
Individual differences | 23 | 37.1% |
The challenges posed by online communication | 15 | 24.2% |
Cognitive conflicts | 10 | 16.1% |
Group grading challenges | 8 | 12.9% |
Working across different time-zones | 6 | 9.7% |
Total | 62 | 100% |
Figure 2. Perceived difficulties in online collaborative group learning
from highest to lowest
The findings suggest that the online collaborative group work could be a valuable means for scaffolding and seemed to have a role both in facilitating and enhancing inservice teachers’ metacognitive knowledge. It is important to note that many inservice teachers unconsciously developed metagonitive knowledge without the instructor’s explicit intervention by engaging in group tasks, while also achieving the goals of the task itself at hand. This finding is aligned with Lin’s assertion (2001) that a supportive online collaborative social environment has the potential to impact the development of metacognition.
Secondly, many teacher participants reported that they experienced benefits from supportive online group members which enhanced their own learning. In particular, belongingness and virtual presence seemed to be very affective factors, since they increased student motivation. Indeed, making classmates aware of their own presence in an online learning environment, either by contributing significantly to the group project or simply by posting short messages (e.g., “I agree” or “I don’t agree”) on the group discussion board, certainly proved to be beneficial in this online learning environment. When students did not see other group members’ postings on the discussion board, they felt they were not functioning as a team. Without any tools to sustain social connections with their online classmates (e.g., being able to see who is online), group members frequently experienced frustration and had a hard time moving along. After all, it has been suggested that one of the benefits of online collaboration is the reduction of anxieties (Gokhale, 1995). Nonetheless, this study showed mixed results in relation to this. While some teachers reported that they felt relieved knowing they were on the right track, some reported a delay in responses made or no responses by team members, which increased their anxieties further. Based on the positive responses, though, we surmise that the online group work experience led some students to recognize the value of a supportive online learning community for their own learning.
Thirdly, learning about the integration of technology, such as instant messaging programs, may have been of value to the teachers, who might otherwise not have been aware of, interested in using, or not have had the opportunity to learn about such tools. This aspect is of particular importance for instructional technology programs, since teachers can experience how a certain technology may be utilized as a means of learning with technology (Jonassen, Peck, & Wilson, 1999).
This study also revealed difficulties that need attention before implementing online group projects. For example, it is presumed that individual differences, cognitive conflicts, and group grading challenges might not be unique difficulties in online environments, but common concerns pertaining to face-to-face collaborative learning as well. However, it is possible that these difficulties are actually more serious in online environments. Additionally, the two other perceived difficulties (online communications and working across different time-zones) were unique concerns pertaining to the online environment. Perhaps, the strong dependence on written-text and asynchronous communications, which are inherent aspects of online communication, may be difficult for many new online participants to get used to. Working across different time-zones might also be very problematic for those who can only communicate online at a specific time. These are areas that need to be explored in future research.
Among the other difficulties and frustrations participants faced was the implementation of a non-differentiated grading system. The instructor chose this “group grading” approach, so that every member would be prepared to take on the necessary responsibilities. However, this sometimes led students to feel less likely to contribute, because individuals became more dependent on others to do the work for them. This effect seems to be a more serious problem in online environments, primarily because participants feel less guilty about not responding or not participating in the work process.
Besides the aforementioned categories, there are other issues for online instructors to consider when implementing online group projects. For example, it is recommended that they consider whether the characteristics of group tasks (e.g., type of group task, requirements, and due dates, etc.) are suitable, taking into account the needs of the inservice teachers’ full time employment. Many projects simply become too time-consuming and too cognitively demanding. Yet, at the same time, the participants also need to consider whether they would like to adhere to high standards within their program of study, and if they can meet these challenges of online graduate work while also balancing other responsibilities. Within many online graduate schools of education, there seems to be a gap between school standards, the instructor’s standards, and the students’ standards. Other aspects that need to be considered involve the class’ attitudes toward collaboration. For this study, involving a group of inservice teachers, it was found that they tended to avoid potentially embarrassing situations, as well as circumstances in which they faced the possibility of offending another member of their group. As a result, they would often contact the instructor in order to resolve these concerns.
Conclusions and Future Studies
Although the constructivist teaching approach, emphasizing collaboration and reflective teaching, has become a major goal of many online teacher education programs, the usefulness of online group work is a subject of ongoing debate and needs to be discussed from a critical perspective. By providing empirical evidence, the current study highlights the need for a better understanding of how inservice teachers perceive their experiences while participating in online group tasks.
For this study, even though the teachers perceived difficulties while participating in the online group project, their positive experiences seemed to outweigh the negative ones. Especially enlightening was the importance of a supportive social environment for fostering metacognitive knowledge. Metacognitive knowledge clearly served a key role, which led to the successful completion of online collaborative group tasks. However, in order for this to take place, there should be awareness among online faculty and instructional designers of the need for a supportive learning environment.
Finally, this study leads to further research in regards to a) how we can help teachers develop more supportive online collaborative learning environments that reduce the difficulties found in this study; b) how we can further distinguish the ways in which students can achieve positive benefits that are not possible in face-to-face environments; and c) how online collaborative learning approaches are currently impacting teachers’ knowledge and practice. For instance, in what ways do these online collaborative efforts offer a means of proper modeling that will be of value to teachers in their own classrooms? These questions require further exploration.
References
Alexandre, P., Schallert, D., & Hare, V. (1991). Coming to terms: how researchers in learning and literacy talk about knowledge. Review of Educational Research, 61, 315-343.
Ball, D.L., & McDiarmid, G.W. (1987). Understanding how teachers’ knowledge changes. National Center for Teacher Education Colloquy, 1(1), 9-13.
Bandura, A. (1986). Social Foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
Bielaczyc, K., & Collin, A. (1999). Learning communities in classrooms; A reconceptualization of educational practice. In C. M. Reigeluth (Ed.), Instructional-design theories and model, II: A new paradigm of instructional theory. Mahwah, NJ: Lawrence Erlbaum Associates Publisher.
Bird, T., Anderson, M.L., Sullivan, B.A., & Swidler, S.A., (1992). Pedagogical balancing acts: A teacher educator encounters problems in an attempt to influence prospective teachers' beliefs. Research report 92-8, East Lansing, MI: National Center for Research on Teacher Learning, Michigan State University, ERIC (ED348359).
Bloom, B. (1956). Taxonomy of educational objectives: Handbook I. Cognitive domain. New York: McKay.
Braaksma, M. A., Rijlaarsdam, G., Van den Bergh, H., & Van Hout-Wolters, B. H. (2004). Observational learning and its effects on the orchestration of writing processes. Cognition and Instruction 22(1), 1-36.
Bransford, J. D., Brown, A., & Cocking, R. (2000). (Eds.), How People Learn: Mind, Brain, Experience and School, Expanded Edition. Washington, DC: National Academy Press.
Brown, A. L. (1994). The advancement of learning. Educational Researcher, 23(8), 4-12.
Brown, A. L. (1997). Transforming schools into communities of thinking and learning about serious matters. American Psychologist, 52, 399-413.
Brown, A. L., & Kane, M. J. (1988). Preschool children can learn to transfer: Learning to learn and learning from example. Cognitive Psychology, 20, 493-523.
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32-42.
Bush, G. (2003). The School Buddy System: The Practice of Collaboration. Chicago: ALA Editions.
Calderhead, J. & Robson, M. (1991). Images of teaching: student teachers’ early conceptions of classroom practice. Teaching and Teacher Education, 7, 1-8.
Chi, M. T. H. (1997). Quantifying qualitative analyses of verbal data: A practical guide. The Journal of the Learning Sciences, 6(3), 271-315.
Chi, M. T. H., Bassock, M., Lewis, M., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145-182.
Cho, K., & Schunn, C. (2003). Successful factors in networked collaboration. In the Proceedings of the 25th Annual Conference of the Cognitive Science Society, Mahwah, NJ: Erlbaum.
Cordero-Ponce, W.L. (2000). Summarization instruction: Effects on foreign language comprehension and summarization of expository texts. Reading Research and Instruction 39(4), 329-350.
Creswell, J. W. (1994). Research Design: Qualitative & Quantitative Approaches. London: SAGE Publications.
Davis, J. H. (2000). Metacognition and multiplicity: the arts as models and agents. Educational Psychology Review, 12(3), 339-359.
Dillenbourg, P. (1999). Introduction: What do you mean by “collaborative learning”? In P. Dillenbourg (Ed.), Collaborative Learning: Cognitive and Computational Approaches, (pp. 1-9). Oxford: UK: Elsevier.
Dillenbourg, P., Baker, M., Blaye, A., & O’Malley, C. (1996). The evolution of research on collaborative learning. In E. Spada & P. Reiman (Eds.), Learning in Humans & Machines: Towards an Interdisciplinary Learning Science (pp. 189-211). Oxford: UK: Elsevier.
Dirkx, J. M. & Smith, R. O. (2004). Thinking out of a bowl of spaghetti: Learning to learning in online collaborative groups. In T. S. Roberts (Ed.), Online Collaborative Learning: Theory and Practice (pp. 132-159). Hershey, PA: Information Science Publishing.
Doolittle, P.E. (2001). The need to leverage theory in the development of guidelines for using technology in social studies teacher preparation: A reply to Crocco and Mason et al. Contemporary Issues in Technology and Teacher Education, 1 (4). Retrieved June 14, 2006, from http://www.citejournal.org/vol1/iss4/currentissues/socialstudies/article2.htm
Duffy, T.M., & Jonassen, D.H. (Eds.) (1992). Constructivism and the technology of instruction: A conversation. Hillsdale, NJ: Lawrence Erlbaum.
Fang, Z. (1996). A review of research on teacher beliefs and practices. Educational Research, 38 (1) 47-64.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A nee area of cognitive-developmental inquiry. American Psychologist, 34(10), 906-911.
Flavell, J. H. (1987). Speculations about the nature and development of metacognition. In F. E. Weinert & R. H. Kluwe (Eds.), Metacognition, Motivation and Understanding (pp. 21-29). Hillside, NJ: Lawrence Erlbaum Associates.
Florio-Ruane, S. & Lensmire, T. J. (1990) Transforming future teachers’ ideas about writing instruction, 22(3), 277-289.
Gagné, R. M., Briggs, L. J., Wager, W. W. (1992). Principles of instructional design. 4th ed. Belmont, CA: Wadsworth/Thomson Learning.
Gokhale, A. (1995). Collaborative learning enhances critical thinking. Journal of Technology Education, 7, 1-2. Retrieved August 20, 2005, from http://scholar.lib.vt.edu/ejournals/JTE/jte-v7n1/gokhale.jte-v7n1.html
Hatano, G. & Inagaki, K. (1992). Desituating cognition through the construction of conceptual knowledge. In P. Light & G. Butterworth (Eds.) Context and cognition. Ways of knowing and learning. (pp. 115-133). New York: Harvester.
Hays, J. R. (1996). A new framework for understanding cognition and affect in writing. In C.M. Levy & S. Ransdell (Eds.), The science of writing (pp. 1-27). Mahwah, NJ: Erlbaum.
Hiltz, S.R. & Turoff, M. (2002). What makes learning effective? Communications of the ACM, 45 (4), 56-59.
Hogan, K. (1999). Relating students’ personal frameworks for science learning to their cognition in collaborative contexts. Science Education, 83, 1-32.
Honebein, P. C. (1996). Seven goals for the design of constructivist learning environments. In B.G. Wilson (Ed.), Constructivist learning environments: Case studies in instructional design. Englewood Cliffs, NJ: Educational Technology Publications.
Horwitz, E. K. (2000). Teachers and students, students and teachers: An ever-evolving partner. The Modern Language Journal, 84(4), 523-535.
Jacobson, R. (1998). Teachers improving learning using metacognition with self-monitoring learning strategies. Education, 118(4), 579-589.
Jegede, O. J. (2002). Facilitating and sustaining interest through an on-line distance peer-tutoring system in a cooperative learning environment. Virtual University Gazette, 35- 45.
Jetton, T. L. (2003). "Using computer-mediated discussion to facilitate preservice teachers' understanding of literacy assessment and instruction." Journal of Research on Technology in Education, 36(2), 171-191.
Johnson, D. W., & Johnson, R. T. (1989). Cooperation and competition: Theory and research. Edina, MN: Interaction Book Company.
Johnson, D. W., Johnson, R. T., & Smith, K. A. (1991). Active Learning: Cooperation in the College Classroom. Edina, MN: Interaction Book Company.
Jonassen, D. H. (1994). Thinking technology: Toward a constructivist view of instructional design. Educational Technology, 30(9), 34-37.
Jonassen, D. H. (1996). Computers as Mind Tools for Schools: Engaging Critical Thinking, 2nd Ed. Upper Saddle River, NJ: Prentice Hall.
Jonassen, D. H., Peck, K. L., & Wilson, B. G. (1999). Learning with Technology: A Constructivist Perspective. Upper Saddle River, NJ: Prentice-Hall, Inc.
Kemery, E. R. (2000). Developing on-line collaboration. In A. Aggarwal (Ed.), Web-based Learning and Teaching Technologies: Opportunities and Challenges (pp. 227-245). Hershey, PA: IDEA Group Publishing.
Kennedy, M. M. (1991). Teaching Academic Subjects to Diverse Learners. Teachers College, Columbia University Press.
Kochan, F. K. (2000). Models for enhancing the professional development for teachers: Overview and framework. In D. J. McIntyre and D. M. Byrd (Eds.), Research on Effective Models for Teacher Education: Teacher Education Yearbook VIII (pp. 1 –9). Thousand Oaks, CA: Corwin Press, Inc.
Levine, J. M., Resnick, L. B, & Higgins, E. T. (1993). Social foundations of cognition. Annual Review of Psychology, 44, 585-612.
Lin, X. (2001). Designing Metacognitive activities. Educational Technology Research and Development, 49(2), 23-40.
Lin, X., Hmelo, C., Kinzer, C. K., & Secules, T. J. (1999). Designing technology to support reflection. Educational Technology Research and Development, 47(3), 43-62.
McInnerney, J. M. & Robert, T. S. (2004). Collaborative or cooperative learning? In T. S. Roberts (Ed.), Online Collaborative Learning: Theory and Practice (pp. 203-214). Hershey, PA: Information Science Publishing.
Oura, Y., & Hatano, G. (2001). The constitution of general and specific mental models of other people. Human Development, 44, 144–159.
Pajares, F. (1992). Teachers' beliefs and educational research: Cleaning up a messy construct. Review of Educational Research, 62, 307-332.
Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension fostering and comprehension monitoring activities. Cognition and Instruction, 1, 117-175.
Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed). Thousand Oaks, CA: Sage.
Pramling, I. (1990). Learning to Learn. A Study of Swedish Preschool Children. New York, NY: Springer Verlag.
Roth, W.-M. (1998). Designing communities. Dordrecht, The Netherlands: Kluwer Academic Publishers.
Rourke, L., & Anderson, T. (2004). Validity in Quantitative Content Analysis. Educational Technology, Research and Development, 52(1), 5-18.
Ruhleder, K., & Michael, T. (2000). Reflective collaborative learning on the web: Drawing on the master class, First Monday, 5(5). Retrieved August 24, 2005, from http://www.firstmonday.org/issues/issue5_5/ruhleder/
Scardamalia, M. & C. Bereiter (1991). Higher levels of agency for children in knowledge building: A challenge for the design of new knowledge media. The Journal of the Learning Sciences, 1(1), 37-68.
Schoenfeld, A. H. (1987). What's all the fuss about metacognition? In A. H. Schoenfeld (Ed.), Cognitive science and mathematics education (pp. 189-215). Hillsdale, NJ: Lawrence Erlbaum Associates.
Schulz, B. (2003). Collaborative Learning in an Online Environment: Will it work for teacher training? In Proceedings of the 14th Society for Information Technology and Teacher Education International Conference (SITE) (pp. 503-504). Charlottesville, VA: AACE.
Smith, K. A. (1995). Cooperative learning: Effective teamwork for engineering classrooms. Retrieved January 20, 2006, from http://fie.engrng.pitt.edu/fie95/2b5/2b54/2b54.htm
Smith, K., & Berg, D. (1997). Paradoxes of Group Life: Understanding Conflict, and Movement in Group Dynamics. San Francisco, CA: The Lexington Press.
Sparks, D. & Hirsh, S. (2000). A National Plan for Improving Professional Development. Retrieved September 2, 2005, from http://www.nsdc.org/library/authors/NSDCPlan.cfm
Sternberg, R. J. (1984). What should intelligence tests test? Implications for a triarchic theory of intelligence for intelligence testing. Educational Researcher, 13(1), 5-15.
Thomas, M. J. W. (2002) Learning within incoherent structures: the space of online discussion forums. Journal of Computer Assisted Learning, 18, 351-366.
Vye, N., Schwartz, D. L., Bransford, J. D., Barron, B. J., & Zech, L. (1998). SMART environments that support monitoring, reflection and revision. In H. Dunlosky & A. Graesser (Eds.), Metacognition in educational theory and practice (pp. 305-347). Hillsdale, NJ: Lawrence Erlbaum Associates.
Vygotsky, L.S. (1978). Mind and Society: The development of higher mental processes. Cambridge, MA: Harvard University Press.
Webb, N. M., Nemer, K. M., & Ing, M. (2006). Small-group reflections: Parallels between teacher discourse and student behavior in peer-directed groups. Journal of the Learning Sciences, 15(1), 63-119.
Zohar, A. (2004). Higher order thinking in science classrooms: Students’ learning and teacher’s professional development. Dordrecht, The Netherlands: Kluwer.
Zohar, A. (2006). The nature and development of teachers’ met strategic knowledge in the context of teaching higher order thinking. The Journal of the Learning Sciences, 15(3), 331-377.
About the Authors
Heejung An is an Assistant Professor of Learning Technologies at the College of Education, William Paterson University. Her research interests are in the areas of online group learning, technology integration in K-12 schools, and knowledge presentation and cognition.
E-mail: anh2@wpunj.edu
Phone: 973-720-2280
Address: William Paterson University, College of Education,
300 Pompton Road, Wayne, NJ 0747
Sang Kyung Kim is the Computer Assisted Language Learning Coordinator of the Intensive English Program at the Pratt Institute. Her research interests are in the interface of instructional design and teaching English as a second language, and the development of collaborative learning initiatives in online environments.
Email: skim35@pratt.edu
Phone: 718-399-4187
Address: Pratt Institute, Intensive English Program
200 Willoughby Avenue, Brooklyn, NY 11205
End Notes
[1] Collaborative and cooperative learning are two different research fields (Dillenbourg, 1999; Dillenbourg, Baker, Blaye, & O’Malley, 1996; McInnerney & Robert, 2004). Dillenbourg (1999), for example, asserts that in collaboration, group members “do the work together,” while in cooperation they “split the work, solve sub-tasks individually and then assemble the partial results into the final output” (p. 11). The similarities and differences of these two terms are beyond the scope of this article. Throughout this article, we use the term collaborative learning and define it as a learning method that implies “working in a group of two or more to achieve a common goal, while respecting each individual’s contribution to the whole” (McInnerney, & Robert, 203, p. 205).
[2] The term “higher order thinking skills” is generally used to refer to the cognitive activities that are beyond recall and comprehension, such as analyzing, synthesizing, and evaluation constructing arguments, asking research questions, making comparisons, solving nonalgorithmic complex problems, dealing with controversies, identifying hidden assumptions, classifying, and establishing casual relationships, and most of the classical scientific inquiry strategies (Bloom, 1956; Zohar, 2004; Zohar, 2006).
[3] A change in teachers’ pedagogical beliefs can allow teachers to be more willing to challenge didactic pedagogical practices in their classrooms, leading to real educational reform. (Alexandre, Schallert, & Hare, 1991; Bandura, 1986; Fang, 1996; Steinberg, 1998). When teachers make a concerted effort to adopt new instructional strategies that they learned as a learner into their instructional practices, fundamental changes can occur in the processes by which teaching and learning takes place (Jonassen, 1994; Honebein, 1996).