A Collaborative Online Learning Design Based on Instructor and Learners Perspective - Essay Example

A Collaborative Online Learning Design Based on and Learners’ Perspective (CECS 6100) Abdulrahman Alamri Introduction There are many articles that have been written about collaborative online learning. Among the advantages mentioned most often are the development of critical thinking and problem solving skills, and also skills related to self-reflection and the co-construction of knowledge and meaning (Chiong et al., 2012) in order to help learners move beyond what they are able to achieve independently (Posey & Lyons, 2011). Learners in collaborative online learning environments work among team or as group members in order to enhance their performance, and to improve their ability to retain information for longer than when they can whilst working on an individual basis. The purpose of collaborating online is to enable learners to interact with each other, to help them share knowledge, and to facilitate them in exchanging thoughts through using online portals (Geiss & Roman, 2013). Online learning incorporates collaborative learning which is recognized as a great and worthwhile opportunity, not only in terms of allowing access for fellow students, but also in giving them chances to work together so to make theor learning take place online more effectively, as compared to the traditional face-to-face class (Tsai, 2011). Collaboration Generally, collaboration is now recognised as one of the most essential skills that are necessary for learners to function effectively within an online community. It is necessary that we know how students learn, communicate, and how the increasing functionality of technology is raising the bar of communication and collaboration (Sulisworo, 2012). By definition, collaborative learning refers to certain environments in which learners engage in a common and authentic task and the methodology applied therein, and in which each peer is dependent on and accountable to the others in the group or team (Tsai, 2011). Bouroumi and Fajr (2014) defined collaboration and cooperation as "teaching strategies that allow students to interact with each other and work together in order to learn more efficiently" (p.66). Cullen, Kullman, and Wild (2013) also mentioned that the practice of collaboration involves "a situation where two or more people learn or attempt to learn something together, and it has strong support from a range of theoretical perspectives including motivation, cognition, and social cohesion" (p. 426). Collaborative learning has also been defined as a pedagogy in which learners come together, usually in groups, and grain in their learning as a result of mutual cooperation. In this arrangement, each student also takes responsibility for assisting in the learning of other students in the group besides his or her own learning, and in this way, they all help each other to be more successful in their learning. The success of initiatives in collaborative learning online also relies on the instructor’s ability to use new media tools to develop and enhance their students’ ability to learn (Westbrook, 2012). In theory at least, activities in online collaborative learning can be considered to play an important role in the new learning paradigm (Capdeferro & Romero, 2012). The gathering of knowledge and of individual thoughts allows online communities to guide the discussions amongst the learners and with experts in a way that overlaps the relationships between cognitive presence, social presence, and teaching presence (Geiss & Roman, 2013). On the other hand, collaborative learning also presents certain significant challenges related to issues such as equity in participation , team building, student assessment, difficulty due to travel and personal schedules. Further potential challenges include student apathy and even hostility towards working in groups, difficulties with selecting groups, lack of essential skills for working in groups, and the problem of free-riders.It is also possible for differences in student abilities to become challenging, especially if they are great, implementing an appropriate scheme of assessment for individuals in the group can be difficult, critical discourse can become difficult to facilitate effectively, and logistical challenges can arise due to the separation of time and place of different learners. As such, experienced and perceived difficulties in implementation often inhibit the adoption of collaborative learning strategies by instructors in online courses (Posey & Lyons, 2011). In this paper, the aim is to study how a collaborative online learning community can be designed based on the learners’ perspective by examining twenty published articles. The challenges associated with collaborative online learning may then be able to be addressed through more appropriate instructional design strategies. Literature Review Alvarez (2012) conducted research in Israel that analyzed the nature of teacher feedback during a writing assignment that took place collaboratively. The purpose was to identify the possible effects of the feedback on the revision of a text written jointly by university students while learning in an asynchronous online learning environment, i.e. at different times. The analysis was conducted during the development of three editions of a Masters level course in online learning,which tooktwo weeks to accomplish. The students (n = 83) were divided into 16 work groups, and they carried out a co-evaluation assignment by using a specific technology tool. On one hand, the results indicated that when teacher feedback includes the giving of suggestions and questions, the students overall tended to respond more constructively. In this case,hey were more inclined to discuss the content they were working with, and consequently, this resulted in significant changes being made in the arguments of the text that they were revising. This shows the importance of the group context for promoting discussion, and of working collaboratively online to construct meaning. On the other hand, the results also indicated that making direct corrections did not cause any significant results, especially when the feedback received was merely corrective or in which the teacher simply expressed his or her opinion. The problem was that it did notgenerate sufficient student responses other than making confirmations. In Caballé’s (2014) study, the aim was to promote online collaborative learning by providing authentic opportunities for interaction, challenging tools and empowering users , so as to influence both learner motivation and engagement. The sample under study comprised of 24 students who submitted the final questions. The researcher focused on a new type of learning objective called a collaborative complex learning object (CC-LO), which was presented based on the virtualization of collaborative learning in order to leverage knowledge gained during the live sessions. As a positive outcome, there was attention on the collaborative sessions, which were animated. The learners were able to observe how avatars discuss and collaborate with each other, how discussion threads develop, and how knowledge is constructed, refined, and then consolidated. Furthermore, it was shown that the more complex aspects of the learning process, such as cognitive assessment and emotional awareness, can also be incorporated in the CC–LOs whilst they are being created. The most noticeable result however, was that happiness was given the highest value whereas the values attributed to the emotions of sadness, anxiety, and anger were very low. Furthermore, Cabble (2010) conducted research to find out the characteristics of the feelings of frustration as a selected negative emotion among online learners that engage in online Computer-Supported Collaborative Learning (CSCL) experiences, and to then identify the sources to which the learners attribute their expression of frustration. The sample of online learners that participated in the study (n = 40) were all students enrolled in the Master of ICT and Education program of the Universitat Oberta de Catalunya (UOC). However, the results also revealed that frustration is actually a common feeling among students who engage in online collaborative learning experiences. The students in this case identified the perception of an asymmetric collaboration among teammates as the most important source of their frustration. Other factors that lead to frustration for online learners were found to include difficulties related to group organization, the lack of shared goals among their team members, imbalances in the quality of individual contributions and the level of commitment, excess of time spent on online tasks, imbalance created between individuals and their collective grades, and difficulties related to communication. As a designer, greater attention should be paid to all these aforementioned reasons. Qiu et al. (2012) conducted a study that examined the effects of class size on the reading and writing loads in graduate-level online courses. Relationships were examined between class size, note reading, note writing, and collaborative discourse. The study investigated 25 graduate-level online courses in which 25 instructors and 341 students were invovled, of which 10 10 instructors and 12 graduate students were interviewed. The researchers employed a mixed method research design that gathered and analyzed both qualitative and quantitative data. The results revealed the importance of selecting an appropriate class size because class size was identified as a major factor that can affect note-reading and writing loads in online graduate courses. In fact, class size was found to be positively correlated with total quantity of notes of students and which instructors read and wrote, but it was negatively correlated with the percentage of notes that students read, their note size, and their note grade level score. In larger sized classes, it was found that participants were more likely to experience the phenomenon of information overload, and that students were more selective in reading notes. The data also suggested that dividing students into small groups for the purpose of holding discussion can minimize the overload effects of large sized classes. The interviewees believed that the use of small groups in large classes benefitted by improving the quality of their collaborative discussions. The findings suggested that the optimum size of a class would be13 to 15 students. A study by Chang’s (2011) examined the factors of student satisfaction and performance in an online collaborative learning environment that involved students in two different cultural contexts. These two contexts were a group of Chinese first year students learning at a national comprehensive university in Beijing, China (n= 159), and a group of Flemish first-year students (n= 205) learning at a regional comprehensive university in Flanders, Belgium. A parallel online learning environment was arranged for both of them involving collaborative group work.The important finding in this study was that student preferences for online collaborative learning may be related to cultural differences, as there can be significant cultural differences with respect to student satisfaction and academic performance in an innovative online learning environment. The results showed that there were significant differences between the Chinese and Flemish students with respect to satisfaction levels withonline collaborative learning. On average, the Flemish students were inclined to spend relatively more time in online collaboration, and were more satisfied overall with the results of group work compared to the Chinese students. The Flemish students did however, have easier access to a computer and the Internet, and on average, they spent more time online, and they frequently used more emails as opposed to skills and knowledge. The Chinese students on the other hand, seemed to enjoy online collaborative learning to a greater extent, and were happier with the contributions made by group members compared to the Flemish students. Overall, both groups of students were satisfied with the functions of the online learning environment. They also appreciated the opportunities to work collaboratively, and agreed that collaborative learning does indeed promote a deeper understanding of the learning content. Chiong (2012) conducted a study to examine the extent of active collaboration in online study groups at a university in Australia. The participants were 193 studentswho were organized into small study groups, with each group having 5 to 8 participants. There were 32 groups altogether, and each group had a member of teaching staff attached to it. Specifically, there were three instructors, each responsible for around 10 to 12 groups, and the groups followed a novel approach based on Evolutionary Game Theory (EGT). This study found that the lack of, or low participation of other group members, was the major reason for students deciding not to participate in the group, or else to reduce their extent of participation. Another commonly faced obstacle was time constraints that were imposed by personal life and job commitments, and this was coupled with the students’ recognition that active participation in a group requires a significant amount of time to be devoted. However, the study also revealed a recognition of the perceived benefits of social learning, and of peer help and support. Furthermore, one of the primary reaons for participating was to exercise their ability to directly improve their final grade, which was by gaining points on their assignments that depended on group collaboration. The goal of getting some extra points that would contribute to the final grade was also a highly common motivator among the students. Fomsi and Njoku (2011) carried out a study to determine the readiness of undergraduate students for the use of online chat for collaborative learning. Data was collected from four hundred (n=400) students from the department of Education Science, University of Port Harcourt, Nigeria. The results indicated that there was no significant difference in the technology based competencies possessed by male and female students, and in the number of hours they spent on online chat (which was less than 2 hours per week). They also discovered that high percentages of both male and female students did not prefer to use chat rooms as an asynchronous communication tool, and that this may be because many of them did not have a personal computer, which reduced their ability to use this form of communication. Gafni & Geri (2010) conducted a study to examine the impact of the relative effectiveness of optional and compulsory online forum assignments. The study compared the grades of MBA students (n=120) who studied an advanced elective course in a blended distance learning university during the years 2005-2009 at the Open University of Israel. The results of this indicated that students are not usually enthusiastic in becoming engaged in collaborative online learning, and that they tend to adopt a satisficing attitude unless they are sufficiently motivated. The results thus demonstrated that compulsory online forum assignments do have potential in improving learning during learning processes. Moreover, the low involvement of students in forum discussions showed that the main factor that contributes to student performance is their own analysisthat is posted on the forum, and which may not necessarily involve collaborative learning explicitly. Guasch et a. (2013) conducted a study to determine what type of feedback best improves the quality of collaborative writing, and the effects of feedback on student learning in an environment based on written communication taking place asynchronously. This research was carried out within the virtual campus (VC) of the Open University of Catalonia (UOC). The students were generally enrolled in this course in their final semester of the bachelor program, and the participants numbered 201 students. This study used a quasi-experimental design with a multi method approach for the information analysis. Students participated in a module structured in three didactic sequences (DSs), which is the prototypical organization of a degree module at UOC. Each DS contained a continuous assessment assignment, following the University’s own evaluation model. The first DS was structured as an individual assignment. The second DS formed the intervention and was performed in groups. The third and final DS was again individual and served as a post-test. For each DS, students wrote an essay. Concerning the type of feedback, the results revealed that epistemic feedback or epistemic and suggestive feedback best improved the quality of collaborative writing performance. The results also indicated the feedback significantly affected students’ collaborative writing performance. All students performed better on the final collaborative essay than on the first draft. The differences in the types of feedback showed the writing products of students receiving epistemic feedback improved more than those of students receiving either corrective feedback or suggestive feedback. Jung et al. (2012) carried out another study that determined the stress factors in online collaborative learning as perceived by 226 Japanese students who used English in their online interactions. They investigated the relationship between the learners’ perceptions and these stress factors. This study involved three phases and the use of a specially prepared research instrument developed for gathering data. The first phase involved the development of the instrument to define various stressors in online collaborative learning based on previous studies. The second phase involved interviewing four educators and seven university students who had gained experience in online collaborative teaching and learning, and were able to refine and elaborate the stressors, and finalize the survey items in light of their comments. The third hase involvedverifying the stressors developed in the first two phases quantitatively with a large number of university students. Th above-mentioned study identified four particular stress factors: (1) self-efficacy, (2) instructional design, (3) technology use, and (4) collaborative process-influence. All of these increased the Japanese university students’ stress levels in collaborative learning online. The investigators suggested that the foreign language skills of students and their language self-efficacy should be considered first of all given that the cultural characteristics of students need to be more developed in terms of cultural sensitivity by using scaffolding strategies that are appropriate to their learning styles. For instance, there were important items that were affected, such as lack of skills in reading and writing in English, lack of confidence in the language, fear of expressing opinions in its, being more conscious about the reactions of peers when using it, the problem of unfamiliar jargons, lack of guidance on using English, lack of confidence in posting in the written format, lack of confidence in responding quickly enough, and the lack of time for self-reflection.The second factor highlighted in the above mentioend study was instructional design. This concerned such design activities as selecting and designing the collaborative tasks, facilitating and supporting the teaching and learning strategies, and structuring and evaluating online collaboration. Lack of clear expectation for group tasks, unclear evaluation criteria, an inappropriate choice of tasks, lack of timely support by instructors, unclear direction for collaborative work, and lack of provision by instructors in giving proper support at different stages of the online discussion also affected the students’ stress levels. The third important factor of echnology use was found to be closely related to equipment and coursework use and support. The important items in this regard included technical errors caused by online discussion tools, lack of technical support, either the lack of or too many rules regarding the use of technology, difficulties related to understanding how to use the online tools, and the fear of having technical problems such as a computer breakdown or lost connection while studying online. The other factors were collaborative processes that had the potential to be ause problems whilst working, and during decision-making within the learning groups. This included, for instance, difficulty in decision-making in groups, the pressure for working collaboratively in groups, disliking studying online, disliking waiting for the responses of other students also engaged in online discussions, a mismatch with the preferred learning style, and low levels of confidence in contributions made by other learners whhilst working collaboratively. Liu & Wenzhen (2012), conducted a study in which they examined the needs of using an online learning system involving the use ofcollaborative media forsupporting adult learning. The participants in this study were 168 graduate students who were both full and part time students working at a Western State University. An online Learning Management System (LMS) called Web Campus was chosen as the collaborative media for building an online learning support community. The study used a Likert questionnaire consisting of 32 statements with open-end questions, which was designed to measure three predictor variables: (1) needs for studies, (2) needs for communication and support, and (3) needs for general information. The results of the study indicated that all three attributes of needs could be used to predict the extent to which an adult learner believes in the needs of such an online learning community. The results indicated that a linear relationship exists between the response variable, needs of online community, and the three predictor variables (i.e. needs for studies, needs for communication and support, and needs for general information). The findings of this study indicated that firstly, an online learning community is needed because it can provide flexibility, and that this is regardless of whether teh students worked full-time or part-time. The students could therefore participate in activities or exchange information without facing any restriction of time or location. Secondly, the students expressed preference for an online learning community that also involved some opportunities to meet face-to-face as well. Thirdly, the study showed the need for students to undergo some training in using the media based tools for their activities. The students also expressed the desire to have more convenient access to technical help. Finally, the students would have liked their professor, advisors and some administrative staff to also be a part of this community so that even stronger support can be provided. Pittenger & Olson-Kellogg (2012) carried out a study in which they evaluated the development and delivery of a hypertext case scenario document for use as a capstone assessment tool for students training for physical therapy at doctoral-level. Multiple sources of quantitative and qualitative data were collected from 50 students enrolled in 2009, thirty-eight of whom completed the entrance survey. Student background attitudes and experiences with online learning and collaborative projects were primarily positive. Attitude towards working as a group was primarily “accepting” of working in a group as eighty-seven percent (87%) of the students (32) responded as such. Sixteen percent (16%) of the students (6) were “very excited.” Despite being generally accepting of working collaboratively in this course, students voiced a number of consistent concerns through open-ended feedback from the entrance survey. Many of the students were concerned about an unequal contribution of work by different group members, of their grade being affected by the lack of work contributed by others in the group, poor communication within groups, and with individuals in the group taking over and not allowing for cooperative learning to take place. The results showed that implemening digital writing collaboratively using a hypertext document is both a feasible and an effective educational strategy. The students working collaboratively with others in groups helped because of being able to bounce treatment ideas off each other to best treat the individual. From a negative standpoint, few students submitted reflection statements and also provided very negative responses in the course evaluation. They claimed that it was frustrating at times when other group members were not participating equally, and were contributing less to the project, and when some students liked to plan ahead whereas others wait until the last minute. Rimor et al. (2010) conducted a study in which they investigated and classified interaction patterns of students working in a collaborative database learning environment using Google Docs. They analyzed the interactions that took place between 44 graduate students in an Open University course. This study employed both qualitative and quantitative measures to analyze the inputs of participants in the database. The results showed that the interaction between the learners using the Google Docs collaborative database was comprised of various dimensions of interaction, and further that the majority of these dimensions represent a relatively low level of complexity. This included the dimensions of externalization, initiative and rapid consensus. Externalisation occurs when the learner makes a contribution to the discussion without referring to those made by other learners. Initiative means group members serving as sources of knowledge by asking questions and by obtaining knowledge reciprocally, and rapid consensus refers to learners accepting the opinions of their peers, not necessarily because they agree with them or because they have been persuaded, but because it provides a way of advancing with the discussion quickly. The finding showed that relatively, around 50% of the discussions between the participants did not develop into any complex levels of interaction. The discussions held by the students typically ended at the stage of “externalization” of personal knowledge, and when no further contribution was made by other participants. The discussion usually developed from this s(externalization) to that of initiation, so that the opinions and viewpoints of other participants could be clarified which then ceased at this level. The results indicated that assertions of both externalisation and initiation constituted almost half of all the assertions. The most frequent dimension observed was single criteria level of building agreement rapidly. Also, the frequency of the complex patterns of interactive discussions evolved into integrative and conflict agreements, which constituted almost 50% of all discussions that developed amongst the students learning in the collaborative database environment. All these aforementioned findings show that the learning activity that takes place in this kind of collaborative online environment strongly promotes “rapid consensus” (29%) and “initiative” (25%). Furthermore, they show that learners are inclined to accept the opinions of their peers, not necessarily because they agree with them, or because they have been persuaded to do so, but because they find it is a way of quickly advancing the discussion. Sherblom et al. (2013) conducted another study to investigate the influence of students knowledge, motivation, skills, apprehension, and the medium of communication medium on the degree of their participation in online classroom discussion. There were 91 student participants at two mid-western universities. This study employed a survey, and queried self-perceptions of (CMC) of the five aforementioned factors, as well as the outcome of their degree of participation in online classroom discussions. The results of the study showed that knowledge, skill, apprehension, and motivation beared the strongest influences on student participation in online classroom discussions. The CMC medium had less of an effect on student participation, but its effect was worth mentioning briefly following the discussion of the other stronger influences. So (2009) conducted a study to investigate how groups make their decision in using asynchronous online discussion forums in a non-mandatory setting, and how after the group decision is made, the group members use online discussion forums for completing a collaborative learning project that requires complex data gathering and research processes. Participants of this study enrolled in a graduate-level blended learning course at a major university in the United States. There were 55 students divided into 12 groups, with each group having 3 to 5 members. Each group conducted only those activities that were deemed to be necessary in order to complete the project, and they presented their findings to the entire class during one of the in-class meetings. The collaborative learning processes were facilitated by making CMC tools such as online spaces for group discussions, file sharing, and real-time chat rooms were made available to the groups. Data was then collected using a self-reporting survey on CMC tools as well as face-to-face interviews with a select number of the students. The results revealed no significant relation between individual proficiency levels, previous experiences, and reported hours of use. The group members with some previous experiences affected the initial decision to try the CMC tools. Moreover, the decision was also affected by the nature of the collaborative learning tasks. After the first trial was shown to be successful, the groups decided to use a certain type of CMC tool in preference to others, and it then became a norm to communicate through using that tool. However, when the initial experience was unsuccessful, the groups explored other alternative forms of communication, and then face-to-face interaction was perceived to be the most efficient mode for conducting group communication. Also, when group decisions were made, the group members participated in online discussion forums at both individual and group levels. The results showed that all group members participated in online discussions, and that the discussion threads were sustained until the completion of the collaborative project. In a study carried out by Tsai (2011), different combinations on students’ computing skills in blended courses were explored through applied online Self-Regulated Learning (SRL) and Collaborative Learning (CL). The participants were 221 undergraduate students in Taiwan. There were four classes of online students: (1) those engaged in online self-regulated learning (SRL) with initiation (G1, n=53), (2) those learning online with initiation (G2, n=68), (3) those engaged in online Collaborative Learning (CL) without initiation (G3, n=68), which were all experimental groups, and the last class, (4) those receiving a traditional lecture (G4, n=32), which was the control group. The students in this study were divided into teams, each of which consisted of 6 to 7 members for engaging in discussion and collaboration. The findings showed that in general, students who received an intervention of online SRL/CL with initiation attained significantly better grades for practical computing skills, whereas those that received the traditional lectures had poorer grades among all the four classes. The results indicated that the computing skills of students in G1 were significantly higher than of those in G2, so the effects of online SRL in the implementation of CL were positive and higher than without it. Also, that the computing skills of students in G2 were found to be on average higher than of those in G3. This suggests that teacher led initiation could help students learn better, and contribute more to the development of their computing skills. The results also indicated that students who learned in the CL context (G1, G2, G3) had significantly higher grades than those who received instruction via the system of traditional lectures (G4). However, there were potential threats to the validity of these results, as they also suggested students in the comparison group were being taught more enthusiastically, and were therefore more involved and motivated than the students in the control group. A study by Korkmaz (2013) examined and attempted to determined the attitude of computer education and instructional technology teacher candidates towards collaborative online learning. The author used mixed method design that consisted of both quantitative and qualitative research phases. The sample comprise of 599 teachers in the quantitative phase and 16 in the qualitative phase, and data was collected from 11 different universities. The results indicated that the participants who were candidates, i.e. training to be teachers, had a generally positive attitude toward collaborative online learning. They believed that online collaborative learning activities have a strong capability to improve the academic achievement and individual development of students in cases where each individual fulfills his or her responsibilities. They also reported that success in online collaborative learning activities requires each individual to fulfill these responsibilities both properly and in a timely manner. Also, it is necessary for individuals to have prior knowledge about the subject, and their level of knowledge and willingness to be in a group must be considered when creating a group. Moreover, the individual learners should preferably be homogeneous in terms of academic achievement level when creating groups as far as possible. Online monitoring systems should then be developed and used in a way that make sure every individual is able to performs his or her task properly and in a timely manner. References Alvarez, I., ialvarezv@uoc.edu, Espasa, A., & Guasch, T. (2012). 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L. 1., alp@umn.edu, & Olson-Kellogg, B. (2012). Leveraging learning technologies for collaborative writing in an online pharmacotherapy course. Distance Education, 33(1), 61-80. doi:10.1080/01587919.2012.667960 Posey, L., & Lyons, L. (2011). The instructional design of online collaborative learning. Journal of Education Research, 5(3), 361-380. Retrieved fromhttp://search.ebscohost.com/login.aspx?direct=true&db=eue&AN=80240121&scope=site Qiu, M., Hewitt, J., & Brett, C. (2012). Online class size, note reading, note writing and collaborative discourse. International Journal of Computer-Supported Collaborative Learning, 7(3), 423-442. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ976357&scope=site;http://dx.doi.org/10.1007/s11412-012-9151-2 Rimor, R., Rosen, Y., & Naser, K. (2010). Complexity of social interactions in collaborative learning: The case of online database environment. Interdisciplinary Journal of E-Learning & Learning Objects, 6, 355-365. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=58036296&scope=site Sherblom, J. C., Withers, L. A., & Leonard, L. G. (2013). The influence of computer-mediated communication (CMC) competence on computer-supported collaborative learning (CSCL) in online classroom discussions. Human Communication, 16(1), 31-39. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=ufh&AN=91248529&scope=site So, H. -. (2009). When groups decide to use asynchronous online discussions: Collaborative learning and social presence under a voluntary participation structure.Journal of Computer Assisted Learning, 25(2), 143-160. doi:10.1111/j.1365-2729.2008.00293.x Sulisworo, D. 1.,. (2012). Designing the online collaborative learning using the wikispaces. International Journal of Emerging Technologies in Learning, 7(1), 58-61. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=eue&AN=79851148&scope=site Tsai, C. (2011). Achieving effective learning effects in the blended course: A combined approach of online self-regulated learning and collaborative learning with initiation. CyberPsychology, Behavior & Social Networking, 14(9), 505-510. doi:10.1089/cyber.2010.0388 Westbrook, C. (2012). Online Collaborative Learning in Health Care Education. European Journal Of Open, Distance And E-Learning, (1), 21 Read More