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Medical and Dental Students’ Perceptions and Experiences of Collaborative Learning: A Systematic Review

2011; Volume: 9; Issue: Supplement Linguagem: Inglês

10.11124/01938924-201109321-00001

2202-4433

Abdulaziz Almajed, Tracey Winning, Vicki Skinner, Raymond Peterson,

Biomedical and Engineering Education

Review question/objective The objective of this systematic review is to synthesise the best available evidence on the medical and dental students’ experiences of collaborative learning. More specifically, the objectives are to identify and synthesise evidence of: 1. Students’ perceptions of collaborative learning, including what collaborative learning activities involve; 2. Students’ understanding of what collaborative learning means; and 3. Facilitating and inhibiting factors that students experience in collaborative learning activities. Background Collaborative learning approaches have been used for the past four decades by many educational organisations at both general and higher education levels. Collaborative learning is defined as an ‘umbrella term for a variety of educational approaches involving the joint intellectual effort by students, or students and teachers together’. (Page 11)1 Others have described it as ‘a situation in which two or more people learn or attempt to learn something together’. (Page 1)2 These definitions describe how collaborative learning operates through the interaction and communication of learners working together, which facilitates interactive knowledge building. Collaborative learning is a common feature of contemporary higher education, and can be facilitated in different ways, e.g. through face-to-face collaboration, or through online activities.3,4 Over the years, universities and colleges have tried different collaborative learning approaches, as summarised below: ‘1. Co-operative learning; 2. Problem-centred instruction: Guided design; Cases; Problem-centred instruction in medical education; Simulations; 3. Writing groups; 4. Peer teaching: Supplemental instruction; Writing fellows; Mathematics workshops; 5. Discussion groups and seminars; 6. Learning communities.’ (Page 15-24)1 Collaborative learning has been characterised as having a number of advantages over other learning methods, e.g. sharing learning experiences, learning skills for searching for information, development of cognitive conflict within a collaborative learning team can encourage learning and simulation of a real work environment.5,6 In medical and dental education, the advantages of collaborative learning are very useful as it provides the students with the required skills for the future real work environment. Doctors and Dentists need to have good communication and social skills, be self-dependent in finding information, have sufficient skills to analyse and solve their patients’ problems and be able to effectively collaborate with colleagues and other health professionals. Collaborative learning approaches are anticipated to develop these skills in medical and dental students, which subsequently will improve the effectiveness of practitioners’ clinical performance. Many programs have made use of these advantages by implementing various collaborative learning activities within their programs; for example, McMaster University in Canada introduced Problem Based Learning (PBL) in their medical program in 1969. Subsequently, many medical and dental schools included collaborative learning opportunities within their programs.6,7 Positive outcomes of collaborative learning have been demonstrated in other contexts. For example, collaborative tasks were reported to increase secondary school students’ understanding of different concepts.8 In addition, a positive correlation between the quality of students’ interactions and their learning outcomes was found. Investigation of students’ accountability and interdependence in a collaborative learning setting demonstrated that 90% of students mentioned that they acted as a team with their classmates, and distributed the tasks fairly between themselves, based on each individual’s skill.9 This study also reported that students learnt from each other’s experience and skills, and that this promoted friendship. Key elements of the design of the collaborative learning activity in this study were that students were allowed to select their friends to be their group members and to select their preferred task subject. This, in turn, helped them to work better as a team and enhanced feelings of relevancy, and ownership of the project. One half of the students mentioned that they encountered conflicts and differences of opinion at the start, but that these were solved by means of group discussion. The effect of friendship is clear, especially when we look to other studies that have monitored students who do not know each other before they started their studies.3 The above studies focussed on the positive results of collaborative learning. Despite the advantages of collaborative learning, various issues may affect student progress. Specifically, collaborative learning and the resultant learning outcome can be directly affected by students’ habits, personal preferences, previous experience, identity, and their understanding of different learning concepts.3,4,10,11,12 As collaborative learning processes require students’ collaboration, the effect of these issues can be reflected on all the students. As noted previously, students’ level of motivation for working in groups and using their own initiative to make the learning process work are significant factors that influence the collaborative learning outcomes.2 For example, while students in a PBL environment felt an ownership of knowledge, developed a sense of responsibility and gained several skills, it was noteworthy that at least one group tended to have a dominant member who tried to lead the group.3 Students who possess strong leadership traits may dominate group members, and this may have a positive effect if they are pulling in the same direction as the tutor. However, this can have a negative effect if the individual with the leadership focus acts in a disruptive or rebellious way, against the main goals of the tutor and the group. In contrast, other groups usually worked collaboratively, switching leaders when necessary in accordance with whoever had the best relevant skills and knowledge. Some students needed time to get used to each other’s styles, and their interaction with other members occurred only after they felt their contributions would be respected. From these findings, it can be concluded that when students do not know each other before they get involved in collaborative work, group dynamics do not always go to plan. Students’ personal factors have a clear and obvious effect on group work, such as the presence of a leading personality, a person’s willingness to work with other members, accepting others’ learning methods, and fear of making mistakes. In contrast, when friendship exists between group members these factors have less effect, or may disappear altogether.9 Along with the previously illustrated factors that affect the collaborative learning environments, culture also has an effect on students’ conception about the nature of the collaborative learning process. A study by Zhang et al. analysed a collaborative environment with respect to culture in a distance learning undergraduate project-based learning course in Taiwan.13 This study showed collaboration emerged only among students within their group, but between groups the situation became competitive. Students were uncomfortable about the change in the instructor’s role from teaching to facilitating. They also reported that Chinese students avoided disagreeing and criticizing colleagues to maintain cultural harmony. Cognitive conflicts are considered to be necessary in collaborative learning environments, as noted previously, this stimulates students’ learning and knowledge searching.5 These findings show how cultural behaviours may interfere with these theoretical underpinnings of the collaborative learning context. Further evidence that students do not routinely engage in cognitive conflicts in collaborative learning was reported following investigation of the different types of activities students completed in PBL groups. It was reported that 53.3% of activities were collaborative, 27.2% were self-directed and 15.7% were constructive.14 Investigation of students’ interactions during the PBL reporting stage showed that cumulative reasoning was the most practised part of learning-related interactions, representing 63% of discussions, whilst exploratory questioning and conflict management represented 10% and 7% of the interactions respectively.15 Students spent little time on knowledge-related conflict management, and this is incongruent with other theoretical findings regarding the PBL process, which consider cognitive conflict to be necessary to elicit learning.5 These findings show how students avoided spending time in asking questions and managing the knowledge-related conflicts, which may result in them completing their session without solving all their issues. In addition to cultural and social factors, language differences between group members may affect the dynamics of the group. A qualitative investigation involving interviews with 19 first year undergraduate international students (Chinese and Indonesians) at the University of Melbourne found that students had difficulty in participating in small group discussions, even though the students insisted that language differences had no effect on their contribution.16 It was concluded that ‘students appear to take up discourses that both resist, and to some extent reinforce culture and language as factors in their identities’. (Page 234)16 Students’ transition from traditional learning methods to collaborative learning methods may present challenges for some students in terms of obtaining information. In a collaborative learning setting, some students find it difficult to know the required level of knowledge, and they usually become uncertain about their knowledge and whether they are ‘on the right track’ or not.10 This differs from what is experienced in conventional learning environments, where students are formally presented with the required knowledge by their teachers by means of lectures and seminars. These views were demonstrated in a study by Bearn and Chadwick10 which found that some students prefer a collaborative learning environment, while others did not and perceived there was a lack of guidance regarding their level of knowledge. It has been demonstrated that students interact with learning activities based on their previous experiences, preferences and learning habits.11,17 Depending on their prior experiences, students who adopt a deep learning approach are self-dependent and use their own learning methods. In contrast students who adopt a surface learning approach depend on external regulation more than self-regulation.11 Students who adopt an inactive learning approach seek external regulation and support in certain occasions e.g. before exams. In addition, these variations in approaches highlight that instructional measures do not have a direct effect on learning outcomes or on the productivity of the learning environment, rather these are affected more by students’ habits and preferences.11 Therefore, different learning strategies may be needed to avoid incomplete achievement of the intended curriculum goals. Cooperation is a crucial factor that needs to be developed between students in collaborative learning particularly in online courses to achieve the course aims. Online student interactions are important in promoting a psychological feeling of proximity and satisfaction. These outcomes were demonstrated by So et al. who examined students’ perceptions of collaborative learning, social existence, and overall satisfaction in an online learning course.18 Students who perceived high levels of collaboration tended to be more satisfied with their course and had high levels of social contact and existence. These findings stress the importance of designing course content in a way that satisfies students’ needs and expectations to maximize potential student interactions. In addition to the previously mentioned factors, collaborative learning may be influenced by a number of different factors associated with students’ individual identities, personalities and social conditions.4 For example, race, age, gender, friendship, their skill set and knowledge-related identity such as the level of interest in academic learning. The role of these factors in an online collaborative learning course, demonstrated that the oldest student in the group acted as a teacher to the other group members. In addition, groups of friends who formed a sub-group or clique, and worked together without inviting the other group members, had a negative influence on the group and individual learning performance. It was evident that racial or cultural background can affect the collaboration and harmony of a learning group, which was reflected in the individual performance. For example, racial minority students’ performance declined when they were moved out of their cultural comfort zone into another group, whilst it improved when they worked with members of their own racial or cultural group.4 Hughes concluded that knowledge-related identity is the most important and effective identity in collaborative learning.4 Students with the greatest level of academic interest, regardless of race, age, sex, etc. were most likely to achieve the greatest success. Some students did not have an interest in learning and, hence, were not motivated to contribute to group work. Hughes suggested that educational institutions and facilitators should work to promote collaboration between all student identities, but a specific focus on knowledge-related identity is important.4 The findings of Hughes’ study supports other findings regarding the roles that individuals play in group dynamics. The environment of collaborative learning is complicated, but it has been shown that it is controlled by several social, psychological and personal factors. Students’ behaviour and interpersonal interactions during group activity may directly affect the students’ relationships with each other and the quality of the processes of their collaboration. Students’ behaviour may affect other students’ cooperation and, hence, lower their trust and confidence in sharing information and knowledge. Research has found that some students, prior to the start of their collaborative course, come with high expectations, but later realise that they have to be challenged to gain knowledge compared to their previous traditional learning experience.10 Research has also shown that some students seek continual reassurance that their performance is adequate during collaboration, to improve self-confidence.13 In summary, it is clear that there are different learning behaviours, habits and preferences that affect the learning environment, and learning does not strictly follow as desired by the curriculum planners or tutors.11 Students who form a racial minority may have different thought processes to other students, and barriers may form which could restrict them from being fully involved in collaborative learning.4 The dominant racial, cultural or educational group may have preconceived ideas, which prevent them from accepting and inviting the view of racial minority students who work with them. Additionally, language skill differences between students may act as a major barrier against full involvement for students in a collaborative learning task, and may reduce the student’s self-confidence about his/her interactions with native language speakers.16 Traditional or cultural beliefs and background may negatively affect freedom to contribute in collaborative tasks, as was reported by Zhang et al. with Chinese students who avoided cognitive conflict with other students to maintain good cultural relationships.13 These sorts of problems directly undermine the basic principles and ideas of the collaborative learning environment, because cognitive conflicts encourage students to search and investigate for knowledge.5 It has been shown previously that students’ personality and preferences impact on the learning environment more than what we think.3 Personal identity and psychological roles influenced the students’ selection criteria of their preferred team members. Some students got involved easily with other group members, and some of them experienced difficulty with engagement. Fear of negative responses from other group members prevented some students from interacting with the rest of the group, especially when they were not sure about the credibility of their contribution. Therefore, it is clear that the collaborative learning context is affected by different and multiple factors that are associated with: students personality and psychological state; technical skills; self-confidence; learning styles; interest in learning; racial background; language differences; acceptance of others, and cultural beliefs and backgrounds.3,4,11,13,16,17 These factors may influence the learning outcome in a negative way, or a positive way. It can be concluded that the present evidence on students’ experiences of collaborative learning is conflicting. Designing a suitable learning context requires a full understanding of students’ perceptions, ideas and beliefs about the collaborative learning environment. In the light of this conflicting evidence regarding the students’ experiences of collaborative learning along with the importance of this learning approach in medical and dental education, a systematic review is needed to provide evidence about students’ perceptions and understanding of collaborative learning. This in turn will inform the literature with key information that can aid in the improving of collaborative learning approaches in medical and dental programs. Additionally, this will help researchers to assess the situation and identify the type of further research that is needed in this area of medical and dental education. An initial search was performed of the Cochrane Database of Systematic Reviews, JBI Library of Systematic Reviews, Medline, CINAHL and ERIC to identify if there are any existing systematic reviews on this topic. No existing or on-going systematic review on this topic has been found. It is important to note that a systematic review that is titled as ‘Effects of Cooperative Learning instructional techniques on science achievement among students ages 11 years to 20 years’ that was published in The Campbell Collaboration Library of Systematic Reviews has been found but this systematic review is not related to professional education and is restricted to school-based collaborative learning activities. Inclusion criteria Types of participants The quantitative and qualitative components of this review will consider studies that include medical and dental students regardless of gender or ethnicity. ‘Medical students’ refer to students enrolled in formal University medical programs, either as undergraduate or postgraduate students, regardless of the duration of the program or the speciality. ‘Dental students’ refer to students enrolled in formal University dental programs, either as undergraduate or postgraduate students, regardless of the duration of the program or the speciality. Phenomena of interest The phenomena of interest for both the quantitative and qualitative components of the review will be the students’ perceptions, conceptions, beliefs, understandings, opinions and experiences of collaborative learning. Types of studies/publications The quantitative component of the review will consider experimental studies, quasi-experimental studies and observational analytical and descriptive studies. The qualitative component of the review will consider studies that focus on qualitative data designs such as, but not limited to, phenomenology, ethnography and grounded theory. In the absence of research studies, other text such as opinion papers and reports will be considered. Search strategy The search strategy aims to find both published and unpublished studies. A three-step search strategy will be utilised in this review. An initial limited search of MEDLINE and CINAHL will be undertaken followed by analysis of the text words contained in the title and abstract, and of the index terms used to describe the articles. A second search using all identified keywords and index terms will then be undertaken across all included databases. Thirdly, the reference list of all identified reports and articles will be searched for additional studies. Studies published in English will be considered for inclusion in this review. Studies published between 1970-2011 will be considered for inclusion in this review. The justification of this time frame is that the majority of studies investigating learning in groups in health professions education began around this time with the introduction of PBL in medical education.7 The databases to be searched include: PubMed CINAHL Embase Scopus Informit ERIC Web of Knowledge A hand search of relevant medical and dental journals (articles from the last ten years) will be performed: for example, European Journal of Dental Education, Medical Education Journal and Medical Teacher. The search for unpublished studies will include: Mednar University medical and dental schools websites: for example, University of Adelaide, McMaster University. Collaborative learning associations, societies or networks: for example, Association for Dental Education in Europe, Association for Medical Education in Europe, American Medical Education and Research Association. Initial keywords to be used are presented in the following table:Table: No Caption available.For searching the various databases, different forms of the keywords (singular and plural forms) and syntax that is specific to the search database, will be used. Assessment of methodological quality Quantitative papers selected for retrieval will be assessed by two independent reviewers for methodological validity prior to inclusion in the review using standardised critical appraisal instruments from the Joanna Briggs Institute Meta Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) (Appendix I). Any disagreements that arise between the reviewers will be resolved through discussion, or with a third reviewer. Qualitative papers selected for retrieval will be assessed by two independent reviewers for methodological validity prior to inclusion in the review using standardised critical appraisal instruments from the Joanna Briggs Institute Qualitative Assessment and Review Instrument (JBI-QARI) (Appendix I). Any disagreements that arise between the reviewers will be resolved through discussion, or with a third reviewer. In the absence of research papers, text and opinion papers will be critically appraised by using standardised critical appraisal instruments from the Joanna Briggs Institute Narrative, Opinion and Text Assessment and Review Instrument (JBI-NOTARI) (Appendix I). Data collection Quantitative data will be extracted from papers included in the review using the standardised data extraction tool from JBI-MAStARI (Appendix II). The data extracted will include specific details about the interventions, populations, study methods and outcomes of significance to the review question and specific objectives. Qualitative data will be extracted from papers included in the review using the standardised data extraction tool from JBI-QARI (Appendix II). The data extracted will include specific details about the interventions, populations, study methods and outcomes of significance to the review question and specific objectives. In the absence of research papers, data from text and opinion papers will be extracted by using the standardised data extraction tool from JBI-NOTARI (Appendix II). Data synthesis Quantitative papers will, where possible, be pooled in statistical meta-analysis using JBI-MAStARI. All results will be subject to double data entry. Effect sizes expressed as relative risk or odds ratio or weighted mean differences and their 95% confidence intervals will be calculated for analysis. A random effects model will be used and heterogeneity will be assessed statistically using the standard Chi-square. Where statistical pooling is not possible the findings will be presented in narrative form including tables and figures to aid in data presentation where appropriate. Qualitative research findings will, where possible, be pooled using JBI-QARI. This will involve the aggregation or synthesis of findings to generate a set of statements that represent that aggregation, through assembling the findings rated according to their quality, and categorising these findings on the basis of similarity in meaning. These categories will then be subjected to a meta-synthesis in order to produce a single comprehensive set of synthesised findings that can be used as a basis for evidence-based practice. Where textual pooling is not possible, the findings will be presented in narrative form. In the absence of research papers, data from text and opinion papers will be synthesised by using JBI-NOTARI. Conflicts of interest None. Acknowledgements I would like to acknowledge Dr Catalin Tufanaru MD, MPH. (Research Associate, Synthesis Science Unit (SSU), The Joanna Briggs Institute, Faculty of Health Sciences, The University of Adelaide, Contact: [email protected]) for supervising the primary reviewer through this protocol. Also I would like to acknowledge The Joanna Briggs Institute for providing peer review feedback on the systematic review protocol. This systematic review forms the initial phase of a PhD program, School of Dentistry, Faculty of Health Sciences, The University of Adelaide, SA 5005, AUSTRALIA.