Inquiry-Based Learning With or Without Facilitator Interactions

Thushani Alwis Weerasinghe, Robert Ramberg and Kamalanath Priyantha Hewagamage

VOL. 26, No. 2

Abstract

This paper discusses findings of a study investigating how students, in four online courses, engaged in inquiry-based learning with and without support from a facilitator. The investigation was conducted by analyzing discussions of the online courses using the community of inquiry model. The results of the study imply that students in online discussions can engage in deep and meaningful learning, even when there is no facilitator interaction. Further, the findings of the analysis suggest that successful inquiries are possible without teacher or facilitator interactions, if learning environments are designed to support students being interactive and the students have motivation, regulatory skills and a willingness to collaborate with their peers.

Résumé

Dans le cadre de cet article, nous discutons les résultats obtenus dans une étude visant à déterminer comment des élèves, participant à quatre cours en ligne, se sont engagés dans un processus d’apprentissage par enquête, soit avec ou sans l’aide d’un facilitateur. L’étude a été réalisée en analysant les discussions relatives aux cours en ligne au moyen du modèle du Community of Inquiry (CoI). Les résultats de l’étude laissent entendre que les élèves participant aux discussions en ligne peuvent réaliser des apprentissages approfondis et significatifs, même en l’absence d’interaction avec un facilitateur. De plus, les résultats de l’analyse suggèrent que des enquêtes peuvent être réussies sans intervention de la part d’un enseignant ou d’un facilitateur si, d’une part, les environnements d’apprentissage sont conçus de manière à favoriser l’interactivité des élèves et, d’autre part, les étudiants ont la motivation, les compétences requises et la volonté de collaborer avec leurs pairs.
  

Introduction

Inquiry-based learning (IBL) is a question-driven learning approach, which has the potential to promote students’ active engagement in online learning. It has been considered an effective method of engaging students in higher-order learning in university-level educational programmes (Garrison & Cleveland-Innes, 2005; Oliver, 2008). IBL processes support students from scientific disciplines in constructing subject knowledge, as well as acquiring reasoning skills and engaging in practices collaboratively (Hmelo-Silver, Duncan, & Chinn, 2007).

According to Hmelo-Silver et al. (2007, p. 100), a teacher in an IBL environment "plays a key role in facilitating the learning process and may provide content knowledge on a just-in-time basis". This line of reasoning implies that teacher or facilitator interactions are essential for students’ learning in IBL environments. Also, research studies pertaining to online learning environments (e.g., Fredericksen, Pickett, Pelz, & Maher, 2000; Swan, 2002; Gibbings, Lidstone, & Bruce, 2010) indicate that the teacher-facilitator’s interaction positively correlates with students’ learning. However, Anderson, et al (2001) report that such a teaching role in an online community of inquiry can be considered a collaborative activity, i.e., consisting of one or more participants in the community. Accordingly, students that belong to a community of inquiry have the opportunity of assuming the role of a teacher. Therefore, it is important to examine teacher interactions further to shed light on, and possibly determine, whether student-student interactions can be more or less important than teacher-facilitator-student interaction for students’ learning in IBL environments. Furthering our knowledge on this would be beneficial for instructional designers and online course developers, who are interested in knowing what sort of interactions should be emphasized and implemented in IBL environments.

In order to examine teacher interactions in an IBL environment, discussions in the learning environment can be analyzed using the teaching presence component of the community of inquiry (CoI) model (Anderson et al., 2001). The CoI model is the analytical tool based on the community of inquiry framework that integrates the interactions of participants in an inquiry-based learning environment. The interactions can be examined by analysing the discussions for social, teaching, cognitive and metacognitive presences. Social and teaching presences help to describe collaboration among the participants in a discussion. The cognitive presence component of the CoI model can be used to investigate the critical thinking skills of the students. The regulatory skills and efficacy, or motivation for engaging in inquiry-based learning, can be explored using the metacognitive presence component of the model.

Shea et al. (2011), who investigated the relationship between the major elements of the CoI model, noted that teaching presence in their learning environments correlated significantly with social presence and cognitive presence. Similar findings were reported by researchers who used the CoI survey instrument, where students’ perceived social, cognitive and teaching presences were investigated (e.g., Arbaugh, 2008; Garrison, Cleveland-Innes, & Fung, 2010; Shea & Bidjerano, 2009). Shea, Vickers and Hayes (2010b) explored the teaching presence in two online courses. The students’ teaching presence (peer teaching) in the course discussions increased gradually, while the instructor’s participation decreased. The discussions in these courses were directed with pre-prepared learning activities and students were assigned the responsibility of teaching. However, the discourses that we analyze and discuss in this paper were not based on pre-decided topics, and students were not instructed to perform teaching functions. The paper discusses how students engaged in inquiry-based learning, with or without the support of a facilitator, who was supposed to play the teaching role in the online discussions. The study is conducted by analyzing threaded discussions in four online courses (http://vle.bit.lk) in a university-level educational programme.

Purpose

Students in a higher educational context can enhance their critical thinking skills by engaging in inquiry based learning processes. Such an inquiry process in an online learning community can be explained with respect to four major phases: triggering event (initial phase), exploration, integration and resolution (Garrison, Anderson, & Archer (2000).

Moving students to higher phases in the inquiry process, i.e., integration and resolution, is considered an indication of students engaging in deep and meaningful learning (Shea et al., 2010a). Even though teaching presence is considered crucial for this move (Celentin, 2007), Anderson theorized that it is possible for deep and meaningful learning to take place when “at least one of the three forms of interaction (student–teacher; student-student; student-content) is at a high level”, while, “the other two may be offered at minimal levels, or even eliminated, without degrading the educational experience (Anderson, 2003, p. 4). This theory implies that deep and meaningful learning is possible even when there are no student-teacher interactions, and this motivated us to investigate how students engage in inquiry based learning in online courses where there are no student-teacher interactions. Therefore, this paper investigates how students in online courses engage in an inquiry-based learning process with or without teacher (facilitator) interactions.

The study was conducted by analyzing two sets of discussion threads where, in one set, students received support from a facilitator, and, in the other, they did not. The findings of the study are discussed with a view to answering the following questions:

1. Can students solve their problems collaboratively, without any teacher (facilitator) interaction?
   
2. How do students support each other in solving problems?
   

Context

The Bachelor of Information Technology (BIT) programme, at the University of Colombo School of Computing, is delivered through a virtual learning environment (VLE) based on a Moodle platform. It is an external degree programme and the students do not receive any lectures from the university teachers, either at a physical location or through a synchronous communication platform. Students meet the university staff only at registration and the final examinations. At the registration desk each student receives an introductory CD of the VLE, which demonstrates the components of the online courses and how to use discussion fora to communicate with other participants. Throughout the courses, the students are supposed to use the e-learning materials in the VLE. The VLE provides interactive learning content, activities and quizzes with automatic feedback, assignments, fora to discuss with other students and sets of downloadable notes that have been authored by the respective teachers.

The discussion threads for the analysis were selected from the first-semester courses, conducted from October 2009 to March 2010. With the exception of one course (C-1), which contained only theoretical subject content, all the courses dealt with both theoretical and practical subject matter. All these courses covered information technology related subjects. More than 2,000 students registered to use the first semester courses in the VLE. The majority of the students in the courses belonged to the 18 to 25 year age group. There was one facilitator to support the students in their discussions. At the beginning of the semester, the facilitator sent a welcome message from each course giving the students instructions in how to update their profiles and how to participate in the social fora. These fora supported students getting to know each other by participating in informal discussions. There were also subject-discussion fora that could be found in each section of a course. The students used these fora to discuss their subject-specific problems and related issues with the other students. The fora were kept open for the duration of the course. However, none of the online course activities were mandatory assignments required to obtain the degree certificate.

Method

In order to understand how students interacted with each other and solved their problems with or without facilitator interactions, two sets of discussion threads were randomly selected from the abovementioned four online courses and analyzed using an adapted version of the Community of Inquiry model.

The analysis using the model revealed the frequencies of cognitive, social, teaching and metacognitive presences in the two sets of discussions. These quantitative findings were compared to determine whether there was a difference between students’ inquiry processes in the two samples and, thereby, to ascertain whether students could solve their problems without facilitator interactions. For this purpose, the findings of the content analysis are discussed with respect to correlation statistics. The correlations were calculated to find the relationship between the teaching presence, and each of the other ‘presences’ in the discussions. Further content in the discussions were qualitatively analyzed to investigate and shed light on how students helped each other in solving their problems.

Sample of Discussions

The sample of discussions consisted of 20 threads where the facilitator had not contributed to the discussion (S_A) and 20 threads where there was at least one message in the first half of a thread posted by the facilitator (S_P). Each discussion in the sample had at least five messages. While S_A consisted of 173 messages, all posted by the students, S_P had 206 student messages and 45 facilitator messages. The number of students that had contributed to a discussion ranged from 3 to 12.

Analytical Instrument

The community of inquiry (CoI) model is the analytical instrument used in the discussion-content analysis reported in this paper. This instrument consists of four separate coding schemes to identify each kind of social, cognitive, teaching and metacognitive presences in a textual discourse.

Social presence describes "the ability of learners to project themselves socially and emotionally in a CoI" (Garrison et al., 2000, p. 94). The social presence coding scheme has three categories: affective, open communication and group cohesion. These categories are defined "in terms of the participants identifying with the community, communicating purposefully in a trusting environment and developing interpersonal relationships" (Garrison, Anderson, & Archer, 2010, p. 7).

Cognitive presence "is the extent to which learners are able to construct and confirm meaning through sustained reflection and discourse in a critical community of inquiry" (Garrison, Anderson, & Archer, 2001, p. 5). The scheme has four categories: triggering event; exploration; integration; and resolution. They represent the phases of an inquiry process in a collaborative learning environment. Triggering event is the initiation phase of a critical inquiry where an issue, dilemma or problem is identified or recognized. The next phase is exploration, where learners tend to grasp the nature of the problem and move to explore relevant information. In the integration phase learners construct meaning from the ideas generated in the exploratory phase. The last phase of the critical inquiry model is resolution, which indicates a resolution of the dilemma or problem that caused the triggering event.

Teaching presence is "the design, facilitation and direction of cognitive and social processes for the purpose of realizing personally meaningful and educationally worthwhile learning outcomes" (Anderson et al., 2001, p. 5). Teaching presence represents the role of teaching, which is carried out with the collaborative involvement of participants in a community. The first category, ‘design and organization’ considers the role of a teacher during the planning and designing process of online learning activities. The other two categories — ‘facilitating discourse’ and ‘direct instruction’ — investigate signs of teaching presence during students’ engagement in learning activities.

Metacognitive presence describes "the set of higher knowledge and skills to monitor and regulate manifest cognitive processes of self and others" (Akyol & Garrison, 2011, p. 184), as well as the motivational states required for achieving learning goals. There are three categories in this coding scheme: knowledge of cognition (KC); monitoring of cognition (MC); and regulation of cognition (RC). KC refers to students’ self-awareness as learners, and motivation for learning in general. MC and RC represent activity-based metacognitive states, which can be observed during the learning process.

The model was adapted to make it more suitable for analyzing discussions in our online courses, and was evaluated for its reliability, using two threads from each of the four courses. The negotiated inter-rater reliability values ranged from 0.9344-1.0000 with Holsti’s co-efficient, and 0.8354–1.0000 with Cohen’s kappa, for discussions in all the courses (for more information see Weerasinghe, Hewagamage, & Ramberg, 2012).

Unit of Analysis and Coding Procedure

The unit of analysis was a chunk that could be a complete message or a meaningful segment of a message, with a cue of a presence that could be identified using the analytical instrument. The analysis was conducted adhering to a set of guides: (1) reformulate messages where essential; (2) understand the inquiry process; (3) comprehend the coding schemes; (4) study the context of the discussions; (5) consider only one coding scheme at a time; and (6) double-check the work (Weerasinghe, Hewagamage, & Ramberg, 2012).

Findings

The analysis of the discussion content using the CoI model supported our understanding of the distribution of social, cognitive and teaching presences in the discussions. The percentages of ‘presences’ in the two samples are displayed in Figs 1 and 2.

Fig 1: Percentages of ‘presences’ in SA

Fig 2: Percentages of ‘presences’ in SP

According to the pie charts in Figs 1 and 2, S_A has a higher percentage of cognitive and metacognitive presence than S_P. The chart in Fig 2 indicates more students’ teaching presence than facilitator teaching presence. The percentage of students’ teaching presence in Fig 1 is close to the sum of the two percentages of students’ teaching presence and the facilitator’s teaching presence in Fig 2. In order to understand students’ activities during the inquiry process, the frequencies of cognitive presence with respect to each category were counted.

Problem-Solving Capability

In S_A ‘presences’ were made up of 13% triggering events (TE), 33% explorations (EX), 41% integrations (IN) and 13% resolutions or applications (RA). S_P had 12% of TE, but there were only 8% of RA. Also, it had a smaller percentage of IN than in S_A. Furthermore, in order to understand how students solved their problems with or without the facilitator’s support, the frequencies of cognitive presence (CP) in the two samples were compared with respect to each course: C-1, C-2, C-3 and C-4 (see Figs 3 and 4). As can be seen in Figs 3 and 4, the students could find solutions to their problems, irrespective of the facilitator’s presence or absence in the discussions.

Fig 3: Frequency of CP- in SP

Fig 4: Frequency of CP- in SA

Additionally, in order to find whether there was a relationship between the facilitator’s teaching presence and other ‘presences’ in the discussions, correlations were calculated (see Table 1).

Table 1. Correlations in S_P

Notes: *p-value < .05; **p -value < .01

Surprisingly, there was no significant correlation between the facilitator’s teaching (F’-TP) presence and the students’ cognitive, metacognitive or social presences. However, there was a significant correlation between students’ teaching presence (S’-TP) and the cognitive presence (CP). Also the statistics in Table 1 show that S’-TP had a positive impact on both metacognitive presence (MP) and social presence (SP). Correlations were calculated using the other data set as well, in order to see whether we could find the same relationships between the ‘presences’ in the discussions without the facilitator’s contribution. The results are displayed in Table 2.

Table 2. Correlations in S_A

Notes: *p-value < .05; **p -value < .01

The correlation statistics in Table 2 are quite similar to the statistics in Table 1. Therefore, the results can be interpreted to show that the students in the courses could engage more in the inquiry processes when they received more teaching support from their peers. In other words, peer teaching was a critical factor for students engaging in inquiry-based learning. Moreover, the correlation statistics revealed that the students’ social presence and metacognitive presence (regulatory skills and motivation) had a positive impact on cognitive presence (students’ learning). Therefore, we further examined the distribution of social presence and metacognitive presence in the two samples.

Social presence. The count of ‘continuing a thread’ indications seemed to dominate the frequency of ‘open communication’ (OC). Therefore, we decided to ignore the continuing thread indicator. However, even after excluding it, OC was the category with the highest number for social presence (SP) clues (see Table 3). The majority of the chunks in both samples were identified using the following indicators: ‘referring explicitly to others’ messages’; ‘requesting support’; ‘encouraging and complementing’; and ‘expressing agreement or disagreement’. Nevertheless, all the other indicators were also used to discover a considerable number of OC clues in the discussions.

The group cohesion category (GC) had the second largest number of chunks, and the majority of them indicated ‘addressing or referring to the group using inclusive pronouns’ or ‘vocatives’ such as ‘brother’, ‘sister’, and names. The rest had the signs of ‘salutation and greeting’. There were no clues about sharing information unrelated to the course, which might also have been matched with the GC category of the SP coding scheme.

There were a very small number of humour indications in both samples. Most of the chunks matched with the affective expression (AE) category had clues of conventional or unconventional expressions to express emotions. The results in Table 3 show that the students in both samples had a similar pattern of interaction in building their social presence in the discussions.

Table 3. Social Presence

Table 4. Metacognitive Presence

Metacognitive presence. The results of the metacognitive presence (MP) in the two samples can be explained in a slightly different way (see Table 4). The students in discussions where the facilitator was not participating (S_A), engaged in more monitoring of cognition (MC) activities than the students in the other sample. This may mean that when the facilitator was not participating in the discussions, the students took more responsibility for monitoring (assessing) their learning (cognition). However, in S_P there was a 34% of knowledge of cognition (KC), while in S_A there were only 28%. This indicates that the students brought in their previously constructed knowledge, or expressed their motivation for studies more when the facilitator participated in the discussions.

Peer Support

The two sets of data, which were obtained by analyzing discussions using the teaching presence coding scheme, were examined further with respect to the list of indicators (see Table 5). The sample of discussions where the facilitator was absent (S_A) had more teaching presence per message than in the other sample (S_P). This signifies that the students performed the role of teaching more when the facilitator was not participating in the discussions. Furthermore, the results in Table 5 reveal that the students provided more facilitation (facilitating discourse), and assessed peer contributions when the facilitator was not participating in the discussions.

Table 5: Students’ Teaching Presence

Design and organization. In S_A, there were five discussions that started with sample examination questions. The initiators of the discussions had provided the appropriate instructions for others to try out the questions. Later in the discussion the initiators had also contributed to the discussions by exploring, integrating and applying, or testing the solutions. The first message in each of these discussions indicated an effective utilization of medium, which could be categorized under ‘design and organization’. Despite this, there was another slightly different sign of design and organization, which could also be matched with the indication of utilizing the medium effectively. In this case, a student, having completed an assignment, wanted to discuss an issue of answering a challenging question. In order to build up the question, the student described a critical context and asked: ‘What will happen if these kinds of things are questioned at an exam? Can somebody answer NO, and others answer YES?’ The student argued that there could not be a specific answer to some questions and invited the peers to express their opinions regarding this. However, in the middle of the discussion, informed that the deadline for the assignment had passed, this student posted the assignment question, which led to initiating another discussion that revealed how the question in the assignment had been answered successfully. This context implied that the intention of starting the discussion was not solely to solve a problem, but rather to use the medium to discuss some issue relevant to the students’ studies.

Direct instructions. The students in the discussions provided more direct instructions to their peers than other supports. There were messages with specific instructions or advice that experienced teachers would give to their students. For example, a student (S1) pointed out that there was a mistake in a quiz. A peer realized that S1 had misunderstood the question and replied, ‘These types of questions are tricky. So, be careful. Sometimes we may have sufficient knowledge, but what it matters is how we apply it.’ In another instance, a student advised another student, who seemed to be confused and stressed, by replying ‘First thing you should do is clear your mind. If you can spend some time meditating, that’s the best way’.

The students used different approaches to explain their answers to their colleagues: scaffolding; storytelling; presenting ideas in point form; replying in the form of questions and answers; using examples or graphical illustrations to clarify the meaning of text; posting quotations or screen shots to prove their arguments; providing short descriptions and references for more details; and describing things by sharing personal experiences. For instance, in replying to a student question, a peer explained the meanings of ‘verifiable’ and ‘reliable’ using a possible conversation between two passengers and a bus conductor. In another instance, a student provided additional explanation in text to clarify how public internet protocol (IP) addresses and private IP addresses work, and ended the explanation reporting, ‘I hope that explained it a little bit more. I really need a diagram to explain it better’. Even though, in this case, the student had not used a diagram, there were a considerable number of indications that the students had used visual aids to explain their replies (see Table 5). In one discussion, in order to explain how search engines find relevant information on the Internet, a student used a diagram that, apparently, was created by him.

We found that students used different techniques to emphasize the meaning of text, such as capital letters, colours, and bold or large type. All these techniques might have been used to convey messages clearly to their peers.

Facilitating discourse. The most prominent indicators of the facilitating discourse category were ‘acknowledging or reinforcing student contributions’, and ‘encouraging or motivating students to participate in the discussion’. The students acknowledged peers’ responses thanking them for their explanations and support. There were clues that students encouraged or motivated their peers to ask questions for further clarification, or to reply to inquiries in discussions. For instance, a student provided an additional explanation of how to calculate binary numbers and added, ‘If you feel that anything is not clear here, please contact me. It is a pleasure to help you’. Another student, after explaining how Internet protocol addresses work, stated, ‘I guess this is enough for now. Later on you’ll understand what these are. If you have any further questions, just ask. I am happy to explain to my friends.’

In another instance a student answered an inquiry and seemed to have requested a peer contribution, by asking, ‘Can somebody explain it better than this, please?’ Also, it seemed that the students wanted others to comment or give feedback on their replies. For example, after providing answers to questions, the students added sentences such as, ‘Can somebody comment on my answer?’ ‘Comment please’ and ‘What do you think of my answer?’ Also there were indications that the students motivated others to reply to unsolved problems. For instance, a student reported in one discussion, ‘:-(, I’m confused. Can someone else explain this?’

Assessment. The number of chunks matched with the assessment category of the teaching presence coding scheme showed the students’ ability to assess or judge each other’s messages. The chunks matched with this category could be identified with respect to three indicators: ‘assessing student’s ability/skill or knowledge’; ‘assessing content’; and ‘assessing work/task’. According to the results in Table 5, the students in both discussion samples judged the content of their peers’ messages rather more than assessing the knowledge or ability of their peers, or the activities reported or presented in the threads. For instance, in one discussion, while disagreeing with the idea posted in a previous message, a student explained a point of view on the issue and ended the post saying, ‘Anyway, your example of a watch as a closed system is a nice one’. Another student, when correcting an idea reported in a previous message, noted, ‘NOOOOOOO, All those are composite keys’. This post implies that the student was annoyed about the reply in the previous message. Also, there were indications of students acting in a more polite way when providing feedback to others’ posts. For example, after noticing a mistake in a previous message, a student posted, ‘There is a small mistake in the answer. The answer must be 0.00001. You have added an extra fraction digit. It’s obvious that you have done it unintentionally. I just wanted to correct it :-)’.

The students seem to have spent their time not only finding mistakes but also appreciating the content in others’ messages. For example, a student, probably after accessing a link posted in a previous message, reported, ‘It is a very useful link. Very clear!’ This was the first time that this student’s name appeared in the discussion. Therefore we determined that by adding ‘Very clear!’ the student had assessed the clarity of the content on the web page.

Summary of Results and Discussion

The discussions analyzed and studied in the present study dealt with student inquiries, which had been started mainly for the purpose of clarifying meaning, solving a practical problem or for finding correct answers to multiple choice questions. The questions had probably been taken from past examination papers or quizzes in the online courses. The discussions were analyzed using an adapted version of the CoI model. The study investigated whether students could get their problems solved collaboratively, without having any teacher (facilitator) interaction, and how students supported each other in solving their problems related to the courses.

Problem-Solving Capability

All the discussions were in the form of interactive dialogues rather than monologues. The findings of the content analysis, using the cognitive presence coding scheme, implied that the students had moved to higher phases of the inquiry process: integration and resolution/application. This implies that the students had engaged in deep and meaningful learning (Shea et al., 2010a). Furthermore, correlation statistics indicated that both the students who received facilitator support and those who did not could engage in the inquiry processes to an equivalent extent. Therefore, the results can be interpreted as indicating that the students in the online discussions could engage in deep and meaningful learning, even when the facilitator was not contributing to the discussions.

The findings of the current study contrast with the results of researchers who emphasize the importance of teacher interactions for deep and meaningful learning to take place (e.g., Celentin, 2007; Shea & Bidjerano, 2009). Nevertheless, it is in line with the suggestion of Arnold and Ducate (2006), who reported "overt teacher facilitation is not necessary for advanced cognitive presence" (p. 57). Similarly, Richardson and Ice (2010) also found that their students moved to the higher phases of the inquiry process. However, the students in their courses had received teacher support, and the teachers had prepared the discussion activities that the students were engaged in. In contrast, however, the threads analyzed and reported in this paper were started by students themselves in order to solve problems and issues that they encountered during the courses.

Garrison (2007) noted that social presence in a community of inquiry should create the conditions required for inquiry and quality interactions, which can lead to achieving learning goals collaboratively. In the present study, we found that there was a positive correlation between students’ social presence and cognitive presence in both samples, whether the facilitator participated or not. This can be explained by the fact that the social presence in the discussions supported the students while engaging in cognitive activities. Also, there was a significant correlation between the students’ teaching presence and cognitive and social presences in all the courses. Shea (2011) also found that teaching presence in their discussions correlated significantly with social presence and cognitive presence. However, teaching presence in their courses had taken into account the instructors’ interactions during online discussions. Despite this, the results of the present study confirm those of previous studies that emphasized the importance of teaching presence and social presence for effective learning to take place in online learning communities (e.g., Garrison et al., 2000; Shea & Bidjerano, 2009).

In the present study, metacognitive presence correlated significantly with cognitive presence and students’ teaching presence. Metacognitive presence considered students’ efficacy, motivation for learning, and self-regulation. According to Akyol and Garrison (2011, p. 186-187), students "become metacognitively aware and assume the regulatory responsibilities for successfully completing the inquiry process" through the teaching presence. As Anderson et al. (2001) described, the role of teaching presence and its responsibilities in an online community of inquiry are shared between the participants of the community. The students in our online discussions engaged in deep and meaningful learning, even when there was no facilitator interaction. In particular, our study revealed that when the facilitator was not participating in the discussions the students were involved in more metacognitive monitoring activities. Therefore, we believe that the results of the present study provide empirical evidence to support the reasoning of Akyol and Garrison (2011).

Peer Support

The two samples of discussions were analyzed with respect to the indicators in the teaching presence coding scheme. This revealed how the students supported each other in their problem-solving activities. The students in S_A (where there were no facilitator interactions) performed all major teaching functions: designing and organization, facilitating discourse, providing direct instructions and assessing. These were considered with the categories of the teaching presence coding scheme.

Design and organization is usually performed by the facilitator (teacher) in an online discussion (Garrison et al., 2000). However, in our sample of discussions where the facilitator did not participate, there were six message chunks identified by the ‘utilizing the medium’ indicator. The student contributions in these discussions did not count towards their final mark in the degree programme. Therefore, the results may be interpreted to indicate that during the semester the students could become accustomed to the online environment, and had the motivation for collaborative co-construction of knowledge while engaging in peer teaching.

The direct instruction category was the predominant category having an average of 54% (47% in S_A and 60% in S_P) of TP elements. The facilitating discourse category of the TP construct identified the second highest number of TP clues. Anderson et al. (2001) also found similar results in an analysis of online discussion content in two graduate-level courses. Furthermore, the analysis reported in this paper discovered which specific functions or activities of direct instruction and facilitation were supported by the students’ collaborative engagement with inquiry-based learning. According to our findings, for the purpose of facilitating the discourses, the students acknowledged or reinforced peer contributions, and encouraged or motivated others to participate in the discussions. The students seemed to have instructed their peers mostly by offering useful examples or illustrations, providing additional explanations, making explicit references, and providing extra learning resources. Also, there were a significant number of clues indicating the provision of specific instructions or advice, and encouraging learning activities. Most of these indications were connected with peer teaching activities.

The present analysis considered three indicators for identifying clues for the assessment category. Each indicator in the assessment category — assessing the student, content and task — seemed to be important for detecting relevant clues in the discussions. The total number of chunks identified by the assessment category was 19% in S_A and 18% in S_P. This provides a clear indication of students’ willingness to collaborate with others, and their ability to assess peer contributions. Shea and Bidjerano (2009) reported that students in their learning environment ‘appreciated instructors’ judicious participation in online discussions’ (p. 551). We also believe that the students need to feel that teachers are monitoring and have control over student activities in the discussions. However, if students are informed of the goals and the learning objectives of the courses, provided with curriculum and support materials, and have acquired the appropriate regulatory skills to carry on their learning, then there is a possibility for meaningful learning to take place. According to Anderson (2003) deep and meaningful learning can take place even when only one of the three types of interactions: student–teacher, student–student and student–content, is at a high level—while the other two types of interactions are reduced to minimum. Therefore, we suppose that the reason behind the students’ engagement in deep and meaningful learning lies mainly in the design of the courses, which supported student interaction in the online discussions. However, further research is needed to determine which specific design components might have supported students to be interactive in inquiry learning.

Limitations

In the present study, we considered only the discussions that started with student inquiries. There were other types of discussions such as discussions based on sharing information and discussions based on activities where the initiator’s apparent intention was to share his/her information/response and receive comments from others. Some of these discussions also had student inquiries. However, in order to make the study robust and reliable we considered the discussions having more than five messages and dealing only with student inquiries. Also we did not consider the discussions that might have taken place via the private message facility in the online courses, since these seemed to be rarely used.

Conclusion

This paper reported on an analysis of discussions in online courses in an undergraduate-level degree programme. Two sets of discussions — one set with facilitator interactions and the other without — were analyzed using the Community of Inquiry model. The results of the study revealed that students in the online discussions could engage in deep and meaningful learning, even when there was no facilitator interaction. The students in both samples of discussions performed the core functions of teaching, as identified using the teaching presence coding scheme. Therefore, this study provides evidence of meaningful inquiry-based learning taking place with minimal or no teacher support. Hence, it rejects the claim of Krischner, Sweller and Clark (2006), who reported that, "after a half-century of advocacy associated with instruction using minimal guidance, it appears that there is no body of research supporting the technique" (p. 83). However, it is important to emphasize that not only course design factors—which support collaboration—but also student’s teaching presence can be considered critical for successful inquiry-based learning. According to the findings of the present study, students should also be motivated to achieve learning goals, have regulatory skills and a willingness to collaborate with their peers in order for deep and meaningful learning to take place. Further research is needed to determine what design factors can possibly encourage the students’ interactions and enhance students engaging in deep and meaningful learning in online learning environments.

Acknowledgement

This study is supported financially by the Swedish International Development Cooperation Agency through the National e-Learning Centre Project at the University of Colombo School of Computing, Sri Lanka. The authors would like to thank the students who participated in the discussions, as well as the facilitator.

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List of Acronyms

CoI – Community of Inquiry

S_A - The sample of discussions where the facilitator was absent

S_P - The sample of discussions where the facilitator was present

TP – Teaching Presence

F’-TP – Facilitator’s Teaching Presence

S’-TP – Students’ Teaching Presence

SP – Social Presence

CP – Cognitive Presence

MP – Metacognitive Presence

TE – Triggering Event

EX - Exploration

IN - Integration

RA – Resolution/Application

AE - Affective Expression

OC – Open Communication

GC – Group Cohesion

KC – Knowledge of Cognition

MC – Monitoring of Cognition

RC - Regulation of Cognition

Thushani A. Weerasinghe is a lecturer at the University of Colombo. She has experience in designing and delivering online courses, and is doing her PhD at the Stockholm University, Sweden. E-mail: thushani@dsv.su.se

Robert Ramberg, is a Professor at the department of computer and systems sciences at Stockholm University. E-mail: robban@dsv.su.se

K. P. Hewagamage is a senior lecturer at the University of Colombo and senior member of IEEE. E-mail: kph@ucsc.lk