Results and Discussion
In this section, students’ interactions in the Moodle environment are described, and then the quality of their interactions in terms of the extent to which new knowledge was co-constructed are examined. The density, centralization, and centrality measures of the course are presented along with the coding results of forum posts.
Social Network Analysis of Students’ Interaction Patterns
According to course requirements, each student had to respond to at least two other students’ original posts in each forum. Thus, each student sent out a minimum of 30 responses to other students in the 15 forums throughout the semester, resulting in 945 total responses. Dividing the total by the number of students, it was found that the average number of responses sent out by each student was 42.95 throughout the semester. This indicates that students in the online community actively participated in discussions and interacted with each other.
The case–by–case matrix of who built on whose forum posts is presented in Table 2. This matrix shows the valued relations among all students, thereby providing more detailed information about the interactions among students. The numbers in the cells show how many responses in total the students whose name appears in the left column sent out to the students whose names appear on the top row. This table provides information on who was (or was not) interacting with whom, as well as the strength of these connections, thereby allowing us to glean an overall understanding of how established the community was.
For the density, centralization, and centrality measures, the matrix was dichotomized (cutoff value = 0) using the function of “transformation of data” provided by the aforementioned SNA software (i.e., Ucinet 6.0). Dichotomous relations are marked with one of two values: 1 (representing an existing relation) and 0 (representing no existing relation) (see Table 3).
Table 2
Students’ Interaction Patterns: Who Built on Whose Notes?
|
D |
C |
J |
K |
A |
V |
J |
B |
E |
E |
J |
N |
R |
S |
T |
A |
C |
K |
S |
E |
T |
K |
Diana |
0 |
6 |
4 |
1 |
6 |
3 |
9 |
3 |
12 |
1 |
3 |
3 |
0 |
5 |
3 |
3 |
2 |
0 |
2 |
8 |
7 |
6 |
Carol |
8 |
0 |
1 |
1 |
5 |
3 |
1 |
4 |
1 |
0 |
0 |
0 |
1 |
2 |
0 |
2 |
0 |
1 |
1 |
0 |
2 |
0 |
Jenny |
4 |
0 |
0 |
0 |
2 |
4 |
2 |
2 |
3 |
2 |
5 |
1 |
0 |
1 |
3 |
3 |
0 |
0 |
2 |
2 |
3 |
1 |
Kristina |
0 |
3 |
1 |
0 |
2 |
1 |
2 |
4 |
0 |
4 |
0 |
0 |
2 |
2 |
0 |
2 |
5 |
2 |
0 |
2 |
1 |
1 |
Anna |
10 |
0 |
1 |
0 |
0 |
1 |
3 |
6 |
0 |
1 |
3 |
2 |
2 |
0 |
0 |
0 |
0 |
1 |
0 |
4 |
0 |
0 |
Vicky |
4 |
1 |
2 |
0 |
2 |
0 |
2 |
0 |
3 |
1 |
1 |
0 |
2 |
2 |
2 |
0 |
2 |
2 |
2 |
5 |
8 |
1 |
Jimmy |
8 |
0 |
3 |
2 |
5 |
0 |
0 |
3 |
8 |
2 |
6 |
4 |
4 |
1 |
7 |
8 |
3 |
9 |
5 |
5 |
10 |
4 |
Ben |
0 |
3 |
0 |
0 |
4 |
2 |
2 |
0 |
2 |
0 |
0 |
0 |
1 |
2 |
0 |
0 |
0 |
0 |
4 |
1 |
3 |
0 |
Emma |
8 |
2 |
1 |
0 |
0 |
0 |
3 |
2 |
0 |
1 |
0 |
2 |
0 |
0 |
2 |
1 |
1 |
2 |
0 |
3 |
8 |
1 |
Ellen |
1 |
0 |
0 |
0 |
0 |
1 |
0 |
2 |
2 |
0 |
1 |
1 |
2 |
3 |
2 |
3 |
2 |
4 |
1 |
1 |
1 |
1 |
Jack |
2 |
2 |
5 |
1 |
2 |
1 |
5 |
0 |
1 |
2 |
0 |
1 |
0 |
0 |
2 |
2 |
3 |
1 |
3 |
2 |
3 |
0 |
Nelson |
6 |
1 |
1 |
0 |
0 |
1 |
2 |
3 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
2 |
1 |
2 |
1 |
1 |
0 |
Robin |
1 |
4 |
1 |
5 |
2 |
2 |
0 |
1 |
0 |
1 |
0 |
3 |
0 |
1 |
0 |
4 |
0 |
0 |
1 |
3 |
0 |
1 |
Sherry |
3 |
2 |
0 |
2 |
1 |
2 |
0 |
3 |
0 |
1 |
2 |
3 |
1 |
0 |
1 |
5 |
2 |
4 |
3 |
0 |
3 |
3 |
Tina |
3 |
0 |
2 |
0 |
0 |
6 |
13 |
1 |
10 |
1 |
5 |
0 |
0 |
2 |
0 |
5 |
6 |
3 |
6 |
2 |
2 |
2 |
Amy |
3 |
0 |
1 |
0 |
0 |
2 |
7 |
1 |
4 |
2 |
3 |
0 |
1 |
6 |
4 |
0 |
3 |
5 |
3 |
1 |
3 |
1 |
Charlie |
1 |
1 |
1 |
2 |
1 |
5 |
3 |
2 |
2 |
1 |
2 |
0 |
0 |
2 |
5 |
5 |
0 |
9 |
2 |
4 |
2 |
1 |
Karen |
0 |
1 |
1 |
0 |
1 |
3 |
0 |
0 |
1 |
2 |
1 |
0 |
1 |
2 |
1 |
2 |
7 |
0 |
2 |
2 |
2 |
2 |
Susan |
0 |
0 |
2 |
2 |
0 |
1 |
2 |
1 |
1 |
1 |
0 |
3 |
2 |
1 |
3 |
1 |
1 |
2 |
0 |
1 |
0 |
2 |
Emily |
1 |
1 |
2 |
1 |
5 |
1 |
2 |
5 |
3 |
0 |
1 |
0 |
1 |
2 |
1 |
2 |
3 |
1 |
0 |
0 |
3 |
4 |
Tiffany |
7 |
2 |
3 |
1 |
0 |
6 |
8 |
1 |
10 |
0 |
1 |
0 |
1 |
5 |
2 |
3 |
0 |
0 |
1 |
2 |
0 |
1 |
Kristin |
2 |
2 |
2 |
1 |
1 |
2 |
4 |
0 |
0 |
0 |
1 |
0 |
0 |
2 |
4 |
2 |
1 |
1 |
2 |
7 |
3 |
0 |
Based on the analysis, the density of the network in terms of students responding to other students’ forum posts was .75. Lipponen et al. (2003) conducted research to investigate the pattern of interactions among a group of students mediated by a Virtual Web School. They found a density of .39 and considered this high. Therefore, it is reasonable to conclude that a density of .75 is very high. The results indicate that all students were well connected with each other, which in turn indicates that the online learning community established through online interactions was quite cohesive.
Table 3
Dichotomized Interaction Pattern: Who Built on Whose Notes?
|
D |
C |
J |
K |
A |
V |
J |
B |
E |
E |
J |
N |
R |
S |
T |
A |
C |
K |
S |
E |
T |
K |
Diana |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
Carol |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
0 |
1 |
1 |
0 |
1 |
0 |
1 |
1 |
0 |
1 |
0 |
Jenny |
1 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
Kristina |
0 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
0 |
1 |
0 |
0 |
1 |
1 |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
Anna |
1 |
0 |
1 |
0 |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
0 |
0 |
Vicky |
1 |
1 |
1 |
0 |
1 |
0 |
1 |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
Jimmy |
1 |
0 |
1 |
1 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
Ben |
0 |
1 |
0 |
0 |
1 |
1 |
1 |
0 |
1 |
0 |
0 |
0 |
1 |
1 |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
0 |
Emma |
1 |
1 |
1 |
0 |
0 |
0 |
1 |
1 |
0 |
1 |
0 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
Ellen |
1 |
0 |
0 |
0 |
0 |
1 |
0 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
Jack |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
0 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
Nelson |
1 |
1 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
0 |
Robin |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
0 |
1 |
0 |
1 |
0 |
1 |
0 |
1 |
0 |
0 |
1 |
1 |
0 |
1 |
Sherry |
1 |
1 |
0 |
1 |
1 |
1 |
0 |
1 |
0 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
Tina |
1 |
0 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
Amy |
1 |
0 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
Charlie |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
Karen |
0 |
1 |
1 |
0 |
1 |
1 |
0 |
0 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
Susan |
0 |
0 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
0 |
1 |
Emily |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
1 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
1 |
1 |
Tiffany |
1 |
1 |
1 |
1 |
0 |
1 |
1 |
1 |
1 |
0 |
1 |
0 |
1 |
1 |
1 |
1 |
0 |
0 |
1 |
1 |
0 |
1 |
Kristin |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
0 |
0 |
1 |
0 |
0 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
1 |
0 |
Centralization measurement enables one to see if the network is centralized around a certain focal participant in the network. The SNA output demonstrated that both the out-degree centralization and the in-degree centralization were 16.3%. This value is low, indicating that the interaction among students was not centralized, but was instead distributed among many participants.
The results for the Freeman’s degree and betweenness centrality measures for each individual student are presented in Tables 4 and 5. These measures allow for the identification of the most central participants in the course. Since dichotomous and directed matrix was used, the degree for each student is the row or column sum for that student. The SNA results show that both the out-degrees (total number of other students to whom a particular student sent comments) and the in-degree (number of other students from whom a particular student received comments) of students varied between 10 and 19. The mean of both out-degree and in-degree was 15.73, while the standard deviations were 2.30 and 2.24, respectively. Three students (Dianna, Jimmy, and Charlie) had the highest out-degree at 19 each and one student (Ben) had a relatively low out-degree of 10. High out-degree indicates that a student actively created connections to other students in the online community (Lipponen et al., 2003). As for the in-degree measure, two students (Emily and Vicky) had the highest in-degree of 19. Nelson had the lowest in-degree of 10. High in-degree indicates that other students often interact with this particular student. Students having the highest total degree—sum of out-degree and in-degree—have the most interactions with others. Emily, with a total degree of 37, had the most interactions with other students in the class. Finally, betweenness results showed that Jimmy and Emily had the highest betweenness values, which indicates that they were in a central position in the interaction network.
Although a student with the highest out-degree did not necessarily have the highest in-degree, one student (Emily) did have the highest total degree (sum of in- and out-degree) and betweenness value. Thus, it is appropriate to conclude that Emily was the most visible student in the online learning community. It appears that no student was in an isolated position in the network since none had both the lowest total degree and the lowest betweenness value.
Based on the findings, one might conclude that Moodle has the capability to support a highly interactive online environment that facilitates broad participation for all students. Further, Moodle may be able to provide an online learning environment that allows students to participate fully in the course, which in turn is an important prerequisite for high quality online learning. According to Esther (2001), such frequent social interactions also scaffold students’ knowledge construction.
Table 4
Individual Degree Centrality
Student |
OutDegree |
InDegree |
NrmOutDeg |
NrmInDeg |
Dianna |
19 |
17 |
90.48 |
80.95 |
Jimmy |
19 |
17 |
90.48 |
80.95 |
Charlie |
19 |
15 |
90.48 |
71.43 |
Emily |
18 |
19 |
85.71 |
90.48 |
Sherry |
17 |
17 |
80.95 |
80.95 |
Amy |
17 |
17 |
80.95 |
80.95 |
Vicky |
17 |
19 |
80.95 |
90.48 |
Jack |
17 |
14 |
80.95 |
66.67 |
Susan |
16 |
17 |
76.19 |
80.95 |
Elen |
16 |
15 |
76.19 |
71.43 |
Tina |
16 |
15 |
76.19 |
71.43 |
Kristin |
16 |
16 |
76.19 |
76.19 |
Karen |
16 |
16 |
76.19 |
76.19 |
Jenny |
16 |
18 |
76.19 |
85.71 |
Tiffany |
16 |
18 |
76.19 |
85.71 |
Kristina |
15 |
11 |
71.43 |
52.38 |
Carol |
14 |
14 |
66.67 |
66.67 |
Robin |
14 |
14 |
66.67 |
66.67 |
Emma |
14 |
16 |
66.67 |
76.19 |
Nelson |
13 |
10 |
61.91 |
47.62 |
Ann |
11 |
14 |
52.38 |
66.67 |
Ben |
10 |
17 |
47.62 |
80.95 |
Table 5
Individual Betweenness Centrality
Student |
Betweenness |
nBetweenness |
Jimmy |
8.90 |
2.12 |
Emily |
8.37 |
1.99 |
Dianna |
7.52 |
1.79 |
Vicky |
7.39 |
1.76 |
Sherry |
7.36 |
1.75 |
Susan |
6.60 |
1.57 |
Jenny |
6.19 |
1.48 |
Tiffany |
5.77 |
1.37 |
Robin |
5.52 |
1.31 |
Karen |
5.31 |
1.27 |
Emma |
4.85 |
1.16 |
Jack |
4.85 |
1.15 |
Charlie |
4.84 |
1.15 |
Ellen |
4.66 |
1.11 |
Amy |
4.60 |
1.10 |
Kristin |
4.40 |
1.05 |
Carol |
3.90 |
0.93 |
Ann |
3.83 |
0.91 |
Ben |
3.47 |
0.83 |
Nelson |
2.78 |
0.66 |
Kristina |
2.45 |
0.58 |
Tina |
2.44 |
0.58 |
In order to give a clearer picture of the entire network, the interaction pattern was also visualized using SNA software, Netdraw2.0, which is presented in Figure 1. The dark black lines indicate reciprocal interactions, meaning the pair of students commented on posts made by each other. The light gray lines indicate unidirectional interactions, with the arrows indicating the direction of interaction.
Figure 1. Visualization of teachers' online interaction patterns.
