Motivation and participation in inquiry learning within a networked learning environment

University Degree Education and Teaching

Motivation and Participation in Inquiry Learning within a Networked Learning Environment

Abstract

Previous research has demonstrated that the uneven nature of students’ participation is one notable challenge of Computer-Supported Learning. In this study the relations between elementary school students’ motivational orientation and their engagement in computer-supported inquiry learning within a networked learning environment were analyzed. The study was case study in nature; one classroom’s study project was examined across two terms. The participants of the study were the teacher and 31 students of one fifth-grade class. The technical infrastructure of the study was provided by Virtual Web School (VWS) developed by Helsinki City Department of Education. A self-report questionnaire was used to assess students’ motivational orientation. Students’ discourse interaction in the database was investigated through social network analysis. The results of the study indicated that although the teacher tried to facilitate the students’ participation, mainly the high learning-oriented students actively engaged in CSCL. It was encouraging, however, that there was moderate reciprocal interaction across gender and motivational orientation groups. Implications for educational practices will be discussed.

Keywords: Computer-supported collaborative learning, motivational orientation, patterns of participation, social network analysis, progressive inquiry

INTRODUCTION

The emergence of knowledge society is transforming educational practices in many ways. In international assessments innovative learning technology, based on the new information and communication technology (ICT), is seen to lead to a new decade of the learning revolution (Pea et al., 1999). Computer-supported Collaborative Learning (CSCL) is expected to increase the quality of education by engaging students and teachers in coordinated efforts to build new knowledge and to solve problems together (Dillenbourg, Baker, Blaye & O'Malley, 1996).

One of the starting points of the present study is the progressive inquiry model of learning developed by Hakkarainen (1998) and his colleagues in the context of CSCL. Characteristic of progressive inquiry is to go beyond conventional learning by pursuing students' own questions and problems of understanding; generating and discussing their own conceptions and explanations for the problems being addressed. The model implies that students themselves should develop functions of monitoring and controlling learning (e.g., Bereiter & Scardamalia, 1987).

It can be stated that the above-presented elements of progressive inquiry impose rather demanding challenges for an individual student’s cognitive capacity. In addition, any learning or performance situation can, from a student’s point of view, be seen as a ‘coping situation’ with many other, e.g. socioemotional and motivational, demands (Boekaerts, 1993). The goals students pursue in a given learning situation depend partly on each student’s interpretation of these demands. Learning may not be seen as the most crucial (or even rational) aim, if the challenges are perceived as a threat to one’s self-worth (Covington, 1992) or some other issues present in the learning environment ‘fill students’ minds’ (e.g. chatting with friends).

From a motivational point of view students’ personal goals represent the energizing and directing force of activity (Pintrich & Schunk, 1996). In classroom studies it has been found that the learning-oriented students (who seek to increase their knowledge and skills) show more active cognitive engagement in learning activities (Meece, Blumenfeld & Hoyle, 1988; Lehtinen et al., 1995) and tend to choose more challenging tasks than other students (Dweck, 1999). Moreover there is evidence that when working with computer supported learning environments, learning-oriented students are more active creating new knowledge and commenting other students’ inquiries in the database (Järvelä et al., 1999). These findings are also in accordance with studies on students’ preferences considering different instructional practices. It has been reported that while learning-oriented students prefer autonomy and possibilities for challenging work, there seem to be students who are not so willing to participate and ‘be active’ during learning situations (Niemivirta, 1998; Peltonen & Niemivirta, 1999).

Further, there are certain indications that rather than helping to overcome motivational, cultural or knowledge-related differences between students, computer-supported learning leads to increasing learning difficulties and performance differences - without strong teacher guidance (Venezky, 1999). Therefore, the uneven nature of students' participation can be considered to be one of the current problems of Computer-Supported Learning.

On the other hand, the promise of the new computer supported learning environments has partly based on the pedagogical assumption that they include elements, which can be regarded as inherently motivating (e.g. possibilities to solve complex, authentic tasks) despite students’ individual differences and prior experiences (CTGV, 1992; Lin et al., 1995; Savery & Duffy, 1995). A few studies have even demonstrated promising results that in some cases students who have problems in adapting to an ordinary school tasks, may find CSCL very motivating and intriguing (Hakkarainen, Lipponen, Järvelä & Niemivirta, 1999). Consequently, there seems to be a need for a more detailed analysis on the patterns and intensity of students’ participation and on the individual differences behind these phenomena.

The present study focused on uncovering the patterns of students' participation by applying methods of social network analysis that provides statistical tools for examining networking relations between students (Wasserman & Faust, 1995; Scott, 1991). The problem addressed was whether high learning-oriented students who are engaged in conventional educational practices would also be most active in the context of CSCL. Palonen and Hakkarainen (2000) found out that there may be substantial gender differences involved in participation in CSCL. Thus, gender was included in the study design to test for similar differences on this data.

The questions addressed were a) how intensively do ...

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The questions addressed were a) how intensively do elementary school students representing both genders and different levels of learning orientation participate in discourse interaction within a networked learning environment; b) whether and how the students take responsibility over their own inquiry and facilitate each other’s participation; c) whether the students’ discourse interaction is dominated by some students.

METHODS

Participants

The study was conducted in a fifth-grade classroom in an ordinary urban elementary school. Altogether 31 students and one teacher participated in the study, which focused on analyzing the students’ activities in two study projects in history. For supporting collaborative building of knowledge, the students used collaborative software called Virtual Web School (VWS) designed by the Media Center of the Helsinki City Department of Education. The VWS was designed to help students to share information and construct learners’ joint knowledge. Students had their own digital portfolio, where all work could be stored (projects, learning materials). There were four networked computers within the classroom that were used for conducting the project.

Data analysis

The students were administered self-report questionnaire to identify their initial motivational orientation at the beginning of the learning project (Niemivirta, 1996). The self-report questionnaire included several subscales, but only the scale for learning orientation was used in this study. The scale contained five items for assessing student’s focus on learning new things and gaining knowledge (e.g. “The most important goal for me in school is to acquire new knowledge”). Items of this scale were used to create a composite score (Cronbach’s alpha coefficient for this scale was .87). In order to make comparisons between students representing different levels of learning orientation, students were divided into two groups on the basis of a median split on this scale. Students with above-median scores were classified in ‘high learning orientation’, and remaining students in ‘low learning orientation’ groups. Gender was equally distributed across the two groups.

Patterns of students’ participation within the VWS were examined by applying social network analysis for analyzed written discourse interactions between the students (Wasserman & Faust, 1995; Scott, 1991). Characteristics of the students' social network was analyzed by examining the intensity of direct interaction among members of a learning community (density), the extent of each member's participation (centrality), and patterns of interaction in the community as a whole (centralization).

The density is a simple way to assess characteristics of a network: the more actors have connections with one another, the denser will be the network. The density of a (binary) network is the number of observed ties divided by the number of all possible ties (Borgatti, Everett & Freeman, 1996b, p. 78; Scott, 1991, p. 74). Density of binary matrix varies between 0 and 1, and it is one in cases that everyone is directly interacting with everyone else. Centralization describes how tightly interaction within a network is organized around particular focal points. A centrality value is calculated for each student in order to find the most active and visible actors in the community, and it was assessed using Freeman's degree (i.e., number of sent and received comments).

The data consisted of the links between students' notes: who interacted with whom by constructing VWS comments. The information was examined as a weighted and directed graph representing the structure of communication, in which the teacher and the pupils were viewed as nodes and the comments as vertices. The data set was dichotomized in the analyses (cut-off point = 0). All analyses were performed by using the Ucinet program (Borgatti, Everett & Freeman, 1999).

RESULTS

Density of Participation

The analysis indicated that the students' network of interaction was not very dense; the density was 0.26 (SD =0.44) for symmetrized data (direction of commenting ignored). In the case of the asymmetric graph based both on sent and received comments, the measure was 0.16 (SD =0.37) of the possible ties. The participating students, taken together, produced 280 written notes. On average, they sent 8.8 (SD = 7.7) comments. All students either sent or received a comment but two students did not send any comments and two did not receive even a single comment.

From the relatively high standard deviations, we may infer that there were subgroups of students that engaged in denser interaction than their fellow students. Therefore, we examined density of students’ interaction as a function of gender and levels of learning orientation. The network was partitioned into blocks the density of which was examined separately on the basis of gender and motivational orientation (low vs. high learning orientation) (see Table 1). In addition, the teacher of the classroom formed her own blocks. However, the densities of blocks with varying sizes are not directly comparable; i.e., larger graphs have lower densities than smaller graphs because only so many ties can in reality be maintained by an individual (Scott 1991, p. 77).

An examination of Table 1 reveals that there were differences between the students’ participation patterns as a function of their gender and motivational orientation. Density of between-student interaction in the case of low learning-oriented students appeared to be lower than that of high learning-oriented students. There were not, however, same kind of drastic gender-related differences in intensity of participation as found in some other studies (Palonen & Hakkarainen, 2000). Table 1 indicates, further, that a substantial part of the discourse interaction took place between the high learning-oriented students. It is encouraging, though, that there was also interaction across borders of gender group as well as across students representing different levels of learning orientation. In many cases low learning-oriented students' comments were sent to the high learning-oriented students while interaction between the low learning- oriented students themselves was not very dense.

Table 1.
Density of Interaction across levels of Learning Orientation (LO) and Gender

Finally, it can be seen that the teacher, who sent 9 messages and received 21 messages from 13 students, interacted with the both gender groups with an equal intensity. It is particularly noticeable, that she engaged in rather intensive interaction with low learning-oriented boys apparently trying to get them involved in CSCL. She was also interacting with high learning-oriented boys and girls. This is to be expected because active participation of these groups provides many opportunities for her to respond and provide support. An open question is why she did not carry out corresponding effort in the case of low learning-oriented girls. It is also to be noticed that interaction between the students and the teacher was bi-directional. In many cases teachers are only commenting students’ productions but there is not any real dialogue involved.

The Centralization of Participation

We also examined the extent to which a whole graph representing VWS students' interaction had a centralized structure (Scott 1991, pp. 92-93). The results of the analysis indicated that students' interaction was not very centralized (0.24 and 0.35 in the case of sent and received comments, respectively). It follows that the students' communicative efforts were distributed among a relatively large number of students.

Table 2 reveals, however, that there were between-student differences in the intensity of engagement in VWS-mediated peer interaction. Most active students could be found among the high learning-oriented girls in the cases of both sent and received comments. Also high learning-oriented boys participated actively but high learning-oriented girls produced approximately twice as many comments as the corresponding boys. The girls contacted a much larger group of fellow students through their comments than any group of boys. However, when the number of actual dialogue partners is concerned (i.e., number of students that one was interacting bi-directionally), learning orientation appeared to be more important factor than gender.

Table 2.
The Centralization of Participation across levels of Learning Orientation (LO) and Gender

*Groups with same letters differ from each other at p<.05 (Nonparametric, MW-test for comparing two groups of cases on one variable). ¹Dialogy partners refer to number of fellow students that a student both sent and received comments so that the interaction was bi-directional.

If we think of VWS students' communication as an information flow consisting of the individual comments, Freeman's 'betweenness' value for a given student shows how often that student is found in the shortest path between two other students. Students who function as “brokers” or mediators between otherwise rather disconnected networks (e.g., boys and girls) have very high betweenness value (Borgatti, Everett & Freeman, 1996b, pp. 82-87). The high learning-oriented girls had a high betweenness value indicating that there were several students who had a significant role in the shared knowledge-building inquiry. Also the high learning-oriented boys’ betweenness value was higher than that of the low learning-oriented students, but at much lower level than that of the former group (i.e., high learning-oriented girls).

Because of the small sample size and abnormal distribution of measures, the statistical significance of these differences were examined using nonparametric versions of t-test and analysis of variance. The findings revealed significant differences (p<.01) on all measures between high learning-oriented and low learning- oriented students (Mann-Whitney test). There were no significant differences between boys and girls at the general level. However, several differences were found across the four groups. Both low learning-oriented boys and girls differed significantly (p<.05) from the high learning-oriented girls’ group on all measures. Low learning-oriented girls differed also from high learning-oriented boys (p<.05), while there were no significant differences between boys’ groups.

DISCUSSION

The results of the study indicated that the level of students’ learning orientation was closely associated with the intensity of their participation in CSCL. In other words, the high learning-oriented students, and most girls, engaged in rather intensive process of inquiry within the VWS. The low learning-oriented students, in contrast, produced fewer comments or pieces of knowledge during the projects examined. These phenomena revealed by the study might appear to be expected or trivial because, in a sense, a disposition to engage in active learning is what we expect from learning-oriented students. However, it is important to remember that the motivational orientation was assessed by using a self-report questionnaire that addressed the students’ general motivational tendencies notwithstanding CSCL.

Moreover, it is not self-evident that students who are learning-oriented would also be the ones who engage in CSCL with the highest intensity. Our earlier studies indicate that for pupils with performance or avoidance orientation in relation to traditional school tasks, CSCL may open up an alternative way of participating in schoolwork (Lipponen & Hakkarainen, 1997; Hakkarainen et al., 1999).

The results of this study indicated that the students’ participation was not equal. It was, however, encouraging that students representing both genders were involved in CSCL inquiry. Students’ participation was not centralized to an extent that only a few students would have produced most of the knowledge. Further, the results indicated that interaction across boundaries of gender or motivational orientation was rather active. This appears to be a very valuable and encouraging aspect of networked learning that would not have been revealed without the methods of social network analysis.

However, these results point out the importance of acknowledging students’ individual differences in the context of CSCL. Apparently, students’ prevailing motivational basis and gender do ‘make a difference’ as far as the participation is concerned. One possible explanation might be students’ different skills in regulating their goal directed activity. Further, it is possible that on the basis of their goal preferences students interpret the characteristics of the learning environment differently. For students with strong learning orientation the new learning environment may seem to provide possibilities to challenge one’s cognitive capacities and gain new knowledge. Instead, some students may experience these elements as new obstacles and demands that they have no interest or prerequisites to encounter.

In both cases, the importance of teacher guidance and support is highlighted. It seems evident that students with motivational problems need more structured instruction and encouragement during computer supported study projects. On the other hand, also students with strong learning orientation may need guidance in their inquiry practices. In-depth learning is demanding for everyone facing the new challenges of CSCL, despite students’ enthusiasm or personal goals.

Certain limitations of the study are important to note. First, because of the small sample size, the findings of the study need further testing with larger populations. Second, the methods used covered only a part of the actual interaction during the projects. Observational data is needed to supplement the results obtained through database analysis.

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