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How students describe the sources of their emotional and motivational experiences during the learning process: A qualitative approach

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Abstract

The aim of the study reported in this paper was to consider the sources of emotional and motivational experiences of secondary school students (N = 18), 12–15 years old, during computer-supported collaborative learning projects. We chose the concept of volition to frame the analysis of the various kinds of descriptions the students give of their emotional experiences in collaborative inquiry. Process-oriented interviews were conducted during and after lessons, and questions dealing with students' self-related beliefs and feelings, and the learning environment were asked. The analysis was complemented with a micro-level video analysis of two students' working processes. The results show that students' descriptions of their emotions had several origins; five different categories were created to describe the various sources of emotional experiences. The case descriptions demonstrate how students express and control their emotions, as well as their motivation.
How students describe the sources of their
emotional and motivational experiences during
the learning process: A qualitative approach
Hanna Ja
¨rvenoja*, Sanna Ja
¨rvela
¨
Research Unit for Educational Technology, Department of Educational Sciences,
P.O. Box 2000, 90014 University of Oulu, Finland
Abstract
The aim of the study reported in this paper was to consider the sources of emotional and
motivational experiences of secondary school students (NZ18), 12e15 years old, during
computer-supported collaborative learning projects. We chose the concept of volition to frame
the analysis of the various kinds of descriptions the students give of their emotional
experiences in collaborative inquiry. Process-oriented interviews were conducted during and
after lessons, and questions dealing with students’ self-related beliefs and feelings, and the
learning environment were asked. The analysis was complemented with a micro-level video
analysis of two students’ working processes. The results show that students’ descriptions of
their emotions had several origins; five different categories were created to describe the various
sources of emotional experiences. The case descriptions demonstrate how students express and
control their emotions, as well as their motivation.
Ó2005 Elsevier Ltd. All rights reserved.
Keywords: Emotion; Motivation; Volition; Computer-supported collaborative learning; Qualitative
research
* Corresponding author. Tel.: C358 8 553 3725; fax: C358 8 553 3744.
E-mail address: hanna.jarvenoja@oulu.fi (H. Ja
¨rvenoja).
0959-4752/$ - see front matter Ó2005 Elsevier Ltd. All rights reserved.
doi:10.1016/j.learninstruc.2005.07.012
Learning and Instruction 15 (2005) 465e480
www.elsevier.com/locate/learninstruc
1. Introduction
Learning situations in modern society are getting increa singly complex and variable,
and learners have to take more responsibility for their own learning. In everyday
learning situations there are different kinds of competitive motives, disturbing
emotions or environmental and social factors that influence the learning process
(Pintrich, 2000). Technology-based learning environments in particular increase the
openness, choice and control of the learning task, while trying to reach more adaptive,
collaborative and situational learning. This creates new challenges for learners who
study in these environments (Ja
¨rvela
¨& Niemivirta, 2001). For example, a student may
be more interested in non-task relevant issues on the Internet than in the on-going
learning task. There can also be contextual distractions, such as too much noise in the
classroom, problems with computers, or difficulties with too open a learning task.
The effects of situational factors on students’ learning imply that students should
exert on-going regulation of motivation and emotions, as well as of actions. Thus,
volitional control becomes crucial for carrying on their work (Corno & Kanfer,
1993). In learning situations, individuals make personal appraisals of the situation’s
meaning based on their former knowledge and experiences (Fredrickson, 2001).
These appraisals along with situational factors and the individual’s interpretations of
them arouse emotions, which then need to be controlled, at least to some extent, to
ensure meaningful goal-oriented behaviour.
Research on emotions has shown that students experience a rich variety of emotions
in academic settings (Schutz & DeCuir, 2002). Results show that academic emotions
are significantly related to student motivation, learning strategies, cognitive resources,
self-regulation and academic achievement (Pekrun, Goetz, Titz, & Perry, 2002). Also,
not only do the emotions themselves vary, but also their sources. Learning situations
instigate a variety of self-referenced, task-related and social emotions. However, even
though there is a lot of research on the effects of emotional factors on classroom
learning (see, e.g., Mayring & von Rhoeneck, 2003), there is hardly any research on
these issues in technology-based classroom learning contexts. Since the interest in
designing new pedagogical environments in different contexts, often with technology,
has increased (Winn, 2002), there is a need to better understand what are the sources
and reasons for students’ emotional experiences in these new learning contexts (Schutz
& DeCuir, 2002;Wosnitza & Volet, 2005).
We have moved in our studies on motivation in technology-based learning
environments from students’ goals and motivational orientations (Ja
¨rvela
¨, 1996;
Ja
¨rvela
¨& Niemivirta, 2001) to the theoretical concepts including more social and
emotional aspects, such as coping or involvement (Veermans & Ja
¨rvela
¨, 2004), and
have, finally, seen that emotional interpretations have the potential to influence
teaching and learning processes in a reciprocal way (Ja
¨rvela
¨, Lehtinen, & Salonen, 2000).
The aim of this study was to identify the sources of emotional experiences in
computer-supported inquiry learning. Specifically, we analysed the reasons the
students give as sources of their emotional experiences in a learning context that
was designed according to recent ideas on computer-supported collaborative
466 H. Ja
¨rvenoja, S. Ja
¨rvela
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learning (Koschmann, Hall, & Miyake, 2002). Also, we examined in detail how two
case students express and control their emotions and motivation in actual computer-
supported learning situations. In what follows, at first the general theoretical
background is introduced and then the specific framework of this study is explained.
This framework assumes that the sources of different emotions function as specific
components in the students’ emotional experiences.
1.1. Studying motivation and emotion in the classroom context
In any learning situation a student has to cope with his or her own emotional and
cognitive demands and conflicts, as well as with social settings and environmental
cues (Volet & Ja
¨rvela
¨, 2001). This is to say that students have to regulate their
cognitive, motivational and emotional learning processes (Boekaerts, 1996;
Boekaerts, Pintrich, & Zeidner, 2000; Schunk & Zimmerman, 1994; Winne &
Hadwin, 1998). Volition involves, besides other control processes, regulation of
motivation. Corno (1994) has defined volition as the ‘‘tendency to maintain focus
and effort toward goals despite distractions’’ (p. 229). Volition is needed particularly
in the execution phase of the learning process, when motivation and goal
commitment are already established, but the student must still sustain and support
the decisions that have been made. Volitional processes strengthen the motivational
aspects that back up goal-oriented actions and control of emotional reactions
(McCann & Garcia, 1999). Unlike Corno (1994), we use the term volition to define
the control processes of motivation and emotion only, and exclude the metacognitive
and environmental control (see, e.g., Pintrich, 1999).
A wide range of emotions influences the learning situation in both the
motivational phase, when students are still considering whether or not and to which
kind of goals to commit themselves, and the volitional phase, when students are
strengthening their commitment towards the selected goals. Even though there is
continuous fluctuation between these phases, the processes the students use in the
different phases of learning vary (Heckhausen & Gollwitzer, 1987). In the volitional
phase, emotions may inhibit or promote actions towards the goals. Emotions can
also affect the variability of the goals during the learning process (Boekaerts, 2001).
That is why recognition and regulation of emotional experiences is an essential part
of the successful volitional control process (McCann & Garcia, 1999).
In Fig. 1 the theoretical framework of the volitional phase of learning is outlined.
This phase includes different integrating parts eselected goals, emotions and
motivational experiences, as well as volitional control strategies (see also Ja
¨rvela
¨&
Niemivirta, 2001). There are several sources and reasons for students’ experienced
emotions during learning. Students’ interpretations of the situation are influenced by
their former personal experiences as well as by their perceptions of themselves, and
by situational, social, and motivation for the task factors (Fredrickson, 2001; Pekrun
et al., 2002). To reach the learning goals students must regulate these emotions by
using volitional control processes. Volitional processes help them to complete the
tasks needed to achieve the established goals.
467H. Ja
¨rvenoja, S. Ja
¨rvela
¨/ Learning and Instruction 15 (2005) 465e480
2. Method
2.1. The study
As mentioned above, the aim of this study was to consider sources of students’
emotional experiences during computer-supported collaborative inquiry learning
projects. We did not attempt to classify or categorize emotional expressions but,
rather, students’ own attributions regarding the sources of their emotions. For this
reason we applied qualitative methodology. Our expectation was that students’
explanations of their experienced emotions would reveal the volitional control
processes students use to control their emotions and motivation. At first, we
analysed students’ descriptions of the sources of their emotional experiences. Then,
we used two case students for a detailed analysis of how they expressed and
controlled these emotions and motivational experiences in an actual learning
situation.
2.2. Participants and procedure
In the research project (see Ja
¨rvela
¨, Hakkarainen, Lehtinen, & Lipponen, 2001),
Finnish secondary school students (NZ18), 7 boys and 11 girls, 12e15 years old,
worked with computer-supported inquiry projects. During the three years of data
collection, students worked with four projects in literature. Each project lasted for
12e24 lessons, and each lesson was 75 min. The topics of the literature projects were
‘‘Racism’’ and ‘‘Time’’ the first year, ‘‘Science Fiction’’ the second year, and
‘‘Drugs’’ the last year.
All the projects followed the same theoretical ideas of inquiry learning
(Hakkarainen & Sintonen, 2002), but there were some differences in how the inquiry
G
O
A
L
S
Motivational experiences
Emotional experiences
S O U R C E S
Motivational
phase
goal
commitment
Volitional control
Volitional
phase
LEARNING SITUATION
Performance SocialContextTaskSelf
Fig. 1. The conceptual framework for the analysis of students’ emotional experiences during the volitional
phase of the learning process.
468 H. Ja
¨rvenoja, S. Ja
¨rvela
¨/ Learning and Instruction 15 (2005) 465e480
process was applied in each topic. The model of progressive inquiry consists of
different phases that can be repeated many times during the inquiry process. These
phases are the following: creating context for a study project, setting up questions or
problems that guide the process of inquiry, creating a working theory,searching and
sharing new information, and setting up subordinate questions. All aspects of inquiry
may be shared between students through the computer-supported learning
environment. The student inquiries have been included in individual and collaborative
work, with and without computers. The Computer-Supported Collaborative
Learning Environments (CSILE) and Knowledge Forum (KF) programs
(Scardamalia & Bereiter, 1994), were utilized in the learning project in order to
structure the inquiry process, to provide tools for inquiry, and to create a forum for the
knowledge construction discussion.
2.3. Interviews
The 18 students were asked to describe their goals, learning strategies,
interpretations of the learning environment and self-related beliefs and feelings
during semi-structured interviews. The interviews were conducted during and after
the actual learning situations in the lessons, about 2e4 times during each learning
project. The interviews were always conducted in the middle or right after the lesson.
Altogether there were 136 interviews. The interview data were transcribed, coded
according to the principles of content analysis (Chi, 1997), and analysed with the
help of the nVivo (Bazeley & Richards, 2000) qualitative data analysis program.
Approximately 550 responses, dealing with students’ interpretations of the
learning environment and self-related beliefs and feelings, were used for the present
analysis. The interview questions to which students responded with emotional
descriptions were as follows: ‘‘What kinds of feelings did you have during this
lesson? Why?’’, ‘‘Was there something boring, unnecessary, interesting or exciting?
Why?’’; ‘‘What do you think about this project compared to other classes? Why?’’, or
‘‘How did you collaborate with other students?’’ ‘‘How did you benefit from working
with other students?’’ (for a more detailed structure of the interviews see Ja
¨rvela
¨&
Salovaara, 2004).
In the first phase of the data driven analysis, students’ different kinds of
descriptions of their emotional expressions were identified. After several repeated
coding sessions, five coding categories were formulated based on the dialectics of
data and theory (Miles & Huberman, 1994). The categories were self,task,
performance,context, and social (see Table 1). Next, a more detailed qualitative
analysis was conducted and students’ responses were coded and assigned to the five
categories formulated in the earlier phase. Because the interviews were semi-
structured and students were able to discuss several topics in the same response,
some responses included elements from more than one category. These responses
were coded in every relevant category.
More specifically, the first phase of the coding was conducted by two independent
researchers and their categories were compared after each coding session until valid
categories were found (Kvale, 1996). The contradictory findings were negotiated and
469H. Ja
¨rvenoja, S. Ja
¨rvela
¨/ Learning and Instruction 15 (2005) 465e480
re-coded until a unified opinion was reached. After the final five coding categories
were formulated, all data were coded according to these categories. To increase the
reliability of the analysis, the principal researcher coded the data several times. After
the principal researcher had finished her final coding, a random selection of the data
(about 30%) was coded by another researcher. Contradictory findings of that sample
(about 10% of the random selection) were negotiated. After consensus was reached
the whole data was coded again by the principal researcher. The principal researcher
also went through about 30% of the data placed in categories in order to confirm the
coherence of coding within each category. Careful coding definitions and multiple
examples were also provided in order to increase the validity of the analysis.
2.4. Video data and case descriptions
Video data collection focused on two students during the last learning project (a
literature project about drugs). This analysis aimed at detailed process-oriented data
regarding students’ working processes. The two case students, Anna (15-year-old
girl) and Ville (15-year-old boy), were videotaped and observed while working in the
classroom. The teacher had been asked to name a group of average students in the
classroom according to their school achievement, and the case students were
randomly chosen from these. Most of the time Anna and Ville spent working with
the computer and with a large part of the other classroom activities (e.g.,
communication with the other students and the teacher, or reading books) they
were videotaped. Their working processes were videotaped during 10 lessons,
yielding about 75 min of data per lesson. The data were analysed with the help of the
Noldus Observer computer program (Noldus Observer, 2003) and the series of
events were transcribed. When the researcher was familiar with the data, she looked
again at the videotapes with the transcriptions and wrote specific descriptions of the
students’ emotional and motivational expressions and volitional behaviour. Finally,
the descriptions of the two case students were made. Also, the case students’
interview data from the same project were used to complement the case descriptions.
Table 1
Categories of the sources for emotional experiences in computer-supported collaborative inquiry context
Category of the sources of
emotional experiences
Description of the source of student’s experienced emotion
Self (nZ204) Former experiences, frustration or common thoughts concerning the
situation, belief of him or herself
Task (nZ64) Domain-specific interest, the task itself
Performance (nZ59) The inquiry project, progress or performance
Context (nZ179) Pedagogical model and its implementation, (teacher’s) instructions,
working on a specific phase of a learning task, classroom environment
Social (nZ46) Interaction or comparison between me/us and others, the atmosphere in
the class, performance in the class
470 H. Ja
¨rvenoja, S. Ja
¨rvela
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3. Results
3.1. Interview data
In this study, an inductive approach (Miles & Huberman, 1994) was used in order
to identify the sources that arouse emotions. Based on students’ answers, five
different categories eself,task,performance,context, and social ewere composed
indicating several sources for the students’ experienced emotions. The dominant
categories (see the Table 2) were the following: self (37%) and context (32%). The
percentages for the other categories were the following: task (12%), performance
(11%), and social (8%).
The self-category included descriptions of experiences that derive from the
students’ former endeavours, their individual interests or general thoughts
concerning the situation, as well as their personal motivational beliefs about
themselves when confronted with the current learning context. Students connected
the source of the experienced emotion, for example, to the meaning of learning or
studying, as can be seen in the following examples. In Example 1, a student reflects
on the current situation in comparison to her former similar experiences and
opinions of the domain. In this example, Student 1 refers to experiences in
schoolwork in general and computer-supported inquiry learning in particular, and
her appraisal of the specific literature project as compared to earlier projects in the
same domain. She feels comfortable and confident, even though she also acknowl-
edges the demands of the project. In Example 2, in contrast, Student 2 cannot find
a meaning for the project and he feels frustrated. Perhaps his less extended
experience with inquiry learning contributes to his frustration.
Example 1
Interviewer: What do you think about this project?
Student 1: This has been quite an important project in literature, the biggest one
I have ever had. It has been hard work, but very interesting.
Example 2
Interviewer: Was there something boring or unnecessary in this project?
Student 2: Everything.
Table 2
The classification of the students’ descriptions of the sources of their emotional experiences in computer-
supported inquiry
Sources n%
Self 204 37
Task 64 12
Performance 59 11
Context 179 32
Social 46 8
471H. Ja
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¨rvela
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Interviewer: Everything? Why?
Student 2: Because, the project was boring and didn’t have any meaning at all.
The task-category included responses in which students’ descriptions derive from
domain-specific interest or the task itself, e.g., ‘‘Drugs are a [socially and personally]
very important issue’’ and ‘‘The book was good’’. These responses primarily
emphasized the meaning of the topic instead of comparing it to personal conceptions
of learning, which was emphasized in the self-category. This can be seen in Example
3 in which Student 3 identifies both the task and the topic of the project as the
sources of her positive feelings.
Example 3
Interviewer: What did you find interesting or inspiring?
Student 3: The topic itself and reading the books.
Interviewer: Why?
Student 3: Well, I like to read and the topic was very relevant and interesting.
The performance-category included responses that indicated emotional experiences,
which were related to the students’ work, progress and performance in the inquiry
project. This category included process-oriented answers like ‘‘Now it’s getting on very
well’’ and ‘‘First I feel awful, but then I think it’s going to be a good study and it doesn’t
feel that bad after all’’. More detailed, in Example 4, Student 4 describes a situation in
which she experienced positive emotions. She felt positive emotions when she was
assured of her ability to finish the project. However, in Example 5, Student 5 feels she is
not able to progress and she is worried about her performance.
Example 4
Interviewer: Could you describe a good phase of your working?
Student 4: It was when I felt that I’ll get it done. That was when the project was
almost finished.
Interviewer: Why did it feel good?
Student 4: I managed to get the project done.
Example 5
Interviewer: What kinds of feelings did you have during the lesson?
Student 5: I didn’t feel anything. I haven’t had time to do the project. If I
manage to get anything done at all, it will be enough.
The context-category included responses that referred to the inquiry model and its
implementation, the teacher’s instruction, working on a specific phase of a task or the
classroom environment in general. In Example 6, a specific phase of the inquiry learning
model arouses confusion to the student. The same happens in Example 7 in which the
task requires writing and sharing the created theory in the learning environment and
Student 7 does not understand how commenting on the other students’ work in the
computer-supported learning environment helps him with his own project. In Example
472 H. Ja
¨rvenoja, S. Ja
¨rvela
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7, the source of the student’s frustration is the particular phase of the inquiry project in
which the students are required to share and discuss their ideas with others, not the social
interaction as such. Responses dealing with the teacher’s instruction were also coded in
this category instead of the social-category, because they were more connected to the
inquiry model used than to the teacher as a person. For example, a student gets bored
with the instruction, because he or she already knows what to do (‘‘It gets on my nerves,
when the teacher explains things that are too obvious’’).
Example 6
Interviewer: What is your opinion of the project in this phase?
Student 6: It is quite ok, but I don’t exactly know what to do with the books [and
I am feeling frustrated]. Why did we need those books? It’s
sometimes complicated to figure out what we have to do.
Example 7
Interviewer: Was there something boring or unnecessary in this project?
Student 7: Yes, when you had to comment on the other students in the
Knowledge Forum.
Interviewer: Why?
Student 7: It took so much time. I just did it.
The social-category responses were related to students’ emotions that derived
from the social and interaction culture of the classroom and the students’ role in it.
In this category, socially oriented emotions dealt with micro-level social contacts of
classmates or other related persons, e.g., ‘‘It is nice to know what other students
think’’. Sources for these emotions were the following: situations related to the
classroom atmosphere, e.g., ‘‘We had a very relaxing atmosphere in the class’’.
Interaction with other students, e.g., ‘‘It is annoying that everybody else is interested
in anything but working’’. Comparison of him or herself to the other students: ‘‘I
don’t know how to survive because the other students know so much and I don’t
know anything’’. In Example 8, the student’s social and context explanations merge
together. The contextual element ethe implemented inquiry learning model e
emphasizes collaboration and sharing, and leads the student to situations where
she has to share her ideas with other students. In any case, the main source for the
student’s negative emotion is social instead of contextual, since she emphasizes the
interaction with her classmates. The student feels anxious when the other students
can read her notes in the computer-supported learning environment. The main
source for the emotional experience is social although the situation was created by
the inquiry model.
Example 8
Interviewer: Did the Knowledge Forum help your working with the inquiry
project?
Student 8: I don’t think so; not especially. Everyone can read my notes there. I
don’t really like the fact that everyone can do that.
473H. Ja
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¨rvela
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As can be seen from the examples, students’ descriptions often included more than
one source for their experienced emotions. However, it was possible to trace which
source(s) was emphasized by comparing the descriptions of the different categories
and looking at the interviews as a whole instead of just the short segments of data.
When summing up the findings, the self-category responses were the most common
source of emotions for 12 students and the second most common source for the other
18 students. For six students, context-descriptions were the most common and self-
category descriptions were the second common. The task-category descriptions were
the most common source for one student, who reported this category as often as the
self-category and the second most common source for two students as well as the
self- or context-category descriptions. No one described his or her experienced
emotions only in terms of ‘performance’ or ‘social’ descriptions. Most of the students
reported all five sources for their emotional experiences, but there were four students
who didn’t report one to three source categories at all.
3.2. Case descriptions
3.2.1. Expression of emotions
Another aim of the study was to analyze how the case students expressed and
controlled their emotions in actual learning situations. Our purpose was to illustrate
the aspects of students’ behaviour that are not readily observable, by combining the
interviews with the video data (see Perry, VandeKamp, Mercer, & Nordby, 2002). In
the descriptions that follow the focus is on the expression of the emotions and how
control of these emotional experiences varied in the different phases of the learning
project and between the case students. The role of the experienced emotions can be
seen in the descriptions of Anna and Ville’s behaviours, as shown in Examples 9 and
10. It can be seen that, especially in the beginning of the learning project, the self-
and contextual-driven emotions play an important role.
Example 9
Ville. In the interviews Ville tells that he is interested in the subject. He thinks
that it is a topical issue and the whole project is ‘‘all right’’. However, in the
first lessons Ville is frustrated and annoyed, because the project seems to be
too large to handle and he does not know what to do and how to start. At
the first lesson he tries to concentrate on understanding what he is expected
to do by listening to the teacher and reading the information. He expresses
his non-task orientation and frustration by shaking his head and talking to
himself, e.g., ‘‘no, no, no’’, and to friends, e.g.,‘‘ We have something else to
do besides this project, don’t you think so Tommi?’’
Example 10
Anna. Anna almost never expresses her feelings by talking or using gestures. She
controls her emotions very well immediately from the beginning of the
lessons. She seems to commit herself to the project in many ways. Anna is
well focused and her concentration is quite good during the whole project.
474 H. Ja
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¨rvela
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In the interviews she mentions that she has made a timetable for herself in
order to help her while working in the project. Anna has chosen her books
in the early phase of the project and finishes it well before the deadline. At
times during the lessons, she observes what is happening in the classroom,
but hardly ever participates in any actions in the classroom. When Anna
has problems with the task or the computer, she almost always tries to solve
them herself before asking anyone. She also waits patiently if she needs help
from the teacher or another student.
In the interviews, 37% of Anna’s experienced emotions were self-category
responses, which is approximately the same as Ville’s self-category responses (38%
of all of his responses). However, in contrast to Ville, there were almost no observable
emotional expressions in Anna’s performance in the video data. Anna ’s behaviour does
not mean that she did not experience emotions, but rather that she was able to control
her emotional reactions. As can be seen in Table 3, Anna talked about her emotional
experiences in the interviews approximately as much as Ville, and her answers included
emotional descriptions in all categories, compared to Ville’s, who did not have any
performance descriptions. There were no social-category responses in either student’s
answers. The difference can be seen in how these two students were able to control their
emotions, e.g., how they managed to volitionally control their emotions.
3.2.2. Volitional control
In the interview data of the 18 students, Anna was also one of the few students
who was able to talk about her volitional strategies. In Example 11, Anna tells in an
interview after the last project how she got started with it.
Example 11
Interviewer: How did you specify what to do?
Anna: I made a kind of timetable. Then I just had to get started. Actually, I
often leave the work for the last minute, but I still manage to get it
done.
While Ville (see Example 12) expressed his emotions more visibly than Anna, he
also seemed to attempt to control the emotions and regulate his actions. For Ville
Table 3
The classification of the case-students’ descriptions of the sources of their emotional experiences
Sources Anna Ville
n%n%
Self 9 37 8 38
Task 4 17 8 38
Performance 4 17 0 0
Context 7 29 5 24
Social 0 0 0 0
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this volitional control was harder than for Anna, and in the beginning of the project
he did not succeed in the control process according to his wishes.
Example 12
Ville. In the first two lessons the teacher gives specific instructions what to do.
The students have to work with the project independently for the first time
on the third lesson. Ville has considerable problems to start working. He
does not understand the instructions and cannot decide what to do. He is
frustrated because he does not seem to understand why they are using the
Knowledge Forum computer environment. Ville expresses his feelings in
many ways. He lays his head on the desk and mumbles to himself. He
complains to his friends. Regardless of his negative emotional expressions
he tries to regulate his actions and starts to work with the task. He asks for
clarifications many times from the teacher and asks him to confirm his
actions. However, emotions take over again and again despite his effort to
control them. Almost anything that happens in the classroom takes Ville’s
attention away from the task.
Despite the differences of the beginning of the project, both Anna and Ville
finished their project in time. After the first lessons both of them were engaged in
working and both of them seemed to take responsibility for their own work. For
example, for one lesson Ville had already planned the content of his project report at
home in order to regulate his working during the lessons. He had also created
computer notes to the Knowledge Forum to help himself construct the final report of
the project (see Example 13).
Example 13
Ville. For the seventh project lesson Ville has made a draft of the context of his
inquiry at home. Ville has an idea to use the Knowledge Forum to control
his ideas. He creates empty Knowledge Forum computer notes in order to
remember and organize what to do. He is proud of the idea and introduces
it to the teacher and to the other students. Ville seems to wait for feedback
for his idea, even though he emotionally feels unsure about it. When the
teacher is introducing the idea to the whole class, Ville suddenly says
‘‘Don’t laugh!’’. In spite of contradictory feedback from his classmates, he
keeps on working as he planned and shows his idea to almost anyone who
is interested in it. He feels satisfied with his own idea and uses it
purposefully in his inquiry.
The cases of Anna and Ville illustrate the importance of volitional control. Anna
had good self-regulation skills and she managed to control her emotional reactions
and action towards the goal during the whole project. The analyses of the interviews
and video data showed that she was able to highlight the motivational aspects of the
task, as can be seen in Example 14, and she also seemed to be able to maintain focus
and effort toward the goals despite distractions.
476 H. Ja
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¨rvela
¨/ Learning and Instruction 15 (2005) 465e480
Example 14
Interviewer: Give me an example of one good phase during the literature project.
Anna: Well.the phase where I was writing the notes to the Knowledge
Forum.
Interviewer: Why it was so good?
Anna: I don’t know. It helped me move forward.
Ville’s working improved after he managed to control his emotions. When the
goal became clearer, he was able to better regulate his actions. At the end of the
project he seemed to take more responsibility for his own learning, and even if he still
expressed his emotions and got distracted from time to time, he managed to return to
work after the distractions much more easily.
Anna and Ville’s cases demonstrate how emotions can be controlled during the
learning process. As Ville showed during the first part of the project, if the emotions
overcome the control efforts, learning and cognitive actions become impossible.
Cognitive actions may also indicate emotional control, as can be seen in Ville’s
Example 14, where writing the computer notes is used as both a cognitive strategy
and for controlling the emotional state.
4. Conclusions
The aim of this study was to understand how students describe their emotional
experiences in computer-supported collaborative inquiry. We expected that by
identifying the sources of students’ experienced emotions it would be possible to
understand students’ volitional control processes. The first analysis aimed at
identifying these different sources. The second analysis based on two case students
provided examples of the control of these emotions as well as of motivation during
the actual learning process. The results showed that there were five main sources for
students’ experienced emotions during the computer-supported inquiry learning. In
this study, self and context were the most frequent sources of emotional experiences.
The students also described task-, performance- and social-driven emotions. Anna
and Ville’s case descriptions, on the other hand demonstrated how the students
express and control their emotions in different ways in actual learning situations and
how this affects their working during the project.
These results are in line with the idea that individuals bring their prior learning
experiences and assumptions to the learning situation (Higgins, 1990; Salonen,
Lehtinen, & Olkinuora, 1998). The data of the two case descriptions show that the
emotions coded in the self-category play an important role, especially in the
beginning of the study, when the goals are not yet so clear. Emotional experiences
arise when the students interpret the situation and begin to compare it to their
former experiences, and to construct personal meanings (Fredrickson, 2001).
However, context and task responses indicate that it is not enough to understand
how students assign meaning to the required learning; contextual factors are also
important in learning situations (Volet & Ja
¨rvela
¨, 2001). In this study there were
477H. Ja
¨rvenoja, S. Ja
¨rvela
¨/ Learning and Instruction 15 (2005) 465e480
surprisingly few responses in the social-category, even though the pedagogical model
and computer-supported learning environment emphasized collaboration and
knowledge sharing. It seems that social sources for emotional experiences are
difficult to investigate and identify from the data, even though students seem to
recognize the social aspects of the learning situation. It could be that emotions
caused by social sources are so private that students do not want to disclose them.
In this study, interviews were used to identify the sources that arouse emotions.
The aim was not to categorize emotional expressions, but to discover explanations
for students’ descriptions of the sources of their emotional expressions. With
interview data, we were able to understand the descriptions and explanations that
students themselves gave for their emotional experiences, and which sources aroused
the most emotions. Interviewing was chosen as the main method for gaining
students’ qualitative opinions and descriptions. Interview data provides rich
qualitative data to construct essential meanings in analysis through the dialectics
of theoretical ideas and empirical data (Kvale, 1996). This is needed since there is
a lack of research on the role of emotions and their control in technology-based and
collaborative learning contexts. However, this kind of semi-structured interview also
had limitations. Not only can the structure of the interview influence the results, but
also the fact that students may hide or be unaware of some sources of their emotions
(Wosnitza & Volet, 2005). To prevent or decrease the effect of the interviewer, the
questions did not deal directly only with feelings, but with the contextual, situation-
specific activities instead. Also, the interview data did not explicitly address the
volitional control strategies of the emotions. In the future, the interview protocol
needs to be improved to better reach these mechanisms. In any case, the different
sources of emotions, which were derived as a result of this study, may present
a better opportunity to develop the protocol.
Finally, in this study, the two students’ case descriptions provided an opportunity
to see how students express and control their emotions in actual learning situations.
Even though there were only two case students, we were able to see how essential
volitional emotion control is for learning and achievement (see also Renninger &
Hidi, 2002). While these cases highlight the importance of emotion control, they also
show how emotions and their control are often invisible and can be seen only
through cognitive actions (Silk, Steinberg, & Morris, 2003). Often, successful
emotion control can only be studied by combining different methods. Qualitative
methods, and a more context-oriented approach, may give new possibilities to shift
the focus from the structure of the stable aspects of the emotions to the processes
related to the individual emotional experiences and the meaning a person attaches to
these experiences (Perry, 2002; Pintrich, 1999; Schutz & DeCuir, 2002).
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Computer Supported Collaborative Learning (CSCL) is one of the most promising innovations which will improve teaching and learning with the help of modern information and communication technology. In this article, we discuss the theoretical principles derived from educational and cognitive psychology for developing CSCL culture in Finnish schools. We also describe a large research project based on the theoretical principles emphasised. The purpose of the research project is to analyse the cognitive and social effects of CSCL in elementary and high schools. The project is still in progress and is being carried out by setting up CSCL networks in several lower and upper elementary schools and also high school classrooms in Finland. In this paper, we report on our intensive case studies for analysing the socio-cognitive effects of CSCL and describe a study where Computer Supported Intentional Learning Environment (CSILE) was used for science learning projects in upper elementary classrooms.
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In this article, the author describes a new theoretical perspective on positive emotions and situates this new perspective within the emerging field of positive psychology. The broaden-and-build theory posits that experiences of positive emotions broaden people's momentary thought-action repertoires, which in turn serves to build their enduring personal resources, ranging from physical and intellectual resources to social and psychological resources. Preliminary empirical evidence supporting the broaden-and-build theory is reviewed, and open empirical questions that remain to be tested are identified. The theory and findings suggest that the capacity to experience positive emotions may be a fundamental human strength central to the study of human flourishing.
Article
In this article, the author describes a new theoretical perspective on positive emotions and situates this new perspective within the emerging field of positive psychology. The broaden-and-build theory posits that experiences of positive emotions broaden people's momentary thought-action repertoires, which in turn serves to build their enduring personal resources, ranging from physical and intellectual resources to social and psychological resources. Preliminary empirical evidence supporting the broaden-and-build theory is reviewed, and open empirical questions that remain to be tested are identified. The theory and findings suggest that the capacity to experience positive emotions may be a fundamental human strength central to the study of human flourishing.