Luthfiyah Nurlaela
Ita Fatchur Romadhoni
Abstract: Students'
engagement in learning is affected by the learning environment including
assigned activities and tasks, ways to provide instructions, and assessment
practices. It is implied that lecturers affect students’ interpretation task
(for better or worse) in what way they organize their learning.The present
study aimed to analyze the influence of students’ task interpretation on their
learning outcomes. It was an experimental type of research with pretest and
posttest control group design. The research subjects were 64 students of the
Dressmaking Study Programof the Home Economics Department of Faculty of Engineering,
of UniversitasNegeri Surabaya (UNESA). They were taking Family Welfare Studies
course. They were divided into an experimental class (29 students) and control
group (35 students). The experimental class was given task-analysis sheet prior
to pre-test, while the control class was not. Another similar treatment for
both groups was guided group discussions with Student Activity Sheet (MFI), and
posttest. The technique for data collection was tests.The data analysis used N-Gain
and t-test. The result showed that: (1) The mean of N-Gain of the control class
was .44 (medium category) and the mean of the experimental class was .73 (high
category); (2) the result of t-test showed that with significance level of .05,
the obtained value was .019. It means that there was a difference in the learning
outcomes of the experimental and the control groups. In conclusion, the
students’ task interpretation affects their learning outcomes.
Key words:
task interpretation, students’ learning outcomes, Family Welfare Studies course
Introduction
In
order to achieve a successful learning, each student must have a consistent
approach (work habit) to complete academic tasks (Butler & Cartier, 2004),
including the students' ability to interpret the demands of work to be
accomplished. Therefore the task interpretation is crucial in determining the learning
success. It is necessary to study what a lecturercan do to improve the task
interpretation effectively.
In
class, lecturers construct learning environments where students work. For
instance, they choose instructional methods (e.g. lectures, small group
discussions); objectives, forms and components of learning activities; and
evaluation practices (which is the standard for evaluating the task). In a
learning environment, lecturers have the potential to affect the formation of
knowledge and competences of students. The learning environment formsthe
students’ approach to learning. This will ultimately affect their learning
(Entwistle&Tait, 1995).
When creating a learning
environment, a lecturer conceptualizes and arranges academic tasks (academic
work). As part of this process, he or she designs activities for students with
the goal of fostering a particular academic work habit and learning outcomes.
The term "activity" generally
refers to a task assigned by a lecturer. The term "task" refers to a
specific and more coherent activity and internally requiring some other
learning activities (such as reading, writing, learning, and problem solving).
Students’ interpretation of assigned
tasks describes their work habits. It is of importance as a basis of success in
accomplishing the task. Some researchers define "engagement" as a very
meaningful and thoughtful approach to complete a task (Paris & Paris,
2001). Referring to the model of metacognition and self-regulation (Butler
&Winne, 1995; Zimmerman &Schunk, 2001), students engagement is defined
as a student activity, coordinating reflective learning process (i.e.
self-regulation) in improving the knowledge of metacognitive and beliefs of
motivation in the context of academic tasks. Thus,
student involvement is associated with self-regulation in the activities,
because it lies in the context of learning (Zimmerman &Schunk, 2001). In
connection with this definition, engagement in the task can be divided into two
recursive phases: task interpretation (carefully defining the requirements of a
specific task), planning (setting a destination, selecting approaches to manage
tasks), implementation (implementing the chosen strategy), monitoring
(continuously tracking the progress associated with the destination), and
evaluation (generating feedbacks about things that have already occurred).
Explaining student engagement requires
an analysis of the quality of their participation in that phase (Butler
&Winne, 1995). It is because students gain experience through tasks, work repeatedly
through these phases. By doing so, they begin to develop the work habits which
they adopt whenever they are faced with academic work.
Task interpretation is very
important for learners’ success in their performance. Butler (1998) stated that
"efficient learners are aware of the task requirements and direct their learning
activities accordingly”.During the first phase of engagement, namely the taskinterpretation,
they interpret the requirements of a given task. Then, they self-regulate all
future learning activities based on their interpretation of the demands of the
task (Butler &Winne, 1995). The interpretation serves to direct duties (e.g.
purpose for which they have set in advance), the strategy they choose and apply,
and criteria for the assessment of their performance during the monitoring and
self-evaluation.
In other words, if the interpretation
of the task is missing or wrong, the learning will not succeed. A student can
work diligently and hard, but their efforts would not be productive to focus on
the learning objectives in question. Thereforethe
task successful interpretation will lead to engagement focused on the tasks and
ultimately affect the students’ success.Therefore, to be successful, the students
must have an approach to academic work including their attention on the task
interpretation.
As previously mentioned, the students'
engagement in learning is influenced by the learning environment, including the
activities and tasks assigned, how the instructions provided, and assessment
practices. It is implied that the lecturer can affect the students’ task interpretationin
the way they organize the learning environment.
Family Welfare Studies
is a compulsory course for the students majoring in Home Economics Education,
including those of Dressmaking Study Program. This course is provided at the
beginning of the semester (1st semester). The purpose of this course includes:
1) the students understand the basic concepts of Family Welfare Science and its
scope; and 2) the students master the Family Welfare Studies as the basis for
the development of the Home Economics Education, as well as mastery of the
welfare of the family, family life and their relation to the state life. The course
materials are comprised of Family Welfare Science, Home Economics, education,
family welfare (PKK), family life as part of science, theoretical perspectives
on the family, the nature of the family, management of family resources as a
system, the definition and scope of family resources, the concept of
decision-making in the family, the allocation of time and housework, family
financial management, gender roles, family welfare, and research methods in the
family.
In this study, the
role of gender was selected as a topic to be studied, because the topic was
considered to be quite interesting and constituted many ill-defined problems.
Practicing problem solving skills requires those ill-defined problems. The
students’ activities of creative and critical thinking can take place. The task
analysis, pretest, posttest, and student activity sheets were developed to
guide the activities.
The
problems of this research raised are: 1) How are the students’ learning
outcomes; and 2) Does the students’ task interpretation influence their
learning outcomes?
Method
The
present study was a quasi-experimental research with a pretest-posttest control
group design. The students’ task interpretation was the independent variable
and the students’ learning outcomes was the dependent variable. The subjects
were the students of Dressmaking Study Program who were taking the Family
Welfare Studies course. They were divided into the experimental group (B Class)
consisting of 29 students and the control class (A Class) totaling 35 students.
The students in the experimental class were given a sheet of task-analysis
prior to the pretest, while the control class was not given the task-analysis
sheet before the pretest. The similar treatmentsfor both groups were the pretest,
guided group discussions with Student Activity Sheet (MFI), and the post-test.
To gather the data, tests were used.
The
students’ learning outcomes were determined on the basis of the students’ test
results consisting of the pretests and posttests. The results of both tests were
used to determine the N-gain score which accounted for the level of the students’
understanding. The qualitative descriptive analysis was done to determine the learning
outcome (Hake, 1999) with the following formula:
Notes:
<g> = gain score (improvement
of the students’ learning outcomes)
Spost = post testscore
Spre = pre testscore
Smax = maximum
score
The
N-gain indicates the differences in understanding of the concepts before and
after the treatment. The criteria for the N-gain according to Hake (1999) are
divided into three levels. They are:
(1)
If <g> ≥.7, it is categorized as ‘high gain’.
(2)
If 0.7><g> ≥ .3, it is categorized as ‘fair/medium gain’.
(3)
If <g> .3, it is categorized as ‘low gain’.
Result
and Discussion
The pretest results
Before
conducting the study, the researchers administered a pretest to determine the
students’ initial ability. The pretest results can be seen in Table 1 as
follows.
Table 1 The
pretest results
|
Data
|
Control Class
|
Experimental Class
|
|
Maximum score
|
16
|
26
|
|
Minimum score
|
58
|
55
|
|
Mean
|
40.74
|
47.10
|
|
Median
|
44
|
48
|
|
Modus
|
45.00
|
48.00
|
|
Standard Deviation
|
10.82
|
5.63
|
Based on the pretest results of the students
in the control class, the class obtained the highest score of 58, the lowest
score of 16, the average score of 40.74 with a standard deviation of 10.82, the
median of 44, and the modus of 45.
From the results of the pretest of
the experimental class, the scores earned included the highest scoreof 55, the lowest score of 26, the
average score of 47.10 with a standard deviation of 5.63, the median of 48 and
the modus of 48.
The posttest results
After
the implementation of learning activities and the administration ofthe Student
Worksheet and tests, the evaluation was performed to determine the students’
learning outcomes in the form of post-test. The posttest results can be seen in
Table 2 below.
Table2The
posttest results
|
Data
|
Control Class
|
Experimental Class
|
|
Maximum score
|
78
|
87
|
|
Minimum score
|
53
|
77
|
|
Mean
|
66.8
|
85.5
|
|
Median
|
67
|
86
|
|
Modus
|
62
|
86
|
|
Standard Deviation
|
6.15
|
2.11
|
From
Table 2, the results of the posttests showed that the control class obtained
the highest score of 78, the lowest score of 53, the average score (mean) of 66.8
with a standard deviation of 2.11, the median of 86, and the modus of 86.
Whereas
the posttest results of the experimental class showed that they obtained the
highest score of 87, the lowest score of 77, the average score (mean) of 85.5
with a standard deviation of 6.15, the median of 67, and the modus of 62.
The N-Gain scores
The
improvement of the students’ learning outcomes in the control class can be seen
from the N-gain average score of 0.44 (included in the medium category);
whereas the one of the experimental class was 0.73 (included in the high
category). Table 3 below reveals the results of N-gain scores.
Table 3 The
N-Gain scores
|
No
|
Class
|
N
|
Scores
|
|||
|
Ideal
scores
|
Minimum
Scores
|
Maximum Scores
|
Average
|
|||
|
1.
|
Control
|
35
|
100
|
.31
|
.56
|
.44
|
|
2.
|
Experimental
|
29
|
100
|
.63
|
.78
|
.73
|
Table
3 reveals that there are 10.34% or 3 students included in the low category,
13.79% or 4 students included in the medium category, and 75.86% or 22 students
in the high category. This shows the significant increase in the students’
learning results after having been given the task analysis.
From
Table 3, the N-gain scores were included mostly in the category of medium and
high. This suggests that there was a significant improvement in the students’
learning outcomes. The task analysis assessed affected the learning outcomes.
The increase in task analysis can be seen in Figure 1 below:
Figure 1 the increase of task analysis
The t-test
results
The
data analysis concerning the students’ learning outcomes by using the t-test is
presented in Table 4.
Table 4Independent Samples t-Test
|
|
Levene's Test for Equality of Variances
|
t-test for Equality of
Means
|
||||||||
|
F
|
Sig.
|
t
|
df
|
Sig. (2-tailed)
|
Mean Difference
|
Std. Error Difference
|
95% Confidence Interval of the
Difference
|
|||
|
Lower
|
Upper
|
|||||||||
|
Values
|
Equal variances assumed
|
30.220
|
.000
|
-15.583
|
62
|
.019
|
-18.68
|
1.19927
|
-21.08598
|
-16.29135
|
|
|
Equal variances not assumed
|
|
|
-16.800
|
43.30
|
.035
|
-18.68
|
1.11239
|
-20.93156
|
-16.44578
|
Table 4 shows
that the obtained results of the analysis was the Sig. (2-tailed) of 0.019
<0.05. On the basis for a decision in an independent sample t-test, it can
be concluded that H0 was rejected and H1 was accepted. It means that there is
influence of the students’ task interpretation on the students’ learning
outcomes.
The
task analysis is believed to lead the student to understand and resolve the
tasks. From time to time and through studies at schools, the researchers
describe how the students developedtheir knowledge of the academic context on which
they base their approach to the academic work.As a part the students’ built
student knowledge, the students develop metacognitive knowledge (i. e. the
knowledge of knowledge), that influence their approach to academic tasks.
At
the beginning of the definition of metacognition, Flavel (1987) defined the
three types of metacognitive knowledge, the person variable, task, and
strategy, which affects the students’ approach to academic work. The person
variable reflects the students’ knowledge about themselves as learners and
others, and about learning the strategies in general. The strategy variable
reflectsthe students’ knowledge about how, when, and where the specific learning
strategies should be used. The task variable reflects the "students'
understanding about relationships between characteristics and associated
processing task demands" (Butler, 1998, p. 280). Flavel found that person,
strategy, and task variables interact to shape how students are involved in the
assigned tasks. The students build metacognitive knowledge all the time, from their
continuous experience with academic work (Paris, Byrnes, & Paris, 2001).
They juxtapose the metacognitive knowledge when performing the self-regulating
in the context of any particular task (Zimmerman &Schunk, 2001).
In
order to succeed in learning, the learners must know more than just the
purposes of tasks. They also need to understand how the academic tasks are
accomplished.
The
students’ task interpretation of the students lead their planning, (e. g.
purpose for which they created), the strategy they choose and how they are
applied, and the criteria for the assessment of their performance during the
monitoring and self-evaluation. Thus, if the interpretation of the assignment
is missing or incorrect, the learning will fail. A student can work diligently
and hard, but their efforts would not be productive to focus on the learning
objectives intended. Thus, the interpretation of a successful assignment is the
basis for a focused engagement in the tasks and they will finally achieve the
successful learning at schools. Therefore, to be successful, the students must
adopt an approach to academic work which is usually included their attention to
the task interpretation.
Conclusion and Suggestion
Based on the previous data analysis, some conclusions
can be drawn as follows: 1) The mean N-Gain of the control class was .44
(medium category), and the mean of the experimental class was .73 (high
category); 2) The result of t-test showed that with a significance level of .05,
the obtained value was .019, which means that there is a difference between the
learning outcomes of the experimental and the control groups. It therefore can
be concluded that the students’ task interpretation affects their learning results.
The suggestions that can be raised include the need to apply the task
interpretation in giving each task to the students. The task Interpretation
helps the students understand the task, plan to complete the task, and
ultimately help them achieve the best academic achievements.
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