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Asia-Pacific Forum on Science Learning and Teaching, Volume 19, Issue 2, Article 7 (Dec., 2018) |
This research used a quantitative method and correlational design. The quantitative data were collected using a survey technique. Correlational research design was used to express the relationship between quantitative variables that had not been manipulated (Fraenkel, Wallen, & Hyun, 2012). Independent variables were gender and grade levels, while the dependent variables were SPS and CA scores. This study was conducted at the end of the academic year when the students had completed all experiments. It was for exploring the students’ mastery of SPS and CA then evaluating the effectiveness of laboratory method that had been applied in one semester. These results can be used as a foundation for lecturers in increasing SPS and developing CA of the students using other laboratory approaches that were considered more effective and efficient.
The participants in the main study were 152 undergraduate chemistry students at the Faculty of Mathematics and Natural Sciences, Yogyakarta State University, Indonesia. There were 75 first-year students attended the General Chemistry Laboratory course and 77 second-year students enrolled in the Analytical Chemistry Laboratory course (see Table I). First-year students carried out the Reaction Rate experiment and second-year students carried out the Gravimetric Analysis experiment. All respondents completed the experiment according to the instructions which had been prepared by the lecturer. During the observation, researchers did not provide any intervention to the participants. Participants (age between 18-20 years old) took part in lectures in odd semester academic year 2017/2018. The sampling technique used the convenience sampling. Creswell (2008) mentioned convenience sampling as when researchers selected participants because they were willing and readily available.
Table I. Distribution of Participants
Gender
N
Percentage
Male
54
35.5
Female
98
64.5
Total
152
100
Grade Levels
First-Year
75
49.3
Second-Year
77
50.7
Total
152
100
Science Process Skills Observation Checklist (SPSOC): The SPSOC developed by Irwanto, Rohaeti and Prodjosantoso (2018) was used to measure the students’ science process skills during the chemistry laboratory course. The SPSOC consisted of 18 statements, including 8 items of basic process skills (44.44%) and 10 items of integrated process skills (55.56%). The basic SPS included observing, inferring, measuring, and communicating. Whereas integrated SPS included identifying and controlling variables, investigating, formulating hypotheses, conducting an experiment, and interpreting data. Each item had a 4-point Likert scale (4=highly observed to 1=unobserved) which the highest score indicates that the students have good science process skills during laboratory activities. The minimum and maximum possible scores obtained by each student were 18 and 72 points respectively. In the pilot study, the instrument was tested to 176 randomly selected undergraduate chemistry students in Yogyakarta. The coefficient of Cronbach’s alpha reliability was .88. It showed that the SPSOC was reliabel to measure the students’ science process skills. The students’ SPS were stratified into 3 levels; low (<36 points), moderate (36–54 points), and high (>54 points).
The following statements were the examples of the SPSOC:
Observing the objects using all the senses
Recording the observations according to their characteristics
Reading the measurement results accurately
Presenting data in the form of tables, graphs, or diagrams
Identifying the independent, dependent, and controlled variables
Choosing the appropriate design to test the hypothesis
Formulating the hypotheses that can be tested for truth
Drawing the conclusions based on a series of investigations
Attitudes towards Chemistry Scale (ATCS): The ATCS designed by researchers was administered to measure students’ attitudes towards chemistry. The ATCS consisted of 9 subscales which were elaborated into 36 statements (18 positive and 18 negative). The subscale included rationality, curiosity, open-mindedness, objectivity, aversion to superstition, suspended judgment, critical mindedness, intellectual honesty, and humility. Each subscale consisted of 4 statements (2 positive and 2 negative), where each item had a 4-point Likert scale (4=strongly agree to 1=strongly disagree). Negative statements were scored in the opposite direction. The minimum and maximum scores possible to be obtained by each student were 36 and 144 points respectively. In the pilot study, the instrument was tested to 145 randomly selected undergraduate chemistry students in Yogyakarta. The coefficient of Cronbach’s alpha reliability was .84. It showed that the ATCS was reliable for measuring students’ attitudes towards chemistry. Students’ attitudes were classified into 3 levels; low/negative (<72 points), moderate/neutral (72–108 points), and high/positive attitudes (>108 points).
The following statements were the examples of ATCS:
I plan an experiment systematically
I would like to make science perfect through chemistry experiments
I observe accurately
I do not acknowledge newer and more relevant theories on chemistry
I am learning to be a chemist
I report the investigation's result honestly
I think laboratory activities help me comprehend how chemistry influences our daily life
I interest to continue the habit of researching outside of lectures
The survey was conducted in November 2017 after obtaining official permission from the Head of the Department of Chemistry Education, Yogyakarta State University, Indonesia. The researchers conducted a survey for the first-year students taking the General Chemistry Lab course and second-year students who attended the Analytical Chemistry Lab course. The first day, the researchers conducted an observation for 100 minutes by using the SPSOC, while the second day the students completed the ATCS for 50 minutes. Before distributing the ATCS, the researchers explained the purposes and objectives of the study to students that this study had no effect on their learning outcomes. In the study, student position was only as a participant. Participants were asked to complete the questionnaire, which was given once at the end of the experiment. Finally, the ATCS was collected to the researchers for administrated and then analyzed.
SPSS 17 (SPSS Inc., Chicago, IL, USA) was performed to analyze data obtained from both instruments. Descriptive statistics were used to test the mean and standard deviation. After fulfilling the normality assumption (p>.05), the t-test was employed to determine the difference between SPS and CA scores between male and female students at the .05 significance level. Pearson’s correlation was conducted to explain the significance of relationships between variables. The strength of the relationship between variables was determined using Cohen’s (1988) correlation coefficient. These criteria were categorized into small (r=.10 to .29), medium (r=.30 to .49) and large effects (r=.50 to 1.00). Finally, regression analysis was executed to express the relationship between SPS and CA.
