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AN EVALUATION OF CHEMISTRY INSTRUMENT MODEL
128 Based on classroom experience, students still do not grasp how to begin practical and continue to ask how to complete the analytical process using chemical instrumentation and how the notion of machine components works, even after it has been repeatedly presented to them. Students also struggle to understand the operation of the instrumentation's components and lack a thorough understanding of chemistry at the atomic and molecular levels. As a result, they failed to evaluate the sample despite receiving the data.
Hence, an instrumentation model was created to aid the teaching system in achieving that goal.
Before this model is used with students, a survey is undertaken to aid in the development of a higher- quality and more relevant model.
In the scope of this study, the selected chemical model is Gas Chromatography Mass Spec (GCMS) which is one of the chemical instrumentation tools commonly used in the laboratory. This study focuses on the process of building such a model. After the construction process is completed, a survey process is conducted to ensure that the quality of construction can be continuously improved
DATA AND RESEARCH METHOD
In this inquiry, the researchers have opted to collect data via a questionnaires form. In accordance with the concept of the quantitative study, questionnaires are the most appropriate data collection instruments to use because this style of questionnaire distribution simplifies the data collection method from respondents. [11,12]. Furthermore, it saves time because data can be acquired more quickly, as well as research expenditures [13]. Thus, consumption questionnaire forms are more appropriate to employ as a method to collect data for this study [12] because they are more practical and effective, and their use can improve the accuracy and truthfulness of the respondents' responses.
The Measurement Concept and procedure
Table 1: Evaluation types of GCMS Model Instrumentation Evaluation Types
Poor (1)
Satisfactory (2)
Fair (3)
Very Good
(4)
Excellent (5) Design
In terms of shape, colour, and design, This model can attract users. The comfort and appropriateness of its use can be ensured.
Material suitability
Material selection is appropriate, easy to obtain, practical, accurate and does not exceed the allocated costs
Between the ages of 25 to 46, 30 participants were taken for this survey who have teaching backgrounds, researchers or degree holders. Likert scale questionnaires were used by 5 (strongly agree, disagree, neutral, agree and strongly agree) [14,15]. Detailed criteria as shown in Table 1. Prior to this survey, a full description of the concept of instrumentation building was given to the respondents. The explanation is presented in the form of a 3D animated video. They were then given a virtual survey form to complete.
129 MAIN RESULTS
a) Reliability data
The raw data for the responses of each participant were coded numerically. Data were entered and Statistical Package for Social Science (SPSS) version 27.0 was used to analyse the results of this project. A Cronbach's alpha by using internal reliability was performed to assess the reliability of the questionnaires.
The internal reliability result is shown in Table 2 below.
Table 2: The internal reliability result.
Reliability Statistics Cronbach's Alpha N of Items
0.863 4
The alpha value is 0.863. Based on Table 1, it can be interpreted that the questions given were understandable for most of the respondents.
b) Normality test
Table 3: Normality Data Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Design [In terms of shape, color, and design]
.273 30 .000 .868 30 .001
Design [The comfort and appropriateness ]
.251 30 .000 .889 30 .005
Material [Material selection is appropriate, easy to obtain, practical]
.260 30 .000 .870 30 .002
Material[selection is accurate and does not exceed the allocated costs]
.283 30 .000 .876 30 .002
a. Lilliefors Significance Correction b. p value < 0.05
By using the Shapiro-Wilk and Kolmogorov-Smirnova test, the statistics show a significant p-value which is lower than 0.05 for both groups. Therefore, the non-parametric data is assumed. Thus, the descriptive data is proceeded to investigate the result.
c) Descriptive analysis
Table 3 represented the data for Designa&b and Materiala&b with sample size, N = 30. The overall mean (M = 3.58). The results were interpreted using descriptive analysis SPSS. From the output data, it remarks a positive respond for design and material for this model development. With the value mean (M= 3.60) it indicates that in average all the respondents gave a good claim in terms of material selection. Furthermore, utilising this approach is projected to be practical in managing instrument analysis. In terms of design which is colour and shape, the lowest value of standard deviation is (SD
= 0.894) and it also found the data collected from the material perspective in term cost consumed
130 showed a bit dispersed (SD = 1.037). As a result of these observations, it appears that the value of the data acquired is comparable. The value of standard deviation is below 1 indicating that all the dataset values are closed to each other [16]. If the data values are all close together, the variance will be smaller. If the data behaves in a normal curve, then 68% of the data points will fall within one standard deviation of the average, or mean data point. This value is considered acceptable.
Table 3: Descriptive Analysis for the Model Design and Material
Designa (shape, colour,
and design)
Designb (comfort &
appropriateness )
Materiala ( selection is appropriate, easy to
obtain, practical)
Materialb (accurate and does
not exceed the allocated costs) 3
0 N
Valid 30 30 30 30
Missing 0 0 0 0
Mean 3.60 3.53 3.60 3.60
Median 4.00 3.50 4.00 4.00
Mode 4 4 4 4
Std. Deviation .894 .973 .968 1.037
Skewness -.322 -.581 -.303 -.683
Std. Error of Skewness
.427 .427 .427 .427
Kurtosis -.489 .333 -.771 .044
Std. Error of Kurtosis
.833 .833 .833 .833
Other than that, these findings highlighted the potential of the model development promising a positive impact to make it a flexible tool as a teaching aid to support the learning environment. This model can attract users in terms of shape, colour and design (M =3.60). In addition, the comfort and appropriateness of its use can be ensured. These findings depicted that the design has to consider the comforts and appropriateness to make it practical to be used during teaching process. It is suggested the model design must be simple, not complicated compartment to catch student attention and curiosity [17]. The results were also in good agreement with other previous studies such as Tsai (2020) in which they suggest that using instructional aids had a good impact on students' learning and interaction with the topic. [17-19]. Tuli et al. (2015) also reported by superimposing virtual visuals on actual ones, it simplifies and improves the user's engagement with the physical world [20]. Apart from the teaching aids applied to the students, some respondents gave the opinion that the addition of digital elements to help students’ visuals such as 3d animation when explaining to students can also help students understand.
131
a) c)
b) d
)
Figure 1: The shape of cumulative data was depicted by a histogram.
CONCLUSION
From these findings of this pilot study, the responders gave positive feedback on the GCMS model's development. The production of models that can be effectively implemented to students must be addressed to maintain a successful and ongoing learning process. As a result, lecturers can utilize this chemical instrumentation model to describe a component in a way that students can grasp clearly and confidently, and they can complete practical on their own without needing much supervision from the lecturer. However, modifications are still required from time to time, such as the addition of more digital components, such as QR codes, to allow pupils to repeat topics. The construction materials can also be improved to make the model more marketable. It is intended that this research would enrich lecturers and researchers, allowing them to produce more engaging and enjoyable teaching and learning experiences.
ACKNOWLEDGEMENT
The author would like to express gratitude to the staff and students at the Preparatory Centre for Science and Technology of Universiti Malaysia Sabah. The Acculturation Grant Scheme at Universiti Malaysia Sabah provided funds for this study (SGA0116-2019).
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