Jurnal Pendidikan Kimia Indonesia

A Study of Students' Difficulties and Conceptual Understanding of the Qualitative and Quantitative Analysis of Organic Compound Elements

2024-11-14T03:49:56+00:00

The study examines the learning difficulties and understanding of concepts faced by 28 chemistry students in organic compound element analysis courses using the RADEC learning model. The results showed a moderate increase in understanding. Still, several factors contributed to the low understanding, such as 28% of students reporting difficulty with Kjeldahl material, 24% with Dumas topics, 5% with Lassaigne destruction topics, 9% with Kjeldahl and Dumas topics, and 5% with digestion, distillation, and titration. Additionally, 24% of students did not understand the meaning of the questions, the lecture material's delivery, and the writing of reaction equations. Lack of preparation, such as reading before lectures, also contributed to low understanding.

The Development of ChemicoMine, Maritime Chemistry Comic Webtoon as an Edutainment Media Accordance to the IMO Regulations

2024-11-14T03:49:52+00:00

Based on the IMO Model Course 7.04 curriculum, chemistry is an introductory course that a candidate for sailor must master. However, most abstract chemistry concepts require technology-based learning media and edutainment. Webtoon is a digital comic that presents the concept of chemistry through real-life visualization strategies to attract student interest. This research aimed to create ChemicoMine, a maritime chemistry comic webtoon whose material content follows IMO regulations. The research method is R&D with the ADDIE model, which is limited to the Development stage. The instruments used in this research were analyst instruments of necessity, the validation tools of storyboard, the instrument validated by an expert in media and material, and the instrument for students. The data analysis techniques used the Likert scale 5. Validation results from an expert in material and media stated that the product received a percentage rating of 87.66% and 95.28% with the category (very good). Student response results obtained percentage of rating of 88.94% with the category (very good). Based on the results, ChemicoMine received a positive student response and can be used as an alternative edutainment media.

The Effect of STAD-Cooperative Learning Model with Concept Maps in Promoting Students’ Self-Efficacy and Conceptual Understanding of Thermochemistry

2024-11-14T03:50:02+00:00

The research sought to explore how employing the Student Team Achievement Division (STAD) cooperative learning model, along with concept maps, impacts the enhancement of students' self-efficacy and grasp of thermochemistry concepts. This study employed a quasi-experimental approach using a pretest-posttest control group design. It was carried out among 127 11th-grade science students from MAN 1 Bengkulu City, chosen through cluster random sampling. The information was gathered by utilizing self-efficacy questionnaires and conceptual understanding tests and was analyzed using Multivariate Analysis of Variance (MANOVA). The findings indicated that the obtained p-value was less than 0.05 (p<0.05), revealing a statistically significant difference in self-efficacy and conceptual understanding between students in the experimental and control groups. This suggests that students in the experimental group showed greater enhancements in self-efficacy and conceptual understanding when compared to those in the controlled group. Thus, These findings revealed that STAD-cooperative learning with concept maps had a better influence in enhancing self-efficacy and student conceptual understanding of thermochemistry.

How Are The Science Process Skills of Prospective Science Teacher Students: Studies in Inorganic Chemistry and Gender

2024-11-14T03:50:05+00:00

Prospective teacher students must be able to design practicums so that the learning process is meaningful. The skills that students develop in carrying out scientific discoveries, namely applying concepts, rules, and characteristics that exist in science, are called science process skills (SPS). Therefore, in building students' knowledge, students must have process skills in teaching so they can teach effectively and must have a good understanding of concepts and strong process skills. This research aims to describe the SPS of prospective science education teacher students through inorganic chemistry courses after going through learning with the discovery learning model. This research uses a quantitative approach with a pre-experimental design one-shot case study research method. The research results show that student SPS as a whole is in the high category with an average percentage of 59.71%. SPS analysis in classes A, B, and C, respectively, has an average percentage of 58.23%, 62.66%, and 58.24% in the high category. SPS analysis based on gender shows that the respective percentage of male students is 53.89% with the medium category for women and 59.81% for the high category.

The Influence of the STAD and NHT Learning Models on Students' Cognitive Achievement and Learning Motivation on Colloid Material in Banyumas

2024-11-14T03:49:59+00:00

This study aims to assess the impact of the Student Team Achievement Division (STAD) and Numbered Head Together (NHT) learning models on students’ cognitive achievement and learning motivation in colloidal material at MA Negeri 1 Banyumas. The study uses a quantitative approach with a quasi-experimental design, involving students from six XI science classes of MA Negeri 1 Banyumas. The first experimental group was taught using the STAD model, while the second group was taught using the NHT model. The sampling technique used was random sampling. Instruments included multiple-choice tests to measure cognitive achievement and learning motivation. Data analysis was carried out using an independent t-test. The results showed that both the STAD and NHT models had a significant impact on students’ cognitive achievement and learning motivation in colloid material. The p-values for the NHT learning model were 0.47 and 0.39, while the p-values for the STAD learning model were 0.17 and 0.16.