Journal
Learning Cycle 7e Model - Based Multiple Representation to Reduce Misconseption of The Student on Heat Theme
Journal of Innovative Science Education · Vol. 7 No. 1 (2018) · pp. 45–52
- ISSN
- 2502-4523, 2252-6412
- Published
- 2018-03-27
- Publisher
- Universitas Negeri Semarang
- Language
- eng
Abstract
Students' success is determined by the conceptual that has been owned by the students while studying certain theme. New concepts will be elusive if the relevant concepts have not been owned by the students. Based on the observation and interview in SMP Negeri 1 Doro indicated that the heat concept is one of the elusive concept in science learning by the students. This study aims to: (1) describe the misconception experienced by students on the heat theme using a diagnostic test that is three-tier multiple choice, (2) determine the implementation of learning cycle 7E model-based multiple representation on the heat theme, (3) determine the effectiveness of the application of the learning cycle 7E model-based multiple representation in reducing misconceptions students on the heat theme. This study used a mixed method research with concurrent triangulation strategy. The identification results of students misconceptions on the heat theme obtained by average percentage of students' conceptions in the category Know the Concept (TK) is 43.44%. The average percentage of students' conceptions in the category Don’t Know the Concepts (TTK) is 15.31%. The average percentage of all misconceptions (MK) experienced by students in heat theme is 41.26%. Sub heat themes that most experienced misconceptions are ice melt events, boiling water events, heat calculations in the chart, the specific heat of water and oil, the absorption and release of heat, and the relationship of the specific heat with temperature changes. The implementation of learning cycle 7E model-based multiple representation obtained by the average percentage of 84.67% with the criteria very well. Learning cycle 7E model-based multiple representation became effective in reducing students misconceptions on the heat theme due to the decrease percentage of students misconceptions in the experimental class 18.72% is higher than the control class which only 9.68%. The analysis calculation result of the Equal Variance Assumed against independent sample of t test towards the decrease of misconceptions level indicate significance (2-tailed) of 0.003 < 0.05, which means that there are differences in average reduction of misconceptions in the experimental class and control class. Students' success is determined by the conceptual that has been owned by the students while studying certain material. New concepts will be elusive if the relevant concepts have not been owned by the students. Based on the observation and interview in SMP Negeri 1 Doro indicated that the heat concept is one of the elusive concept in science learning by the students. This study aims to: (1) describe the misconception experienced by students on the heat material using a diagnostic test that is three-tier multiple choice,(2) determine the implementation of learning cycle 7E model-based multiple representation on the heat material, (3) determine the effectiveness of the application of the learning cycle 7E model-based multiple representation in reducing misconceptions students on the heat material. This study used a mixed method research with concurrent triangulation strategy. The identification results of students misconceptions on the heat material obtained by average percentage of students' conceptions in the category Know the Concept (TK) is 43.44%. The average percentage of students' conceptions in the category Don’t Know the Concepts (TTK) is 15.31%. The average percentage of all misconceptions (MK) experienced by students in heat material is 41.26%. Sub heat materials that most experienced misconceptions are ice melt events, boiling water events, heat calculations in the chart, the specific heat of water and oil, the absorption and release of heat, and the relationship of the specific heat with temperature changes. The implementation of learning cycle 7E model-based multiple representation obtained by the average percentage of 84.67% with the criteria very well. Learning cycle 7E model-based multiple representation became effective in reducing students misconceptions on the heat material due to the decrease percentage of students misconceptions in the experimental class 18.72% is higher than the control class which only 9.68%. The analysis calculation result of the Equal Variance Assumed against independent sample of t test towards the decrease of misconceptions level indicate significance (2-tailed) of 0.003 <0.05, which means that there are differences in average reduction of misconceptions in the experimental class and control class.
Collaboration network of the authors
40 authors · 216 co-authorship links · 8 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- State University of Semarang
- University of Indonesia
- University of Szeged
- National Research and Innovation Agency
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Ani Rusilowati | State University of Semarang | 10 |
| Hartono Hartono | Affiliation unknown | 4 |
| Lisdiana Lisdiana | Affiliation unknown | 4 |
| Sudarmin Sudarmin | Affiliation unknown | 4 |
| Arif Widiyatmoko | State University of Semarang | 3 |
| Sunyoto Eko Nugroho | State University of Semarang | 3 |
| Masturi Masturi | State University of Semarang | 3 |
| Bambang Subali | Affiliation unknown | 3 |
| Isa Akhlis | State University of Semarang | 3 |
| Budi Astuti | Affiliation unknown | 3 |
| Fidia Fibriana | State University of Semarang | 2 |
| Saiful Ridlo | State University of Semarang | 2 |
| Navies Luthvitasari | Affiliation unknown | 2 |
| Putut Marwoto | State University of Semarang | 2 |
| Achmad Sopyan | Affiliation unknown | 2 |
| Siti Alimah | State University of Semarang | 2 |
| Sulhadi Sulhadi | Affiliation unknown | 2 |
| Sigit Saptono | State University of Semarang | 2 |
| Ellianawati Ellianawati | State University of Semarang | 2 |
| Wiwi Isnaeni | State University of Semarang | 2 |
| Hardi Suyitno | Affiliation unknown | 2 |
| . Hartono | Affiliation unknown | 2 |
| Hadi Susanto | National Research and Innovation Agency | 2 |
| Mosik Mosik | Affiliation unknown | 2 |
| Supriyadi Supriyadi | Affiliation unknown | 2 |
| Khumaedi Khumaedi | Affiliation unknown | 2 |
| Parmin Parmin | State University of Semarang | 2 |
| Novi Ratna Dewi | State University of Semarang | 2 |
| Prasetyo Listiaji | University of Szeged | 2 |
| Nathan Hindarto | State University of Semarang | 2 |
| Murbangun Nuswowati | State University of Semarang | 2 |
| Woro Sumarni | State University of Semarang | 2 |
| Sri Haryani | Affiliation unknown | 2 |
| Eko Purwanti | Affiliation unknown | 2 |
| Muhammad Hanif Nadhif | University of Indonesia | 1 |
| Hanif Assyarify | Affiliation unknown | 1 |
| Em Yunir | University of Indonesia | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.