Reflections of simulated patients on breast models as an evaluation of learning media in midwifery education

Herlyssa Herlyssa(1*), Elly Dwi Wahyuni(2), Juli Oktalia(3)
(1) Poltekkes Kemenkes Jakarta III
(2) Poltekkes Kemenkes Jakarta III
(3) Poltekkes Kemenkes Jakarta III
(*) Corresponding Author
DOI : 10.30604/jika.v8i3.2061

Abstract

Breast models are one of the learning media used by simulated patients in midwifery care practicums. Simulated patients' perspective is a new understanding in the selection of learning media. It is hoped that the results of the reflection carried out by the simulation patient can be used for the procurement of laboratory equipment and the development of designing learning models that are lower cost but have good effectiveness. This study aims to obtain group reflections from simulation patients regarding breast models used by simulation patients for midwifery cares scenario. This research is conducted by descriptive-analytic research. The sample in this research is the total population of the simulated patients in one midwifery school in Jakarta (24 respondents). Data collection was carried out through questionnaires. There are 3 breast models. We coded these three models into A, B, and C. The research results show that based on model function indicators, model B has a better function with a mean of 4.00 compared to model A (mean 3.18) and model C (mean 3.93). Based on model design, model B is also considered to have the best design (mean 3.67) compared to models A and C. The results of this study show that the most recommended model to use is model B (91.6%), followed by model C (66.7%) and model A (50%). The simulation patient recommends that the use of breast models should meet several criteria such as ethical norms, the weight of the model, the flexible nature of the model, ease of use, and comfort, it can be combined with other learning models, and students are not afraid to use it without worrying about damaging it.

Keywords


Breast Model; Simulation; Learning Media; Midwifery Education

References


Alirezabeigi, S., Masschelein, J., & Decuypere, M. (2020). Investigating Digital Doings through Breakdowns: A Sociomaterial Ethnography of a Bring Your Own Device school. Learning, Media and Technology, 45(2), 193-207.

Alsoufi, A., Alsuyihili, A., Msherghi, A., Elhadi, A., Atiyah, H., Ashini, A., ... & Elhadi, M. (2020). Impact of the COVID-19 Pandemic on Medical Education: Medical Students’ Knowledge, Attitudes, and Practices Regarding Electronic Learning. PloS one, 15(11), e0242905.

Bogren, M., Kaboru, B. B., & Berg, M. (2021). Barriers to delivering quality midwifery education programmes in the Democratic Republic of Congo—An Interview Study with Educators and Clinical Preceptors. Women and Birth, 34(1), e67-e75.

Dai, X., Ke, C., Quan, Q., & Cai, K. Y. (2021). RFlySim: Automatic Test Platform for UAV Autopilot Systems with FPGA-Based Hardware-in-the-Loop Simulations. Aerospace Science and Technology, 114, 106727.

de Paula Ferreira, W., Armellini, F., & De Santa-Eulalia, L. A. (2020). Simulation in Industry 4.0: A State-of-the-Art Review. Computers & Industrial Engineering, 149, 106868.

Dewenter, R., Linder, M., & Thomas, T. (2019). Can Media Drive the Electorate? The Impact of Media Coverage on Voting Intentions. European Journal of Political Economy, 58, 245-261.

Firoozehchian, F., Zareiyan, A., Geranmayeh, M., & Behboodi Moghadam, Z. (2022). Domains of Competence in Midwifery Students: A Basis for Developing a Competence Assessment Tool for Iranian Undergraduate Midwifery Students. BMC Medical Education, 22(1), 704.

Fromm, J., Radianti, J., Wehking, C., Stieglitz, S., Majchrzak, T. A., & vom Brocke, J. (2021). More than Experience?-On the Unique Opportunities of Virtual Reality to Afford a Holistic Experiential Learning Cycle. The Internet and Higher Education, 50, 100804.

Glenton, C., Javadi, D., & Perry, H. B. (2021). Community health workers at the dawn of a new era: 5. Roles and tasks. Health Research Policy and Systems, 19(3), 1–16.

Herlyssa, H., Wahyuni, E. D., Astuti, J. D., & Rahayu, S. (2022). Penggunaan Model Abdomen Smart pada Pasien Simulasi dalam Meningkatkan Kompetensi Penilaian Tinggi Fundus Uteri pada Ibu Nifas. Prosiding Semnas Hilirisasi Hasil Penelitian dan Pengabdian Masyarakat Tahun 2022, 52-59.

Herlyssa, Elly Dwi Wahyuni, Jujun Dwi Astuti, & Sri Rahayu. (2022). SMART Abdomen Model as Clinical Learning Media in Improving Midwifery Student Competence in Postpartum Care. SEAJOM: The Southeast Asia Journal of Midwifery, 8(2), 75-82. https://doi.org/10.36749/seajom.v8i2.181

Herlyssa, H., Wahyuni, E. D., Astuti, J. D., & Rahayu, S. (2023, July). The Use of the" SMART" Abdomen Model to Achieve Student Competency Improvement in Physical Examination in Postpartum. In Proceeding International Conference on Health Research and Science (Vol. 1, No. 1, pp. 276-289).

Hernon, O., McSharry, E., MacLaren, I., & Carr, P. J. (2023). The Use of Educational Technology in Teaching and Assessing Clinical Psychomotor Skills in Nursing and Midwifery Education: A State-of-the-Art Literature Review. Journal of Professional Nursing, pp. 45, 35-50.

Karambatsakidou, A., Steiner, K., Fransson, A., & Poludniowski, G. (2020). Age-Specific and Gender-Specific Radiation Risks in Paediatric Angiography and Interventional Cardiology: Conversion Coefficients and Risk Reference Values. The British Journal of Radiology, 93(1110), 20190869.

Levorstad, T., Saue, M. S., Nilsen, A. B. V., & Vik, E. S. (2022). Midwives’ Experiences of an Organizational Change in Early Postpartum Care Services in Norway: A Qualitative Study. European Journal of Midwifery, 6.

Lomicka, L., & Ducate, L. (2021). Using Technology, Reflection, and Noticing to Promote Intercultural Learning during Short-Term Study Abroad. Computer Assisted Language Learning, 34(1-2), 35-65.

O'Connor, M., Stowe, J., Potocnik, J., Giannotti, N., Murphy, S., & Rainford, L. (2021). 3D Virtual Reality Simulation in Radiography Education: The Students' Experience. Radiography, 27(1), 208-214.

Ramdhan, M. (2021). Metode Penelitian. Cipta Media Nusantara.

Risnaini, E., Hakim, Z. R., & Taufik, M. (2020). Thematic-Based Big Book Learning Media as a Facility of Visual Learning Styles for Students. Jurnal Ilmiah Sekolah Dasar, 4(3), 407-419.

Salifu, D. A., Heymans, Y., & Christmals, C. D. (2022). Facilitating the Development of Clinical Competence in a Low-Resource Setting: Perceptions and Challenges of Nurse Educators. Nurse Media Journal of Nursing, 12(1).

Sexcio, E. B., & Dafit, F. (2022). Card Macth Circle: Innovative Learning Media on Social Science Learning in Grade IV Elementary School. Journal of Education Technology, 6(1), 156-164.

Simamora, R. M. (2020). The Challenges of Online Learning during the COVID-19 Pandemic: An Essay Analysis of Performing Arts Education Students. Studies in Learning and Teaching, 1(2), 86-103.

Suri, D., & Chandra, D. (2021). Teacher's Strategy for Implementing Multiculturalism Education Based on Local Cultural Values and Character Building for Early Childhood Education. Journal of Ethnic and Cultural Studies, 8(4), 271-285.

Susanti, A. I., Ali, M., Hernawan, A. H., Rinawan, F. R., Purnama, W. G., Puspitasari, I. W., & Stellata, A. G. (2022). Midwifery Continuity of Care in Indonesia: Initiation of Mobile Health Development Integrating Midwives’ Competency and Service Needs. International Journal of Environmental Research and Public Health, 19(21), 13893.

Tabroni, I., Irpani, A., Ahmadiah, D., Agusta, A. R., & Girivirya, S. (2022). Implementation and Strengthening of the Literacy Movement in Elementary Schools Post the COVID-19 Pandemic. Multicultural Education, 8(01), 15-31.

Tambak, S. (2021). The Method of Counteracting Radicalism in Schools: Tracing the Role of Islamic Religious Education Teachers in Learning. MIQOT: Jurnal Ilmu-ilmu Keislaman, 45(1), 104-126.

Towers, A., Dixon, J., Field, J., Martin, R., & Martin, N. (2022). Combining Virtual Reality and 3D?Printed Models to Simulate Patient?Specific Dental Operative Procedures—A Study Exploring Student Perceptions. European Journal of Dental Education, 26(2), 393-403.

Zhang, Z., Chong, A., Pan, Y., Zhang, C., & Lam, K. P. (2019). Whole Building Energy Model for HVAC Optimal Control: A Practical Framework Based on Deep Reinforcement Learning. Energy and Buildings, pp. 199, 472-490.


Article Statistic

Abstract view : 114 times
PDF (Bahasa Indonesia) views : 19 times

Dimensions Metrics

How To Cite This :

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 Elsa Surya

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.