A Task Model for Supporting Virtual Laboratory based on Inquiry Skills, Social and Scientific Communication

siska Desy fatmaryanti, Umi Pratiwi, Raden Wakhid Akhdinirwanto, Dwi Sulisworo

Abstract


Comprehensive monitoring in virtual laboratory learning needs a task model. This model was design based on inquiry skills, social and scientific communication of prospective physics teachers. This research was research and development (R&D) using a preliminary study (literature studies, field surveys, and preparation of the initial product) and development of the model (within limited testing). Respondents were 54 prospective physics teachers and five physics lecturers from several universities in Indonesia. The analysis was done by descriptive qualitative, and quantitative. There are two essential parts of the task model. The first part consists of six inquiry steps, which describe the interactions between students with their virtual experiments. The second part consists of three inquiry steps that analyze how students communicate their virtual experiments through verbal, picture, and diagrammatic representations. Based on these findings, the task model's design is essential to develop inquiry skills, social and scientific communication for prospective physics teachers. The researcher can use this task model in the next step of R&D.


Keywords


Task Model; Virtual Laboratory; Inquiry Skills; Social Communication; Scientific communication

References


D. Liu, P. Valdiviezo-Díaz, G. Riofrio, Y. M. Sun, and R. Barba, “Integration of Virtual Labs into Science E-learning,” Procedia Comput. Sci., vol. 75, no. Vare, pp. 95–102, 2015.

Gunawan, A. Harjono, H. Sahidu, and H. L, “Virtual Laboratory of Electricity Concept to Improve Prospective Physics Teachers’ Creativity,” J. Pendidik. Fis. Indonesia., vol. 13, no. 2, pp. 79–87, 2017.

E. Ural, "The Effect of Guided-Inquiry Laboratory Experiments on Science Education Students' Chemistry Laboratory Attitudes, Anxiety, and Achievement," J. Educ. Train. Stud., vol. 4, no. 4, pp. 217–227, 2016.

S. D. Fatmaryanti, Suparmi, Sarwanto, Ashadi, and H. Kurniawan, “Magnetic force learning with Guided Inquiry and Multiple Representations Model (GIMuR) to enhance students’ mathematics modeling ability,” Asia-Pacific Forum Sci. Learn. Teach., vol. 19, no. 1, pp. 1–22, 2018.

Chu Samuel et al., 21st Century Skills Development Through Inquiry-Based Learning. Singapore: Springer, 2017.

S. J. Husnaini and S. Chen, "Effects of guided inquiry virtual and physical laboratories on conceptual understanding, inquiry performance, scientific inquiry self-efficacy, and enjoyment," Phys. Rev. Phys. Educ. Res., vol. 15, no. 1, p. 10119, 2019.

K. N. Marambe, J. D. Vermunt, and H. P. A. Boshuizen, “A cross-cultural comparison of student learning patterns in higher education,” High. Educ., vol. 64, no. 3, pp. 299–316, 2012.

D. Sulisworo, S. P. Agustin, and E. Sudarmiyati, "Cooperative-blended learning using Moodle as an opensource learning platform," Int. J. Technol. Enhanc. Learn., vol. 8, no. 2, pp. 187–198, 2016.

E. Darsih, “Learner-Centered Teaching: What Makes It Effective,” Indones. EFL J., vol. 4, no. 1, p. 33, 2018.

J. R. Brinson, “Computers & Education Learning outcome achievement in non-traditional ( virtual and remote ) versus traditional ( hands-on ) laboratories : A review of the empirical research,” Comput. Educ., vol. 87, pp. 218–237, 2015.

R. Estriegana, J. A. Medina-Merodio, and R. Barchino, “Student acceptance of virtual laboratory and practical work: An extension of the technology acceptance model,” Comput. Educ., vol. 135, no. August 2018, pp. 1–14, 2019.

A. H. Maarop and M. A. Embi, “Implementation of Blended Learning in Higher Learning Institutions: A Review of Literature,” Int. Educ. Stud., vol. 9, no. 3, p. 41, 2016.

C. Fowler, “Virtual reality and learning: Where is the pedagogy?,” Br. J. pf Educ. Technol., vol. 46, no. 2, pp. 412–423, 2015.

M. J. Jacobson, C. E. Taylor, and D. Richards, “Computational scientific inquiry with virtual worlds and agent-based models: new ways of doing science to learn science,” Interact. Learn. Environ., vol. 24, no. 8, pp. 2080–2108, 2016.

S. E. Brownell, J. V. Price, and L. Steinman, “Science communication to the general public: Why we need to teach undergraduate and graduate students this skill as part of their formal scientific training,” J. Undergrad. Neurosci. Educ., vol. 12, no. 1, pp. 6–10, 2013.

M. Akçayir, G. Akçayir, H. M. Pektaş, and M. A. Ocak, “Augmented reality in science laboratories: The effects of augmented reality on university students’ laboratory skills and attitudes toward science laboratories,” Comput. Human Behav., vol. 57, pp. 334–342, 2016.

A. Konak, T. K. Clark, and M. Nasereddin, “Using Kolb’s Experiential Learning Cycle to improve student learning in virtual computer laboratories,” Comput. Educ., vol. 72, pp. 11–22, 2014.

M. Gall, J. Gall, and W. R. Borg, Educational research: An introduction, 8th ed. New York: Pearson Education, 2007.

W. Swann, “The Impact of Applied Cognitive Learning Theory on Engagement with eLearning Courseware,” J. Learn. Des., vol. 6, no. 1, pp. 61–74, 2013.

C. Y. Li, “Persuasive messages on information system acceptance: A theoretical extension of elaboration likelihood model and social influence theory,” Comput. Human Behav., vol. 29, no. 1, pp. 264–275, 2013.

A. Amiati and J. Ikhsan, “the Effect of Virtual Reality Laboratory on Conceptual Understanding in Electrolytes and Non-Electrolytes,” J. Educ. Learn., vol. 13, no. 3, pp. 362–369, 2019.

C. J. Wenning, “Levels of inquiry: Hierarchies of pedagogical practices and inquiry processes,” J. Phys. Teach. Educ. Online, vol. 2, no. 3, pp. 3–11, 2005.

C. J. Wenning, “Experimental Inquiry in Introductory Physics Courses,” J. Phys. Teach. Educ. Online, vol. 6, no. 2, pp. 2–8, 2011.

Abdurrahman, F. Ariyani, H. Maulina, and N. Nurulsari, "Design and validation of inquiry-based STEM learning strategy as a powerful alternative solution to facilitate gifted students facing 21st-century challenging," J. Educ. Gift. Young Sci., vol. 7, no. 1, pp. 33–56, 2019.

S. Dole, L. Bloom, and K. Kowalske, “Transforming Pedagogy : Changing Perspectives from Teacher-Centered to Learner-Centered The Interdisciplinary Journal of Problem-based Learning Transforming Pedagogy : Changing Perspectives from Teacher-Centered to Learner-Centered,” Interdiscip. J. Probl. Learn., vol. 10, no. 1, 2015.

S. F. E. Rovers, R. E. Stalmeijer, J. J. G. van Merriënboer, H. H. C. M. Savelberg, and A. B. H. de Bruin, "How and why do students use learning strategies? A mixed-methods study on learning strategies and desirable difficulties with effective strategy users," Front. Psychol., vol. 9, no. DEC, pp. 1–12, 2018.

W. Zhang, Y. Hsu, C. Wang, and Y. Ho, “International Journal of Science Exploring the Impacts of Cognitive and Metacognitive Prompting on Students ’ Scientific Inquiry Practices Within an E-Learning Environment," Int. J. Sci. Educ., no. January 2015, pp. 37–41, 2015.

S. D. Fatmaryanti, Suparmi, Sarwanto, Ashadi, and D. A. Nugraha, “Using multiple representations model to enhance student’s understanding in magnetic field direction concepts,” in Journal of Physics: Conference Series, 2019, vol. 1153, no. 1.

S. D. Fatmaryanti, Ashari, and V. S. Wahidah, “Students’ representation based on high order thinking skills for the concept of light,” in Journal of Physics Conference Series, 2020, vol. 1517, no. 1, p. 12056.

E. Vuopala, P. Hyvönen, and S. Järvelä, “Interaction forms in successful collaborative learning in virtual learning environments,” Act. Learn. High. Educ., vol. 17, no. 1, pp. 25–38, 2016.

D. K. Tari and D. Rosana, “Contextual Teaching and Learning to Develop Critical Thinking and Practical Skills,” in Journal of Physics: Conference Series, 2019, vol. 1233, no. 1, p. 12102.

D. Sulisworo, D. A. Kusumaningtyas, and T. Handayani, “Self-Regulated Learning of Junior High School Students to Predict Online Learning Achievement,” in International Conference on Community Development (ICCD 2020), 2020, pp. 203–207.

M. Pedaste et al., “Phases of inquiry-based learning: Definitions and the inquiry cycle,” Educ. Res. Rev., vol. 14, pp. 47–61, 2015.

M. Cukurova, R. Luckin, E. Millán, and M. Mavrikis, “The NISPI framework: Analysing collaborative problem-solving from students’ physical interactions,” Comput. Educ., vol. 116, pp. 93–109, 2018.

N. Hernández-Sellés, Pablo-César Muñoz-Carril, and M. González-Sanmamed, “Computer-supported collaborative learning: An analysis of the relationship between interaction, emotional support and online collaborative tools,” Comput. Educ., vol. 138, pp. 1–12, 2019.




DOI: http://doi.org/10.11591/ijere.v11i1.21737

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Institute of Advanced Engineering and Science

International Journal of Evaluation and Research in Education (IJERE)
p-ISSN: 2252-8822, e-ISSN: 2620-5440

View IJERE Stats

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