10 SES 13 B, Research on Programmes and Pedagogical Approaches in Teacher Education
Today in the face of economic, environmental, and social challenges, formal education often becomes a gatekeeper to many professions that require specific types of skill sets and expertise. In addition, pervasiveness of digital technologies has increased the pace at which individuals communicate and exchange information, requiring competence in processing multiple forms of information to accomplish tasks that are trans-disciplinary including the field of education.
To survive and thrive in today’s fast-changing schools and systems, prospective teachers will need to become adaptive experts. Experts who can apply the skills that they can also predict the outcomes of those skills and who can solve the problems for the novel situations using their knowledge and experiences can be defined as “adaptive experts” (Hatano & Inagaki, 1986). To be an adaptive expert, learning experiences should promote being innovative and efficient to grow and develop simultaneously (Schwartz, Bransford & Sears, 2005). Adaptive experts tend to be more open to investigate, to use their metacognitive and self-regulation skills, and to hold more advanced personal epistemologies. These characteristics make the adaptive experts flexible, innovative, and creative especially in novel situations (Hatano & Oura, 2003). Undergraduate education can play a critical role in improving the adaptive skills that are important for prospective teachers’ future productivity and adaptability in every field. Therefore, teacher education must integrate practice and mastery of adaptive expertise (AE) dimensions in the undergraduate curriculum.
Classrooms are the unique contexts that are really unexpected each hour every day. Insana (2015) define classrooms as ‘complex adaptive systems’. Therefore, teachers who have AE skills will be able to handle unexpected situations easily. In addition, integration of new information and communication technologies into education and pervasiveness of STEM education makes it necessary to be more adaptive for both prospective and experienced teachers (Crawford, et. al. 2005). Hence, it is important to train adaptive expert teachers to prepare them for this challenging and swiftly developing environment. Therefore, identifying the AE characteristics of prospective teachers will help to make suggestions to enhance the quality of teacher education.
Based on the information above this study aims to interpret the students’ AE characteristics. In addition, it is aimed to investigate the relationships among participants’ AE related responses and demographic variables.
To determine the “baseline” AE among the sample population, an adaptive expertise survey (AES) (Fisher & Peterson, 2001) is administered to 110 prospective from different domains and different ranks. The participants were selected from a research university located at the capital city of the country. The instrument contains questions defining four dimensions of AE: multiple perspectives, metacognitive self-assessment, goals and beliefs, and epistemology. AES includes demographic questions (e.g., department, rank, experience, etc.) and a 42 items, 6-point AE Likert-scale. To reveal the dimensions of the instrument factor analysis will be used. To examine the relationships between AE dimensions and participants’ characteristics, F-tests (ANOVA) will be run. The reliability of the scale will be computed with reference to Cronbach’s alphas.
The expected outcomes for the study is that the students from different departments will have different AES scores because they have different experiences during their education. One other expected result is that students who have more research and work experience will have higher AES scores. Students with higher ranks will have higher AES scores as well. In many related studies that scrutinize the change of AE manifestation of students through years (Fisher & Peterson, 2001; Martin et al., 2006; Paletz et al., 2013, Walker et al., 2006) it was also found that AE characteristics had improved over time with diverse experience. These results will provide insights into research conducted to enhance undergraduate prospective teacher education. These findings expectedly will indicate that multiple perspectives, goals and beliefs, metacognitive skills and epistemology are good indicators of developing AE and that educators should consider promoting those skills in their teaching.
Crawford, V.M., Schlager, M., Toyama, Y., Riel, M., & Vahey, P., (2005). Characterizing Adaptive Expertise in Science Teaching. Paper presented at the American Educational Research Association Annual Conference, Montreal, Canada Fisher, F. T., & Peterson, P. L. (2001). A tool to measure adaptive expertise in biomedical engineering students. Paper presented at the ASEE Annual Conference and Exposition, Albuquerque, NM. http://www.scopus.com/inward/record.url?eid=2-s2.0-8744239096&partnerID=40&md5=3b7859499bcbb6cf2f25e203562fe054 Hatano, G., & Oura, Y. (2003). Commentary: Reconceptualizing school learning using insight from expertise research. Educational Researcher, 32(8), 26-29. doi: 10.3102/0013189x032008026 Hatano, G., & Inagaki, K. (1986). Two Courses of Expertise. In H. W. Stevenson, H. Azuma & K. Hakuta (Eds.), Child development and education in Japan (pp. 262-272). New York: W.H. Freeman. Insana, L.E. (2015). Understanding Adaptive Teaching Expertise in An Elementary Classroom Viewed as a Complex Adaptive System (Doctoral dissertation). University of Illinois at Urbana-Champaign Martin, T., Petrosino, A, J., Rivale, S., & Diller, K. R. (2006). The development of adaptive expertise in biotransport. New Directions for Teaching and Learning, 108, 35-47. doi: 10.1002/tl Paletz, S. B. F., Kim, K. H., Schunn, C. D., Tollinger, I., & Vera, A. (2013). Reuse and Recycle: The Development of Adaptive Expertise, Routine Expertise, and Novelty in a Large Research Team. Applied Cognitive Psychology, 27, 415–428. doi: 10.1002/acp.2928 Schwartz, D. L., Bransford, J. D., & Sears, D. (2005). Efficiency and Innovation in Transfer. In J. P. Mestre (Ed.), Transfer of Learning from a Modern Multidisciplinary Perspective. Greenwich, CT: IAP. Walker, J. M. T., Cordray, D. S., King, P. H., & Brophy, S. P. (2006). Design Scenarios as an assessment of adaptive expertise. International Journal of Engineering Education, 22(3), 645-651.
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