Knowledge Construction Schemata of Teachers in Solving Real World Non-Routine Problem Situation: Their Implications to Mathematics Education
Main Article Content
Abstract
The study investigated the nature of Knowledge Construction Schemata (KCS) that teacher-solvers use to solve a real-world non-routine problem situation. Eighteen Math teachers in different schools of Region I and the Cordillera Administrative Region were given a carefully selected power problem, which they solved in at most two hours. Results showed that rigid procedural framework of thought characterizes respondents’ KCS in solving problems. Based on this framework, solvers see solutions to a problem situation as purely routine or algorithmic procedures, a condition that makes them selective in interpreting data. They give meaning only to quantitative data while ignoring the qualitative ones, resulting in incomplete solution steps and failure to solve the problem. The influence of the routine type of problem solving appears to be so entrenched that solvers could not find meaning in qualitative data and venture to alternative solution steps that do not necessarily address the problem situation. An important component of problem solving, which is making necessary adjustments in response to a new problem situation (accommodation process), remains a great challenge among the teacher-solvers. Their KCS nature is heavily confined to assimilation processes, which seem responsible for keeping solvers from making exploratory attempts that could have paved the way for more productive problem solving. The study recommends that real-world non-routine type of problem-solving be integrated with school mathematics to develop among the students flexible, reflective, and transformational KCS.
Article Details
References
Verywellmind. https://www.verywell.com/what-
is-a-schema-2795873
Cherry, K. (2017). What is a Schema in Psychology?
Verywellmind. https://www.verywell.com/what-
is-a-schema-2795873
DiMaggio, P. (1997). Culture and Cognition.
Annual Review of Sociology, 23: 263-287.
https://doi.org/10.1146/annurev.soc.23.1.263
Hein, G.E. (1991). Constructivist learning theory.
Exploratorium. https://www.exploratorium.edu/
education/ifi/constructivist-learning
Jurdak, M. (2016). Learning and teaching real
world problem solving in school mathematics: A
multiple-perspective framework for crossing
boundary. Springer international publishing
Switzerland.
McLeod, S. (2018). Jean Piaget’s theory of cognitive
development. SimplyPsychology. https://www.
simplypsychology.org/piaget.html
Nadkarni, S., & Narayanan, V.K. (2007). Strategic
schemas, strategic flexibility, and firm
performance: The moderating role of industry
clock speed. Strategic Management Journal, 28 (3):
243-270. https://doi.org/10.1002/smj.576
Orleans, A.V. (2007). The condition of secondary
school physics education in the Philippines:
Recent developments and remaining challenges
for substantive improvements. Australian
Educational Researcher, 34(1):33-54. https://link.
springer.com/article/10.1007/BF03216849
Piaget, J., & Inhelder, B. (1958). The Growth of
Logical Thinking From Childhood To
Adolescence. London: Routledge, https://doi.
org/10.4324/9781315009674
Polya, G. (1957). How to Solve It. Princeton
University Press, USA. https://math.hawaii.edu/
home/pdf/putnam/PolyaHowToSolveIt.pdf
Schoenfeld, A. (1994). Reflections on doing and
teaching mathematics. In A. Schoenfeld (Ed.).
Mathematical Thinking and Problem Solving.
(pp. 53-69). Hillsdale, NJ: Lawrence Erlbaum
Associates
TIMMS & Pirls International Study Center. (2003).
Average Achievement in the Mathematics
Content Areas. TIMSS & PIRLS International
Study Center, Lynch School of Education, Boston
College. https://timss.bc.edu/PDF/t03_down
load/T03_M_Chap3.pdf.
Wadsworth, B.J. (2004). Piaget’s theory of cognitive
and affective development: Foundations of
constructivism. Longman Publishing.