Abstract
Abstract The importance of learning style in student’s learning performance has been gaining scholar’s attention since it was coined in the early 70s. Atmatzidou’s robotics procedure of a five-stages robotic activities was deployed in the research. This study adopts a case study research design for gathering and analyzing data as the case research allows the exploration of unforeseen phenomena and offers insights into the interdependencies among components revealed in the study. This research introduces the use of Lego Mindstorm as the mean of pro-filing a student’s behavioral patterns. Student’s behavior patterns, then, mapped into radar charts to present the extent of both Kolb and science, technology, engineering, and math (STEM)’s profile of student’s learning style categories. The paper contributes to theory by extending Kolb’s Learning Style instrument by mapping the pattern of learning styles identified in the research and exploring students learning experience. Dominant four-domain-indicators captured during the activities characterize Students’ learning profiles. While the Kolb Learning Style and its instrument are considered classic in hands-on literature, the use of educational robotics to elaborate students’ learning style is novel in the literature that may affect the delivery of non-technology subjects in the curricula.
Highlights
The importance of learning style in student’s learning performance has been gaining scholar’s attention since it was coined in the early 70s
This research introduces the use of Lego Mindstorm as the mean of profiling a student’s behavioral patterns
While the Kolb Learning Style and its instrument are considered classic in hands-on literature, the use of educational robotics to elaborate students’ learning style is novel in the literature that may affect the delivery of non-technology subjects in the curricula
Summary
Abstract: The importance of learning style in student’s learning performance has been gaining scholar’s attention since it was coined in the early 70s. This research introduces the use of Lego Mindstorm as the mean of profiling a student’s behavioral patterns. Student’s behavior patterns, mapped into radar charts to present the extent of both Kolb and science, technology, engineering, and math (STEM)’s profile of student’s learning style categories. The paper contributes to theory by extending Kolb’s Learning Style instrument by mapping the pattern of learning styles identified in the research and exploring students learning experience. While the Kolb Learning Style and its instrument are considered classic in hands-on literature, the use of educational robotics to elaborate students’ learning style is novel in the literature that may affect the delivery of non-technology subjects in the curricula. Conceptualization (Theorist - weak) Abstract Conceptualization (Theorist – medium). Concrete Experience (Pragmatist - weak) Concrete Experience (Pragmatist - medium). Active Experimentation (Activist - strong) Reflective Observation (Reflector – strong) Active Experimentation (Activist – very strong) Reflective Observation (Reflector – strong) Active Experimentation (Activist – medium) Active Experimentation (Activist – strong) Active Experimentation (Activist – very strong) Indicator 2 Abstract
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