Date of Award
8-17-2023
Publication Type
Dissertation
Degree Name
Ph.D.
Department
Education
Keywords
Conceptual Change;Experimental Studies;Human Reaction Time;Mathematical Identity;Pendulum Motion;Physics Education Research
Supervisor
George Zhou
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
This study focuses on the probabilistic aspect of international students’ intuitive and counter-intuitive conceptions of pendulum motion. The probability here is rooted in a moving neural time average in the mind for characterizing students’ cognition (sampling and decision making) and learning processes (resampling and making a new decision) rather than a frequentist’s or a neural counter’s way of keeping track of learning occurrences in the mind’s conceptual space. I follow the daily use of the word "time" for any durable and differentiable interval that everyone can observe or measure directly and the words "reaction time" for any uncertain latency period in the mind/brain, an unobservable construct of the neural network timing theory. To sharpen the aforementioned focus, I argue that a new taxonomy of physics concepts is needed to save the mathematical identification of the classical and modern physics concepts, highlighting the role of such a renewed recognition of the language of physics brought to conceptual change studies. Over four decades of conceptual change studies have been based on the assumption that students come to the science classroom with their pre-instructional understanding of natural phenomena. However, it is largely ignored that the students’ prior intuitive knowledge is probabilistic in time, representing some results of the idiosyncratic sampling of their daily experiences. In this study, I built on such a conceptual linchpin to expand Zhou’s (2012) hybrid space for science education to construct a two-dimensional time-based probabilistic conceptual learning theory. In particular, I asked the following research questions: 1) What are the roles of a mathematically defined physics concept (such as T = 2π√(l/g) ) in influencing the sampling and decision-making processes during learning, which international students use to change their concepts in science learning? 2) How can the effects of such a Sampling and Decision-making mechanism be measured non-verbally? 3) What are the pedagogical implications of using the new taxonomy? To address these questions, I conducted two experiments to measure international students’ conceptual change in time situated in the context of learning pendulum motion. After reviewing pre-existing literature, I laid the foundation for a new theoretical framework of active learning with a probabilistic frame of reference. Next, a convergent parallel mixed-method research design was detailed to study the temporal aspects of students’ active learning of pendulum motion. In Experiment 1, a pendulum period-matching was developed to prototype the experimental procedure for comparing the reaction times of making a correct or incorrect decision (a hit, a correct rejection, a miss, or a false positive) and to develop a new percentage correct analysis procedure. Experiment 2 examined international students’ sampling and decision-making in a pendulum period-matching task of a string pendulum with cheeks. This experiment demonstrated the feedback's effect on changing the students’ decision-making. Following the experiments, a qualitative study with five interviews showed students’ false identification of irrelevant factors as the determining one and the fragmented nature of students’ intuitive ideas. Together, the results have converged on the probabilistic aspect of students’ active learning mechanisms in their minds. The manifold pedagogical implications of such a probabilistic cognitive “revolution” has also been discussed.
Recommended Citation
Li, Lin, "On a New Taxonomy of Concepts and Conceptual Change: A Probabilistic Frame of Reference and Its Experimental Manifestations" (2023). Electronic Theses and Dissertations. 9305.
https://scholar.uwindsor.ca/etd/9305