Monica Resendes

Understanding the nature of science and scientific progress: A theory-building approach

In 1993 Carey and Smith conjectured that the most promising way to boost students’ understanding of the nature of science is a “theory-building approach to teaching about inquiry.” The research reported here tested this conjecture by comparing results from two Grade 4 classrooms that differed in their emphasis on and technological support for creating and improving theories. One class followed a Knowledge Building approach and used Knowledge Forum®, which together emphasize theory improvement and sustained creative work with ideas. The other class followed an inquiry approach mediated through collaborative project-based activities. Apart from this, the two classes were demographically similar and both fell within the broad category of constructivist, inquiry-based approaches and employed a range of modes and media for investigative research and reports. An augmented version of Carey and Smith’s Nature of Science Interview showed that the Knowledge Building approach resulted in deeper understanding of the nature of theoretical progress, the connections between theories and facts, and the role of ideas in scientific inquiry.

Two tales of time: uncovering the significance of sequential patterns among contribution types in knowledge-building discourse

ABSTRACT As collaborative learning is actualized through evolving dialogues, temporality inevitably matters for the analysis of collaborative learning. This study attempts to uncover sequential patterns that distinguish “productive” threads of knowledge-building discourse. A database of Grade 1–6 knowledge-building discourse was first coded for the posts’ contribution types and discussion threads’ productivity. Two distinctive temporal analysis techniques – Lag-sequential Analysis (LsA) and Frequent Sequence Mining (FSM) – were subsequently applied to detecting sequential patterns among contribution types that distinguish productive threads. The findings of LsA indicated that threads that were characterized by mere opinion-giving did not achieve much progress, while threads having more transitions among questioning, obtaining information, working with information, and theorizing were more productive. FSM further uncovered from productive threads distinguishing frequent sequences involving sustained theorizing, integrated use of evidence, and problematization of proposed theories. Based on the significance of studying temporality in collaborative learning revealed in the study, we advocate for more analytics tapping into temporality of learning.