RESUMO
Causal mechanistic reasoning is a thinking strategy that can help students explain complex phenomena using core ideas commonly emphasized in separate undergraduate courses, as it requires students to identify underlying entities, unpack their relevant properties and interactions, and link them to construct mechanistic explanations. As a crossdisciplinary group of biologists, chemists, and teacher educators, we designed a scaffolded set of tasks that require content knowledge from biology and chemistry to construct nested hierarchical mechanistic explanations that span three scales (molecular, macromolecular, and cellular). We examined student explanations across seven introductory and upper-level biology and chemistry courses to determine how the construction of mechanistic explanations varied across courses and the relationship between the construction of mechanistic explanations at different scales. We found non-, partial, and complete mechanistic explanations in all courses and at each scale. Complete mechanistic explanation construction was lowest in introductory chemistry, about the same across biology and organic chemistry, and highest in biochemistry. Across tasks, the construction of a mechanistic explanation at a smaller scale was associated with constructing a mechanistic explanation for larger scales; however, the use of molecular scale disciplinary resources was only associated with complete mechanistic explanations at the macromolecular, not cellular scale.
Assuntos
Biologia , Química , Currículo , Estudantes , Biologia/educação , Química/educação , Humanos , PensamentoRESUMO
In recent years, much of the emphasis for transformation of introductory STEM courses has focused on "active learning", and while this approach has been shown to produce more equitable outcomes for students, the construct of "active learning" is somewhat ill-defined and is often used as a "catch-all" that can encompass a wide range of pedagogical techniques. Here we present an alternative approach for how to think about the transformation of STEM courses that focuses instead on what students should know and what they can do with that knowledge. This approach, known as three-dimensional learning (3DL), emerged from the National Academy's "A Framework for K-12 Science Education", which describes a vision for science education that centers the role of constructing productive causal accounts for phenomena. Over the past 10 years, we have collected data from introductory biology, chemistry, and physics courses to assess the impact of such a transformation on higher education courses. Here we report on an analysis of video data of class sessions that allows us to characterize these sessions as active, 3D, neither, or both 3D and active. We find that 3D classes are likely to also involve student engagement (i.e. be active), but the reverse is not necessarily true. That is, focusing on transformations involving 3DL also tends to increase student engagement, whereas focusing solely on student engagement might result in courses where students are engaged in activities that do not involve meaningful engagement with core ideas of the discipline.