Context affects all.
Reasoning, representing changes with a word. |
Students’ explanations of evolution by natural selection show that student reasoning is inconsistent when presented with seemingly similar assessments. Their performance differs when asked conceptually equivalent questions that differ in the context.
Considering that, I try to quantify how taxon (human vs. non-human animal) and the type of trait (structural vs. functional) influence students’ reasoning about evolution by natural selection. Here context is defined as the words in the question prompt. Paper: de Lima, J., & Long, T. M. (2023). Students explain evolution by natural selection differently for humans versus nonhuman animals. CBE—Life Sciences Education, 22(4), ar48. https://doi.org/10.1187/cbe.21-06-0145 |
Scientific models are specialised representations of a concept, process or phenomenon, with the purpose of helping illustrate, explain, or predict. As a tool, models lend themselves to both instruction and assessment.
I want to ask questions about the effect of context on the content and architecture of student-generated models. Here context is defined as the words in the question prompt. |
While narratives are a frequently used tool to elicit students' understanding of scientific concepts, they are not the mode by which students can represent their reasoning.
I am trying to understand the influence of mode of response (i.e. narrative v/s student-generated model) on the content and accuracy of their representations. Here context is defined as the mode by which students respond to the same question prompt. |
When constructing a mechanistic explanation about an observed phenomena, students have to consider scalar levels below the observed phenomena. This usually involves referring back to knowledge they obtained in previous classes.
I want to investigate if the context in which they are asked to reason about mechanisms influences the nature of their mechanistic explanations. Here context is defined as the course and discipline (i.e. chemistry v/s biology) in which the prompt is provided to the student. Paper: Schwarz, C. V., Cooper, M. M., Long, T. M., Trujillo, C. M., de Lima, J., ... Stoltzfus, J. R. (2020). Mechanistic Explanations Across Undergraduate Chemistry and Biology Courses. In M. Gresalfi & I. Horne (Eds.), The Proceedings from the Fourteenth International Conference of the Learning Sciences (ICLS) 2020, Volume 1 (pp. 625–628). repository.isls.org//handle/1/6712 |
Inclusive classrooms
foster belonging, also increase learning gains |
Doctoral teaching assistants (TAs) provide key support for learning in STEM fields because they are present during exercises, labs and projects when students are actively engaging with course material. We use the lens of Social Cognitive Theory (SCT) to analyse data on the pre and post course teaching priorities of 20 doctoral TAs who followed a 5 day practice-intensive course on STEM HE.
TAs reported self efficacy gains for designing instruction, addressing disruptive behaviour and managing student attention spans after the course. Their priorities also appear to shift away from ‘teaching’ and towards ‘learning’. Paper: Isaac, S., de Lima, J. (2022) Effect of a practice-intensive course on doctoral teaching assistants’ teaching self-efficacy and priorities. Proceedings of the 50th SEFI Annual Conference 2022. 10.5821/conference-9788412322262.1148 |
In many large enrollment introductory classrooms, student assistants (SAs) contribute to the classroom climate in addition to the teachers and the students. We use an inclusive teaching framework to map out the ideas about inclusive practices that these SAs are bringing into the classrooms.
We found that student assistants have strong positive ideas and beliefs about inclusion in the classroom, as well as their responsibility in creating inclusive classrooms. They are also self-aware about areas where they could improve (e.g. pedagogical skills promoting inclusion). Paper: de Lima, J., Isaac, S., & Kovacs, H. (2023). Inclusive engineering classrooms: Student teaching assistants’ perspectives. Proceedings of the SEFI 2023 Conference. https://doi.org/10.21427/Z015-7602 |