STEM Trends
Alignment of Curriculum Outcomes and Classroom Discourse to Assessments: Modelling Higher-order Thinking in Science Classrooms
Paper Presentation in a Themed Session Zanele Masuku
Data were collected through document analysis and semi-structured interviews with twelve science heads of departments (HODs) and senior teachers, who are experienced in teaching high school physical sciences. The documents that were analysed are past question papers and teachers’ notes used for teaching and assessing learners. The Revised Bloom’s taxonomy (Anderson and Krathwohl, 2001) was used as a conceptual framework in analysing the collected data. The interviews were recorded, transcribed, anonymized, and coded for themes. The findings highlighted diversity among the teachers in four areas: their own understanding of the concept of higher-order thinking, practical utilization of instructional strategies related to modelling and fostering higher order thinking in the classroom, beliefs about students’ abilities to acquire higher-order thinking skills, and self-perception regarding teaching towards higher-order thinking. It was found that in general the teachers understand what higher-order thinking skills are. Their daily preparation documents revealed that they do plan for modelling higher-order thinking. However, in actual fact, they treated difficult class exercises or tasks as being a higher-order thinking exercise. Assessments and tests conducted were mainly content driven and did not test for any higher-order thinking. Most teachers seldom model higher-order thinking abilities among their students. Only a minority of teachers see modelling of higher-order thinking as an important objective of teaching physical sciences. In summary, teachers are uncertain about the whole issue of modelling higher-order thinking in schools.
What Makes the Next STEM Worker?
Paper Presentation in a Themed Session Wendy Chen
Since the Industrial Revolution, the West has witnessed rapid economic growth thanks to the fast development of science and technology. However, as of 2016, the Randstad STEM Study data reported that over three million STEM (Science, Technology, Engineering, and Math) jobs in the US could not be filled by qualified workers and that US students have expressed decreased interest in pursuing a STEM career as they grow older. It is thus important to investigate empirically what may affect students’ STEM career inclination. By using a nationally-representative longitudinal dataset and building upon the ecosystem literature, this paper finds that STEM learning ecosystem plays an important role.
Can Problem Solving Be Problematized: The Historical Shadow of STEM Literacy
Paper Presentation in a Themed Session Lei Zheng
The policy and scholarship of STEM education take for granted the idea that students must be prepared with competencies of problem-solving and decision-making through STEM practices for civil life. Drawing upon the theory of historical and social epistemology (Daston, 1995; Popkewitz, 2013), I problematize the governmental power historically implicated in this idea by asking: what make possible problem-solving and decision-making to be thought as the fundamental and universal literacy of science and democracy that order particular ways of learning and living in curriculum practices. In this paper, I first review the literature in the history of social/science that has critically analyzed the knowledge-power relations implicated in collapsing science, democracy, and human/nature after World War II. Then, I examine how problem-solving was circulated in transnational curriculum reforms with systems analysis of human quality (Peccei, 1979/2013) and human learning (Botkin et al., 1979). With the fear of a sudden global catastrophe prognosed by the Club of Rome (OECDA, 1969) and the economic boom of Japan in the 1980s, learning and curriculum were “innovated” in the US and other OECD countries to be anticipatory (Shane and Tabler, 1981; OECD, 1979). That is to prepare students for the most-likely future by asking them to simulate problem-solving and decision-making in “collected” contexts. This innovative effort did not challenge the status quo as it intended but reinscribed it by objectivizing the potentialities of human body-minds as the infinite resources that could be controlled scientifically for problem-solving and decision-making to actualize the events without “surprise.”
