11 SES 02, Science and Quality of Education
Student performance from Singapore in the international achievement tests such as PISA and TIMSS have been very commendable in recent years. What is less certain, but of great interest to the international community is the exact nature of classroom instruction in the state; specifically what goes on in science classrooms. For example, we know that while teachers here devote slightly more hours to their job than their counterparts in the UK (Lee & Poon, 2004), how they actually teach science and the intellectual demands that they place on their learners is largely a mystery (Lee, 2014). The current study is part of a larger project to answer such necessary questions in Grade 5 and 9 science classrooms in Singapore about the nature of:
- pedagogical practices
- teacher pedagogical reasoning, and
- intellectual quality of knowledge work.
For policymakers and curriculum researchers, knowing these will give hitherto unknown insights into how major local educational reforms in the 2000s have been understood, implemented or perhaps ignored by the primary agents of change – classroom teachers. More levels of school could be chosen of course, but these two grades align well with PISA/TIMSS requirements and will allow for better comparisons. Some other research have already suggested that East Asian states have succeeded in PISA/TIMSS precisely because of the lack of difficult and time-consuming inquiry teaching as well as high amounts of directed frontal teaching (see Jerrim, 2015; Lau & Lam, 2017; Lee, Kim, & Yoon, 2015). Compared to Western states, high-stakes testing and tracking are normative policies throughout education systems in Singapore and Asia. If all these reports are true, then it poses a genuine conundrum for Asian policymakers who have been strongly advocating critical 21st century skills to prepare their youth for the knowledge economy. The results that we present are thus a significant baseline coding study of science teaching practices and fills the gap in our knowledge regrading everyday science teaching in Singapore. As far as we know, no studies of such nature have been reported in a European context and thus we look forward to sharing our findings at the conference and having new dialogs.
Theoretical framework and instruments
A systematic and theoretically-valid coding scheme has been devised over a decade to capture the generic constructs of teaching (eg whole-class instruction, questioning, interactional patterns etc) and knowledge levels (eg factual, procedural, conceptual, metacognitive) that are being developed. Aspects of the coding instrument have been tested in local math classrooms and an Israeli study on primary pedagogy. This has been modified again to account for the disciplinary moves and skills peculiar to science education (i.e. inquiry focus, opportunities for epistemic reasoning, hands-on work etc). Three science experts have given their inputs to refine the instrument that was originally developed as a generic one. Aspects of our science and generic coding scheme will be shared at the conference, but an earlier version can be found in Luke, Freebody, Cazden, and Lin (2007).
Sample & Methods We sampled 10 mainstream schools and 10 classroom teachers in (total 90 lessons in Grade 5 and 9 (Physics)) over one unit of work of their choice (typically 1-2 weeks of lesson coverage). These teachers were nominated by their schools as being typical/average science teachers, which was our explicit request. We also conducted short post-lesson interviews with teachers and students, and collected artefacts of student work (high-medium-low scoring) for that unit of work. All lessons were segmented into 5 minute phases and coded for all the above pedagogical practices and others too. Coding proceeded with low-inference coding (ie what visibly seems to be the case) before another round of more intense or higher inference coding (ie. looking to interpret the meanings of the episode). We analyzed the aggregate statistical data from coding as shown below. We will mention too about the impressions of the first author who had taken a educational connoisseurship stance as a former science teacher as he viewed all the classroom videos (Eisner, 2017).
What we found was that in terms of Knowledge, there was an emphasis on Factual Knowledge in 59% of phases per lesson for Grade 5 (46% in Grade 9). Procedural Knowledge was less in Grade 5 (39%) compared to Grade 9 (61%) and Conceptual Knowledge was present half of Grade 5 (49%) and Grade 9 (43%) phases. We did not observe much phases where Epistemic Knowledge (4% in both grades). This is where we expect to see teachers and students debate, justify, deliberate on knowledge claims, nor did we see a lot of Metacognitive Knowledge (4% in both grades). The results are broadly comparable to the Singapore PISA 2015 findings, where local science teaching shows a stronger emphasis on procedural and epistemic knowledge than content knowledge. In terms of Epistemic Talk, we found respectable proportions of Explanatory Talk (42% in Grade 5, 40% in 9). Procedural Talk was stronger in Grade 9 (61%) than in 5 (38%), but there was room for Epistemic Virtues Talk (5% in P5, 1% in S3) where talk focuses on the nature of science, justifying and arguing for scientific claims. Likewise, an average of 86% of all phases had teacher closed questions with students requiring to respond with the correct answers, and 25% with teacher open questions where there are multiple answers. In terms of the Scientific Skills that are exemplified in the official Syllabus, we found that observation, communicating in scientific terms, analysing patterns, compare and contrast, and inference to be represented moderately in P5 and S3 classrooms. We also note that in both levels students tend to engage in investigation far more than other scientific processes such as decision-making or creative problem solving.
Eisner, E. (2017). The enlightened eye: Qualitative inquiry and the enhancement of educational practice. New York: Teachers College Press. Jerrim, J. (2015). Why do East Asian children perform so well in PISA? An investigation of Western-born children of East Asian descent. Oxford Review of Education, 41, 310–333. Lau, K.-C., & Lam, Y.-P. T. (2017). Instructional practices and science performance of 10 top-performing regions in PISA 2015. International Journal of Science Education, 39, 2092–2149. Lee, Y.-J. (2014). Science education in a straightjacket: The interplay of people, policies, and place in an East-Asian Developmental State. In A.-L. Tan, C. L. Poon, & S. S. L. Lim (Eds.), Inquiry into the Singapore science classroom: Research and practices (pp.165--189). Dordrecht: Springer. Lee, Y.-J., Kim, M., Jin, Q., Yoon, H.-G., & Matsubara, K. (2017). East-Asian primary science curricula: An overview using revised Bloom’s Taxonomy. Dordrecht: Springer. Lee, Y.-J., & Poon, C. L. (2014).The professional work of teachers in Singapore: Findings from a work-shadowing study. Asia Pacific Education Review, 15, 525–535. Luke, A., Freebody, P., Cazden, C., and Lin A. (2007). The Singapore coding scheme. Available at https://repository.nie.edu.sg/bitstream/10497/254/1/CORE_TechRpt04_CodingScheme_final.pdf
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