Tuesdays reading, from - Taking Science to School -- is intended to summarize what is known about childrens thinking, about what the goals of science education should be, and then combine the two by providing a broad brush treatment of how to engineer effective science education. It is aimed at a fairly general audience. But this semester you have been learning about some of the state of the art by reading several seminal papers in the field of developmental psychology. Given your added level of expertise, how well do you think the chapter achieves its goals? Be prepared to discuss specific strengths and weaknesses. In addition, think about the characterization of what science is. Is the four strand characterization consistent with your view of science?
Q. Is the four strand characterization consistent with your view of science?
By and large, I found that the 'four strand' approach encompassed most of the key aspects of science. However, there were a few points which I felt could have been included in these strands, such as:
-The role of competing theories over time. One problem that occurs frequently in science is the development of multiple different theories which all aim to account for the same evidence. At times, these competing theories can be sorted out immediately via a particular experiment which can falsify all but one of the theories. However, at other times it is near impossible to discriminate amongst these theories immediately (e.g., role of domain specific vs. domain general knowledge as previously discussed in class). I think that greater emphasis should be placed on these types of situations, as they illustrate that science is not a linear development of a single theory; sometimes multiple theories exist and have to be dealt with in some fashion for long periods of time before competing theories can be eliminated or reconciled within a single framework, a la Kuhn.
-the fact that science is not committed to particular techniques or methodological approaches. Many domains of scientific inquiry are not suitable for scientific study in the popular sense astronomers don't bring planets into their laboratories and perform causal experimentation on them in confined conditions. I think that in developing a means of teaching science, the chapter does not sufficiently address the need to emphasize that science is about public validation and questioning of empirical data via operationalized techniques, regardless of the particular domain or methodology. This would help emphasize the broader scope of scientific inquiry (e.g., natural experiments; historical study) in addition to reinforcing its core tenets.
-the importance of 'top down' rational reasoning in science. I think that science education in general doesn't sufficiently emphasize the role that top down reasoning and intuition has in developing a theory. Rather, it emphasizes what happens once a theory has been proposed how to test it, how to expand it, how to develop new tests. I think that it is important to acknowledge the importance of top down and historical knowledge of a field can have on developing theories, and how variability in these types of knowledge leads to very divergent approaches and theories (e.g., PDP vs. dual route theories of verb production).
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Klahr & Li:
-One of the problems with transferring basic research to applied settings that was discussed in the paper is that basic experiments are too controlled and do not reflect the variability on multiple dimensions encountered in applied settings. This leads to the reverberation between basic and applied research (the Bohr and Edison quadrants), which is sometimes not very effective because the two types of research do not line up very well. To what extent are these issues now moot with improved statistical techniques which allow more basic research to be conducted in more applied settings without loss of control or precision as to which variables are interacting with which other variables?
Blair
Oh, and a quick news report which is tangentally related to science education and public science discussion in general: http://arstechnica.com/news.ars/post/20080224-getting-the-public-to-pay-attention-to-good-science.html
Blair's point about intuition is interesting. This is because one of the critical factors discussed in philosophy of science is the notion of abductive inference. This is the pattern of reasoning whereby people observe an effect and reason backwards to the most likely explanation. For example, if I notice the street is wet in the morning, I quickly infer that it rained during the night. This mode of reasoning is not strictly valid since there could have been other things that caused the street to be wet, but I accept it nonetheless. Do patterns of abductive reasoning (hypothesis generation) change over the lifespan, and if so what implications would this have for the way science should be taught?
As for the point about basic and applied research, I don't think that better statistics will completely erase the difference since there will still be differences in the nature and quality of the data itself. You can't for example, do fMRI scans on people while they are in the middle of taking their morning shower. As the imaging technology improves, however, to the point where we can monitor people outside of the lab, this distinction probably will become less and less of an issue. However, we still have a ways to go before that happens.
I think the four proposed strands of scientific proficiency incorporates many of the relevant features of scientific understanding; however, perhaps this explanation does not encapsulate all of the factors that contribute to scientific proficiency. It is suggested that scientific reasoning be as much a part of basic education as language arts and math, and while I agree with this sentiment I think it is not quite fair to lump science in with these other subjects because it literally builds on those subjects. A broad example is that science learning relies, especially later in education, on good reading skills. Students make the transition from learning to read to reading to learn sometime around 3rd grade, and proficiency in reading may limit proficiency in science. As another example, consider Strand 4, addressing productive participation in discourse. To do so, one is required to have excellent written and oral communication skills, an understanding of their audience, debate skills, as well as confidence and a supportive cultural environment. To allow for proficiency in Strand 2, addressing evaluation of scientific evidence, one must be skilled in statistical understanding, to accuratley gauge the significance of an observation. Teaching statistical theory may be at least as important as teaching science, or at the very least they should go hand in hand - yet, most education systems leave this subject matter to advanced high school or college courses.
This report also mentions on occasion the role of the teacher as a person who assesses a child's progress and administers effective education appropriately. I may be wrong about the state of education for teachers, but I think this might be a lofty goal. Who is preparing the teachers to do this? Are teachers able to easily access further education, once they are actively playing a teacher role? Can they keep up with the current state of education research, given their workload? Are they inclined to do so?
Even if they are inclined and encouraged to be more precise in delivering educational needs on a student by student basis (or even student group by student group basis), they are bound by the constraints of the school system they belong to. More imperatively, how can teachers choose appropriate assessments and effective education styles when there seems to be disagreement among education researchers as to the proper course of action?
I definitely agree with Erika on the fact that science builds on other subjects like mathematics, language and statistics and it is my opinion that this fact has not been addressed sufficiently. For example, one of the goals for science education is "generate and evaluate scientific evidence and explanations". How one generates evidence however is based on the tools that are available at a given time. Children have certain tools as well. To give an example, children might know that gravity exists and that it pools objects downwards because they can see its effects. The evidence in this example is direct visual observation, which can be used to explain gravity in its basic terms. This same tool can be used to explain a number of observations. At the same time however, this same tool might lead to certain misconceptions about certain observation that cannot be directly seen. Heat, momentum and temperature might be such examples. Shouldn't one of the goals of science education be to identify what tools children might have at a given time and what tools might be better to teach children in order to more effectively understand science?
Do child exhibit systematic types of errors in CVS before receiving instructional intervention? What do children's early errors reveal about their knowledge?
Is it the case that basic research is applied more in special education classrooms? I can see where basic research with children that have developmental disorders (like autism) would help teachers with behavioral issues in a classroom or even teaching methods. We know that a lot of grant money goes towards research on atypical development with intentions on intervention - but does this extend to how to educate them?
Also, the question was raised in class about how previous lectures in the class can relate to applied research in education. I was wondering to what extent brain research or neuroscience findings can influence education.
In the Klahr and Li Paper, it seems that CVS is best taught with explicit instruction and some amount of questioning to ensure understanding, but I was wondering how the interaction of discovery learning and explicit instruction might aid understanding.
Also, Rob Goldstone had a slide in his ed bag where he had a ton of different variables that we can further characterize instruction with (e.g. direct vs discovery, active vs passive, familiar vs unfamiliar, etc.) how would the direct instruction condition CVS in the Klahr and Li paper amount on all these dimensions?
More broadly, in education research and also in cognitive develoment, we tend to assume that all children learn the same -- for example, we look for a type of instruction that works the best above another type, or try to characterize how children think at a certain stage -- but what about the idea that different children learn differently -- for example, perhaps some children learn more strongly from direct instruction, while others discovery is better -- thus, are individual differences undervalued or disregarded in education research?
-bryan
p.s. Jaime, I also think the combination of neuroscience and education is fascinating -- I wonder how neuroscientists can contribute to questions related to education -- for example, is their characteristic brain activation that might tell us what strategies children are using to learn -- this might prove fruitful in determinging what instruction to foster to different children at different stages in learning.
I feel that ideas of what science is and the four strands of science in this chapter are focusing on scientific research, rather than science as a whole. The discussion seems to be about how to teach children the methods and principles of scientific research. However, science also includes a huge body of knowledge about the natural world that children need to learn, including biology, chemistry, geology, and physics. Granted, this knowledge was arrived at through research. But it is just as important for children to learn the current knowledge in the many areas of science, as well as methods for scientific research. Therefore, a complete curriculum needs to include the current knowledge in science.
It may be a very good idea to incorporate the teaching of current knowledge with scientific methods in some instances. For example, when teaching a child about gravity, also have them conduct experiments to prove its existence.
In the paper, it is briefly mentioned about the long-term effect of giving direct instruction. However, it seems like there needs to be some kind of education scheme incorporating making own discoveries/hand-on experience. For the faster effect, giving instruction is good, but students might get depended on the help, rather than thinking by themselves. Is there any study that tries to find how much of direct instruction is good?
Although there was no differences found in physical vs. virtual training, I expect there would be some differences of performance when instruction is given during the training?
I have another question about long-term effect. Many people forget what they learn in school after they go to the college or have the job. See how happy kids are when they beat adults in "Are you smater than the 5th grade?".
I think the long-term memory area in psychology may tact this question, and I also believe people from education have some studies here. Is there some studies try to transfer the result from psychology to education?
