Characterizing Student Engagement in Science Practices

Rachael Mayhew Author

07/27/2021 Added

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Summer REU 2021 Chemistry poster presentation.

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[00:00:00.940]Hi, my name is Rachel Mayhew,
[00:00:02.450]and I've been working with Katie Patterson and Alena Moon
[00:00:05.180]on their project,
[00:00:06.130]Characterizing Student Engagement in Science Practices.
[00:00:09.150]To start, let's give you some background.
[00:00:11.860]In 2012, the next generation science standards
[00:00:14.480]establish a framework that emphasizes the importance
[00:00:16.850]of focusing on both scientific skills
[00:00:19.170]in addition to scientific knowledge.
[00:00:22.070]They listed eight practices,
[00:00:23.590]and we've built our task ground two of them.
[00:00:26.100]Engaging in argument from evidence,
[00:00:28.260]and analyzing, and interpreting data.
[00:00:31.990]After some pilot interviews,
[00:00:33.400]we found some frameworks that aligned with our results.
[00:00:36.610]That students follow
[00:00:37.680]a process of activating prior knowledge,
[00:00:39.690]interpreting data, and form it a claim.
[00:00:42.580]We found that as they did this process,
[00:00:45.390]they experienced and expressed great amounts of uncertainty.
[00:00:48.150]And so we began to look into two types of uncertainty.
[00:00:51.010]Constant uncertainty,
[00:00:52.240]which is the feeling of confusion
[00:00:53.820]about the subject of an issue.
[00:00:55.720]This kind shows itself in questions like,
[00:00:57.680]what does this mean?
[00:00:59.140]And epistemic uncertainty,
[00:01:00.720]which is a feeling of confusion surrounding
[00:01:02.600]how to approach a problem.
[00:01:04.220]Questions like, how do I answer this?
[00:01:05.900]fall into this category.
[00:01:08.160]This gap in the research led us to our research question.
[00:01:12.870]How do undergraduate chemistry students manage uncertainty
[00:01:15.910]when engaging in science practices?
[00:01:18.290]To answer this,
[00:01:19.180]a task that highlights argumentation
[00:01:21.050]and use of evidence is crafted.
[00:01:22.980]It's rooted in biochemistry
[00:01:24.490]and focuses on the ability of an anti MRSA molecule
[00:01:27.800]to kill bacteria.
[00:01:30.610]Here's the task.
[00:01:32.040]You can see there is a set of molecules on the left,
[00:01:34.260]and a data table on the right,
[00:01:35.590]which lists the functional groups of each molecule.
[00:01:38.870]Soon it's forgiven a broad request
[00:01:40.900]to make a claim about the relationship
[00:01:42.640]between the structures and how efficient it is.
[00:01:45.690]We collected students
[00:01:46.700]from an advanced undergraduate biochemistry course
[00:01:49.040]to participate in small group interviews,
[00:01:51.310]and these interviews were recorded,
[00:01:52.920]transcribed, and analyzed.
[00:01:56.430]Our analysis involves separating the interview
[00:01:58.660]into segments of discussion on one topic.
[00:02:01.220]We call the segments episodes.
[00:02:03.220]Each of these episodes were event assigned a code
[00:02:05.540]that fell under one of the four levels of discussion.
[00:02:09.440]These levels are ranked on the amount
[00:02:11.170]of uncertainty present in the discussion.
[00:02:13.370]Towards the top, there's more uncertainty.
[00:02:15.390]Towards the bottom, there should be very, very little.
[00:02:18.950]The first level, data processing,
[00:02:20.690]consists mostly of students making sense of the task.
[00:02:23.740]It often appears early on,
[00:02:25.190]or wherever students need a little more guidance
[00:02:27.320]in their work.
[00:02:28.360]The second level, arguments about men,
[00:02:30.360]is largely students beginning to make their claim.
[00:02:33.470]They start to incorporate data trends,
[00:02:35.220]and different reasoning skills.
[00:02:36.940]The third level, data interpretation is reading the data
[00:02:39.740]and noting trends in the results such as comparisons,
[00:02:42.720]and it is used quite often throughout the discussion.
[00:02:46.370]The final level, argument finalization,
[00:02:48.610]is when students produce their final claim.
[00:02:51.690]Now, let's look at some excerpts.
[00:02:53.910]I pulled one from each level of discussion
[00:02:55.850]that exemplifies the type of interaction scene.
[00:02:58.950]These are all from the same interview
[00:03:00.530]with participants Linda and Tim.
[00:03:03.830]To start, data processing.
[00:03:06.180]I have bolded instances of uncertainty
[00:03:08.590]that are present.
[00:03:09.970]Here, Tim is very outright about his confusion
[00:03:12.550]and expresses his epistemic uncertainty in an outburst.
[00:03:15.920]He begins listing data trends to cope
[00:03:17.670]and the interview steps in to redirect him.
[00:03:20.270]Tim manages his uncertainty
[00:03:21.870]through expressing his confusion and seeking help.
[00:03:25.660]Now, we move to argument development.
[00:03:29.230]Tim creates a vague claim and provide some reasoning
[00:03:32.010]while confirming with Linda that his reasoning is sound.
[00:03:35.010]Linda comes in and refined Tim's initial claim.
[00:03:39.000]Tim is managing his uncertainty here by double checking
[00:03:41.530]with his partner to make sure they are on the same page.
[00:03:44.140]After Linda agrees and betters his claim,
[00:03:46.230]both students proceed to find another claim to work on
[00:03:48.720]after this episode ended.
[00:03:51.970]Now, with data interpretation,
[00:03:53.300]there is less uncertainty seen,
[00:03:54.920]but that just is because the students are reading the data
[00:03:59.260]and trying to note trends.
[00:04:01.930]There aren't really many questions asked here,
[00:04:04.020]but Tim and Linda are talking about
[00:04:08.350]the different MIC ranges of two molecules
[00:04:10.610]and they're just speculating how it's correlated
[00:04:13.210]to functional groups.
[00:04:16.480]Lastly, with argument finalization,
[00:04:20.310]the students were prompted for their final claim
[00:04:22.190]and Tim begins to restate the previous interpretations
[00:04:25.230]and claims with evidence
[00:04:26.520]from the table provided on the task.
[00:04:29.810]Argument finalization,
[00:04:31.330]much like data interpretation
[00:04:33.870]by it's standard should have no uncertainty present.
[00:04:38.980]To understand the interview as a whole,
[00:04:41.080]this image at the top is created.
[00:04:43.030]It represents the sequence of episodes
[00:04:45.180]in what level of discussion it falls under.
[00:04:47.750]You can see that students alternate
[00:04:49.280]between the different levels of discussion,
[00:04:51.010]often using data interpretation as a stepping stone
[00:04:53.610]between different levels.
[00:04:55.590]At the beginning of the discussion, students swap
[00:04:57.543]between data processing and data interpretation,
[00:05:01.030]which helps to clarify their epistemic uncertainty.
[00:05:04.410]In the middle, the students alternate
[00:05:05.890]between argument development and data interpretation
[00:05:09.150]as they understand how to answer it with tasks
[00:05:11.220]that struggle with their continent uncertainty.
[00:05:14.660]Argument finalization comes up after the students discuss
[00:05:17.430]what to include, and the students presented
[00:05:19.280]their final claim.
[00:05:20.630]The episodes after were clarification questions
[00:05:23.020]from the interviewer.
[00:05:26.090]We've created this diagram to help visualize the flow
[00:05:28.710]of conversation as students complete a biochemistry task.
[00:05:32.910]Starting at data processing,
[00:05:34.270]students who move back into data interpretation,
[00:05:37.260]where they can either go back to processing,
[00:05:39.250]or move to argument development.
[00:05:42.500]The interaction between arguments development
[00:05:44.250]and data processing is fairly one-sided
[00:05:46.810]and these interactions help to produce
[00:05:48.550]the student's final claim.
[00:05:51.610]From the data we collected, we have two main conclusions.
[00:05:56.440]Firstly, students face their uncertainty
[00:05:58.700]by talking in a questioning tone
[00:06:00.270]when they are assigned a task that involves forming claims.
[00:06:05.440]I've seen an argument development students post cleanse
[00:06:07.810]to each other until there is consensus.
[00:06:10.460]This expression of uncertainty opens their claims
[00:06:12.670]to criticism and leaves their statements
[00:06:14.530]with a lack finality, indicating that the discussion
[00:06:17.120]can still develop.
[00:06:19.960]Second, we have found that students closely follow Chen's,
[00:06:23.300]raise, maintain, and reduce model
[00:06:25.330]when managing uncertainty.
[00:06:27.670]Early in the discourse, students raise uncertainty
[00:06:29.970]by asking questions, maintain that while searching
[00:06:32.360]for relevant data and reduce that
[00:06:33.860]as they finalize the claim.
[00:06:36.000]But this information we are better informed
[00:06:37.870]in how students progress through discussion
[00:06:40.310]while managing their uncertainty.
[00:06:43.610]Thank you to the National Science Foundation.
[00:06:45.770]This project is funded by NSF REU Grant.
[00:06:49.380]And thank you to the Department of Chemistry
[00:06:51.180]at the University of Nebraska-Lincoln,
[00:06:53.180]for the opportunity to participate
[00:06:54.840]in summer research program.
[00:06:57.290]Thank you to the Moon group
[00:06:58.270]for their useful suggestions and support.
[00:07:00.920]And thank you for listening.

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