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A genetics-inspired approach could improve classroom analysis



A genetics-inspired approach could improve classroom analysis

Tools that have helped identify genetic markers of disease or fitness in organisms can do the same for STEM education, according to a new approach developed in Nebraska. Credit: Marilyne Stains & Robert Erdmann; Illustration: Scott Schrage | University Communication

To understand the disparity between the fields of educational research and genomics, it is sufficient to examine how each could define the word "coding".

For Marilyne Stains of Nebraska, whose research on STEM teaching recently earned her the Presidential Career Award for Scientists and Engineers, this means classifying the behavior of instructors and students in the classroom.

Robert Erdmann, who earned his Ph.D. in Plant Genetics Studies before joining the Stains Lab, describes how organisms store biological instruction manuals that make life possible.

But Stains brought Erdmann on board precisely because his academic background was different from his, giving him the opportunity to add a different perspective and voice to his lab. This interdisciplinary investment has been successful in the form of Classroom as Genome, a genetics-inspired approach that the duo has developed to better analyze and interpret the data collected in the classroom.

The researchers said that statistical and visualization tools that have accelerated the search for genetic indicators of the disease or the physical form of organisms could do the same.

"I think the big innovation here is to be able to leverage tools already validated and existing in completely different areas and apply them to data on education," said Stains, an associate professor of chemistry. "The tools we use here help us identify behavioral patterns of instructors (and) students that we really could not use with traditional statistics alone."

By comparing the notes while brainstorming the approach, Stains and Erdmann identified some critical but easily overlooked similarities between genomes and classrooms.

The duo realized, for example, that both have multiple layers of information that can be lost or compressed if one only looks at the set. Collectively, a genome can be considered as the complete catalog of the genetic plans of an organism. To understand the genome at a practical level, however, one has to dig into the deepest layers: what are the actual DNA and genes, how do the instructions embedded in the genes are transcribed and translated, why this process sometimes fails.

Most of the traditional approaches to analyzing data in the classroom are more like first-in-class than in the past, the researchers said, lacking the dynamics that sometimes best reflect the way instructors teach and teach students. Stains and Erdmann wanted the nuances. They wanted an approach that took into account both the influence of the sequence – how one element might cause or affect the next – and the interaction between events occurring simultaneously or overlapping in the time. And they wanted to discern significant patterns among huge amounts of data collected from hundreds or even thousands of classrooms.

Geneticists have faced similar challenges, but even greater ones, when they studied the genomes of organisms, many of which contain millions, even billions of nucleotide bases, the four "letters" of the alphabet of DNA. The rise of bioinformatics in recent decades has allowed geneticists to interpret the equivalents of words, pages and chapters of instruction manuals formed by this code, as well as syntax, punctuation and other rules that determine the transcription.

For Erdmann, these amazing advances also represented unrealized potential.

"What I saw was an opportunity to use the same bioinformatics tools that I had used for plant biology for a unique and creative purpose: to analyze data with many parallels to biological data but "Having not been seen in this context before," said Erdmann, now at the University of Minnesota in Rochester. "I think we were both very happy with the ease with which they were used and the results we got when we tested the tools."

In front of the class

Stains and Erdmann said that one of the main advantages of the "The classroom as a genome" approach is that it can incorporate multiple ways to measure the same observations in the classroom. A common instrument, called COPUS, categorizes the presence or absence of behaviors and interactions in the classroom. Other instruments classify the perceived quality or other aspects of these events.

Educational researchers typically analyze data from different instruments independently of each other, Stains said. But the new approach will allow researchers to overlay the presence, quantity, and quality of a practice or interaction to a single visualization tool, giving them a more comprehensive but still understandable view of the style of instructor or class culture, she said.

"Classrooms are chaotic places," said Erdmann. "You want to be able to get as much information as possible and not waste any of your time.This is an excellent data structure to use for that.

"This allows researchers to simultaneously use the best parts of several tools to get more information from the same set of data."

To illustrate the use and value of Classroom as a genome, Stains and Erdmann included examples and case studies, the latter containing data from a 2015 article, during the presentation of their approach in the journal CBE – Life Sciences Education.

Their examples were questions that education researchers could better address using the approach, alongside genomic equivalents that were already being answered through bioinformatics. A class question to determine how well the clicker questions are homogeneously dispersed over a period of instruction has been paired with the distance that separates a genetic code from other instances of the same code in a genome.

In a related case study, the tandem used COPUS data and a genomics visualization tool to test the hypothesis that instructors asking clicker questions also encourage students to collaborate before answering. Stains and Erdmann then expanded the analysis to demonstrate the extent of related issues or assumptions that the approach could address.

"I think this will be particularly useful for educational researchers or those who know nothing about these techniques," said Stains. "If you already use bioinformatics, language and thought patterns are probably common, but especially for people outside of this world, it was really important to show what these tools look like (and what they can do). make.

"It's kind of a proof of concept to see the potential of these methods, but I think it's so new that we have to illustrate it."

Stains and Erdmann said they hoped the opposite would also be true, that experienced scientists, more familiar with laboratory analysis than in classrooms, would eventually appreciate and possibly use the latter.

"This could be a good bridge between people from university departments who are more organic and those who think more in the direction of education," Erdmann said. "If you offer their worlds the opportunity to collide, this can be very helpful for both parties in terms of thinking about education in new ways and to help make educational research a reality. about which more people think. "


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More information:
Robert M. Erdmann et al. The classroom as a genome: use of genomics and bioinformatics tools to inform classroom observation data, CBE – Life Sciences Education (2019). DOI: 10.1187 / cbe.18-07-0116

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University of Nebraska-Lincoln




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A genetics-inspired approach could improve classroom analysis (July 12, 2019)
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at https://phys.org/news/2019-07-genetics-inspired-approach-classroom-analysis.html

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