I think that it would be of great value to develop a panel of experts who would identify a few “good” designs from each lab round. The panel of experts could consist of the more experienced players, as well as some of the developers.
Post those designs along with the winning designs and/or in GetSat, and describe the characteristics that qualified that particular design, in the minds of the experts, as a “good” design.
This would provide role models for learning within each lab-round.
(Of course, this idea comes from a beginner-level player.)
This is a very interesting idea.
Do you think the panel should be something official that the EteRNA website itself should highlight their opinions?
…or should this panel be just one of player side activities so that game does not officially credit certain people more?
I am hoping that the “experts” (Eterna RNA synthesis team) would write a brief lab report about the results from each lab.
Having a report from the experts would be especially helpful as a learning tool for beginner-level players, as well as providing a starting point for player to discuss the results. If the report was posted in GetSat, then all the players would have the opportunity to comment, agree, disagree, and debate any of the points. The feedback from each lab would be conveniently located in one place.
The report does not need to include a discussion of materials, procedures, or data analysis. It could consist of only observations and comments.
The report should include a picture of one or more of the higher synthesis-scoring designs with the various features considered to be good design identified. Example: this is the GAAA tetra-loop, the G-G 1-1 loops, the specific location of GC pairs at the base of the stacks, etc.
Examples of comments: All of the neck designs in Round X failed to synthesize. Only 1 neck design (see image) was successfully synthesized. It was unexpected to the team that #x-#y pair did not bond.
Thank you for your time and consideration of this idea.
on second thought. . . some players might be very interested in seeing the data analysis used to determine the synthesis score.