Week's Plan:
Do a literature review on modelling problem solving.
Do a literature review on sequence mining.
Do some writing for graph-layouts, proposing the idea, edit the chapter on sequence mining, based on my findings for this week.
Week's Accomplishments:
I read a number of works on sequence mining and became more familiar with their goals, focus, and nomenclature. I also read up on modelling problem solving, which went much further away from logging tutors and states of problems and much more towards the state of the mind and ACT-R. It seems there is a significant gap between the states we can generate from tutors and data and the states modeled in psychology research.
In the case of sequence mining that challenge is the very act of identifying the sequences. The problems have long target strings and really long data-strings, in the thousands of characters. In our case the challenge isn't discovering the sequences, though the algorithms developed from that field would be useful in our tool. Our challenge is to identify which sequences are most meaningful. For this, we need to look at the community structure and discoveries we can make from the networking field. By investigating the graph-invariants of the problem-solution space we can gain insight to which states are important.
I also wrote up my arguments and proposed ideas for investigating these aspects mentioned above.
Problems:
No problems these week.
Next Week's Plan:
Meet with Tiffany on Monday and discuss my proposed arguments. Continue writing up my proposal in a more concrete manner. I need to organize the text I have into a single consistent document. Where all the related works from each of the papers appear in the same related work section, combine the introductions, etc. and remove redundancy in the text. Specifically I will focus on the proposed research section and provide the necessary related works for those sections. I will have some text for proof-reading at the end of the week.
Other Pieces of Work: (I just don't want to forget these ideas, not sure how necessary / important they are)
We should export the frequency data for the stoichiometry data and load that into yEd and see what see.
We should write some type of data loader that lets load in "hint-actions" so we can see where students request hints.
I should develop a Data-Properties class to more appropriately manage the different functions we have available depending on what type of data is read in. Basically the object just stores a dozen or so flags that are set based on what columns are read in, in the data-import stage of the program.
Do a literature review on modelling problem solving.
Do a literature review on sequence mining.
Do some writing for graph-layouts, proposing the idea, edit the chapter on sequence mining, based on my findings for this week.
Week's Accomplishments:
I read a number of works on sequence mining and became more familiar with their goals, focus, and nomenclature. I also read up on modelling problem solving, which went much further away from logging tutors and states of problems and much more towards the state of the mind and ACT-R. It seems there is a significant gap between the states we can generate from tutors and data and the states modeled in psychology research.
In the case of sequence mining that challenge is the very act of identifying the sequences. The problems have long target strings and really long data-strings, in the thousands of characters. In our case the challenge isn't discovering the sequences, though the algorithms developed from that field would be useful in our tool. Our challenge is to identify which sequences are most meaningful. For this, we need to look at the community structure and discoveries we can make from the networking field. By investigating the graph-invariants of the problem-solution space we can gain insight to which states are important.
I also wrote up my arguments and proposed ideas for investigating these aspects mentioned above.
Problems:
No problems these week.
Next Week's Plan:
Meet with Tiffany on Monday and discuss my proposed arguments. Continue writing up my proposal in a more concrete manner. I need to organize the text I have into a single consistent document. Where all the related works from each of the papers appear in the same related work section, combine the introductions, etc. and remove redundancy in the text. Specifically I will focus on the proposed research section and provide the necessary related works for those sections. I will have some text for proof-reading at the end of the week.
Other Pieces of Work: (I just don't want to forget these ideas, not sure how necessary / important they are)
We should export the frequency data for the stoichiometry data and load that into yEd and see what see.
We should write some type of data loader that lets load in "hint-actions" so we can see where students request hints.
I should develop a Data-Properties class to more appropriately manage the different functions we have available depending on what type of data is read in. Basically the object just stores a dozen or so flags that are set based on what columns are read in, in the data-import stage of the program.
