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Anton Anikin added Developed_software_tool_was_applied__.tex
almost 9 years ago
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Developed software tool was applied for creation of personal collections for the course "Programming Languages. C++" in Volgograd State Technical University. Testing included the following steps: creation of personal collections by students themselves using Collection Builder; creation of personal collections for students by tutors-experts; comparative analysis of created collections, assessment of collections quality, estimation of collection creation time.
As a quality criterion for the personal learning collection we used the relevance to the search query, at that, the relevance is defined on the basis of the following quantitative metrics that used in information retrieval tasks \cite{Rijsbergen}:
Precision: $p=\frac{\left|{RL}_{COL}^{'} \right|}{\left|{RL}^{'}_{COL} \right|+\left|{RL}^{''}_{COL}\right|}$,
Recall: $r=\frac{\left|{RL}_{COL}^{'} \right|}{\left|{RL}^{'} \right|}$,
F-measure: $F=\frac{2}{\frac{1}{p}+\frac{1}{r}}$,
where ${RL}^{'}_{COL}$ - relevant resources of the collection,
${RL}^{''}_{COL}$ - irrelevant resources of the collection,
${RL}^{'}$ - relevant resources in the repository,
${RL}^{''}$ - irrelevant resources in the repository,
${RL}$ - resources in the repository,
${RL}_{COL}$ - resources of the collection,
${RL}^{'}\bigcup {RL}^{''}=RL$,
${RL}^{'}_{COL}\bigcup {RL}^{''}_{COL}={RL}_{COL}$.
The precision and recall are the base metrics, F-measure - one of the derivative metrics.
Test results has shown that:
\begin{enumerate}
\item the average time of collection creation decreased almost by 99\%;
\item automatically generated collection contains 100\% of learning resources obtained by the intersection of the collections created by tutors for each student, and 91\% of learning resources obtained by combining the tutors collections;
\item the average value of collection recall increased by 29\%, precision - by 2,9\%, F-measure - by 16,3\% in comparison with non-automated process.
\end{enumerate}
These facts allow to draw a conclusion that developed models, method and software tool are effective and efficient for creation of new personal learning content.
