Plan recognition for ELEs using interleaved temporal search

Oriel Uzan, Reuth Dekel, Ya'akov Gal

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Exploratory Learning Environments (ELE) provide a rich educational environment for students, but challenge teachers to keep track of students' progress and to assess their performance. This paper proposes an algorithm that decomposes students complete interaction histories to create hierarchies of interdependent tasks that describe their activities in ELEs. It matches students' actions to a predefined grammar in a way that reflects students' typical use of ELEs, namely that students solve problems in a modular fashion but may still interleave between their activities. The algorithm was empirically evaluated on peoples interaction with two separate ELEs for simulating a chemistry laboratory and for statistics education. It was separately compared to the state-of-the-art recognition algorithm for each of the ELEs. The results show that the algorithm was able to correctly infer students' activities significantly more often than the state-of-the-art, and was able to generalize to both of the ELEs with no intervention. These results demonstrate the benefit of using AI techniques towards augmenting existing ELEs with tools for analyzing and assessing students' performance.

Original languageAmerican English
Title of host publicationArtificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings
PublisherSpringer Verlag
Number of pages4
ISBN (Print)9783642391118
StatePublished - 1 Jan 2013
Event16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, TN, United States
Duration: 9 Jul 201313 Jul 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7926 LNAI


Conference16th International Conference on Artificial Intelligence in Education, AIED 2013
Country/TerritoryUnited States
CityMemphis, TN

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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