Project Activities
Key outcomes
People and institutions involved
IES program contact(s)
Products and publications
ERIC Citations: Find available citations in ERIC for this award here.
Select Publications:
Dennis, S. (2003). An alignment-based account of serial recall. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 25, No. 25).
Dennis, S. (2005). An Exemplar-Based Approach to Unsupervised Parsing. In Proceedings of the 27th Annual Conference of the Cognitive Science Society (pp. 583-588). Hillsdale, NJ: Erlbaum.
Dennis, S. (2004). An unsupervised method for the extraction of propositional information from text. Proceedings of the National Academy of Sciences, 101 (suppl_1), 5206-5213.
Dennis, S. (2005). A memory-based theory of verbal cognition. Cognitive Science, 29 (2), 145-193.
Dennis, S. (2007). Introducing Word Order in an LSA Framework. In T. Landauer, D. McNamara, S. Dennis, and W. Kintsch (Eds.), Handbook of Latent Semantic Analysis (pp. 449-466). Mahwah, NJ: Erlbaum.
Doxas, I., Dennis, S., and Oliver, W. (2007). The Dimensionality of Language. In Proceedings of the 29th Annual Conference of the Cognitive Science Society (pp. 227-232). New York: Erlbaum.
Harrington, M., & Dennis, S. (2003). Structural priming in sentence comprehension. In Proceedings of the Annual Meeting of the Cognitive Science Society (Vol. 25, No. 25).
Kintsch, W., McNamara, D.S., Dennis, S., and Landauer, T.K. (2007). LSA and Meaning: In Theory and Application. In T. Landauer, D. McNamara, S. Dennis, and W. Kintsch (Eds.), Handbook of Latent Semantic Analysis (pp. 467-480). Mahwah, NJ: Erlbaum.
Landauer, T.K. (2007). LSA as a Theory of Meaning. In T. Landauer, D. McNamara, S. Dennis, and W. Kintsch (Eds.), Handbook of Latent Semantic Analysis (pp. 3-35). Mahwah, NJ: Erlbaum.
Steyvers, M., Griffiths, T.L., and Dennis, S. (2006). Probabilistic Inference in Human Semantic Memory. Trends in Cognitive Sciences, 10 (7): 327-334.
Supplemental information
- Automation to construct and instantly score multiple-choice Cloze tests. This tool was used as a beginning point to develop the more innovative constructed-response Open-Cloze activity described below.
- A constructed-response "Open-Cloze" activity and assessment in which learners supply, rather than choose, missing words. This activity provides learners with practice that supports the acquisition of word meaning, as well as the assessment of the learner's knowledge of the meaning(s) of a word. This tool proved challenging to develop, but by the end of the project they were able to obtain adequate system-human agreement. They then used this tool as a summative assessment tool across multiple words, and also provided general feedback to the students after they completed the Open-Cloze activity. This development is in many ways the foundational achievement of this project and holds large promise in future uses.
- An automated "Meaningful Sentence" activity and assessment. In this tool, students were asked to write sentences requiring the words-to-be learned (an authentic school-based task), and the system instantly evaluated the degree to which the word was used appropriately in the sentence. This was completed early in the project and successfully.
- A revised and extended version of Summary Street . This product was evaluated through an NSF award. The IES award supported the development of tools integrated into the current system. These tools provided graphic feedback both to students and teachers as to the progress of their summaries.
- Tools to support individualized choice of practice words and reading passages. This objective was not met as originally intended, in part because it was contingent upon successful attainment of the tool development described above. The time it took to accomplish that development work took them to the end of their project period. However, the team did begin to explore how to use Lexile ratings and publisher-provided grade leveling in the choice of words and readings.
- In addition, the project attained several goals that were not originally proposed, but which are central to the long-term success of this set of studies. As the team developed these new tools, they realized the demands of scoring and feedback using the new tools required the researchers to develop and test a new model of language that better captures sentences that are similar in meaning but which vary in their syntax and structure. This addition of a syntactic dimension to the semantically driven LSA model has important implications for future work and was highly innovative.
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