Mooshak is a web system with support for assessment in computer science.
Several experiments were designed to analyse the impact of different features such as graph size, and amount of difference between solution and attempt. The proposed algorithm was validated with thousands of graphs with different features produced by a synthetic data generator. However, the motivation for developing this algorithm is to combine it with other assessment models, such as the test case model used for programming language assessment. This data model is able to accommodate diagram languages, such as UML or ER diagrams, for which this kind of assessment is typically used. The proposed algorithm is applicable to any type of document that can be parsed into its graph-inspired data model.
The proposed algorithm uses heuristics to test the most promising mappings first and prune the remaining when it is sure that a better mapping cannot be computed. Given two graphs, a solution and an attempt of a student, this approach computes a mapping between the node sets of both graphs that maximizes the student’s grade, as well as a description of the differences between the two graph. OL27694571W Page_number_confidence 92.06 Pages 342 Partner Innodata Pdf_module_version 0.0.18 Ppi 360 Rcs_key 24143 Republisher_date 20220319223416 Republisher_operator Republisher_time 482 Scandate 20220318140556 Scanner Scanningcenter cebu Scribe3_search_catalog isbn Scribe3_search_id 9782212120912 Tts_version 4.This paper proposes a structure driven approach to assess graph-based exercises. Access-restricted-item true Addeddate 15:12:19 Bookplateleaf 0002 Boxid IA40407508 Camera USB PTP Class Camera Collection_set printdisabled External-identifier
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