A Study about Placement Support Using Semantic Similarity

This paper discusses Latent Semantic Analysis (LSA) as a method for the assessment of prior learning. The Accreditation of Prior Learning (APL) is a procedure to offer learners an individualized curriculum based on their prior experiences and knowledge. The placement decisions in this process are ba...

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Published inEducational technology & society Vol. 17; no. 3; pp. 54 - 64
Main Authors Katz, Marco, van Bruggen, Jan, Giesbers, Bas, Waterink, Wim, Eshuis, Jannes, Koper, Rob
Format Journal Article
LanguageEnglish
Published Palmerston North International Forum of Educational Technology & Society 01.07.2014
Subjects
Classification
College Students
Colleges & universities
Cosine function
Curricula
Decision analysis
Documentation
Educational aspects
Educational environment
Educational evaluation
Educational technology
Electronic learning
Expertise
Foreign Countries
Full Length Articles
Hypothesis Testing
Indexes
Individualized Instruction
Latent learning
Latent semantic analysis
Learning
Learning procedures
Learning Processes
Management
Modeling
Natural Language Processing
Netherlands
Networks
Open Universities
Paragraph Composition
Placement
Prior Learning
Psychology
Resistance (Psychology)
Semantics
Semiotics
Student Evaluation
Student Placement
Technology application
Term weighting
Netherlands
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Summary:This paper discusses Latent Semantic Analysis (LSA) as a method for the assessment of prior learning. The Accreditation of Prior Learning (APL) is a procedure to offer learners an individualized curriculum based on their prior experiences and knowledge. The placement decisions in this process are based on the analysis of student material by domain experts, making it a time-consuming and expensive process. In order to reduce the workload of these domain experts we are seeking ways in which the preprocessing and selection of student submitted material can be achieved with technological support. This approach can at the same time stimulate research about assessment in open and networked learning environments. The study was conducted in the context of a Psychology Course of the Open University of the Netherlands. The results of the study confirm our earlier findings regarding the identification of the ideal number of dimensions and the use of stopwords for small-scale corpora. Furthermore the study indicates that the application of the vector space model and dimensionality reduction produces a well performing classification model for deciding about relevant documents for APL procedures. Together we discuss methodological issues and limitations of our study whilst also providing an outlook on future research in this area.
ISSN:1176-3647
1436-4522
1436-4522