A Study about Placement Support Using Semantic Similarity

Dec 3, 2014·
Marco Kalz
Marco Kalz
,
Jan van Bruggen
,
Bas Giesbers
,
Wim Waterink
,
Jannes Eshuis
,
Rob Koper
· 1 min read
Abstract
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.
Type
Publication
Journal of Educational Technology & Society, 17(3), 54-64. JSTOR
publications publications

Kalz, M., Van Bruggen, J., Giesbers, B., Waterink, W., Eshuis, J., & Koper, R. (2014). A study about placement support using semantic similarity. Journal of Educational Technology & Society, 17(3), 54-64. https://www.jstor.org/stable/jeductechsoci.17.3.54

Distance Education Open Learning MOOCS Survey Development
Marco Kalz
Authors
Marco Kalz
Professor of Educational Technology

I am a researcher in educational technology whose work explores how digital technologies reshape learning, teaching, and educational institutions. My research combines educational technology, learning sciences, feedback research, and critical perspectives on digital transformation.Current areas of interest include peer feedback and feedback literacy, open and networked learning, AI and misinformation in education, digital learning ecologies, and the societal implications of data-driven and platform-based education. Methodologically, my work spans empirical learning research, psychometric scale development, design-oriented research, and conceptual analyses of digital transformation in education.

I am working as a full professor of educational technology and Chief Information/Chief Digital Officer (CIO/CDO) at the Heidelberg University of Education. I serve as associate editor of the International Journal of Artificial Intelligence in Education and editorial board member of the Journal of Computing in Higher Education. I am a senior-fellow of the Interuniversity Center for Educational Sciences (ICO) and the Dutch research school on information and knowledge systems (SIKS). I work as director of the study program E-Learning and Media Education and director of the Heidelberg Centre for Digital Transformation in Education. Over the years I could secure approx. 4 Mio EUR of research funding for my institutions from competitive projects with a total budget of 36 Mio EUR. I have been an invited keynote speaker on more than 60 conferences and events. Besides European projects I am regularly involved in educational innovation and consulting projects with partners inside and outside of my institutions including clients like the International Labour Organisation, United Nations Environment Program, the European Commission, UNESCO, OECD or other international and national organizations.