Technology can help to approximate prior knowledge of learners

The assessment of prior knowledge is an expensive and time consuming process. Marco Kalz, researcher at CELSTEC, has developed a web-based service that can save the assessor a lot of time. The evaluation has shown that the prototype can successfully classify 85% of the cases. On October 16th 2009 he defends his PhD at the Open Universiteit Nederland in Heerlen.

Portfolio assessment

Learners increasingly expect that their prior qualifications and learning experiences are given appropriate recognition when they start their studies. To assess prior knowledge, the learner composes a portfolio with his qualifications and learning experiences. The contents of this portfolio should be compared with the competences demanded in the learning course or programme. Language technology can support this activity. Kalz developed a webbased service based on language technology. This service assesses the prior knowledge by comparing the content of the learner portfolio with documents of the target course. The prototype detects which documents are relevant and which aren’t. He found that with this prototype service he could successfully classify 85% of the cases. With some changes he is confident that it is possible to reduce the false negatives and false positives to less than 10%.

Promising results and opportunities for personalization

He concludes that his model is a good prediction model for classifying relevant and irrelevant documents in APL procedures. It is furthermore possible to approximate the prior knowledge of learners by looking at the similarity between content of learner portfolios and documents of the targeted study programme. These results suggest that it is possible in the future to let computers do the first step in the process of Assesment of Prior Knowledge, thus significantly decreasing the time the assessors have to invest in the process. In addition, there is a lot of potential to reuse the approach for personalization of learning activities in the future.

Marco Kalz (1975, Aachen) defends his PhD thesis 'Placement Support of Learners in Learning Networks' on October 16th, 16.00 hrs, at the Open Universiteit Nederland in Heerlen. Promotor is prof. dr. E.J.R. Koper, co-promotor is dr. J.M. van Bruggen.

On Marco Kalz

Marco Kalz was born in 1975 in Aachen (Germany) and has a teacher degree for special education and German language for secondary schools. In 2003 he obtained his master degree on media education and instructional design. In 2002 he started as a research assistant in the group for media education and knowledge management of the university of Duisburg, where he worked on the use of mobile devices for teaching and learning in higher education. In 2004 he joined the new established educational technology research group at Fernuniversität Hagen where his research was dedicate to the use of social software for self-directed competence development. In 2006 he joined the Centre for Learning Sciences and Technologies at the Open Universiteit Nederland where he worked in the European funded project TENCompetence.