Quality Prediction of Open Educational Resources A Metadata-based Approach

In the recent decade, online learning environments have accumulated millions of Open Educational Resources (OERs). However, for learners, finding relevant and high quality OERs is a complicated and time-consuming activity. Furthermore, metadata play a key role in offering high quality services such as recommendation and search. Metadata can also be used for automatic OER quality control as, in the light of the continuously increasing number of OERs, manual quality control is getting more and more difficult. In this work, we collected the metadata of 8,887 OERs to perform an exploratory data analysis to observe the effect of quality control on metadata quality. Subsequently, we propose an OER metadata scoring model, and build a metadata-based prediction model to anticipate the quality of OERs. Based on our data and model, we were able to detect high-quality OERs with the F1 score of 94.6%.

[1]  Nelson Piedra,et al.  A Proposal of Quality Assessment of OER Based on Emergent Technology , 2019, 2019 IEEE Global Engineering Education Conference (EDUCON).

[2]  Péter Király,et al.  Measuring completeness as metadata quality metric in Europeana , 2018, 2018 IEEE International Conference on Big Data (Big Data).

[3]  Veronica Segarra-Faggioni,et al.  Exploring the provenance and accuracy as metadata quality metrics in assessment resources of OCW repositories , 2018, ICETC '18.

[4]  Audrey Romero Pelaez,et al.  Metadata Quality Assessment Metrics into OCW Repositories , 2017, ICETC.

[5]  Edmundo Tovar Caro,et al.  Recommendation of open educational resources. An approach based on linked open data , 2017, 2017 IEEE Global Engineering Education Conference (EDUCON).

[6]  Cristina Hava Muntean,et al.  VQAMap: A Novel Mechanism for Mapping Objective Video Quality Metrics to Subjective MOS Scale , 2016, IEEE Transactions on Broadcasting.

[7]  Panos Constantopoulos,et al.  Measuring Quality in Metadata Repositories , 2015, TPDL.

[8]  Matej Durco,et al.  Towards automatic quality assessment of component metadata , 2014, LREC.

[9]  Donatella Castelli,et al.  Dealing with metadata quality: The legacy of digital library efforts , 2013, Inf. Process. Manag..

[10]  Athanasios Manitsaris,et al.  Quantifying and measuring metadata completeness , 2012, J. Assoc. Inf. Sci. Technol..

[11]  Erik Duval,et al.  Automatic evaluation of metadata quality in digital repositories , 2009, International Journal on Digital Libraries.

[12]  Athanasios Manitsaris,et al.  A Conceptual Framework for Metadata Quality Assessment , 2008, Dublin Core Conference.

[13]  Hugo Minni,et al.  Identifier management and resolution: conforming the IEEE standard for learning object metadata , 2008 .

[14]  David M. Nichols,et al.  A lightweight metadata quality tool , 2008, JCDL.

[15]  Elena García Barriocanal,et al.  Complete metadata records in learning object repositories: some evidence and requirements , 2005, Int. J. Learn. Technol..

[16]  Erik Duval,et al.  Quality Metrics for Learning Object Metadata , 2006 .

[17]  Diane I. Hillmann,et al.  The Continuum of Metadata Quality: Defining, Expressing, Exploiting , 2004 .