DIGITAL LIBRARY
UNDERSTANDING AND IMPROVING THE USE OF TECHNOLOGY IN CLASSROOM ASSESSMENT
Nanyang Technological University (SINGAPORE)
About this paper:
Appears in: INTED2015 Proceedings
Publication year: 2015
Pages: 6035-6039
ISBN: 978-84-606-5763-7
ISSN: 2340-1079
Conference name: 9th International Technology, Education and Development Conference
Dates: 2-4 March, 2015
Location: Madrid, Spain
Abstract:
Technology can support various assessment processes such as scoring of students’ answers and as a depository of students’ assignments. However, while there is strong interest in the use of technology in classroom assessments, there is a lack of clarity on the role of technology in the assessment process (Ng, 2014). This ambiguity hampers its incorporation in classroom assessments. Technology-enabled assessments should provide something beyond what is available in standard paper and pen formats so that it capitalizes on the affordances of technology such as sharing, collaboration, customization, and personalization (McLoughlin & Lee, 2007). Otherwise it might not be worthwhile to adopt the innovation. Puentedura’s SAMR model of technology adoption (Puentedura , 2012) which is a framework for describing the different levels of technology adoption in teaching and learning (Redecker & Johannessen, 2013) is a viable lens to evaluate the value added by technology in the assessment process (Ng, 2014). In the assessment context, for levels 1 and 2, the focus is on how technology could enhance current assessment practices or do something better within the old assessment framework while for levels 3 and 4, the emphasis is on how technology could transform assessment practices. This paper will discuss how the SAMR model can be adapted to help teachers deliberate on how they are using technology-enabled assessments in their classrooms. Used appropriately, this model could guide educators to modify, redefine and improve the use of technology for classroom assessments.
Keywords:
Technology-enabled assessment, classroom assessment, SAMR model, assessment