Title: Open assessment methodology-based decision support system in blended learning environments

Authors: G.M. Shivanagowda; R.H. Goudar; Umakanth P. Kulkarni

Addresses: Department of Computer Science Engineering, Shri Dharmasthala Manjunatheshwara College of Engineering and Technology, Dharwad, India ' Department of Computer Network Engineering, Visvesvaraya Technological University, Belgaum, India ' Department of Computer Science Engineering, Shri Dharmasthala Manjunatheshwara College of Engineering and Technology, Dharwad, India

Abstract: Personalising education is one of the 16 grand challenges as per the National Academy of Engineering, USA. Measuring the outcomes of education and the progress of learning has an essential role in generating personalised feedbacks and recommendations in personalised learning. The data obtained by traditional assessment tools like written and oral examinations, mass assignments do not reflect the real state of the student's knowledge and progress of learning. Learning activities outside the classroom are not observable adding to the imprecision of recommendations. This paper share one of our assessment practice called 'open assessment method' developed and practiced during 2012-2015 along with the design of a decision support system. It is built around a 'class activity sheet' with Google technologies, enhances the observability of the learning environment. This technological adaption leads to improvement in student's participation, generating data useful for composing recommendations on a personal basis with teacher's interventions.

Keywords: open assessment method; OAM; teaching practices; decision support system; DSS; students modelling; personalised recommendation; blended learning environments; BLE.

DOI: 10.1504/IJKL.2020.106646

International Journal of Knowledge and Learning, 2020 Vol.13 No.2, pp.81 - 97

Accepted: 14 Feb 2019
Published online: 16 Apr 2020 *

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