DIGITAL LIBRARY
LEARNING OUTCOMES ASSESSMENT USING MULTIPLE STATISTICAL HYPOTHESIS TESTING AND INSTANT RESPONSE SYSTEM TECHNOLOGY
American University in Dubai (UNITED ARAB EMIRATES)
About this paper:
Appears in: EDULEARN11 Proceedings
Publication year: 2011
Pages: 4739-4742
ISBN: 978-84-615-0441-1
ISSN: 2340-1117
Conference name: 3rd International Conference on Education and New Learning Technologies
Dates: 4-6 July, 2011
Location: Barcelona, Spain
Abstract:
Modern trends in higher education stress the importance of relying on the specification and assessment of well defined learning outcomes to continuously improve the learning experience. The advantages of using learning outcome assessment are multifold. Students will have a better understanding of the expectations of a course or program. Faculty members will be able to know what is working and what is not working in their courses. Administrators will be able to provide accountability results to funding agencies and meet the requirements of accreditation bodies. The difficulty in implementing such a methodology stems from the fact that grades alone cannot be an indicative and accurate measure of the various learning outcomes of a certain course or program. For instance, in multisection courses, the course grade could be an inconsistent measure. Moreover, a final grade is an indication of the aggregate performance of a student in a certain course rather than a measure of meeting specific objectives. Hence, the need to incorporate specific assessment instruments in courses to measure the specified outcomes. The easiest way to implement these measures is to blend specific questions on exams, assignments, etc. to probe results on course outcomes. Alternatively, add-on tests or assignments could be introduced. The assessment process, to date, hasn’t benefited well from classroom technologies, such as interactive response systems. Interactive response systems are designed to allow individual responses by students to be collected, scored, and tabulated. In this work, we demonstrate the use of such systems for a real-time assessment in a higher education setting. A software layer was developed which enables the formation and testing of multiple hypotheses related to a certain student population. The applications in enhancing the learning experience are endless.