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An Internet Based Educational Assessment Tool
Author(s) -
Jerome Eric Luczaj,
Chia Y. Han
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--12066
Subject(s) - session (web analytics) , computer science , the internet , class (philosophy) , event (particle physics) , active learning (machine learning) , multimedia , process (computing) , world wide web , artificial intelligence , physics , quantum mechanics , operating system
Sustaining a continuous improvement process through assessment requires tools to automatically collect and organize outcome data and methods to evaluate the data pertinent to program objectives. To identify activities that reflect student learning and understanding, to better understand when student learning occurs and to optimize institutional and instructor-based efforts to promote student learning, we contend institutions and instructors need information about student behavior that is both timely and timed. We propose an automated, Internet-based, activity collection system that will capture student classroom activity, sequence this activity into event trails, associate these trails to learning units and connect these events to learning outcome assessment. Too often connections between program objectives, instruction and student learning are made in retrospect as supposition based only upon final outcomes and vague recollection of the events. The internet-based, client-server system will augment the classroom session by allowing the students to annotate instructional streams for personalized review, take notes, and provide real-time feedback to the instructor via a networked computer. As students perform actions during the course of instruction, both in class and as they review class instructional streams, the system collects their activities into a timed sequence. The content within the instructional streams provides the context. Student evaluation on each content area will provide the final link between instruction and student performance. By unobtrusively recording these activities as timed, synchronized events, a data trail can be created that links final outcomes to specific student and instructor activities. This rich collection of activity data can be mined to gain a better understanding of when and how learning occurs and what can be done to improve it. This paper will describe how the system will be incorporated into the learning environment and what benefits it will produce.

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