Supporting learning in large classes: online formative assessment and automated feedback

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Abstract

—The provision of formative assessment and formative feedback is challenging for an educator working with large cohorts of students. To avoid being overwhelmed with the volume of work, appropriate technologies need to be selected to support learners and scale the module assessment and delivery to accommodate the size of the class. This paper presents the results of implemented online formative assessment delivery for a large postgraduate cohort of both full- and part-time students. We experimented with early and frequent student access to online formative assessment followed by immediate automated feedback. We review the impact of this assessment regime on student experience and achievement of learning outcomes. Endof-term student feedback indicates that frequent online quizzes, formative feedback and repetitive practicing were very well received by the students. We observe sustained levels of student engagement through data collected during student interaction with online module content and assessment. Analysis of the data has determined that the quizzes which had the highest number of attempts showed strong correlation with the highest student scores at the end-of-term exam. Such an experiment reflects how students learn via online content delivery and make use of available learning technologies for self-directing and practicing in computing subject. Frequent access to online formative assessment tool followed by immediate automated feedback helps to create effective learning environment and accommodate learners in large full-time and part-time classes
Original languageEnglish
Title of host publicationProceedings of 30th Annual Conference of the European Association for Education in Electrical and Information Engineering (EAEEIE-2021), Prague, 1-3 September, 2021
EditorsDusan Maga, Jiri Hajek
PublisherCzech Technical University, Publishing House
Pages158-161
Number of pages4
Edition1
ISBN (Electronic)CFP2196D-USB
ISBN (Print)978-1-7281-9324-3
DOIs
Publication statusPublished - 01 Sep 2021

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