Evaluating and Grading Students in Large-Scale Image Processing Courses

Artner, Nicole M.; Janusch, Ines; Kropatsch, Walter G.

doi:10.1109/mcg.2015.107

Cited by 1 publication

(1 citation statement)

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“…The ratio students/teacher is increasing on a daily basis. Thus, it is not strange to find in the literature works related with the best methodology to deal with this growing problem [46]. In [47] two alternatives were considered for the evaluation of software usage capability: group project assignment (team development of a simulation project) and an individual computer based exam.…”

Section: Methods For the Assessment Of Acquired Knowledgementioning

confidence: 99%

Teaching Image and Video Processing With a Practical Cases-Based Methodology at the University of Alicante

Gil¹,

García²,

Méndez³

et al. 2016

EDULEARN Proceedings

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At universities, the courses about computer vision and image processing have been usually taught using a classical methodology based on textbooks, notes and practical exercises which are explained on a blackboard, although sometimes the teachers use video projector and PC presentations for showing slides with static contents; mainly slides with text, figures and photos. However, this teaching model is focused in teacher instead of students and consequently, this approach is not effective when the teacher seeks to achieve cognitive objectives which involve a student's critical thinking. That is, student should be able to develop skills such as acquired knowledge about how filters, operators, methods and techniques for image processing are implemented by computer vision software libraries. Besides, student should be motived to use that background in order to solve practical and real problems in which it is advisable both a study and an analysis of features based on image processing. This manuscript presents the development, implementation and assessment of a practical-casesbased engineering course, concretely in the Image and Video Processing degree course at the University of Alicante. All course lectures and hands-on laboratory activities have as the main goal that student acquires not only image-specific technical skills but also general knowledge in data analysis to discover phenomena in pixel regions of images and video frames. This way, our teaching-learning process accomplishes both knowledge assimilation and skill developments using a strategy continuous evaluation. In addition, this work presents the progress of student results as well as a comparison between the assessments and scores of students in this year and past years in issues related to specific subject. The Image and Video Processing course is a compulsory subject of Degree in Multimedia Engineering at the University of Alicante in Spain. It is taught during 14-week period of the third academic year, also it has a workload of 6 ECTS (European Credit Transfer and Accumulation System) distributed as 30 hours of computer and laboratory practices and 30 hours of theory class. Nowadays, 80 students are enrolled in this course.

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Section: Methods For the Assessment Of Acquired Knowledgementioning

confidence: 99%