Point Cloud-Based Automatic Assessment of 3D Computer Animation Courseworks

Abstract

Computer-supported assessment tools can bring significant benefits to both students and teachers. When integrated in traditional education workflows, they may help to reduce the time required to perform the evaluation and consolidate the perception of fairness of the overall process. When integrated within on-line intelligent tutoring systems, they could provide students with a timely feedback and support self-assessment activities. The current work presents an alternative approach (and not just a "yet-anotherimplementation") to the problem of automatically evaluating technical skills needed to create 3D computer animations. Although some solutions have been reported already in the literature, their applicability is partially constrained, as they require the teaching staff to define evaluation criteria that are strictly linked to the particular animation technique being assessed. Students are forced to operate in environments where they can only perform a part of the required animation steps, by using a pre-defined set of techniques and tools. To address such limitations, the proposed system exploits shape-and time-based features extracted from the 3D point clouds (i.e., the set of data points) describing animated geometries, which are independent of the particular animation techniques used. Experimental observations collected in the evaluation of course assignments in which students were asked to recreate 3D animations of deformable meshes prepared by the teaching staff showed a good correlation between automatic and manual evaluations. Obtained results confirmed the ability of the proposed approach to cope with heterogeneous evaluation tasks in which the relevant learning outcomes can be properly considered.

Assessment analysis: methods and implementation options for multiple-choice exams

“…Sanna et al (2012) present a computer vision and image analysis-based tool for automatic assessment of 3D-modelling exams. Other authors (Lamberti et al, 2014;Paravati et al, 2017) present approaches for automatic assessment of 3D animation assignments.…”

Evaluation of Humans and Software for Grading in an Engineering 3D CAD Course

“…al. which evaluated 3D animations using point clouds [10]. Paravati's technique sought to train an automated grading algorithm and then compare the algorithm with manual grading by the course instructors.…”

A Qualitative Insight into User Experiences of an Intelligent Tutoring System to Learn Sketching Skills.

“…Learning using ITS does not require students to be at a physical class location or university space at a specific time [4]. Another advantage of ITS cited by literature is that ITS helps in reducing the grading workload of instructors and, at the same time, mitigate unfair or inconsistent grading [5] It is also important to note that although ITS has many advantages, ITS is more valuable when it is used alongside a human instructor and not when a human instructor is completely replaced [6]. A recent meta-analysis review comprising 50 studies concluded that ITS was beneficial for student learning in 46 out of 50 studies [3].…”