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This paper provides a survey of the variety of computer vision [CV] and image processing [IP] courses being taught at institutions around the world. The survey shows that, in addition to classic survey courses in CV/IP, there are many focused and multidisciplinary courses being taught that reportedly improve both student and faculty interest in the topic. It also demonstrates that students can successfully undertake a variety of complex lab assignments. In addition, this paper includes a comparative review of current textbooks and supplemental texts appropriate for CV/IP courses.

This paper describes a course in image computation that is designed to follow and build up an established course in computer graphics. The course is centered on images: how they are generated, manipulated, matched and symbolically described. It builds on the student's knowledge of coordinate systems and the perspective projection pipeline. It covers image generation techniques not covered by the computer graphics course, most notably ray tracing. It introduces students to basic image processing concepts such as Fourier analysis and then to basic computer vision topics such as principal components analysis, edge detection and symbolic feature matching. The goal is to prepare students for advanced work in either computer vision or computer graphics.

Leadership Education Development (LED) teaching results in criticism and debate in the learning atmosphere for students. The significant challenges in LED are analyzing how research can successfully be applied to benefit the students’ teaching, the political essence of education, identifying education research as a science, and the dislocation between educational research and education practice. Teaching and research are two critical ties to tertiary education programs. Two psychological tools have been built from archived research data and show how this form of reuse allows pedagogue to directly link research and teaching. This manuscript proposed an Optimized Learning Strategy (OLS) to improve curriculum development. OLS provides strategies for learning that increase learning ability, learning experience, boost understanding, and connect with previous knowledge of new information. This paper presents the real practice of the development of LED teaching programming. Finally, the results show the students highly recommended OLS based on case study analysis to measure teaching and learning methods.

As increasingly more research efforts are geared towards creating robots that can teach and interact with children in educational contexts, it has been speculated that endowing robots with artificial empathy may facilitate learning. In this paper, we provide a background to the concept of empathy, and how it factors into learning. We then present our approach to equipping a robotic tutor with several empathic qualities, describing the technical architecture and its components, a map-reading learning scenario developed for an interactive multitouch table, as well as the pedagogical and empathic strategies devised for the robot. We also describe the results of a pilot study comparing the robotic tutor with these empathic qualities against a version of the tutor without them. The pilot study was performed with 26 school children aged 10–11 at their school. Results revealed that children in the test condition indeed rated the robot as more empathic than children in the control condition. Moreover, we explored several related measures, such as relational status and learning effect, yet no other significant differences were found. We further discuss these results and provide insights into future directions.

To enhance the effectiveness of learning genetics, we have developed a series of individual computer programs integrating interactivity with animated processes. It was noted that, although the content of the programs varied, the programs all contained a number of common features, including the ability to display text and images, present animated content, and interact with the user. These common features led us to the development of an innovative and unified framework of integrated functions for modeling and simulations. The framework, named "GeneAct" was developed to standardize and accelerate the development of the computer based genetics learning programs and was used as the application programming interface (API). The API allows the content to be imbued with rich text (text with multi-formats), static images, and animations; and it also allows the program to be interactive.

While Learning Analytics has been widely used to improve learning experiences such as course content, activities, and assessments, it plays a significant role in providing data-driven insight into the efficacy of a program. This chapter sheds light on how big data can be used in curriculum development to ensure that the skills and competencies students learn at educational institutions align with those required in the current and future job market. By exploring three case studies in which big data has been utilized to revise and update curricula in different fields, this chapter suggests that big data allows curriculum designers to make data-driven decisions which leads to a higher rate of employability and satisfaction among students. This chapter also discusses the limitations and challenges of using big data in education.

This paper describe CAILS, an experimental Computer Assisted Iconic Language System which deals with three specific areas in communication: Cross-linguistic, visual/spatial concept representation and visual educational technique. Designed for interpersonal communication, this system functions with generally comprehensible visual referents. Each area has some specific syntax which is clear and easy to learn. CAILS takes advantage of visual memory of the user. The basic idea of this system is that an individual can, using basic visual references, compose a message, represent a concept and teach a rule. The specificity of the images eliminates ambiguity. For convenience, we classified visual references or «words» in the following categories: Hands, Movements, Expression, and Pictures.

When properly use, CAILS produce « iconic message objects» which may be presented to the intended recipient

This paper presents an analysis of Filipino and Japanese students’ facial expressions and hand gestures while solving a series of computer programming exercises. Frequently occurring Facial Action Coding System (FACS) muscle movements such as the widening of the eye (AU-5) and sucking of the lip (AU-28), as well as the occurrence of hand gestures, are identified and discussed in relation to the reported affective states of engagement and confusion. We show that it is possible to build models for predicting engagement and confusion using facial expressions and typing information. We believe that this study can help in the development of affectively aware computer systems for learning programming that can work with different cultures.

We describe the Cataway (Catapult Segway), a Segway RMP-based mobile robotic platform which can autonomously throw a ball at a given target, intended to be used as a companion for a human beach ball player. The platform’s throwing mechanism and software architecture were designed, implemented and tested as part of a students’ lab course in practical mobile robotics. The concept allows students to gain practical experience with an actual mobile robot through a motivating scenario and a gentle learning curve. We present results of a simple, yet effective machine learning approach which allows the robot to learn to hit its target from any position.