The E-learning Circle – a holistic software design tool for e-learning

The article introduces the E-learning Circle, a tool developed to assure the quality of the software design process of e-learning systems, considering pedagogical principles as well as technology. The E-learning Circle consists of a number of concentric circles which are divided into three sectors. The content of the inner circles is based on pedagogical principles, while the outer circle specifies how the pedagogical principles may be implemented with technology. The circle’s centre is dedicated to the subject taught, ensuring focus on the specific subject’s properties. The three sectors represent the student, the teacher and the learning objectives. The strengths of the E-learning Circle are the compact presentation combined with the overview it provides, as well as the usefulness of a design tool dealing with complexity, providing a common language and embedding best practice. The E-learning Circle is not a prescriptive method, but is useful in several design models and processes. The article presents two projects where the E-learning Circle was used as a design tool.

Impact Study of Nonverbal Facial Cues on Spontaneous Chatting with Virtual Humans

Non-verbal communication (NVC) is considered to represent more than 90 percent of everyday communication. In virtual world, this important aspect of interaction between virtual humans (VH) is strongly neglected. This paper presents a user-test study to demonstrate the impact of automatically generated graphics-based NVC expression on the dialog quality: first, we wanted to compare impassive and emotion facial expression simulation for impact on the chatting. Second, we wanted to see whether people like chatting within a 3D graphical environment. Our model only proposes facial expressions and head movements induced from spontaneous chatting between VHs. Only subtle facial expressions are being used as nonverbal cues - i.e. related to the emotional model. Motion capture animations related to hand gestures, such as cleaning glasses, were randomly used to make the virtual human lively. After briefly introducing the technical architecture of the 3D-chatting system, we focus on two aspects of chatting through VHs. First, what is the influence of facial expressions that are induced from text dialog? For this purpose, we exploited an emotion engine extracting an emotional content from a text and depicting it into a virtual character developed previously [GAS11]. Second, as our goal was not addressing automatic generation of text, we compared the impact of nonverbal cues in conversation with a chatbot or with a human operator with a wizard of oz approach. Among main results, the within group study -involving 40 subjects- suggests that subtle facial expressions impact significantly not only on the quality of experience but also on dialog understanding.