Ildikó Pelczer

Expressions of Emotions in Virtual Agents: Empirical Evaluation

Human communication is mainly based on speech, gestures, facial and bodily expressions. Nonverbal expressions, as body posture and small movements, regulate social interactions. These results lead to an ever-growing effort from behalf of researchers in the human-computer interaction field to include emotions and emotional expressivity in their projects. Evaluation of emotion expressions recognition becomes, thus, an important step in the development of project involving interaction between humans and avatars. In the present paper we describe the results of an evaluation experiment made in two settings: discrimination between three videos looking for a specific emotion expression and identification task that asks for the selection of a list of a seen expression. The obtained results are similar to previous studies from the field and underline again the necessity of careful design of some particular emotions, especially those one that can be considered from the same family.

A Review on Problem Posing in Teacher Education

Over the last two decades, researchers have shown increased interest in problem posing in mathematics professional development. In the context of teaching mathematics, problem posing can entail asking questions during classroom interactions to assess student understanding, modifying existing problems to adjust the difficulty level of a task, and creating problems to meet instructional objectives. In this chapter, we review the research conducted between 1990 and 2012 on problem posing in mathematics methods courses in elementary teacher education. Despite the range of foci, goals, and theoretical perspectives in the literature, we describe ways in which problem posing has been investigated in the preservice teacher population. Despite the paucity of empirical studies, we were able to group these studies into three distinct categories: (a) problem posing as a skill integral to the practice of teaching mathematics; (b) problem posing as an activity separate from teaching; and (c) problem posing as a tool to assess an outcome variable (for researchers) or as a tool for teaching or assessing the development of preservice teachers’ knowledge or beliefs. Implications for mathematics teacher educators that stem from the review of the literature are discussed.

A Pedagogical Corpus to Support a Language Teaching Curriculum to Revitalize an Endangered Language: The Case of Labrador Inuttitut

An obstacle to revitalizing an endangered language is the shortage of authentic speech samples for learners to use as models. Digital recordings of community elders performing traditional chores and special rituals or narrating legends and myths are often made to overcome this obstacle. These recordings, however, contain speech that lacks the crucial features of conversational speech that make them appropriate instructional models. Effective model utterances should be short, have a stand-alone format, and have similar structures to utterances used in everyday transactions, which must be labeled and tagged and organized into a searchable corpus. To date, however, no such corpus exists for indigenous languages, and compiling one is an enormous task. To provide native speech models for adult Labrador Inuit learning their endangered language, Inuttitut, the authors explored the feasibility of building a specialized corpus potentially useful for aiding classroom instruction, using an internationally recognized open-source search and retrieval system called Topic Maps to create its database.

Design of a System for Automated Generation of Problem Fields

We describe the design of a computer system for problem field generation in mathematics. The concept of problem fieldrefers to a sequence of related problems. The relationship between the problems assures that their successive solution promotes deep learning of the topic (sequence problems). We define four relations between the fields problems: difficulty and rule, question or property preservation. The problems difficulty is given by problem-type, algebraic complexity and difficulties of the problems question and rule used for solution. A problem field based on difficulty will modify one of the above elements in order to get new problems from existing ones. In rule- and property-preserving generation the fields problems differ in their type or difficulty level. In question preserving generation the problems maintain the initial problems unknown. Once the details of the change are established the new problem will be generated using templates, rules and examples.