A Study on the Role of Affective Feedback in Robot-Assisted Learning.

In recent years, there have been many approaches to using robots to teach computer programming. In intelligent tutoring systems and computer-aided learning, there is also some research to show that affective feedback to the student increases learning efficiency. However, a few studies on the role of incorporating an emotional personality in the robot in robot-assisted learning have found different results. To explore this issue further, we conducted a pilot study to investigate the effect of positive verbal encouragement and non-verbal emotive behaviour of the Miro-E robot during a robot-assisted programming session. The participants were tasked to program the robot's behaviour. In the experimental group, the robot monitored the participants' emotional state via their facial expressions, and provided affective feedback to the participants after completing each task. In the control group, the robot responded in a neutral way. The participants filled out a questionnaire before and after the programming session. The results show a positive reaction of the participants to the robot and the exercise. Though the number of participants was small, as the experiment was conducted during the pandemic, a qualitative analysis of the data was carried out. We found that the greatest affective outcome of the session was for students who had little experience or interest in programming before. We also found that the affective expressions of the robot had a negative impact on its likeability, revealing vestiges of the uncanny valley effect.

An Approach to Task Representation Based on Object Features and Affordances.

Multi-purpose service robots must execute their tasks reliably in different situations, as well as learn from humans and explain their plans to them. We address these issues by introducing a knowledge representation scheme to facilitate skill generalization and explainability. This scheme allows representing knowledge of the robot's understanding of a scene and performed task. We also present techniques for extracting this knowledge from raw data. Such knowledge representation and extraction methods have not been explored adequately in previous research. Our approach does not require any prior knowledge or 3D models of the objects involved. Moreover, the representation scheme is easy to understand for humans. The system is modular so that new recognition or reasoning routines can be added without changing the basic architecture. We developed a computer vision system and a task reasoning module that works with our knowledge representation. The efficacy of our approach is demonstrated with two different tasks: hanging items on pegs and stacking one item on another. A formalization of our knowledge representation scheme is presented, showing how the system is capable of learning from a few demonstrations.

Human-in-the-loop error detection in an object organization task with a social robot.

In human-robot collaboration, failures are bound to occur. A thorough understanding of potential errors is necessary so that robotic system designers can develop systems that remedy failure cases. In this work, we study failures that occur when participants interact with a working system and focus especially on errors in a robotic system's knowledge base of which the system is not aware. A human interaction partner can be part of the error detection process if they are given insight into the robot's knowledge and decision-making process. We investigate different communication modalities and the design of shared task representations in a joint human-robot object organization task. We conducted a user study (N = 31) in which the participants showed a Pepper robot how to organize objects, and the robot communicated the learned object configuration to the participants by means of speech, visualization, or a combination of speech and visualization. The multimodal, combined condition was preferred by 23 participants, followed by seven participants preferring the visualization. Based on the interviews, the errors that occurred, and the object configurations generated by the participants, we conclude that participants tend to test the system's limitations by making the task more complex, which provokes errors. This trial-and-error behavior has a productive purpose and demonstrates that failures occur that arise from the combination of robot capabilities, the user's understanding and actions, and interaction in the environment. Moreover, it demonstrates that failure can have a productive purpose in establishing better user mental models of the technology.

An IT-based self-checking system of spreadsheet exercises for learners with visual impairments.

PURPOSE: In vocational education and training of computer literacy as part of vocational rehabilitation, learners often work on problem-solving exercises as self-study assignments, and check if their answers are correct. Sighted learners can get information on their incorrect answers by comparing their answers with the correct answers. However, learners with visual impairments largely depend on their teachers for getting this feedback. To remove this dependence, we designed a self-checking system for learners with visual impairments to verify the correctness of their answers. In this paper, we report the results of a usability study to evaluate whether learners with visual impairments can self-check spreadsheet problem-solving exercises using our system in a teacherless environment. METHODS: Usability evaluation experiment was conducted using 2 × 2 crossover design with people with visual impairments (n = 11). The participants checked their answers (detected and corrected errors) after working on problem-solving exercises in two ways: (i) manually; and (ii) using our system. The system usability was evaluated by measuring Detection-And-Correction (DAC) ratio as effectiveness, time taken and the number of steps required for DAC as efficiency, and System Usability Scale score as satisfaction. RESULTS AND CONCLUSIONS: The results show that all the participants could complete the DAC task by using our system, and the time required for DAC task was significantly reduced by using our system as compared to by checking manually. Our system enables learners with visual impairments to self-check problem-solving exercises answers. However, to increase the user satisfaction, the number of required keystrokes needs to be decreased.

Vocational rehabilitation for learners with visual impairments to improve their computer literacy is becoming increasingly important.Learners with visual impairments have the potential to acquire computer literacy in a teacherless environment by using simple assistive software like our self-checking system.Simple assistive software for learners with visual impairments like our self-checking system may have a positive effect not only on learners with visual impairments but also on sighted people.Moreover, our system reduces the teaching load of the teachers so that they can be more effective in helping learners with visual impairments.

Towards Automatic Skeleton Extraction With Skeleton Grafting.

This article introduces a novel approach to generate visually promising skeletons automatically without any manual tuning. In practice, it is challenging to extract promising skeletons directly using existing approaches. This is because they either cannot fully preserve shape features, or require manual intervention, such as boundary smoothing and skeleton pruning, to justify the eye-level view assumption. We propose an approach here that generates backbone and dense skeletons by shape input, and then extends the backbone branches via skeleton grafting from the dense skeleton to ensure a well-integrated output. Based on our evaluation, the generated skeletons best depict the shapes at levels that are similar to human perception. To evaluate and fully express the properties of the extracted skeletons, we introduce two potential functions within the high-order matching protocol to improve the accuracy of skeleton-based matching. These two functions fuse the similarities between skeleton graphs and geometrical relations characterized by multiple skeleton endpoints. Experiments on three high-order matching protocols show that the proposed potential functions can effectively reduce the number of incorrect matches.

The Double Framing Effect of Emotive Metaphors in Argumentation.

In argumentation, metaphors are often considered as ambiguous or deceptive uses of language leading to fallacies of reasoning. However, they can also provide useful insights into creative argumentation, leading to genuinely new knowledge. Metaphors entail a framing effect that implicitly provides a specific perspective to interpret the world, guiding reasoning and evaluation of arguments. In the same vein, emotions could be in sharp contrast with proper reasoning, but they can also be cognitive processes of affective framing, influencing our reasoning and behavior in different meaningful ways. Thus, a double (metaphorical and affective) framing effect might influence argumentation in the case of emotive metaphors, such as "Poverty is a disease" or "Your boss is a dictator," where specific "emotive words" (disease, dictator) are used as vehicles. We present and discuss the results of two experimental studies designed to explore the role of emotive metaphors in argumentation. The studies investigated whether and to what extent the detection of a fallacious argument is influenced by the presence of a conventional vs. novel emotive metaphor. Participants evaluated a series of verbal arguments containing either "non-emotive" or "emotive" (positive or negative) metaphors as middle terms that "bridge" the premises of the argument. The results show that the affective coherence of the metaphor's vehicle and topic plays a crucial role in participants' reasoning style, leading to global heuristic vs. local analytical interpretive processes in the interplay of the metaphorical and the affective framing effects.

Investigating cognitive holding power and equity in the flipped classroom.

In recent years, the flipped classroom has been proposed as an alternative paradigm of teaching, and has been demonstrated to improve the students' knowledge and skills, engagement, and self-efficacy. At the same time, as the number of students seeking higher education is growing and the needs of these students are rapidly evolving, it has become necessary to improve their cognitive holding power and enhance equity among them. The goal of this study is to investigate the impact of the flipped classroom on improving the students' cognitive holding power and enhancing equity. For this study, the flipped classroom was implemented for teaching undergraduate university students' course "An Introduction to Instructional Technology". In the class, whiteboard and Smartboard were used to discuss and clarify ambiguous ideas related to the topic and to present the model answers for the tasks. Outside the class, video files and Google applications (Word, PPT, Drive) were used for delivering learning materials. WhatsApp was used for communication and Google form was used for designing learning activities and assessment. The results of the study indicate: (1) to some extent flipped classroom can be a solution for improving students' cognitive holding power, especially in performing learning tasks and following teacher' instructions. (2) Equity among the students can be enhanced in the flipped classroom. These findings have implications for using the flipped classroom in managing the diversity of university students through enhancing equity among them and improving their abilities.

Analyzing Visual Metaphor and Metonymy to Understand Creativity in Fashion.

The role of figurative language such as metaphor and metonymy in creativity has been studied in cognitive linguistics. These methods can also be applied to analyze non-linguistic data such as pictures and gestures. In this paper, we analyze fashion design by focusing on visual metaphor and metonymy. The nature of creativity in fashion design has not been fully studied from a cognitive perspective compared to other related fields such as art. We especially focus on fashion design as a communication tool between the designer and audience in conveying a designer's image of human beings. Photos from two fashion shows were analyzed. We carried out an experiment to compare how human images in two shows are interpreted by those who are familiar with fashion and those who are not. We obtained three results: (1) As far as figurative (metaphorical and metonymic) interpretations of human images are concerned, two groups with different levels of familiarity with fashion had significantly different patterns of responses to two shows. (2) For the non-figurative interpretations (such as physical or personal attributes), no significant difference in the pattern of response to the show was observed between the two groups. However, the participants as a whole responded to the two shows differently. (3) In addition, for the non-figurative interpretations, the fashion experts found significantly more attributes in human images than the other group. The results show that the analysis of figurative interpretations is effective in understanding how familiarity with fashion affects the mode of seeing fashion shows.

Creative Argumentation: When and Why People Commit the Metaphoric Fallacy.

This article aims to understand when and why people accept fallacious arguments featuring metaphors (metaphoric fallacy) as sound arguments. Two experiments were designed to investigate, respectively, when and why participants fell into the metaphoric fallacy. In the first experiment, participants were provided with a series of syllogisms, presented in natural language, containing in their first premise either a lexically ambiguous, literal middle term or a metaphorical middle term, i.e. the term that "bridges" the first premise with the second premise, and ending with a true, false or plausible conclusion. For each argument they were asked to evaluate whether the conclusion followed from the premises. Results show that the metaphoric fallacy is harder to detect in case of arguments with plausible conclusion with a conventional metaphor rather than a novel metaphor as middle term. The second experiment investigated why participants considered the metaphoric fallacy with plausible conclusion as a strong argument. Results suggest that participants' belief in the conclusion of the argument, independent from the premises, is a predictor for committing the metaphoric fallacy. We argue that a creative search for alternative reasons justifies participants' falling into the metaphoric fallacy, especially when the framing effect of a metaphor covertly influences the overall reading of the argument. Thus, far from being a source of irrationality, metaphors might elicit a different style of reasoning in argumentation, forcing participants to find an alternative interpretation of the premises that guarantees the believed conclusion. In this process, conventional metaphors are revitalized and extended through the second premise to the conclusion, thereby entailing an overall metaphorical reading of the argument.

Word-sentences and an interaction-based account of language evolution.

Considerations from an interaction-based approach to the evolution of language and the role of word-sentences therein show that the object-attribute ontology is arrived at a much later stage. Therefore, Hurford's arguments, by focusing on the predicate-argument structure, seem to miss out on most of the interesting aspects of the early stages in language evolution.