No abstract

No abstract

Assistive technology (AT) helps bridge the gap between students with learning disabilities (LD) and their peers without LD. However, this implies a need for teachers to become well-trained and proficient in the use of AT. There are established AT competencies for educators, and AT services professionals must be knowledgeable about AT to select and recommend specific technology to individual education program teams. Professionals should also be well-versed with AT to be able to train students in its use. There is a significant need for research on teachers’ knowledge and perceptions of AT (i.e., interest in using it and barriers to incorporating it) as well as the best ways to provide AT training. To investigate these areas, a survey was administered to teachers of students with LD at the elementary and middle school levels. Our results indicated that completing an AT course in college along with self-reported AT proficiency in iPad reading apps were associated with higher ratings of AT knowledge. Additionally, higher AT proficiency ratings and completing AT college course work were associated with perceptions of college preparation of AT, but these factors did not predict perceptions of workplace preparation. Teachers were clearly interested in utilizing AT but felt their college did not adequately prepare them in AT, and funding issues were the most common barriers to implementing AT. Our findings suggest a need for an emphasis on AT training in college courses.

In human-computer interaction people often interpret the interaction with the computer as interactions with humans. The social agency theory suggests that social cues like the face and voice of the agent motivate this interpretation. In two off-line experiments in which comprehension scores and liking ratings were collected, we found that participants preferred natural agents with natural voices, as predicted by the social-cue hypothesis. Although female agents with male voices formed an exception, this was explained by a stereotype effect. These findings support the social-cue hypothesis and the social agency theory that human characteristics are applied in the perception of computational animated conversational agents.Intelligent dialogue systems have received considerable attention in fields such as artificial intelligence, computer science, cognitive science, and computational linguistics. Throughout the years, these systems have become progressively more sophisticated, with intelligent systems for train control (Allen et al., 1995), travel bookings (Rudnicky et al., 1999, and personnel work (Franklin, 2001). A subset of these intelligent dialogue systems are intelligent tutoring systems. These are computer-based instructional systems that continuously make inferences about a student's mastery of topics, facts, rules and mental models in order to dynamically adapt instruction and to deliver the right information at the right time. Various tutoring systems have been tested on humans and have proven to facilitate learning. For example, there are well-tested tutors of computer literacy (such as

The Action-sentence Compatibility Effect (ACE) is a well-known demonstration of the role of motor activity in the comprehension of language. Participants are asked to make sensibility judgments on sentences by producing movements toward the body or away from the body. The ACE is the finding that movements are faster when the direction of the movement (e.g., toward) matches the direction of the action in the to-be-judged sentence (e.g., Art gave you the pen describes action toward you). We report on a pre-registered, multi-lab replication of one version of the ACE. The results show that none of the 18 labs involved in the study observed a reliable ACE, and that the meta-analytic estimate of the size of the ACE was essentially zero.