Improving the Accessibility of the Traditional Lecture: An Automated Tool for Supporting Transcription

Abstract

The lecture is in its multiple forms the most commonly used method for transferring information in the University curriculum, yet there are serious questions regarding its effectiveness and accessibility in relation to disabled students and those for whom English is not their first language. Although there has been substantial progress that has been made in the area of Automatic Speech Recognition, current systems are still below the level required for accurate transcription of lectures. The Semantic and Syntactic Transcription Analysing Tool is a step forward in the production of meaningful postlecture materials, with minimal investment in time and effort by academic staff. This paper reports on the results of a study to assess the validity of SSTAT .

Technology Acceptance Evaluation by Deaf Students Considering the Inclusive Education Context

“…From this search, 175 items were found and, after applying exclusion criteria, it resulted in 07 included papers. Therefore, from this review, seven papers were selected [3,5,16,18,23,26,27].…”

“…On the subject of types of technology considered by researchers, [3] proposed a mobile application that translates a given English written phrase to Signwriting and vice-versa, as an alternative to exchanging SMS between people who are D/HH and hearing individuals; [5] conceived a speech rehabilitation system for D/HH children between 1 and 4 years old that use cochlear implants; [16] proposed a prototype of Sign Language Interpreter Module (SLI Module) to improve Web accessibility for deaf users, providing alternative information formats, which was evaluated by thirty one D/HH students with ages between 15 and 21; [18] evaluated mixed reality, using animated avatars, within an assistive learning system with hearing and deaf students; [23] proposed a Semantic and Syntactic Transcription Analysing Tool (SSTAT) to improve the quality of transcriptions delivered by automatic speech recognition systems, and evaluated it with deaf and hearing students; [26] investigated acceptance of the Dictation function of Nuance's Sample Voice Recognition App among eleven D/HH students with age average of 28; and, [27] chose Digital TV as the technology which was subsequently evaluated by people who are deaf and hearing individuals.…”

“…With respect to the constructs used by these researchers, [5] conducted acceptance evaluation with TAM but did not use other constructs; [26] used TAM in their investigation, including other factors that were relevant for technology use in educational environments, such as: hedonic quality attributes (emotional user experience), usability, future expectations of educational improvement, social influence, empowerment of technology, educational barriers; [27] proposed ADOPT-DTV model, adapted from UTAUT, and included three constructs -self-sufficiency, anxiety, attitudes -regarding the use of technologies and intention of adoption (will adopt, undecided, won't adopt). [3,16,18,23] proposed a new technology and conducted technology acceptance evaluations; however, these authors did not use or propose structured models. [3] evaluated preference between SMS and translation, acceptance, system functionalities, ease of use, and consistency between desktop and mobile systems; [16] evaluated usability (including satisfaction, ease of use and comprehension), sign language interpreter (including lip reading and hands-movements), subtitles (including size and readability), and video playback controls (including size of buttons and usefulness); [18] evaluated percentage of acceptance, effectiveness, absent-mindedness, and quality of animated avatars; and, [23] evaluated the following aspects: (i) perception of transcription quality (accuracy); (ii) perceived acceptance of transcripts (between having transcription or not); (iii) usefulness (referring to the quality of transcripts); and, (iv) perceived usability (also referring to the quality of transcripts).…”

“…[3,16,18,23] proposed a new technology and conducted technology acceptance evaluations; however, these authors did not use or propose structured models. [3] evaluated preference between SMS and translation, acceptance, system functionalities, ease of use, and consistency between desktop and mobile systems; [16] evaluated usability (including satisfaction, ease of use and comprehension), sign language interpreter (including lip reading and hands-movements), subtitles (including size and readability), and video playback controls (including size of buttons and usefulness); [18] evaluated percentage of acceptance, effectiveness, absent-mindedness, and quality of animated avatars; and, [23] evaluated the following aspects: (i) perception of transcription quality (accuracy); (ii) perceived acceptance of transcripts (between having transcription or not); (iii) usefulness (referring to the quality of transcripts); and, (iv) perceived usability (also referring to the quality of transcripts).…”