Hearing Imparied Learner
Supporting hearing-impaired students using ICTs
Michael Crocker, Memorial University of Newfoundland
Problem
Hard-of-hearing students demonstrate lower math, reading, and writing skills than hearing counterparts, even though their mental abilities are on par with their peers (Debevc, Stjepanovic, & Holzinger, 2014). Kiboss (2012) found Kenyan high schools students with hearing impairment scored lower in math tasks. Stoner, Easterbrooks, and Laughton (2005) reported that elementary students with hearing loss in the United States demonstrated lower writing skills and literacy outcomes. Students who are deaf or hard-of-hearing may also struggle to learn a second language (Zamfirov & Saeva, 2013). Hard-of-hearing students often demonstrate lower homework completion rates, lower overall motivation, and may receive lower standards from their teachers (Liu & Hong, 2007).
Deaf students experience particular difficulty when learning technical skills, which may be due to a lack of signs for technical terms (Andrei, Osborne, & Smith, 2013) and a lack of qualified interpreters (Marschark et al., 2005). Even with effective sign interpretation, latency in interpreter processing time may cause issues (Long, Marchetti, & Fasse, 2011). Deaf students often perceive that they receive a distorted message when a non-signing instructor’s lecture is translated by the interpreter (Long, Vignare, Rappold, & Mallory, 2007). Hard-of-hearing students may also suffer from visual input overload as they simultaneously attempt to pay attention to the instructor, interpreter, and any visual aids that may be presented (Marschark et al., 2005). Deaf students often miss out on secondary learning opportunities that are afforded to hearing peers (Parton, 2006). Opportunities to learn from classmates are often lessened due to communication difficulties with hearing students (Long et al., 2011) and teachers struggle to provide them after class learning support (Liu & Hong, 2007). Extra learning resources may not be accessible, as non-captioned video clips are often used in class (Slobodzian, 2009) and there is a widespread lack of accessible interactive materials (Parton, 2006).
Role of ICTs
Hashim, Tasir, and Mohamad (2013) pointed out that the problems that hard-of-hearing students face in the traditional classroom provide opportunities for the e-learning movement. E-learning is considered particularly important for disabled students (Debevc et al., 2014). Kuzu (2011) observed that a properly-designed e-learning platform could improve students’ outcomes and satisfaction among hearing-impaired, lower primary math students in Kenya. Yang and Lay (2005) demonstrated that a software-based training tool for Mandarin phonemes could increase motivation among hearing-impaired students learning the language, with the ability to receive instant feedback particularly valued. Zamfirov and Saeva (2013) showed that a specially-designed computer program could lead to higher performance among hearing-impaired English students in Bulgaria. Software can also be used to assist in the interpreting process and technical concepts that pose particular hurdles for sign-language interpreters can be delivered using computer-generated signing avatars (Andrei et al, 2013). Parton (2006) also called for interactive applications and the use of signing avatars to promote active learning among deaf students.
Long et al. (2011) reported that hard-of-hearing students perform better academically in online courses. Deaf students in web-based courses report satisfaction that they are receiving the same material in the same manner as their hearing peers (Parton, 2005). Email and discussion board communication in online courses allow hard-of-hearing students to interact with their peers and instructors more and they share their opinions and ideas more fully (Long et al., 2007). Web-based courses that employ video conferences may give access to more skilled, remote sign language interpreters, provide students with greater ability to collaborate with peers, and give deaf students increased access to adult hearing-impaired role models (Parton, 2005). Parton (2006) contended that blended learning worked best for deaf students when the courses are designed to bring the communication benefits of the online course to the live experience in the classroom. Hard-of-hearing students in blended courses report that the quality and quantity of interaction with peers and instructors is improved over a live course (Long at al., 2007).
The use of mobile computing for hearing-impaired students may be particularly beneficial as it frees their learning from time and place considerations, increases their motivation, and allows them to get immediate responses to questions from peers and instructors (Kuzu, 2011). Liu and Hong (2007) developed a learning support system to help instructors provide after class support to hearing-impaired junior high students via mobile technology, which led to higher homework completion rates. The use of tablet computers shows potential for deaf students and may lead to improved note-taking and collaboration via wireless file-sharing (Parton, 2006).
Obstacles
Most technical solutions tend to leverage deaf students’ enhanced visual skills (Kiboss, 2012), which can often lead to an overload of visual input that they have no hope of keeping up with (Long et al., 2011). Even in a standard classroom, simultaneous attention to visual inputs is problematic with a signing interpreter and the students’ attention can be further taxed by the addition of visual technologies (Marschark et al., 2005). Technology solutions should be designed with the special needs of hard-of-hearing students in mind and with the input of their teachers (Portugal & de Souza Couto, 2012). It is also important to design software to minimize distractions (Parton, 2005) and to be configurable, so extra channels of visual information can be turned off and on by the student (Colwell, Jelfs, & Mallett, 2005).
Conducting research to measure the effectiveness of technology solutions for deaf students is difficult due to low sample sizes, given the low occurrence of hearing impairment in the general population and the movement to integrate most deaf students in mainstream classes (Stoner et al., 2005). It is also problematic to generalize findings as hard-of-hearing people are not a homogeneous group (Stoner et al., 2005) and they differ on level of impairment, use of hearing aids or cochlear implants, and preferred communication mode (Slobodzian, 2009). This heterogeneous nature of hearing impairment often leads to a lack of organizational and government policy on technology use for deaf education (Zamfirov & Saeva, 2013). Many systems that have been developed have resulted from the grassroots efforts of faculty to design their own solutions (Portugal & de Souza Couto, 2012).