Web-Based Experimentation for Students with Learning Disabilities

Web-Based Experimentation for Students with Learning Disabilities

Venkata Chivukula (Rensselaer Polytechnic Institute, USA) and Michael Shur (Rensselaer Polytechnic Institute, USA)
DOI: 10.4018/978-1-4666-4422-9.ch060
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Abstract

Assistive technologies can go a long way in helping learning disabled students to keep-up with their classmates. The ubiquity of internet as an active social networking, communication, and education platform has opened up a wide range of new possibilities for web-based lectures and experimentation that can be used to assist learning disabled students. To this end, the authors developed and applied Automated Internet Modeling (AIM) Lab dedicated to semiconductor device modeling and characterization. Their lab has been extensively used for teaching courses on semiconductor devices at senior and graduate levels. Recently, AIM-lab incorporated additional functionality such as You-Tube compatible on-line video feeds, audio and visual collaboration with peers via web-messaging in order to meet the needs of learning disabled students and make their learning process more effective. In this chapter, the authors focus on recent advances in the development of remote experimentation labs in the context of engineering education with an emphasis on general technological issues and specific experiments offered. Systematic evaluation of educational benefits derived from using these labs will also be presented.
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Introduction

Challenges in Learning Disability Education

The number of students with Learning Disabilities (LD) has grown rapidly in last 20 years, there were about 783,000 children in the US identified with LD in 1976 and in 1992 the LD population has grown to approximately 2.3 million in U.S. (Swanson, 2000). Learning disability disorder can be classified by one or more psychological processes involved in understanding or in using spoken or written language. The disability may manifest itself as an imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations. Conditions such as perceptual disabilities, brain injury, minimal brain dysfunction, dyslexia, and development aphasia may lead to LD (Lerner & Kline, 2005). Each year about 120,000 students are identified as LD in U.S.; they comprise almost 50% of all placements into special education (U.S. Office of Education, 1994).

As an example, Figure 1 illustrates percentage of LD students with hyperactivity disorder in the United States. As a result, increasing numbers of LD students are attending colleges. Enrollment increases of these students in two-year and four-year post-secondary colleges can be attributed to better academic preparation, improved transition planning, and increased availability of federal monies for LD scholarships and model programs (Brinckerhoff, McGuire, & Shaw, 2002). Despite this progress, the retention and degree completion rates of LDs in postsecondary education have not followed the same trajectory, with many students dropping out during their first year (Belch, 2004; Horn, Berktold, & Bobbit, 1999; Stodden, 2001). Their failure at the college can be related to inadequate academic preparation (Horn, Berktold, & Bobbit, 1999), lack of transition support between high school and college (Frieden, 2004), fragmentation and inconsistency in service provision (Frieden, 2004), a lack of teaching staff knowledge for dealing with LD and the absence of appropriate accommodation and modifications (Malakpa, 1997; Villarreal, 2002). All these factors play a crucial role in LD students learning experience with one of the most important being teaching staff-student relationship. A recent study of 86 postsecondary students with LD demonstrated that “the response a student receives to a request for assistance or accommodation for learning disability, particularly from a professor, likely affects the student’s willingness to seek help in future” (Hartman-Hall & Haaga, 2002, p. 271). Unfortunately, many teaching staff shy away from working with students with LD because they are ill equipped to teach these students (Mull, Sitlington, & Alper, 2001; Muller, 2006). Most of them rely on student disability office on campus for direction/instruction on how to serve students with LD. Student disability office identifies students with particular learning disability disorder and communicates specific accommodations for a particular student to the instructor. Most common accommodations include extended time on tests or modified assessments, note taking services, or books on tape (Hawke, 2004). While these accommodations are beneficial for students with LD, they are not a panacea and often only serve students who identify themselves as having disability (Orr & Hammig, 2009). Such accommodations do not go far enough to address barriers embedded in the curriculum design and increase teaching staff awareness in understanding the best practices in teaching students with LD. This chapter starts with brief review of learning aids current available for teaching LD students. It also highlights the recent trends/advances in instruction technology. We then discuss the advantages of using web-based remote experimentation technologies as opposed to conventional lab environment and review various remote labs developed for teaching courses in microelectronics world-wide, briefly presenting their highlights and important features. We present the architecture of our Automated Internet Modeling Lab (AIM-Lab) and its user interface. We describe advantages of using AIM-Lab and highlight important features built into AIM-Lab that serve the needs of LD students. We include a step-by-step description of running AIM-Lab CMOS experiment. Finally, we conclude this chapter presenting future research directions.

Figure 1.

Diagnosed attention deficit hyperactivity disorder and learning disability (United States, 2004-2006 http://www.cdc.gov/ncbddd/adhd/data.html)

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