The utilization of technology in Educational Reform - Research Proposal Example

Introduction The utilization of technology has been one of the primary objectives in educational reform. The proposition is that in using technology,educational programs can be made more effective and efficient, allow for greater facility for research and development as well facilitate performance and professional standards monitoring and response (Gardner et al, 2003; Technology and Education”, 2006). However, though the sentiment is certainly popular, researchers such as Quinn (2003), Rapp (2007) and Stahmer (2007), efforts have been concentrated on general curriculums leaving special needs programs significantly outpaced. Lahm (2003) supports this concern by pointing out that professional concern for special needs classes has not been packed by equal political or administrative effort. A situation that she believes is leaving little facility to implement or measure the impact of the adoption of technology in special education curriculums. Research, Trends and Perspectives Determining what influences achievement of students in special education who have used technology over those who have not requires first the identification of technology use, methodology and evaluation measures used. At the same time, there is an equal need to develop performance standards that will be able to attribute variance in performance directly with the use of the technology. It should be noted that the correlation between students’ technological competency is not to be equated with student proficiency or achievement. Therefore, determining variance in proficiency or achievement among students due to the utilization of technology should entail control over the type of curriculum, students or instructors (Gardner et al, 2003). Concentrating on special education students, studies will also need to account for the client conditions and health. Subsequently, there is also a need to identify what factors may limit the impact of technology use from socio-cultural, political, economic or medical perspectives. Moreover, there is also a need to account for the nature of technology adaptation itself such as productivity paradoxes, rates of adaptation and competency requirements among others (“Technology and Education”, 2006). The technology-focused educational reform emerged as major agenda in the 1990’s. Initial programs were designed as support social services but eventually, efforts became the prerogative of educational institutions. Programs transitioned from general programs to enhance the well-being of vulnerable groups identified through schools then became more specific to individuals’ area of concern, developing services specific for physical, psychological, learning or socio-cultural concerns (Crain et al. 1990). Subsequent services were further refined under special education provisions wherein technology was primarily used to assess conditions or to augment intervention strategies particularly for communication and skill building (Schlosser et al, 1995). The efforts have been part of long term studies indicating that interventions for children with special need benefit significantly from community and familial reinforcement (Cuvo & Klatt, 1992). Thus, the modes of technology adoption for special education programs have extended from educational institutions which has resulted the highlight of communication and information networking. One major challenge however is that actual programs for students often access to innovative programs are difficult to develop and maintain which creates limitation to access or long-time participation in programs (Crain et al, 1990; Quinn, 2003). Therefore, though the was significant growth in the utilization of technology, there is a need to qualify whether efforts are directly or indirectly affect special education students’ performance and whether variances are be considered qualifiers between performance of students who are able to use technological tools in special education classes (Gardner et al, 2003). According to the opinion of Paramore and Higbee (2005), the child’s exposure and aptitude for technology remains to be the primary factors for consideration in adapting technology into special education programs. However, as Krause and associates (2007) point out, actual performance also depends on the access to services, sustainability of programs and continuous development of interventions. These have culminated in the current focus of special education technology adaptation of technology into curriculums: developing greater sensitivity and responsiveness to students’ needs, increasing competencies and developing social networks and partnerships (Gardner et al, 2003; Lahm, 2003). This in turn has changed the factors affecting adaptation, utilization and assessment of student performance. For Rapp (2007), the external factors critical to special education student response and performance have needed greater valuation due to the direction of current technology applications. This is not to diminish the significance of student factors in performance but is to highlight a higher degree of sensitivity of special education students to the former. There is admittedly a difficulty in attributing variances in performance to specific technology applications. If a comparison were to be made arbitrarily based on when technology is employed are not without consideration of student’s diagnoses, exposure and facility for technology for example, then results will not be able to quantify or qualify correctly for the technology inputs (Krause et al, 2007). Conclusion Current research shows generally a positive correlation with the use of technology. However, there is limited research indicating the degree of dependence of student performance in special education and the use of technology. In a similar manner, there is indication that methodologies or strategies are not universal, showing a high variances in terms of perceived effectiveness or level of satisfaction (Lahm, 2003). Though research developed based on mainstream technology use can provide insights for special education trends, sensitivity to the impact of students’ conditions and health (Gardner et al, 2003). Moreover, since there many students in special education programs encounter greater stress, there are more external factors that can impact their performance (Stahmer, 2007). There are key challenges in the assessing variances in special students’ performance based on the use of technology. The first phase of the challenge involves isolating the impact of technology from other factors affecting the performance. Then, there is the challenge of accommodating for the individual conditions and health of students. Finally, due to the current emphasis in collaborative education in the field, there is a need to evaluate the impact of these factors to performance. Then, there is a need to develop understanding of the nature of technology adaptation itself since there are paradoxes, performance curves and assimilation trends that can impact significantly children’s performance. References Crain, L. S., Mangravite, D. N., Allport, R., Schour, M. and Biakanja, K. (1990). Health care needs and services for technology-dependent children in developmental centers. West J Med. April; 152(4): 434–438. Cuvo, A. J. and Klatt, K. P. (1992). Effects of community-based, videotape, and flash card instruction of community-referenced sight words on students with mental retardation. J Appl Behav Anal. Summer; 25(2): 499–512. Gardner, J. Emmett, Wissick, Cheryl A., Schweder, Windy and Canter, Loralee Smith (2003). Enhancing Interdisciplinary Instruction in General and Special Education: Thematic Units and Technology. Remedial and Special Education, Jun; 24: 161 - 172. Krause, Jean C., Kegl, Judy A. and Schick, Brenda (2007). Toward Extending the Educational Interpreter Performance Assessment to Cued Speech. J Deaf Stud Deaf Educ. 13(3): 432–450. Lahm, Elizabeth A. (2003). Assistive Technology Specialists: Bringing Knowledge of Assistive Technology to School Districts. Remedial and Special Education, Jun; 24: 141 - 153. Paramore, Nancy W. and Higbee, Thomas S. (2005). An Evaluation of a Brief Multiple-stimulus Preference assessment with Adolescents with Emotional-behavioral disorders in an Educational Setting. J Appl Behav Anal. Fall; 38(3): 399–403 Quinn, David M. (2003). Legal Issues in Educational Technology: Implications for School Leaders. Educational Administration Quarterly, Apr; 39: 187 - 207. Rapp, John T (2007). Further Evaluation of Methods to Identify Matched Stimulation. J Appl Behav Anal Spring; 40(1): 73–88. Schlosser, R W, Belfiore, P J, Nigam, R, Blischak, D. and Hetzroni, O. (1995). The effects of speech output technology in the learning of graphic symbols. J Appl Behav Anal. 1995 Winter; 28(4): 537–549. Stahmer, Aubyn C. (2007). The Basic Structure of Community Early Intervention Programs for Children with Autism: Provider Descriptions. J Autism Dev Disord. Technology and Education. (2006). National Education Online Journal. Retrieved July 30, 2008 from http://www.nea.org/technology/index.html. Read More