Classification of Incoming Freshman in a Public University Based on the Variables of Academic Performance, Use of Digital Technology

Authors

  • Javier Organista Sandoval Instituto de Investigación y Desarrollo Educativo Universidad Autónoma de Baja California
  • Lewis McAnally Salas Instituto de Investigación y Desarrollo Educativo Universidad Autónoma de Baja California
  • Patricio Henríquez Ritchie Instituto de Investigación y Desarrollo Educativo Universidad Autónoma de Baja California

Keywords:

Educational technologies, freshman students characteristics, first-year students.

Abstract

During the first semester of 2008 a research study was conducted with incoming freshman in the School of Administrative and Social Sciences (FCAyS—acronym in Spanish) of the Ensenada campus of the Universidad Autónoma de Baja California (UABC). The purpose was to characterize the new students based on academic achievement (grade point averages in high school and the first semester of college), family context (parents’ schooling) and use of technology (computers and the Web). A survey of technology use developed within the framework of the research was applied to a sample of 438 students. The results show that the majority of the students are female (2 out of 3) and that 4 out of 5 have computers at home. About 80% of the students showed an intermediate level of proficiency in computer technology and the Web. Two classifying techniques were employed: CHAID and a cluster analysis to explore the development of patterns based on the above-mentioned variables. The result of the applied CHAID analysis highlights the importance of the variables of gender, parental schooling and level of immersion in the Web for the classification. The cluster analysis (k-means) generated four clusters; of these, cluster 1, which had the lowest average grades and the highest levels of computer and Web immersion, is noteworthy, because it suggests a non-educational use of technological resources. In contrast, cluster 4 presented the highest grade point average in college, a moderate level of computer use and a low level of immersion in the Web. This suggests a greater commitment to academics by reduced use of the computer and the Web for recreational purposes.

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References

Bebell, D., O’Dwyer, L., Russell, M. y Hoffman, T. (2007). Advancing data collection in the digital age: methodological challenges and solutions in educational technology research. Boston. MA: Boston College, Technology and Assessment Study Collaborative. Documento presentado en la Annual Meeting of American Educational Research Association Meeting, Chicago, IL. Recuperado de: http://www.bc.edu/research/intasc/PDF/Methodological%20challenges_v2.2.pdf

Bebell, D., Russell, M. y O’Dwyer, L. (2004). Measuring teachers’ technology uses: Why multiple-measures are more revealing. Journal of Research on Technology in Education, 37(1), 45-63.

Chaín, R. R. (2001). Alumnos y trayectorias. Procesos de análisis de información para diagnóstico y predicción. En ANUIES (Ed.), Deserción, rezago y eficiencia terminal en las IES. Propuesta metodológica para su estudio. Serie Investigaciones. México: ANUIES.

Cuesta, M. y Herrero, F. J. (2010). Introducción al muestreo. Depto. de Psicología, Universidad de Oviedo. Recuperado de: http://www.psico.uniovi.es/Dpto_Psicologia/metodos/tutor.7/

Curry, J. y Kennedy, M. (2005). Digital divide or digital development? The Internet in Mexico. Firstmonday, 11(3). Recuperado de: http://firstmonday.org

Directorio para la educación y cultura (2003). SESIUSS Project. Final Report. Programa Sócrates-Minerva, Comisión Europea. Recuperado de: http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:C:2003:177:0003:0024:ES:PDF

Du, J., Havard, B., Sansing, W. y Yu, Ch. (2004). The impact of the technology use on low-income and minority students’ academic achievement: educational longitudinal study of 2002. Association for Educational Communications and Technology, Chicago, IL. (No. de servicio de reproducción de documentos ERIC ED 485 086)

Duart, J. M., Gil, M., Pujol, M. y Castaño, J. (2008). La universidad en la sociedad red: usos del Internet en educación superior. Barcelona: Ariel.

Henríquez-Ritchie, P. y Organista-Sandoval, J. (2010, julio-diciembre). Clasificación de niveles de uso tecnológico: una propuesta con estudiantes de recién ingreso a la universidad. CPU-e, Revista de Investigación Educativa, 11. Recuperado de
http://www.uv.mx/cpue/num11/inves/hernandez-uso-tecnologico.html

Hunley, S., Evans, J., Hachey, M., Krise, J., Rich, T. y Schell, C. (2005). Adolescent computer use and academic achievement. Adolescent, Summer, 2005. Recuperado de: http://findarticles.com/p/articles/mi_m2248/is_158_40/ai_n14815097

Kass, G. V. (1980). An exploratory technique for investigating large quantities of categorical data. Applied Statistics, 29(2), 119–127.

Lei, J. (2010). Quantity versus quality: A new approach to examine the relationship between technology use and student outcomes. British Journal of Educational Technology, 41(3), 455-472.

Lowther, D., Jones, M. y Plants, R. (2000). Preparing tomorrow’s teachers to use web-based education. En: B. Abbey (Ed.), Instructional and cognitive impacts of web-based education. Hershey, PA: Idea Group Publishing.

Morales, C. (1999). Etapas de adopción de la tecnología informática al salón de clases. XV Simposio Internacional de Computación en la Educación. Universidad de Guadalajara.

O’Dwyer, L., Russell, M. y Bebell, D. (2005). Identifying teacher, school, and district characteristics associated with middle and high school teachers’ use of technology: a multilevel perspective. Journal of Educational Computing Research, 33(4), 369-393.

Organista, J. y Backhoff, E. (1999, octubre-diciembre). El uso de Internet para administrar tareas, exámenes y asesorías en la educación superior. Revista de la Educación Superior, 28(112). Recuperado de: http://www.anuies.mx/servicios/p_anuies/publicaciones/revsup/res112/art4.htm

Organista, J., Lavigne, G. y McAnally-Salas, L. (2008). Análisis de la actividad en línea del estudiante y su relación con el aprendizaje de Estadística. Revista Electrónica en Actualidades Investigativas en Educación, 8(3). 1-28. Recuperado de http://revista.inie.ucr.ac.cr/articulos/3-2008/archivos/estadistica.pdf

Prensky, M. (2001). Digital natives, Digital immigrants. On the Horizon, MCB University Press, 9(5). Recuperado de http://www.marcprensky.com/

Protheroe, N. (2005). Technology and student achievement. Research Report. National Association of Elementary School Principals. Recuperado de: http://d6test.naesp.org/resources/2/Principal/2005/N-Dp46.pdf

Ravitz, J. y Mergendoller, J. (2002). Technology use and achievement in Idaho schools: A state wide study of schools, teachers and students. Final Evaluation Report, Fundación J. A. y Kathryn Albertson. Novato, CA: Buck Institute for Education. (No. de servicio de reproducción de documentos ERIC 478 614)

Russell, M., O’Dwyer, L., Bebell, D. y Miranda, H. (2004). Technical report for the USEIT study. Boston, MA: Boston College, Technology and Assessment Study Collaborative. Recuperado de: http://www.bc.edu/research/intasc/researchprojects/USEIT/pdf/USEIT_r11.pdf

Schacter, J. (1999). The impact of education technology on student achievement. What the most current research has to say. (No. de servicio de reproducción de documentos ERIC ED 430 537)

Van Braak, J., Tondeur, J. y Valke, M. (2004). Explaining different types of computer use among primary school teachers. European Journal of Psychology of Education, 19(4), 407-422.

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Published

2012-05-01