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

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

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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Organista Sandoval, Javier, McAnally Salas, Lewis, Henríquez Ritchie, Patricio
التنسيق: Online
اللغة:spa
منشور في: REDIE es una publicación del Instituto de Investigación y Desarrollo Educativo (IIDE). 2012
الوصول للمادة أونلاين:https://redie.uabc.mx/index.php/redie/article/view/293
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الوصف
الملخص: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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