An initial comparison of the learning propensities of 10 through 12 students for data analytics education

Jamie Kennedy, Pramod Abichandani, Adam Fontecchio

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

The main focus of this ongoing effort is to compare the learning propensities of 10 through 12 students for data analytics education. Towards this end, a Microsoft Excel based university-level environmental engineering module was taught in a high school classroom with students in grades 10 through 12. The module focused on understanding the current trends and challenges in environmental pollution management and policy. Students were required to procure, analyze, and visualize data in order to propose an environmental policy that was aimed at reducing pollution. Initial data collected from the assessment of the student work alludes to the fact that despite being taught the same material by the same professor and teaching assistant, the success of the students, as measured by their final grades, varies substantially with their academic year. The underclassmen in high school did not display the academic maturity and comprehension that was displayed by the high school seniors. On the other hand, seniors demonstrated a strong propensity to learn and perform well.

Original languageEnglish (US)
Title of host publication2013 Frontiers in Education Conference
Subtitle of host publicationEnergizing the Future, FIE 2013 - Proceedings
Pages916-918
Number of pages3
DOIs
StatePublished - Dec 1 2013
Externally publishedYes
Event43rd IEEE Annual Frontiers in Education Conference, FIE 2013 - Oklahoma City, OK, United States
Duration: Oct 23 2013Oct 26 2013

Publication series

NameProceedings - Frontiers in Education Conference, FIE
ISSN (Print)1539-4565

Other

Other43rd IEEE Annual Frontiers in Education Conference, FIE 2013
CountryUnited States
CityOklahoma City, OK
Period10/23/1310/26/13

All Science Journal Classification (ASJC) codes

  • Software
  • Education
  • Computer Science Applications

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